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Duluth MN–WI Metropolitan Area

The Duluth MN–WI Metropolitan Area, commonly called the Twin Ports, is a small metropolitan area centered around the cities of Duluth, Minnesota and Superior, Wisconsin. The Twin Ports are located at the western part of Lake Superior (the westernmost part of North America's Great Lakes) and together are considered one of the larger cargo ports in the United States. The Twin Ports are close to many natural attractions such as the North Shore, the Apostle Islands, and the Superior National Forest.

The area is home to two long bridges: the Richard I. Bong Memorial Bridge (carrying U.S. Highway 2) and the John Blatnik Bridge (carrying I-535 and U.S. Highway 53). Each bridge reaches across more than 1.5 miles (2.5 km) across the mouth of the Saint Louis River. The Aerial Lift Bridge was constructed in 1905 and is on the National Register of Historic Places. It must be raised each time a vessel enters or leaves Duluth's harbor; the inlet on the Wisconsin side is not similarly obstructed.

Together, the cities rank as the 19th-busiest port in the country overall (44.2 million short tons [ 40.1 million tonnes ] per year) as of 2002, though the area is the 7th-busiest port (13.8 million short tons [ 12.5 million tonnes ] per year) when measured on foreign exports alone.

The census bureau's Twin Ports metropolitan statistical area, an area much larger than the Duluth metropolitan area includes all of Wisconsin's Douglas County, and Minnesota's Carlton and Saint Louis counties. With a 2020 census population of 291,638, the Duluth MSA ranked as the 170th largest metropolitan area in the United States. A tourist location that boasts many scenic natural amenities, approximately 6.7 million tourists visit The City of Duluth each year.

Communities
Populations as of 2020 Census:

Principal city

 * Duluth (86,697)

Places with 10,000 to 50,000 inhabitants

 * Superior, WI (26,751)
 * Hibbing (16,214)
 * Cloquet (12,568)
 * Hermantown (10,221)

Places with fewer than 10,000 inhabitants

 * Virginia (8,423)
 * International Falls (5,802)
 * Rice Lake (4,136)
 * Saginaw (3,910) unincorporated
 * Eveleth (3,718)
 * Proctor (3,120)
 * Esko (2,082)
 * Scanlon (991)
 * Carlton (948)
 * Wrenshall (428)
 * Oliver, WI (399)

Infrastructure
The four tallest buildings are in Duluth, the Alworth Building, Historic Old Central High School, Maurices Headquarters, Medical Arts Building. The Bong Bridge leads to from Duluth to Superior. The Bong bridge was built in 1985 and is 11,800 ft (3,600 m) long. The Blatnik Bridge also leads to from Duluth to Superior. The Blatnik Bridge was built in 1965 and is 7,975 feet (2,431 m) long. Canal Park is a heavy tourist area in Downtown Duluth. In Virginia the tallest bridge in Minnesota (Hwy 53 Bridge) connecting Eveleth to Virginia. The Hwy 53 Bridge covers the Rouchleau Mine. The bridge opened in 2017 and is 204 ft. high in the air and spans 1,125 ft.

Hospitals

 * Essentia Health St. Mary's Medical Center - Duluth - (Level 1 Trauma Center)

 * St. Luke's Hospital - Duluth - (Level 2 Trauma Center)

 * Essentia Health St. Mary's Hospital - Superior - (Level 4 Trauma Center)

 * Community Memorial Hospital - Cloquet - (Level 4 Trauma Center)

Shopping

 * Miller Hill Mall

Attractions

 * Aerial Lift Bridge
 * AMSOIL Arena
 * Bayfront Festival Park
 * Blatnik Bridge
 * Canal Park
 * Enger Tower
 * Glensheen Mansion
 * Gooseberry Falls
 * Great Lakes Aquarium
 * Lake Superior Railroad Museum
 * Leif Erikson Ship
 * Minnesota Point
 * Oldest Operating Hockey Arena in Minnesota
 * Spirit Mountain Ski Area
 * Superior City FC Soccer Games
 * Tallest Bridge in Minnesota
 * World's Largest Freestanding Hockey Stick

Colleges and universities

 * College of St. Scholastica - Duluth
 * Fond du Lac Tribal and Community College - Cloquet
 * Lake Superior College - Duluth
 * Northwood Technical College - Superior, WI
 * University of Minnesota Duluth - Duluth
 * University of Wisconsin, Superior - Superior, WI

Interstates

 * I-35.svg I-35
 * I-535.svg I-535

U.S. Highways

 * US 2.svg US 2
 * US 53.svg US 53
 * US 169 (MN).svg US 169

Minnesota Highways

 * MN-23.svg MN 23
 * MN-61.svg MN 61 – North Shore
 * MN-194.svg MN 194 – Central Entrance – Mesaba Avenue
 * MN-210.svg MN 210

St. Louis County Highways

 * St Louis County Route 4 MN.svg Saint Louis County Road 4 – Rice Lake Road

Transit

 * Duluth Transit Authority
 * Indian Trails
 * Jefferson Lines

Airports

 * Duluth International Airport - Duluth (DLH)
 * Sky Harbor Airport & Seaplane Base - Duluth (KDYT)

MSA
The Twin Ports metropolitan statistical area, an area much larger than the Duluth MN–WI metropolitan area, includes 4 counties, of which 3 are in Minnesota and 1 in Wisconsin. St. Louis County is Minnesota's largest county by area.

Duluth MN–WI Metropolitan Statistical Area

title: Duluth MN–WI Metropolitan Area


text:
Prefectures of Guinea

Guinea is divided into 8 regions among which the national capital Conakry ranks as a special zone (and is further divided into 5 communes). The other 7 regions are further subdivided into 33 prefectures and thence into sub-prefectures; which are later subdivided into local units (i.e.: districts and quarters) and further subdivided into smaller units (i.e.: villages and sectors).

Prefectures
The special zone of Conakry and the 33 prefectures are shown below according to their region, with their populations at recent censuses:

license: Creative Commons - Attribution Share-Alike - https://creativecommons.org/licenses/by-sa/4.0/

title: Prefectures of Guinea


text:
List of postal codes of Canada: R

This is a list of postal codes in Canada where the first letter is R. Postal codes beginning with R are located within the Canadian province of Manitoba. Only the first three characters are listed, corresponding to the Forward Sortation Area (FSA).

Canada Post provides a free postal code look-up tool on its website, via its applications for such smartphones as the iPhone and BlackBerry, and sells hard-copy directories and CD-ROMs. Many vendors also sell validation tools, which allow customers to properly match addresses and postal codes. Hard-copy directories can also be consulted in all post offices, and some libraries.

Manitoba
There are currently 76 FSAs in this list.

title: List of postal codes of Canada: R


text:
Latent semantic analysis

Latent semantic analysis (LSA) is a technique in natural language processing, in particular distributional semantics, of analyzing relationships between a set of documents and the terms they contain by producing a set of concepts related to the documents and terms. LSA assumes that words that are close in meaning will occur in similar pieces of text (the distributional hypothesis). A matrix containing word counts per document (rows represent unique words and columns represent each document) is constructed from a large piece of text and a mathematical technique called singular value decomposition (SVD) is used to reduce the number of rows while preserving the similarity structure among columns. Documents are then compared by cosine similarity between any two columns. Values close to 1 represent very similar documents while values close to 0 represent very dissimilar documents.

An information retrieval technique using latent semantic structure was patented in 1988 by Scott Deerwester, Susan Dumais, George Furnas, Richard Harshman, Thomas Landauer, Karen Lochbaum and Lynn Streeter. In the context of its application to information retrieval, it is sometimes called latent semantic indexing (LSI).

Occurrence matrix
LSA can use a document-term matrix which describes the occurrences of terms in documents; it is a sparse matrix whose rows correspond to terms and whose columns correspond to documents. A typical example of the weighting of the elements of the matrix is tf-idf (term frequency–inverse document frequency): the weight of an element of the matrix is proportional to the number of times the terms appear in each document, where rare terms are upweighted to reflect their relative importance.

This matrix is also common to standard semantic models, though it is not necessarily explicitly expressed as a matrix, since the mathematical properties of matrices are not always used.

Rank lowering
After the construction of the occurrence matrix, LSA finds a low-rank approximation to the term-document matrix. There could be various reasons for these approximations:

 * The original term-document matrix is presumed too large for the computing resources; in this case, the approximated low rank matrix is interpreted as an approximation (a "least and necessary evil").
 * The original term-document matrix is presumed noisy: for example, anecdotal instances of terms are to be eliminated. From this point of view, the approximated matrix is interpreted as a de-noisified matrix (a better matrix than the original).
 * The original term-document matrix is presumed overly sparse relative to the "true" term-document matrix. That is, the original matrix lists only the words actually in each document, whereas we might be interested in all words related to each document—generally a much larger set due to synonymy.

The consequence of the rank lowering is that some dimensions are combined and depend on more than one term:

 * {(car), (truck), (flower)} → {(1.3452 * car + 0.2828 * truck), (flower)}

This mitigates the problem of identifying synonymy, as the rank lowering is expected to merge the dimensions associated with terms that have similar meanings. It also partially mitigates the problem with polysemy, since components of polysemous words that point in the "right" direction are added to the components of words that share a similar meaning. Conversely, components that point in other directions tend to either simply cancel out, or, at worst, to be smaller than components in the directions corresponding to the intended sense.

Derivation
Let $$X$$ be a matrix where element $$(i,j)$$ describes the occurrence of term $$i$$ in document $$j$$ (this can be, for example, the frequency). $$X$$ will look like this:

\begin{matrix} & \textbf{d}_j \\ & \downarrow \\ \textbf{t}_i^T \rightarrow & \begin{bmatrix} x_{1,1} & \dots & x_{1,j} & \dots & x_{1,n} \\ \vdots & \ddots & \vdots & \ddots & \vdots \\ x_{i,1} & \dots & x_{i,j} & \dots & x_{i,n} \\ \vdots & \ddots & \vdots & \ddots & \vdots \\ x_{m,1} & \dots & x_{m,j} & \dots & x_{m,n} \\ \end{bmatrix} \end{matrix} $$

Now a row in this matrix will be a vector corresponding to a term, giving its relation to each document:

 * $$\textbf{t}_i^T = \begin{bmatrix} x_{i,1} & \dots & x_{i,j} & \dots & x_{i,n} \end{bmatrix}$$

Likewise, a column in this matrix will be a vector corresponding to a document, giving its relation to each term:

 * $$\textbf{d}_j = \begin{bmatrix}

x_{1,j} \\ \vdots \\ x_{i,j} \\ \vdots \\ x_{m,j} \\ \end{bmatrix}$$

Now the dot product $$\textbf{t}_i^T \textbf{t}_p$$ between two term vectors gives the correlation between the terms over the set of documents. The matrix product $$X X^T$$ contains all these dot products. Element $$(i,p)$$ (which is equal to element $$(p,i)$$) contains the dot product $$\textbf{t}_i^T \textbf{t}_p$$ ($$ = \textbf{t}_p^T \textbf{t}_i$$). Likewise, the matrix $$X^T X$$ contains the dot products between all the document vectors, giving their correlation over the terms: $$\textbf{d}_j^T \textbf{d}_q = \textbf{d}_q^T \textbf{d}_j$$.

