Dimitrios Alexandros

Evangelos Zervopoulos

Alexandros Geramanis

Asterios Toulakis

Dimitrios Papamichail

Theofanis Triantafylloy

Katia Tasoulas

Kermanidis

Language Processing for Predicting Suicidal Tendencies: A Case Study in Greek Poetry

Keywords: NLP, Suicide, Poetry

des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

A significant amount of research has been conducted on the topic of identifying mental health illnesses through the means of text analysis. For instance, such analysis has been used to predict various psychological states [START_REF] Pennebaker | Linguistic styles: Language use as an individual difference[END_REF]. Being able to detect such psychological states in their early stages, through the means of Natural Language Processing (NLP) techniques could be of vital importance, before they lead to an unfortunate conclusion for the individual.

Furthermore, a great deal of effort has gone into discerning suicidal tendencies through the writer's language use, as suicide is a leading cause of death all over the world [START_REF] Bertolote | A global perspective on the magnitude of suicide mortality[END_REF]. More specifically, there have been multiple recent attempts focusing on suicide notes. Pestian et al. [START_REF] Pestian | Suicide note classification using natural language processing: A content analysis[END_REF] concluded that NLP could be used to differentiate between genuine and elicited suicide notes, by achieving a higher classification rate than mental health professionals. Many have tried to tackle the problem of emotion detection in suicide notes utilizing various methods, including entropy classification [START_REF] Wicentowski | emotion detection in suicide notes using maximum entropy classification[END_REF] and latent sequence models [START_REF] Cherry | Binary classifiers and latent sequence models for emotion detection in suicide notes[END_REF] in the pursuit of better understanding the suicidal mind.

Additionally, with the rise of the digital era and widespread use of the Internet, the phenomena of micro-blogging and social media emerged. This has resulted in an increasingly large proportion of people who use these means daily to express their feelings and opinions. Thus, there has been major interest in examining whether these can be useful in predicting suicidal ideation. Zhang et al. [START_REF] Zhang | Using linguistic features to estimate suicide probability of chinese microblog users[END_REF] deduced that such a task is realizable using the Chinese version of the Linguistic Inquiry and Word Count (LIWC), as well as Latent Dirichlet Allocation (LDA), on Chinese micro-blog users' data. Litvinova et al. [START_REF] Litvinova | Identification of suicidal tendencies of individuals based on the quantitative analysis of their internet texts[END_REF] developed a mathematical model to predict suicidal tendencies based on Russian Internet texts, employing numerical rather than linguistic features. Burnap et al. [START_REF] Burnap | Machine classification and analysis of suicide-related communication on twitter[END_REF] aimed to identify suicide related topics from posts on Twitter by training baseline classifiers, then improving upon them with an ensemble classifier.

It has been proven that suicide rates among artists, such as musicians and poets, are significantly higher than rates pertaining to the general population [START_REF] Jamison | Manic-depressive illness and creativity[END_REF][START_REF] Raeburn | Psychological issues and treatment strategies in popular musicians: A review, part i[END_REF][START_REF] Stack | Suicide among artists[END_REF]. Lightman et al. [START_REF] Lightman | Using computational text analysis tools to compare the lyrics of suicidal and non-suicidal songwriters[END_REF] deployed Coh-Metrix and LIWC to contrast textual features of suicidal and non-suicidal songwriters. Mulholland and Quinn [START_REF] Mulholland | Suicidal tendencies: The automatic classification of suicidal and non-suicidal lyricists using nlp[END_REF] composed a corpus consisting of songs from various English lyricists, which was comprised of a development, a training and a test set. This corpus was then used to derive lexical, syntactic, semantic class and n-gram features. These were