Now, from the theory of linear algebra, there exists a decomposition of $$X$$ such that $$U$$ and $$V$$ are orthogonal matrices and $$\Sigma$$ is a diagonal matrix. This is called a singular value decomposition (SVD):

\begin{matrix} X = U \Sigma V^T \end{matrix} $$

The matrix products giving us the term and document correlations then become

\begin{matrix} X X^T &=& (U \Sigma V^T) (U \Sigma V^T)^T = (U \Sigma V^T) (V^{T^T} \Sigma^T U^T) = U \Sigma V^T V \Sigma^T U^T = U \Sigma \Sigma^T U^T \\ X^T X &=& (U \Sigma V^T)^T (U \Sigma V^T) = (V^{T^T} \Sigma^T U^T) (U \Sigma V^T) = V \Sigma^T U^T U \Sigma V^T = V \Sigma^T \Sigma V^T \end{matrix} $$

Since $$\Sigma \Sigma^T$$ and $$\Sigma^T \Sigma$$ are diagonal we see that $$U$$ must contain the eigenvectors of $$X X^T$$, while $$V$$ must be the eigenvectors of $$X^T X$$. Both products have the same non-zero eigenvalues, given by the non-zero entries of $$\Sigma \Sigma^T$$, or equally, by the non-zero entries of $$\Sigma^T\Sigma$$. Now the decomposition looks like this:

\begin{matrix} & X & & & U & & \Sigma & & V^T \\ & (\textbf{d}_j) & & & & & & & (\hat{\textbf{d}}_j) \\ & \downarrow & & & & & & & \downarrow \\ (\textbf{t}_i^T) \rightarrow & \begin{bmatrix} x_{1,1} & \dots & x_{1,j} & \dots & x_{1,n} \\ \vdots & \ddots & \vdots & \ddots & \vdots \\ x_{i,1} & \dots & x_{i,j} & \dots & x_{i,n} \\ \vdots & \ddots & \vdots & \ddots & \vdots \\ x_{m,1} & \dots & x_{m,j} & \dots & x_{m,n} \\ \end{bmatrix} & = & (\hat{\textbf{t}}_i^T) \rightarrow & \begin{bmatrix} \begin{bmatrix} \, \\ \, \\ \textbf{u}_1 \\ \, \\ \,\end{bmatrix} \dots \begin{bmatrix} \, \\ \, \\ \textbf{u}_l \\ \, \\ \, \end{bmatrix} \end{bmatrix} & \cdot & \begin{bmatrix} \sigma_1 & \dots & 0 \\ \vdots & \ddots & \vdots \\ 0 & \dots & \sigma_l \\ \end{bmatrix} & \cdot & \begin{bmatrix} \begin{bmatrix} & & \textbf{v}_1 & & \end{bmatrix} \\ \vdots \\ \begin{bmatrix} & & \textbf{v}_l & & \end{bmatrix} \end{bmatrix} \end{matrix} $$

The values $$\sigma_1, \dots, \sigma_l$$ are called the singular values, and $$u_1, \dots, u_l$$ and $$v_1, \dots, v_l$$ the left and right singular vectors. Notice the only part of $$U$$ that contributes to $$\textbf{t}_i$$ is the $$i\textrm{'th}$$ row. Let this row vector be called $$\hat{\textrm{t}}^T_i$$. Likewise, the only part of $$V^T$$ that contributes to $$\textbf{d}_j$$ is the $$j\textrm{'th}$$ column, $$\hat{ \textrm{d}}_j$$. These are not the eigenvectors, but depend on all the eigenvectors.

It turns out that when you select the $$k$$ largest singular values, and their corresponding singular vectors from $$U$$ and $$V$$, you get the rank $$k$$ approximation to $$X$$ with the smallest error (Frobenius norm). This approximation has a minimal error. But more importantly we can now treat the term and document vectors as a "semantic space". The row "term" vector $$\hat{\textbf{t}}^T_i$$ then has $$k$$ entries mapping it to a lower-dimensional space. These new dimensions do not relate to any comprehensible concepts. They are a lower-dimensional approximation of the higher-dimensional space. Likewise, the "document" vector $$\hat{\textbf{d}}_j$$ is an approximation in this lower-dimensional space. We write this approximation as

 * $$X_k = U_k \Sigma_k V_k^T$$

You can now do the following:
 * See how related documents $$j$$ and $$q$$ are in the low-dimensional space by comparing the vectors $$\Sigma_k \cdot \hat{\textbf{d}}_j $$ and $$\Sigma_k \cdot \hat{\textbf{d}}_q $$ (typically by cosine similarity).
 * Comparing terms $$i$$ and $$p$$ by comparing the vectors $$\Sigma_k \cdot \hat{\textbf{t}}_i$$ and $$\Sigma_k \cdot \hat{\textbf{t}}_p$$. Note that $$\hat{\textbf{t}}$$ is now a column vector.
 * Documents and term vector representations can be clustered using traditional clustering algorithms like k-means using similarity measures like cosine.
 * Given a query, view this as a mini document, and compare it to your documents in the low-dimensional space.

To do the latter, you must first translate your query into the low-dimensional space. It is then intuitive that you must use the same transformation that you use on your documents:

 * $$\hat{\textbf{d}}_j = \Sigma_k^{-1}U_k^T{\textbf{d}}_j $$

Note here that the inverse of the diagonal matrix $$\Sigma_k$$ may be found by inverting each nonzero value within the matrix.

This means that if you have a query vector $$q$$, you must do the translation $$\hat{\textbf{q}} = \Sigma_k^{-1} U_k^T \textbf{q}$$ before you compare it with the document vectors in the low-dimensional space. You can do the same for pseudo term vectors:

 * $$\textbf{t}_i^T = \hat{\textbf{t}}_i^T \Sigma_k V_k^T$$

 * $$\hat{\textbf{t}}_i^T = \textbf{t}_i^T V_k^{-T} \Sigma_k^{-1} = \textbf{t}_i^T V_k \Sigma_k^{-1}$$

 * $$\hat{\textbf{t}}_i = \Sigma_k^{-1} V_k^T \textbf{t}_i$$

Applications
The new low-dimensional space typically can be used to: Synonymy and polysemy are fundamental problems in natural language processing:
 * Compare the documents in the low-dimensional space (data clustering, document classification).
 * Find similar documents across languages, after analyzing a base set of translated documents (cross-language information retrieval).
 * Find relations between terms (synonymy and polysemy).
 * Given a query of terms, translate it into the low-dimensional space, and find matching documents (information retrieval).
 * Find the best similarity between small groups of terms, in a semantic way (i.e. in a context of a knowledge corpus), as for example in multi choice questions MCQ answering model.
 * Expand the feature space of machine learning / text mining systems
 * Analyze word association in text corpus
 * Synonymy is the phenomenon where different words describe the same idea. Thus, a query in a search engine may fail to retrieve a relevant document that does not contain the words which appeared in the query. For example, a search for "doctors" may not return a document containing the word "physicians", even though the words have the same meaning.
 * Polysemy is the phenomenon where the same word has multiple meanings. So a search may retrieve irrelevant documents containing the desired words in the wrong meaning. For example, a botanist and a computer scientist looking for the word "tree" probably desire different sets of documents.

Commercial applications
LSA has been used to assist in performing prior art searches for patents.

Applications in human memory
The use of Latent Semantic Analysis has been prevalent in the study of human memory, especially in areas of free recall and memory search. There is a positive correlation between the semantic similarity of two words (as measured by LSA) and the probability that the words would be recalled one after another in free recall tasks using study lists of random common nouns. They also noted that in these situations, the inter-response time between the similar words was much quicker than between dissimilar words. These findings are referred to as the Semantic Proximity Effect.

When participants made mistakes in recalling studied items, these mistakes tended to be items that were more semantically related to the desired item and found in a previously studied list. These prior-list intrusions, as they have come to be called, seem to compete with items on the current list for recall.

Another model, termed Word Association Spaces (WAS) is also used in memory studies by collecting free association data from a series of experiments and which includes measures of word relatedness for over 72,000 distinct word pairs.

Implementation
The SVD is typically computed using large matrix methods (for example, Lanczos methods) but may also be computed incrementally and with greatly reduced resources via a neural network-like approach, which does not require the large, full-rank matrix to be held in memory. A fast, incremental, low-memory, large-matrix SVD algorithm has recently been developed. MATLAB and Python implementations of these fast algorithms are available. Unlike Gorrell and Webb's (2005) stochastic approximation, Brand's algorithm (2003) provides an exact solution. In recent years progress has been made to reduce the computational complexity of SVD; for instance, by using a parallel ARPACK algorithm to perform parallel eigenvalue decomposition it is possible to speed up the SVD computation cost while providing comparable prediction quality.

Limitations
Some of LSA's drawbacks include:

 * The resulting dimensions might be difficult to interpret. For instance, in
 * {(car), (truck), (flower)} ↦ {(1.3452 * car + 0.2828 * truck), (flower)}
 * the (1.3452 * car + 0.2828 * truck) component could be interpreted as "vehicle". However, it is very likely that cases close to
 * {(car), (bottle), (flower)} ↦ {(1.3452 * car + 0.2828 * bottle), (flower)}
 * will occur. This leads to results which can be justified on the mathematical level, but have no immediately obvious meaning in natural language. Though, the (1.3452 * car + 0.2828 * bottle) component could be justified on account of the fact that both bottles and cars have transparent and opaque parts, are man made and with high probability contain logos/words on their surface; thus, in many ways these two concepts "share semantics." That is, within a language in question, there may not be a readily available word to assign and explainability becomes an analysis task as opposed to simple word/class/concept assignment task.

 * LSA can only partially capture polysemy (i.e., multiple meanings of a word) because each occurrence of a word is treated as having the same meaning due to the word being represented as a single point in space. For example, the occurrence of "chair" in a document containing "The Chair of the Board" and in a separate document containing "the chair maker" are considered the same. The behavior results in the vector representation being an average of all the word's different meanings in the corpus, which can make it difficult for comparison.   However, the effect is often lessened due to words having a predominant sense throughout a corpus (i.e. not all meanings are equally likely).
 * Limitations of bag of words model (BOW), where a text is represented as an unordered collection of words. To address some of the limitation of bag of words model (BOW), multi-gram dictionary can be used to find direct and indirect association as well as higher-order co-occurrences among terms.
 * The probabilistic model of LSA does not match observed data: LSA assumes that words and documents form a joint Gaussian model (ergodic hypothesis), while a Poisson distribution has been observed. Thus, a newer alternative is probabilistic latent semantic analysis, based on a multinomial model, which is reported to give better results than standard LSA.

Semantic hashing
In semantic hashing documents are mapped to memory addresses by means of a neural network in such a way that semantically similar documents are located at nearby addresses. Deep neural network essentially builds a graphical model of the word-count vectors obtained from a large set of documents. Documents similar to a query document can then be found by simply accessing all the addresses that differ by only a few bits from the address of the query document. This way of extending the efficiency of hash-coding to approximate matching is much faster than locality sensitive hashing, which is the fastest current method.

Latent semantic indexing
Latent semantic indexing (LSI) is an indexing and retrieval method that uses a mathematical technique called singular value decomposition (SVD) to identify patterns in the relationships between the terms and concepts contained in an unstructured collection of text. LSI is based on the principle that words that are used in the same contexts tend to have similar meanings. A key feature of LSI is its ability to extract the conceptual content of a body of text by establishing associations between those terms that occur in similar contexts.

LSI is also an application of correspondence analysis, a multivariate statistical technique developed by Jean-Paul Benzécri in the early 1970s, to a contingency table built from word counts in documents.

Called " indexing" because of its ability to correlate related terms that are  in a collection of text, it was first applied to text at Bellcore in the late 1980s. The method, also called latent semantic analysis (LSA), uncovers the underlying latent semantic structure in the usage of words in a body of text and how it can be used to extract the meaning of the text in response to user queries, commonly referred to as concept searches. Queries, or concept searches, against a set of documents that have undergone LSI will return results that are conceptually similar in meaning to the search criteria even if the results don’t share a specific word or words with the search criteria.

Benefits of LSI
LSI helps overcome synonymy by increasing recall, one of the most problematic constraints of Boolean keyword queries and vector space models. Synonymy is often the cause of mismatches in the vocabulary used by the authors of documents and the users of information retrieval systems. As a result, Boolean or keyword queries often return irrelevant results and miss information that is relevant.

LSI is also used to perform automated document categorization. In fact, several experiments have demonstrated that there are a number of correlations between the way LSI and humans process and categorize text. Document categorization is the assignment of documents to one or more predefined categories based on their similarity to the conceptual content of the categories. LSI uses example documents to establish the conceptual basis for each category. During categorization processing, the concepts contained in the documents being categorized are compared to the concepts contained in the example items, and a category (or categories) is assigned to the documents based on the similarities between the concepts they contain and the concepts that are contained in the example documents.

Dynamic clustering based on the conceptual content of documents can also be accomplished using LSI. Clustering is a way to group documents based on their conceptual similarity to each other without using example documents to establish the conceptual basis for each cluster. This is very useful when dealing with an unknown collection of unstructured text.

Because it uses a strictly mathematical approach, LSI is inherently independent of language. This enables LSI to elicit the semantic content of information written in any language without requiring the use of auxiliary structures, such as dictionaries and thesauri. LSI can also perform cross-linguistic concept searching and example-based categorization. For example, queries can be made in one language, such as English, and conceptually similar results will be returned even if they are composed of an entirely different language or of multiple languages.

LSI is not restricted to working only with words. It can also process arbitrary character strings. Any object that can be expressed as text can be represented in an LSI vector space. For example, tests with MEDLINE abstracts have shown that LSI is able to effectively classify genes based on conceptual modeling of the biological information contained in the titles and abstracts of the MEDLINE citations.

LSI automatically adapts to new and changing terminology, and has been shown to be very tolerant of noise (i.e., misspelled words, typographical errors, unreadable characters, etc.). This is especially important for applications using text derived from Optical Character Recognition (OCR) and speech-to-text conversion. LSI also deals effectively with sparse, ambiguous, and contradictory data.

Text does not need to be in sentence form for LSI to be effective. It can work with lists, free-form notes, email, Web-based content, etc. As long as a collection of text contains multiple terms, LSI can be used to identify patterns in the relationships between the important terms and concepts contained in the text.

LSI has proven to be a useful solution to a number of conceptual matching problems. The technique has been shown to capture key relationship information, including causal, goal-oriented, and taxonomic information.

LSI timeline

 * Mid-1960s – Factor analysis technique first described and tested (H. Borko and M. Bernick)
 * 1988 – Seminal paper on LSI technique published
 * 1989 – Original patent granted
 * 1992 – First use of LSI to assign articles to reviewers
 * 1994 – Patent granted for the cross-lingual application of LSI (Landauer et al.)
 * 1995 – First use of LSI for grading essays (Foltz, et al., Landauer et al.)
 * 1999 – First implementation of LSI technology for intelligence community for analyzing unstructured text (SAIC).
 * 2002 – LSI-based product offering to intelligence-based government agencies (SAIC)

Mathematics of LSI
LSI uses common linear algebra techniques to learn the conceptual correlations in a collection of text. In general, the process involves constructing a weighted term-document matrix, performing a Singular Value Decomposition on the matrix, and using the matrix to identify the concepts contained in the text.

Term-document matrix
LSI begins by constructing a term-document matrix, $$A$$, to identify the occurrences of the $$m$$ unique terms within a collection of $$n$$ documents. In a term-document matrix, each term is represented by a row, and each document is represented by a column, with each matrix cell, $$a_{ij}$$, initially representing the number of times the associated term appears in the indicated document, $$\mathrm{tf_{ij}}$$. This matrix is usually very large and very sparse.

Once a term-document matrix is constructed, local and global weighting functions can be applied to it to condition the data. The weighting functions transform each cell, $$a_{ij}$$ of $$A$$, to be the product of a local term weight, $$l_{ij}$$, which describes the relative frequency of a term in a document, and a global weight, $$g_i$$, which describes the relative frequency of the term within the entire collection of documents.

Some common local weighting functions are defined in the following table.

Some common global weighting functions are defined in the following table.

Empirical studies with LSI report that the Log and Entropy weighting functions work well, in practice, with many data sets. In other words, each entry $$a_{ij}$$ of $$A$$ is computed as:

 * $$g_i = 1 + \sum_j \frac{p_{ij} \log p_{ij}}{\log n}$$

 * $$a_{ij} = g_i \ \log (\mathrm{tf}_{ij} + 1)$$

Rank-reduced singular value decomposition
A rank-reduced, singular value decomposition is performed on the matrix to determine patterns in the relationships between the terms and concepts contained in the text. The SVD forms the foundation for LSI. It computes the term and document vector spaces by approximating the single term-frequency matrix, $$A$$, into three other matrices— an m by r term-concept vector matrix $$T$$, an r by r singular values matrix $$S$$, and a n by r concept-document vector matrix, $$D$$, which satisfy the following relations:

$$A \approx TSD^T$$

$$T^T T = I_r \quad D^T D = I_r $$

$$S_{1,1} \geq S_{2,2} \geq \ldots \geq S_{r,r} > 0 \quad S_{i,j} = 0 \; \text{where} \; i \neq j$$

In the formula, A is the supplied m by n weighted matrix of term frequencies in a collection of text where m is the number of unique terms, and n is the number of documents. T is a computed m by r matrix of term vectors where r is the rank of A—a measure of its unique dimensions ≤ min(m,n). S is a computed r by r diagonal matrix of decreasing singular values, and D is a computed n by r matrix of document vectors.

The SVD is then truncated to reduce the rank by keeping only the largest k « r diagonal entries in the singular value matrix S, where k is typically on the order 100 to 300 dimensions. This effectively reduces the term and document vector matrix sizes to m by k and n by k respectively. The SVD operation, along with this reduction, has the effect of preserving the most important semantic information in the text while reducing noise and other undesirable artifacts of the original space of A. This reduced set of matrices is often denoted with a modified formula such as:

 * A ≈ Ak = Tk Sk DkT

Efficient LSI algorithms only compute the first k singular values and term and document vectors as opposed to computing a full SVD and then truncating it.

Note that this rank reduction is essentially the same as doing Principal Component Analysis (PCA) on the matrix A, except that PCA subtracts off the means. PCA loses the sparseness of the A matrix, which can make it infeasible for large lexicons.

Querying and augmenting LSI vector spaces
The computed Tk and Dk matrices define the term and document vector spaces, which with the computed singular values, Sk, embody the conceptual information derived from the document collection. The similarity of terms or documents within these spaces is a factor of how close they are to each other in these spaces, typically computed as a function of the angle between the corresponding vectors.

The same steps are used to locate the vectors representing the text of queries and new documents within the document space of an existing LSI index. By a simple transformation of the A = T S DT equation into the equivalent D = AT T S−1 equation, a new vector, d, for a query or for a new document can be created by computing a new column in A and then multiplying the new column by T S−1. The new column in A is computed using the originally derived global term weights and applying the same local weighting function to the terms in the query or in the new document.

A drawback to computing vectors in this way, when adding new searchable documents, is that terms that were not known during the SVD phase for the original index are ignored. These terms will have no impact on the global weights and learned correlations derived from the original collection of text. However, the computed vectors for the new text are still very relevant for similarity comparisons with all other document vectors.

The process of augmenting the document vector spaces for an LSI index with new documents in this manner is called folding in. Although the folding-in process does not account for the new semantic content of the new text, adding a substantial number of documents in this way will still provide good results for queries as long as the terms and concepts they contain are well represented within the LSI index to which they are being added. When the terms and concepts of a new set of documents need to be included in an LSI index, either the term-document matrix, and the SVD, must be recomputed or an incremental update method (such as the one described in ) is needed.

Additional uses of LSI
It is generally acknowledged that the ability to work with text on a semantic basis is essential to modern information retrieval systems. As a result, the use of LSI has significantly expanded in recent years as earlier challenges in scalability and performance have been overcome.

LSI is being used in a variety of information retrieval and text processing applications, although its primary application has been for concept searching and automated document categorization. Below are some other ways in which LSI is being used:

 * Information discovery (eDiscovery, Government/Intelligence community, Publishing)
 * Automated document classification (eDiscovery, Government/Intelligence community, Publishing)
 * Text summarization (eDiscovery, Publishing)
 * Relationship discovery (Government, Intelligence community, Social Networking)
 * Automatic generation of link charts of individuals and organizations (Government, Intelligence community)
 * Matching technical papers and grants with reviewers (Government)
 * Online customer support (Customer Management)
 * Determining document authorship (Education)
 * Automatic keyword annotation of images
 * Understanding software source code (Software Engineering)
 * Filtering spam (System Administration)
 * Information visualization
 * Essay scoring (Education)
 * Literature-based discovery
 * Stock returns prediction
 * Dream Content Analysis (Psychology)

LSI is increasingly being used for electronic document discovery (eDiscovery) to help enterprises prepare for litigation. In eDiscovery, the ability to cluster, categorize, and search large collections of unstructured text on a conceptual basis is essential. Concept-based searching using LSI has been applied to the eDiscovery process by leading providers as early as 2003.

Challenges to LSI
Early challenges to LSI focused on scalability and performance. LSI requires relatively high computational performance and memory in comparison to other information retrieval techniques. However, with the implementation of modern high-speed processors and the availability of inexpensive memory, these considerations have been largely overcome. Real-world applications involving more than 30 million documents that were fully processed through the matrix and SVD computations are common in some LSI applications. A fully scalable (unlimited number of documents, online training) implementation of LSI is contained in the open source gensim software package.

Another challenge to LSI has been the alleged difficulty in determining the optimal number of dimensions to use for performing the SVD. As a general rule, fewer dimensions allow for broader comparisons of the concepts contained in a collection of text, while a higher number of dimensions enable more specific (or more relevant) comparisons of concepts. The actual number of dimensions that can be used is limited by the number of documents in the collection. Research has demonstrated that around 300 dimensions will usually provide the best results with moderate-sized document collections (hundreds of thousands of documents) and perhaps 400 dimensions for larger document collections (millions of documents). However, recent studies indicate that 50-1000 dimensions are suitable depending on the size and nature of the document collection. Checking the proportion of variance retained, similar to PCA or factor analysis, to determine the optimal dimensionality is not suitable for LSI. Using a synonym test or prediction of missing words are two possible methods to find the correct dimensionality. When LSI topics are used as features in supervised learning methods, one can use prediction error measurements to find the ideal dimensionality.

Articles on LSA

 * Latent Semantic Analysis, a scholarpedia article on LSA written by Tom Landauer, one of the creators of LSA.

Talks and demonstrations

 * LSA Overview, talk by Prof. Thomas Hofmann describing LSA, its applications in Information Retrieval, and its connections to probabilistic latent semantic analysis.
 * Complete LSA sample code in C# for Windows. The demo code includes enumeration of text files, filtering stop words, stemming, making a document-term matrix and SVD.

Implementations
Due to its cross-domain applications in Information Retrieval, Natural Language Processing (NLP), Cognitive Science and Computational Linguistics, LSA has been implemented to support many different kinds of applications.
 * Sense Clusters, an Information Retrieval-oriented perl implementation of LSA
 * S-Space Package, a Computational Linguistics and Cognitive Science-oriented Java implementation of LSA
 * Semantic Vectors applies Random Projection, LSA, and Reflective Random Indexing to Lucene term-document matrices
 * Infomap Project, an NLP-oriented C implementation of LSA (superseded by semanticvectors project)
 * Text to Matrix Generator, A MATLAB Toolbox for generating term-document matrices from text collections, with support for LSA
 * Gensim contains a Python implementation of LSA for matrices larger than RAM.

title: Latent semantic analysis


text:
List of rivers of Georgia (U.S. state)

List of rivers of Georgia (U.S. state).

By drainage basin
This list is arranged by drainage basin, with respective tributaries indented under each larger stream's name.

Atlantic Ocean

 * Savannah River
 * Abercorn Creek
 * Black Creek
 * Knoxboro Creek
 * Ebenezer Creek
 * Brier Creek
 * Little River
 * Hudson River
 * Tugaloo River
 * Chattooga River
 * Tallulah River
 * Coleman River
 * Toccoa Creek
 * Broad River
 * Bull River
 * Shad River
 * Halfmoon River
 * Wilmington River
 * Skidaway River
 * Herb River
 * Odingsell River
 * Ogeechee
 * Little Ogeechee River (Chatham County)
 * Vernon River
 * Canoochee River
 * Williamson Swamp Creek
 * Rocky Comfort Creek
 * Little Ogeechee River (Hancock County)
 * Bear River
 * Medway River
 * Belfast River
 * Tivoli River
 * Laurel View River
 * Jerico River
 * North Newport River
 * South Newport River
 * Sapelo River
 * Broro River
 * Mud River
 * Crescent River
 * Duplin River
 * North River
 * South River
 * Darien River
 * Altamaha River
 * Ohoopee River
 * Little Ohoopee River
 * Ocmulgee River
 * Little Ocmulgee River
 * Alligator Creek
 * Gum Swamp Creek
 * Tobesofkee Creek
 * Swift Creek
 * Towaliga River
 * Alcovy River
 * South River
 * Walnut Creek
 * Yellow River
 * Oconee River
 * Little River
 * Apalachee River
 * Middle Oconee River
 * Mulberry River
 * North Oconee River
 * Butler River
 * Hampton River
 * Frederica River
 * Mackay River
 * Brunswick River
 * Turtle River
 * Buffalo River
 * Little Satilla River
 * Satilla River
 * Little Satilla River
 * Big Satilla Creek
 * Little Satilla Creek
 * Alabaha River
 * Seventeen Mile River
 * Cumberland River
 * Crooked River
 * St. Marys River
 * North River

Gulf of Mexico

 * Suwannee River
 * Withlacoochee River
 * Okapilco Creek
 * Little River
 * New River
 * Alapaha River
 * Alapahoochee River
 * Willacoochee River
 * Suwannoochee Creek
 * Okefenokee Swamp
 * Black River
 * Gum Swamp
 * Aucilla River
 * Ochlockonee River
 * Little Ochlockonee River
 * Apalachicola River (FL)
 * Chattahoochee River
 * Sawhatchee Creek
 * Pataula Creek
 * Hannahatchee Creek
 * Upatoi Creek
 * Bull Creek
 * Mulberry Creek
 * Mountain Oak Creek
 * Flat Shoal Creek
 * Yellowjacket Creek
 * Beech Creek
 * New River
 * Caney Creek
 * Dog River
 * Billy Creek
 * Nancy Long Creek
 * Camp Creek
 * Sweetwater Creek
 * Noses Creek
 * Peachtree Creek
 * Nancy Creek
 * Sope Creek
 * Sewell Mill Creek
 * Willeo Creek
 * Vickery Creek (Big Creek tributary)
 * Hog Wallow Creek
 * Foe Killer Creek
 * Crooked Creek
 * Johns Creek (Chattahoochee River tributary)
 * Chestatee River
 * Tesnatee Creek
 * Soque River
 * Hazel Creek
 * Lick Log Creek
 * Law Creek
 * Little Hazel Creek
 * Deep Creek
 * Liberty Creek
 * Shoal Creek
 * Alley Creek
 * Flint River
 * Spring Creek
 * Ichawaynochaway Creek
 * Kinchafoonee Creek
 * Muckalee Creek
 * Mobile River (AL)
 * Alabama River (AL)
 * Coosa River
 * Chattooga River
 * Etowah River
 * Little River
 * Noonday Creek
 * Dykes Creek
 * Oostanaula River
 * Johns Creek (Oostanaula River tributary)
 * Alan Creek
 * Conasauga River
 * Jacks River
 * Coosawattee River
 * Cartecay River
 * Ellijay River
 * Tallapoosa River
 * Little Tallapoosa River
 * Mississippi River
 * Ohio River
 * Tennessee River (TN)
 * Hiwassee River
 * Toccoa River
 * Nottely River
 * Little Tennessee River

Miscellaneous

 * River Styx - Georgia has two very small rivers named after the mythical Styx. Both flow into swamps.  One is in the Savannah River watershed, the other is in the St. Marys River watershed.

Alphabetically

 * Alabaha River
 * Alan Creek
 * Alapaha River
 * Alapahoochee River
 * Alcovy River
 * Alley Creek
 * Allez River
 * Alligator Creek
 * Altamaha River
 * Apalachee River
 * Aucilla River
 * Ball Creek
 * Bear River
 * Beech Creek
 * Belfast River
 * Big Satilla Creek
 * Big Satilla River
 * Black Creek (Ogeechee River tributary)
 * Black Creek (Savannah River tributary)
 * Black River
 * Brier Creek
 * Broad River
 * Broro River
 * Brunswick River
 * Buffalo River
 * Bull Creek
 * Bull River
 * Camp Creek
 * Caney Creek
 * Canoochee River
 * Cartecay River
 * Chattahoochee River
 * Chattooga River, the northeast boundary with South Carolina
 * Chattooga River (Alabama-Georgia), in northwest Georgia
 * Chestatee River
 * Coleman River
 * Coleoatchee Creek
 * Conasauga River
 * Coosa River
 * Coosawattee River
 * Crescent River
 * Crooked Creek
 * Crooked River
 * Cumberland River
 * Darien River
 * Deep Creek
 * Dog River
 * Duplin River
 * Dykes Creek
 * Ebenezer Creek
 * Ellijay River
 * Etowah River
 * Flat Shoal Creek
 * Flint River
 * Foe Killer Creek
 * Frederica River
 * Gum Swamp Creek
 * Halfmoon River
 * Hampton River
 * Hannahatchee Creek
 * Hazel Creek
 * Herb River
 * Hiwassee River
 * Hog Wallow Creek
 * Hudson River (Georgia)
 * Ichawaynochaway Creek
 * Jacks River
 * Jerico River
 * Johns Creek (Chattahoochee River tributary)
 * Johns Creek (Oostanaula River tributary)
 * Kettle Creek
 * Kinchafoonee Creek
 * Knoxboro Creek
 * Laurel View River
 * Law Creek
 * Liberty Creek
 * Lick Log Creek
 * Little Hazel Creek
 * Little Ochlockonee River
 * Little Ocmulgee River
 * Little Ogeechee River (Chatham County)
 * Little Ogeechee River (Hancock County)
 * Little Ohoopee River
 * Little River (Columbia County, Georgia)
 * Little River (Etowah River tributary)
 * Little River (Oconee River tributary)
 * Little River (Withlacoochee River tributary)
 * Little Satilla Creek
 * Little Satilla River
 * Little Tallapoosa River
 * Little Tennessee River
 * Mackay River
 * Medway River
 * Middle Oconee River
 * Mountain Oak Creek
 * Muckalee Creek
 * Mud River
 * Mulberry Creek
 * Mulberry River
 * Nancy Creek
 * New River (Chattahoochee River tributary)
 * New River (Withlacoochee River tributary)
 * Noonday Creek
 * North Newport River
 * North Oconee River
 * North River (Darien River tributary)
 * North River (St. Marys River tributary)
 * Noses Creek
 * Nottely River
 * Ochlockonee River
 * Ocmulgee River
 * Oconee River
 * Odingsell River
 * Ogeechee River
 * Ohoopee River
 * Okapilco Creek
 * Oostanaula River
 * Pataula Creek
 * Peachtree Creek
 * River Styx
 * Rocky Comfort Creek
 * Runaway Negro Creek
 * St. Marys River
 * Sapelo River
 * Satilla River
 * Savannah River
 * Sawhatchee Creek
 * Sewell Mill Creek
 * Shad River
 * Shoal Creek
 * Sixteen Mile River
 * Skidaway River
 * Sope Creek
 * Soquee River
 * South Newport River
 * South River (Darien River tributary)
 * South River (Ocmulgee River tributary)
 * Spring Creek
 * Suwannee River
 * Suwannoochee Creek
 * Sweetwater Creek
 * Swift Creek
 * Tallapoosa River
 * Tallulah River
 * Tesnatee Creek
 * Tivoli River
 * Tobesofkee Creek
 * Toccoa River
 * Towaliga River
 * Tugaloo River
 * Turtle River
 * Upatoi Creek
 * Vernon River
 * Vickery Creek, or Big Creek
 * Willacoochee River
 * Willeo Creek
 * Williamson Swamp Creek
 * Wilmington River
 * Withlacoochee River
 * Yellow River
 * Yellowjacket Creek

title: List of rivers of Georgia (U.S. state)


text:
Wikipedia:Articles for deletion/Peter Wagner

The text doesn't seem to have any relation to the title. A google search for "Peter Wagner" "Modern Knowledge System" doesn't give any links. Thue 19:06, 29 May 2004 (UTC)

Has nothing to do with the title, and the info there is gibberish. Delete. RickK 19:17, 29 May 2004 (UTC)
 * Delete. I concur with the above users.  Acegikmo1 19:51, 29 May 2004 (UTC)


text:
Television South West

Television South West (TSW) was the ITV franchise holder for the South West England region from 1 January 1982 until 31 December 1992, broadcasting from studios at Derry's Cross in Plymouth, Devon.

Origins and Launch
On 28 December 1980 TSW was awarded the contract to serve the South West England region from the night of 31 December 1981 at 12 midnight for a 10-year period, succeeding incumbent Westward Television, which had served the area since 1961.

TSW promised greater investment in the area including the introduction of electronic news gathering facilities at a number of sites in the region (a process already started by Westward) and a stronger emphasis on local programming (an area in which Westward had been particularly successful).

However, TSW's success in winning the contract may have been helped by boardroom friction within Westward which had blighted the company for several years and incurred criticism from the Independent Broadcasting Authority. During negotiations to purchase Westward's facilities at Derry's Cross in Plymouth, the management of TSW bought the whole Westward company for £2.38 million and thus went on air four months early on 12 August 1981, although it transmitted under the Westward name until the end of the year.

TSW was seen as slightly more ambitious than both its predecessor Westward Television and its successor Westcountry Television and its presentation, although still homelier than much seen on ITV and not dissimilar to that of Westward, was considered more professional than that of its forebear.

TSW was one of the last ITV companies to start broadcasting 24 hours a day, which it did on 2 September 1988 – the same day as Border Television, Tyne Tees Television and Grampian Television. It was also one of the first ITV companies to broadcast in NICAM digital stereo, which it started doing in summer 1990.

Launch
Shortly, right after Roger Shaw delivered the closing announcement on Westward's closing night, TSW began with a short video clip of a champagne bottle being opened accompanied by the short audio version of the station ident "That's Soul, Write". Shaw then reappeared wearing a modern suit (no longer in a dinner jacket), and now in a modern chair, surrounded by staff wearing TSW T-shirts and holding 2" videotapes. This was clearly to remind viewers of a new modern era. Shaw made the first announcement on TSW:

...let's say welcome to 1982 from your new television station, Television South West, with the promise a full-bodied blend of the new and familiar. And from all of us here on duty in these first few seconds of 1982, a happy new year from and with TSW. And to get the new year off to a good-humoured start, we have a brand new comedy with Peter Cook and Mimi Kennedy in The Two of Us.

This was followed by the full version of TSW's ident. The comedy programme was followed by further continuity, an epilogue, weather & shipping forecast and closedown – all with TSW branding. However, when the screen finally faded to black at approximately 12:40am on 1 January 1982, Shaw made a final out-of-vision courtesy announcement and managed to mention the now-defunct Westward one last time, saying 'from all the staff here at Westward – good night'.

Franchise loss and closure
On 16 October 1991, following changes to the way ITV contracts were issued (via a blind auction rather than a bid on merits and potential) it was announced that TSW had lost its franchise because of an 'unrealistic business plan' related to its bid, which was viewed by the Independent Television Commission (ITC) as being far too high. This triggered TSW to apply for a judicial review against the ITC, on the grounds that its bid had been unfairly dismissed. TSW believed that it was a casualty of the ITC's wish not to renew TVS's franchise, despite being the highest bid, while renewing Granada's when it had been outbid. The case went right to the House of Lords, but was rejected in February 1992. The implications of the court case did change the behaviour of the ITC into being more open with regards to its business.

TSW's high bid of £16.12 million had been influenced largely by managing director Harry Turner's correct expectation of competitors for its franchise area, which were TeleWest Broadcasting (not to be confused with the telecommunications provider of the same name) and Westcountry Television, the latter "looking frighteningly well organised" that had worried TSW. TeleWest was headed by local independent programme producer Mallory Maltby and included BBC News personality Angela Rippon and several ex-TSW personnel in its line-up, but had failed on quality grounds unlike Westcountry. Westcountry, meanwhile, was chaired by merchant banker Stephen Redfarn, who was a former associate of James Gatward (one of the founders of neighbouring TVS), received the support of such figures as John Banham (the then-director of Confederation of British Industry), Frank Copplestone (the former managing director of TVS's predecessor Southern Television) and John Prescott-Thomas (a television executive at BBC South West), and had financial backing from Associated Newspapers, Brittany Ferries and South West Water, which TSW had assumed would have helped Westcountry to "certainly bid to their maximum capacity", a bid a "worried" TSW itself had estimated would have been £12 million a year rather than the less-than-£8 million Westcountry ended up bidding.

Closing ceremony
Westcountry Television won the South West region franchise and took over from TSW at midnight on 1 January 1993. On 31 December 1992, TSW marked its final day of transmission with a number of special programmes and continuity links. Continuity announcers Sally Meen and Tristram Payne shared the daytime announcing/newsreading shift with Ian Stirling and Ruth Langsford taking over for the last few evening shifts. The day's schedule included the final edition of Gus Honeybun's Magic Birthdays, a repeat of the award-winning documentary, A Day in the Life of...Beryl Cook and a one-hour TSW Today special featuring the last regional news bulletin and an expansive look back at TSW's programming. Along with other ITV broadcasters, with the exceptions of TVS, which broadcast its own farewell special, Goodbye to All That, and both Scottish Television and Grampian Television which broadcast the traditional Hogmanay, the last ever programme broadcast on TSW was Thames Television's own farewell programme, entitled The End Of The Year Show: The Best... from Thames.

After that show's closing credits, the final sign-off announcement was made by Ian Stirling and Ruth Langsford at 11:55pm, bidding farewell to the departing station by thanking the viewers and paying tribute – after which, TSW handed over to ITN for the news headlines and midnight chimes of the Big Ben in a brief news bulletin entitled Into the New Year. At the end of the bulletin, transmission was switched to Westcountry Television.

After 1993
After the franchise loss, TSW undertook a reverse takeover with the White Ward Group, makers of safety footwear and associated articles. The name of the company was changed to UK Safety Ltd, and traded for a number of years, before entering administrative receivership.

Upon losing the franchise, the directors of TSW established a public film and television archive, based around the back catalogue of Westward and TSW programmes they owned. They created the TSW Film and Television Archive, one of the first and largest of what has now become a network of regional film archives. The archive is a charitable trust, existing to preserve the region's moving image heritage. It is open to the public and holds film and television recordings from a wide variety of sources, including donations from the general public.

The archive, renamed the South West Film and Television Archive (SWFTA) in 2003, holds the entire surviving back catalogue of Westward and TSW programmes, and several tens of thousands of other items (which all have a connection to the south-west of England) donated by members of the general public.

The SWFTA, now known as The Box, aims to preserve moving image material as a resource for future generations. The archive is managed by a qualified archivist who is supported by a team of employed staff and volunteers, most of whom came from TSW. They regularly supply material for a wide variety of educational and other uses. They provide community film shows and help anyone with an interest in using or viewing the material they hold. SWFTA participated in the national digitising project Unlocking Film Heritage.

Studios
When TSW won the franchise, the company purchased Westward's studio facilities at Derry's Cross, Plymouth along with all the staff. The studios, which had suffered from a lack of investment under Westward, were completely refurbished with a £4 million investment programme which saw the introduction of new production equipment and an additional studio being constructed. The refurbishment was completed two years later.

When TSW lost its franchise, its successor, Westcountry, chose not to purchase the studios, preferring new facilities just outside Plymouth, at Langage Science Park, Plympton instead, ending 31 years of broadcasting from Derry's Cross Studios. Transmission control of the new station would not be handled in Plymouth as previously, but in Cardiff at HTV Wales headquarters. The old TSW studios were then stripped with the equipment being auctioned, and the building itself was converted into offices. A solicitors practice called Foot Anstey (formerly Foot & Bowden) was then based there until 16 March 2009 The former studios were demolished just before Christmas 2009 to make way for an adjacent retail, residential and hotel development.

In addition to the Plymouth base, TSW also operated a newsroom and remote studio in Yeovil, as well as local offices in Barnstaple and Exeter.

Station identity
TSW's symbol was an abstract design representing palm trees, rolling hills and water; features typical of the region.

The music accompanying the original ident was a section of the station theme, That's Soul, Write, written and composed by Will Malone, which was also aired regularly at closedown until 1985.

In September 1989, when the ITV network introduced a new corporate logo and national on-air identity, TSW was one of the five regions that didn't use the generic idents designed for the region, preferring to stay with their own idents.

Programming
Like its predecessor, TSW produced few programmes for the ITV network. Exceptions to this included the game shows, That's My Dog and Sounds Like Music and children's cartoon Tube Mice, about mice who lived beneath the London Underground. It also produced The Cut Price Comedy Show, a short-lived production broadcast in the early days of Channel 4. Locally, TSW continued to utilise the Westward star Gus Honeybun, a rabbit puppet that (along with the station's continuity announcers) read out birthday dedications on-air to children from the area, who had sent in their cards to him.

TSW also specialised in making relatively highbrow programmes for the region; in the arts world, it produced documentaries showcasing amongst others, leading concert pianist Moura Lympany, potter Bernard Leach, and sculptor Barbara Hepworth.

Scheduling opt-outs
TSW was a notably regional company, declaring itself as a channel in its own right, rather than just being part of the ITV network. It had a reputation for scheduling to suit its own requirements and would often broadcast particular shows at different times to the other ITV regions or even opt out of network activity completely. Such notable scheduling changes included:

 * Series two of Blockbusters was not broadcast in full. Around 50 editions of the 1984/5 series were shown eight months later, during summer holiday mornings: 1 July – 24 August 1985.
 * Weekday editions of Gus Honeybun's Magic Birthdays often replaced the first and last Children's ITV live in-vision continuity links of the day, from 1987 – 1990.
 * The Australian soap, Home and Away was moved from its 5:10pm teatime repeat slot to a much earlier time-slot of 3:27pm on 20 September 1989. It stayed in this afternoon time-slot for three years until September 1992.
 * The networked sitcom, The Piglet Files, starring Nicholas Lyndhurst, was not shown on TSW until a few months after its original run in all other ITV regions. Another networked sitcom, The Nineteenth Hole, starring Eric Sykes, was dropped mid-run after complaints from viewers regarding its politically incorrect humour.
 * The ITV Chart Show was dropped on occasions (mostly for special programmes) so that TSW could show its weekly news review for deaf people, The South West Week.

Additionally, Channel Television, the ITV contractor for the Channel Islands required a network feed from another nearby ITV region on the mainland, which was provided by Westward Television for many years, until it lost its franchise in 1981. TSW took over the requirement from 1982, until 1986, when Channel switched to TVS for the feed instead. After TVS lost its franchise in the 1991 ITV auction round, Meridian Broadcasting provided the network feed from 1993 onwards.

Programmes

 * About Britain (contributions for the ITV network)
 * Amoebas to Zebras
 * The Cut Price Comedy Show (for Channel Four)
 * Freeze Frame
 * Frootie Tooties
 * Gardens For All (1982–1992)
 * Get Fresh (contributions for the ITV network, 1986–88)
 * Ghost Train (contributions for the ITV network, 1989–1991)
 * Gus Honeybun's Magic Birthdays (1982–1992)
 * Highway (contributions for the ITV network, 1983–1992)
 * Interpub (1986–88)
 * ITV Telethon (local and networked contributions, 1988, 1990, 1992)
 * Judi (1984; featuring Judi Spiers)
 * Judi Goes On Holiday (1986)
 * Morning Worship (contributions for the ITV network, 1982–1992)
 * Mr TSW (male beauty pageant, 1982–85)
 * Nightcall
 * Postscript
 * Scene South West
 * Sounds Like Music
 * The South West Week (1982–1992)
 * That's My Dog (1984–88)
 * TeleViews
 * Today (1986–1989)
 * Today South West (1982–86)
 * Treasures of the Mindlord (1986)
 * TSW Community Action
 * TSW Farming Week
 * TSW Newsport (1982–1992)
 * TSW Sportsweek (1982 – c.1990)
 * TSW Today (1989–1992)
 * Tube Mice (1988)
 *  Tuesday View (1986–89)
 * Wavelines (1988–89)

title: Television South West


text:
TSW

TSW may refer to:

 * Tactical Support Wing, a unit of the United States Navy
 * Television South West, the ITV franchise holder for the South West England region from 1 January 1982 until 31 December 1992
 * The Secret World, a 2012 MMORPG from developer Funcom
 * Tiger Sports Wheels, a custom alloy wheel manufacturer
 * Tin Shui Wai, a town located in the northwestern part of the New Territories, Hong Kong, in Yuen Long District
 * Topical steroid withdrawal
 * Trader's and Scheduler's Workbench, Oil & Gas functionality for SAP ERP
 * Train Sim World, a 2018 video game from Dovetail Games
 * Tsuen Wan station, Hong Kong; MTR station code

title: TSW


text:
Alex Ross

Nelson Alexander Ross (born January 22, 1970) is an American comic book writer and artist known primarily for his painted interiors, covers, and design work. He first became known with the 1994 miniseries Marvels, on which he collaborated with writer Kurt Busiek for Marvel Comics. He has since done a variety of projects for both Marvel and DC Comics, such as the 1996 miniseries Kingdom Come, which he also cowrote. Since then he has done covers and character designs for Busiek's series Astro City, and various projects for Dynamite Entertainment. His feature film work includes concept and narrative art for Spider-Man (2002) and Spider-Man 2 (2004), and DVD packaging art for the M. Night Shyamalan film Unbreakable (2000). He has done covers for TV Guide, promotional artwork for the Academy Awards, posters and packaging design for video games, and his renditions of superheroes have been merchandised as action figures.

Ross's style, which usually employs a combination of gouache and wash, has been said to exhibit "a Norman-Rockwell-meets-George-Pérez vibe", and has been praised for its realistic, human depictions of classic comic book characters. His rendering style, his attention to detail, and the perceived tendency of his characters to be depicted staring off into the distance in cover images has been satirized in Mad magazine.

Early life
Alex Ross was born in Portland, Oregon, and raised in Lubbock, Texas, by his United Church of Christ minister father, Clark, and his mother, Lynette, a commercial artist from whom he would learn many of the trademarks of his artistic style. Ross first began drawing at age three, and was first influenced by superheroes when he discovered Spider-Man on an episode of the children's TV series The Electric Company.

He would later be influenced by comics artists such as John Romita Sr., Neal Adams, George Pérez and Bernie Wrightson, and attempted to imitate Pérez' style when he did superhero work, and Wrightson's when he did what he calls "serious" work. By age 16, Ross discovered the realistic work of illustrators such as Andrew Loomis and Norman Rockwell, and envisioned one day seeing such styles applied to comic book art.

At age 17, Ross began studying painting at the American Academy of Art in Chicago, where his mother had studied. During his years there, Ross discovered the work of other artists like J. C. Leyendecker and Salvador Dalí, whose "hyper-realistic quality", Ross saw, was not that far removed from that of comics. It was during this time that he formed the idea to paint his own comic books. Ross graduated after three years.

1990s
After graduating, Ross took a job at an advertising agency as a storyboard artist. Ross's first published comic book work was the 1990 five-issue miniseries, Terminator: The Burning Earth, written by Ron Fortier and published by NOW Comics. Ross created all of the art, from pencils through coloring for the series. He performed similar work on a variety of titles over the next few years. His first work for Marvel Comics was to have been printed in the science-fiction anthology series Open Space #5 but the title was cancelled with issue #4 (August 1990). Ross's story was printed in 1999 as a special supplement to Wizard's Alex Ross Special. In 1993, he completed his first painted superhero assignment, the cover of a Superman novel, Superman: Doomsday & Beyond.

During this time, Ross met writer Kurt Busiek, and the two began submitting proposals for series that would feature paintings as their internal art. Marvel agreed to a project that would tell much of the history of the Marvel Universe from the perspective of an ordinary person. That limited series, Marvels, was released in 1994, and chronicled the life of a photojournalist, as he reacted to living in a world of superheroes and villains.

Busiek, Ross, and penciller Brent Anderson created Astro City, first published by Image Comics in 1995 and later by WildStorm Comics. The series features an original superhero world and continues the theme of Marvels, exploring how ordinary people, superheroes and villains react to a world where the fantastic is commonplace. Ross paints the covers and helps set the costumes and the general look and feel for the series, which has been published sporadically in recent years.

In 1996, Ross worked with writer Mark Waid on the DC Comics limited series Kingdom Come, which presents a possible future for the DC Universe in which Superman and several other classic superheroes return from retirement to tame a generation of brutal antiheroes. The work featured Ross's redesigned versions of many DC characters, as well as a new generation of characters. Ross co-created the original character Magog, patterning his appearance and costume on Cable and Shatterstar, two characters created by Rob Liefeld. DC Comics writer and executive Paul Levitz observed that "Waid's deep knowledge of the heroes' pasts served them well, and Ross' unique painted art style made a powerful statement about the reality of the world they built."

Ross followed Kingdom Come with Uncle Sam, an experimental non-superhero work for DC's Vertigo line that examines the dark side of American history. Ross drew the lenticular covers for Superman: Forever #1 (June 1998) and Batman: No Man's Land #1 (March 1999). Between 1998 and 2003, writer Paul Dini and Ross produced annual tabloid-sized editions celebrating the 60th anniversaries of DC Comics' Superman (Superman: Peace on Earth), Batman (Batman: War on Crime), Shazam (Shazam! Power of Hope), and Wonder Woman (Wonder Woman: Spirit of Truth), as well as two specials featuring the Justice League, Secret Origins and Liberty and Justice.

2000s
In the early 2000s, with writer Jim Krueger, Ross plotted and designed characters for a trilogy of Marvel limited series, Earth X, Universe X, and Paradise X, which combined dozens of Marvel characters from various time periods.

When M. Night Shyamalan's film, Unbreakable was released to video in 2001, the DVD included an insert with Ross's original art, as well as a commentary by Ross, regarding superheroes, in the movie's special features.

In 2001, Ross won acclaim for his work on special comic books benefiting the families of those killed in the September 11, 2001, attacks, including his portraits of paramedics, police and firefighters. He has designed DC merchandise, including posters, dinner plates, and statues. In late 2001, Ross painted four covers to the December 8, 2001, TV Guide, which depicted Tom Welling, Kristin Kreuk and Michael Rosenbaum of the TV series Smallville, and Superman.

Ross designed a series of costumes for the 2002 film Spider-Man, though they were not used in the film. In the film's video game tie-in, as an Easter egg, it is possible to unlock a playable version of Ross's Spider-Man design. When using this, the Green Goblin will feature one of Ross's unused character outfits. Ross's design was featured as an unlockable costume and available in a white version in the PlayStation game Spider-Man 2: Enter Electro.

In early 2002, Ross designed the promotional poster for the 2002 Academy Awards, which depicted Oscar perched atop the First National Building. The Academy loaned Ross an actual Oscar statuette for a week for him to use as reference for the painting. Ross stated that he photographed members of his family as if they were receiving it. That same year, he was one of four artists who depicted Spider-Man on one of the covers to the April 27, 2002, issue of TV Guide as a promotional tie-in to the feature film Spider-Man.

Ross illustrated the cover art on the Anthrax albums We've Come for You All (2003), Music of Mass Destruction (2004), Worship Music (2011), and For All Kings (2016).

In 2003, Pantheon Books published the coffee table book Mythology: The DC Comics Art of Alex Ross, written and designed by Chip Kidd, and featuring a foreword written by M. Night Shyamalan. In late 2005, a paperback version of the book was published to include new artwork by Ross, including sketches for his Justice mini-series. Also in 2004, Ross designed 15 paintings for the opening credits of the film Spider-Man 2. The paintings presented key elements from the first film. Ross later donated the paintings to be auctioned off on eBay to benefit the United Cancer Front.

In 2005, Ross designed the DVD illustration covers for the re-release of Gatchaman by ADV Films. He appeared in a featurette discussing his involvement of Gatchaman in his career.

In August 2005, Ross worked again with writer Jim Krueger and penciler Doug Braithwaite on 12-issue, bi-monthly limited series Justice for DC Comics. The series focuses on the enemies of the Justice League of America banding together in an effort to defeat them.

The cover of the "Savior of the Universe Edition" DVD of the 1980 film Flash Gordon, released on August 7, 2007, features a cover painted by Ross. An avid fan of the film, he starred in a featurette on the DVD where he discussed the movie, which he names as his favorite movie of all time.

In 2008, Ross embarked on projects focusing on Golden Age characters: Project Superpowers with Jim Krueger for Dynamite Entertainment. That same year, Ross wrote and illustrated Avengers/Invaders. It features Marvel characters but was published by Dynamite Entertainment. The story pits World War II versions of Captain America, Namor, and other classic war characters against the modern Avengers groups. Late 2008 saw the release of two Ross prints that were made into T-shirts: one, "Bush Sucking Democracy Dry", featuring George W. Bush as a vampire sucking the blood from Lady Liberty, and the other, "Time for a Change", featuring Barack Obama as a superhero. The latter was made into a T-shirt, with which Obama was seen posing at a public event. Ross painted the "Kollectors Edition" cover for the console game Mortal Kombat vs. DC Universe. The artwork was released on October 9, 2008, as was a video chronicling Ross's process of painting it. Ross is featured in his own segment on the Blu-ray/DVD included in the package.

Dynamite Entertainment announced that Ross would illustrate covers for the Fighting American series.

2010s
Other Ross projects for Dynamite include acting as the creative director on The Phantom comic book series. and teaming with Kurt Busiek on Kirby: Genesis, an eight-issue miniseries which debuted in 2011. The series was their first full collaboration since Marvels 17 years previous, and features a large group of Jack Kirby's creator-owned characters, the rights to which were acquired by Dynamite, such as Silver Star, Captain Victory, Galaxy Green, Tiger 21, and the Ninth Men. Ross handled the series' co-plotting, designs, and covers, apart from overseeing the book overall with Busiek, who was the writer.

Since 2011, Ross has been painting covers for several Dynamite titles such as The Green Hornet, Silver Star, Captain Victory, The Bionic Man, Lord of the Jungle, The Spider, among others.

In 2012 Ross drew promotional artwork of Ratonhnhaké:ton, the main character of the video game Assassin's Creed III, used on the cover of the April 2012 issue of Game Informer and the collectible steelbook case provided with certain editions of the game. that same year, Ross returned to interior painted art with Masks, a story in which the Shadow, the Spider, the Green Hornet, Zorro, and others join forces to combat a mutual threat.

In 2013 Ross created an exclusive GameStop pre-order poster for the video game Watch Dogs, which was scheduled for debut November 19 of that year, but was delayed to 2014. The game is set in Ross's home city, Chicago, which Ross emphasized in the image by placing the Willis Tower and the elevated train tracks in the background.

With Marvel's "All-New, All-Different Marvel" relaunch, Ross did a variety of covers for the main comics in the relaunch such as the cover for The Amazing Spider-Man and Squadron Supreme.

In 2015, following the conclusion of that year's "Secret Wars" storyline, Ross designed the high-tech variation of Spider-Man's costume that the character wore during Dan Slott and Giuseppe Camuncoli's run on The Amazing-Spider-Man.

2020s
In 2020, Ross provided the main cover for the Marvel Comics book The Rise of Ultraman #1. In the ensuing early part of that decade, he had stints as the regular cover artist on Marvel titles including Iron Man, Black Panther, Captain America, and Immortal Hulk.

In April 2022, Ross was reported among the more than three dozen comics creators who contributed to Operation USA's benefit anthology book, Comics for Ukraine: Sunflower Seeds, a project spearheaded by editor Scott Dunbier, whose profits would be donated to relief efforts for Ukrainian refugees resulting from the February 2022 Russian invasion of Ukraine. Ross provided the cover to the hardcover edition of the book.

In September 2022, Ross released Fantastic Four: Full Circle, a 64 page graphic novel in which the Fantastic Four venture through the Negative Zone, on which Ross served as both writer and artist, in collaboration with colorist Josh Johnson for Marvel Comics. The book was the first long-form work that Ross both wrote and drew, and was his take on a classic '60s FF story by Stan Lee and Jack Kirby. The American Library Association listed it among their 2022 Best Graphic Novels for Adults, noting "The layouts and storytelling are unmistakably those of Alex Ross, but he has also exchanged his usual realistic palette for a bolder more expressive color scheme." Chris Neill, writing for Kotaku, praised the book, noting the "fairly meat and potatoes plot", but applauding the art, calling it "the best looking comic you'll see this year". Neill opined that whereas Ross' usual style can exhibit a stiffness by making the reader too aware that they are looking at a painting, thus hampering the storytelling flow, his decision to ink his lines and use a limited palette of flat colors with no modern computer shading techniques gave the art a greater quality of grit and texture. Neill also lauded the digital dot screen effect that harkened back to the technqiue used to render comics in decades past. Michael Cavna included it in The Washington Post's list of the Ten Best Graphic Novels of 2022.

Personal life
As of December 2018, Ross lives in the suburbs of Chicago.

Toys
DC Direct, the collectibles division of DC Comics, has produced three sets of action figures from the comic book Kingdom Come based on Alex Ross's artwork. The first set of figures included Superman, Wonder Woman, Green Lantern, and Hawkman. The second set included Batman, Red Robin, Captain Marvel, and Kid Flash. The last set included Magog, Flash, Armored Wonder Woman, and Deadman. An exclusive figure of Red Arrow was released through ToyFare magazine. DC Direct also released several other Ross-designed characters through their Elseworlds toylines. These figures included the Spectre, Norman McCay, Jade, Nightstar, Aquaman, and Blue Beetle. Ross designed the costume the current incarnation of Batwoman wears; this character has been released in action-figure form by DC Direct as part of its "52" line of toys.

DC Direct has released a line of action figures for the comic book Justice based on Alex Ross's artwork:

 * Series 1: Bizarro, Sinestro, Cheetah, Flash, Superman, Superman (variant)
 * Series 2: Aquaman, Batman, Black Canary, Black Manta, Parasite
 * Series 3: Green Lantern, the Joker, Plastic Man, Poison Ivy, Wonder Woman
 * Series 4: Black Adam, Hawkman, Shazam!, Solomon Grundy, Zatanna
 * Series 5: Brainiac, Green Arrow, Lex Luthor, Martian Manhunter, Martian Manhunter (Translucent), Red Tornado.
 * Series 6: Batman Armored, Green Lantern Armored, Hawkgirl, Scarecrow.
 * Series 7: Aquaman Armored, Gorilla Grodd, Green Lantern John Stewart, Superman Armored
 * Series 8: Batgirl, Captain Cold, Supergirl, Toyman

In 2019, Hasbro released several figures based on Alex Ross's art as part of the Marvel Legends line. The toys were released to celebrate the 80th anniversary of Marvel Comics, and included Ross-designed versions of Iron Man, Thor and Captain America.

Awards

 * National Cartoonists Society Comic Book "Reuben" Awards
 * 1998 National Cartoonists Society Comic Book "Reuben" Award for Superman: Peace on Earth.
 * 2022 National Cartoonist Society Reuben Award Best Graphic Novel Nominee (Pending), Fantastic Four: Full Circle
 * Eisner Awards
 * 1994 Will Eisner Comic Industry Awards – Nominee – Best Cover Artist: (for Marvels [Marvel])
 * 1994 Will Eisner Comic Industry Awards – Winner – Best Painter/Multimedia Artist: (Marvels (Marvel))
 * 1996 Will Eisner Comic Industry Awards – Winner – Best Cover Artist: (for Kurt Busiek's Astro City [Jukebox Productions/Image])
 * 1997 Will Eisner Comic Industry Awards – Winner – Best Cover Artist: (for Kingdom Come [DC] and Kurt Busiek\'s Astro City [Jukebox Productions/Homage])
 * 1997 Will Eisner Comic Industry Awards – Winner – Best Painter/Multimedia Artist: (Kingdom Come (DC Comics))
 * 1998 Will Eisner Comic Industry Awards – Winner – Best Cover Artist: (for Kurt Busiek's Astro City [Jukebox Productions/Image] and Uncle Sam [DC/Vertigo])
 * 1998 Will Eisner Comic Industry Awards – Winner – Best Painter/Multimedia Artist: (Uncle Sam [DC Comics/Vertigo])
 * 1999 Will Eisner Comic Industry Awards – Winner – Best Painter/Multimedia Artist: (Superman: Peace on Earth [DC Comics])
 * 2000 Will Eisner Comic Industry Awards – Winner – Best Cover Artist: (for Batman: No Man's Land, Batman: Harley Quinn, and Batman: War on Crime [DC]; and Kurt Busiek's Astro City [Homage/DC/Wildstorm]; and America's Best Comics alternate #1 [Wildstorm/DC])
 * 2000 Will Eisner Comic Industry Awards – Winner – Best Painter/Multimedia Artist: (Batman: War on Crime (DC Comics))
 * 2003 Will Eisner Comic Industry Awards – Winner – Bob Clampett Humanitarian
 * 2010 Will Eisner Comic Industry Awards – Nominee – Best Cover Artist: (Astro City: The Dark Age (DC Comics/WildStorm); Project Superpowers (Dynamite))
 * Harvey Awards
 * 1994 Harvey Awards Best Artist or Penciller Alex Ross, for Marvels (Marvel Comics)
 * 1997 Harvey Awards Best Artist or Penciller Alex Ross for Kingdom Come (DC)
 * 1996 Harvey Awards Best Cover Artist Alex Ross, for Kurt Busiek's Astro City #1 (Image)
 * 1997 Harvey Awards Best Cover Artist Alex Ross, for Kingdom Come #1 (DC)
 * 1998 Harvey Awards Best Cover Artist Alex Ross, for Kurt Busiek's Astro City (Image/Homage), Batman: Legends of the Dark Knight #100 (DC), Squadron Supreme (Marvel Comics)
 * 1999 Harvey Awards Best Cover Artist Alex Ross, for Kurt Busiek's Astro City (Image/Homage), Superman Forever (DC), Superman: Peace on Earth (DC)
 * 1994 Harvey Awards Best Continuing or Limited Series Marvels, by Kurt Busiek and Alex Ross; edited by Marcus McLaurin (Marvel Comics)
 * 1995 Harvey Awards Best Single Issue or Story Marvels #4, by Kurt Busiek and Alex Ross; edited by Marcus McLaurin (Marvel Comics)
 * 2000 Harvey Awards Best Graphic Album of Original Work Batman: War on Crime by Paul Dini and Alex Ross, edited by Charles Kochman and Joey Cavalieri (DC)
 * 1995 Harvey Awards Best Graphic Album of Previously Published Work Marvels by Kurt Busiek and Alex Ross; edited by Marcus McLaurin (Graphitti Graphics)
 * 1994 Harvey Awards Special Award for Excellence in Presentation Marvels, by Kurt Busiek and Alex Ross; edited by Marcus McLaurin; design by Joe Kaufman and Comicraft (Marvel Comics)

Ross won the Comics Buyer's Guide's CBG Fan Award for Favorite Painter seven years in a row, resulting in that publication's retirement of that category. Comics Buyer's Guide Senior Editor Maggie Thompson commented in regard to this in 2010, "Ross may simply be the field's Favorite Painter, period. That's despite the fact that many outstanding painters are at work in today's comic books." Ross was also named Best Cover Artist by the CBG Awards 11 years in a row, from 1995 to 2005.

Ross won the 2005 Wizard Fan Award for Favorite Painter (Justice)

DC Comics

 * Sandman Mystery Theatre Annual #1 (eight pages, among other artists) (1994)
 * Kingdom Come, miniseries, #1–4 (1996)
 * U.S. (a.k.a. Uncle Sam), miniseries, #1–2 (1997)
 * Superman and Batman: World's Funnest (three pages, among other artists) (2000)
 * Batman Black and White Vol. 2, "Case Study" (eight pages, among other artists) (2002)
 * Action Comics #800 (one page, among other artists) (2003)
 * The World's Greatest Super-Heroes, collected anthology (2005)
 * Superman: Peace on Earth (1998)
 * Batman: War on Crime (1999)
 * Shazam!: Power of Hope (2000)
 * Wonder Woman: Spirit of Truth (2001)
 * JLA: Secret Origins (2002)
 * JLA: Liberty and Justice (2003)
 * Justice, limited series, #1–12 (painting over Doug Braithwaite pencils, 2005–2007)
 * JSA Kingdom Come Special: Superman (pencil art, colors by Alex Sinclair) (2009)

Dynamite Entertainment

 * Avengers/Invaders, limited series, #1–12 (2008–2009) (Marvel/Dynamite)
 * Project Superpowers #1–8; vol. 2 #1–13 (2008–2010)
 * Kirby Genesis #0–8 (with Jack Herbert) (2011-2012)
 * Masks #1 (2012)

Eclipse Comics

 * Miracleman: Apocrypha #3 (nine page story) (1992)

Image Comics

 * Battle of the Planets #0.5 (pencils only, among other artists) (2002)

Marvel Comics

 * Clive Barker's Hellraiser #17–18 (1992)
 * Marvels, miniseries, #0–4 (1994)
 * Earth X, miniseries, #1–12 (backup text stories) (1999–2000)
 * The Torch, miniseries, #1–8 (script) (2009–2010)
 * Captain America #600 (two pages, among other artists) (2009)
 * Marvelocity: The Marvel Comics Art of Alex Ross (ten pages) (2019)
 * Fantastic Four: Full Circle (writer and artist) (2022)

Now Comics

 * Terminator: The Burning Earth #1–5 (1990)

DC Comics

 * Action Comics #871 (2009)
 * Astro City:
 * Astra Special #1–2 (2009)
 * Astro City vol. 3 #1–46 (2013–2017)
 * A Visitors Guide (2004)
 * Beauty (2008)
 * Dark Age, Book One #1–4 (2005)
 * Dark Age, Book Two #1–4 (2007)
 * Dark Age, Book Three #1–4 (2009)
 * Dark Age, Book Four #1–4 (2010)
 * Dark Age 1: Brothers and Other Strangers (2008)
 * Local Heroes #1–5 (2003–04)
 * Samaritan (2006)
 * Silver Agent (2010)
 * Special #1 (2004)
 * Batman #676–686 (2008–2009)
 * Batman: Harley Quinn #1 (1999)
 * Batman: Legends of the Dark Knight #100 (1997)
 * Batman: No Man's Land #1 (1999)
 * Black Adam: The Dark Age, miniseries, #1 (2007)
 * Captain Atom: Armageddon (2005)
 * Countdown to Infinite Crisis #1 (painting over Jim Lee pencils) (2005)
 * Crisis on Multiple Earths #1, 3–4 (2002–2006)
 * DC Comics Presents (Julius Schwartz tribute):
 * The Flash (2004)
 * Mystery in Space (2004)
 * Detective Comics #860 (2010)
 * Green Lantern vol. 4 #1 (variant cover)
 * The Greatest Stories Ever Told:
 * Batman #1–2 (2005–2007)
 * Flash (2007)
 * Green Lantern (2006)
 * JLA (2006)
 * Joker (2008)
 * Shazam! (2008)
 * Superman #1–2 (2004–2006)
 * Superman/Batman (2007)
 * Wonder Woman (2007)
 * History of the DC Universe (2002)
 * Justice League of America vol. 2 #12; The Lightning Saga (2007–2008)
 * JSA #68–69, 72–81; Annual #1 (2005–2008)
 * JSA Kingdom Come Special: Magog (2009)
 * JSA Kingdom Come Special: The Kingdom (2009)
 * Justice Society of America vol. 3 #1–26 (2007–2009)
 * 9-11: The World's Finest Comic Book Writers & Artists Tell Stories to Remember #2 (2002)
 * Space Ghost, miniseries, #1–6 (2005)
 * Spectre vol. 3 #22 (1994)
 * Supergirl vol. 4 #35
 * Superman #675–683 (2008)
 * Superman: Forever #1 (1998)
 * Superman: Strength, miniseries, #1–3 (2005)
 * Superman/Fantastic Four (1999)
 * Superman vs. the Flash (2003)

America's Best Comics

 * America's Best Comics Special #1 (2001)
 * Promethea #1 (1999)
 * Tomorrow Stories #1 (1999)
 * Tom Strong #1 (1999)
 * Top 10 #1 (1999)

Dynamite Entertainment

 * A Game of Thrones #1–2 (2011)
 * Avengers/Invaders, limited series, #1–12; Giant-Size #1 (2008–2009) (Marvel/Dynamite)
 * Bionic Man #1–5 (2011)
 * Black Terror #1–10 (2008–2009)
 * Buck Rogers #1 (2010)
 * Captain Victory #1–4 (2011–2012)
 * Death-Defying' Devil #1–4 (2008–2009)
 * Dragonsbane #1 (2012)
 * The Green Hornet #1–12 (2010–2011)
 * Kirby Genesis #1–4 (2011)
 * Lord of the Jungle #1 (2012)
 * Lone Ranger vol. 2 #1 (2012)
 * Silver Star #1–3 (2011)
 * Last Phantom #1–10 (2010–2012)
 * Masquerade #2–4 (2009)
 * Vampirella #1 (2010)
 * Voltron #1–2 (2011–2012)

Marvel Comics

 * All-New, All-Different Avengers #1–15 (2015–2016)
 * All-New Captain America #1 (2014)
 * The Amazing Spider-Man #568, 600, 789–800 (2008–2018), vol. 4 #1–32 (2015–2017)
 * Avengers vol. 6 #1–674 (2016–2017)
 * Avengers vol. 7 #10/700 (2018)
 * Black Panther vol. 6 #1 (2016)
 * Captain America vol. 5 #34 (2008)
 * Captain America vol. 8 #695 (2017)
 * Captain America vol. 9 #1–30 (2018–2021)
 * Captain Marvel vol. 3 #1, 3, 17 (2002–2003)
 * Captain Marvel vol. 8 #1 (2019)
 * Daredevil #500 (2009)
 * Daredevil/Spider-Man, miniseries, #1–4 (2001)
 * Earth X #0-12 (1999)
 * Falcon vol. 2 #1 (2017)
 * Fantastic Four vol. 6 #1, 6
 * Fantastic Four: Full Circle (2022)
 * 4 (Universe X Special) #1 (2000)
 * Guardians of the Galaxy vol. 3 #18 (2014)
 * Guardians 3000 #1–6 (2014–2015)
 * Marvels X #1–6 (2020)
 * The Immortal Hulk #1–50 (2018–2021)
 * The Incredible Hulk #600 (2009)
 * Invaders Now!, miniseries, #1–5 (2010–2011)
 * The Invincible Iron Man vol. 3 #600 (2018)
 * The Mighty Captain Marvel #1 (2017)
 * Miracleman, reprint, #5 (variant cover) (2014)
 * Paradise X #0–12 (2002)
 * The Rise Of Ultraman #1 (2020)
 * Spider-Woman, vol. 2 #1 (2009)
 * The Torch miniseries #1–8 (2009–2010)
 * Uncanny X-Men #500 (2008)
 * Savage Hulk #1 (2014)
 * Secret Wars #1–9 (2015)
 * Tony Stark: Iron Man #1, 9 (2018–2019)
 * Universe X #0–12 (2001)

Other publishers

 * Battle of the Planets #1–12 (2002–2003) (Image)
 * Battle of the Planets/Thundercats (2003) (DC/Image)
 * Battle of the Planets/Witchblade (2003) (Image)
 * Call of Duty: Black Ops II "Origins" Downloadable Content Cover Art (2013)
 * Life with Archie #37 (variant cover) (Archie Comics)
 * Star Wars #1–20 (2013–2014) (Dark Horse)

title: Alex Ross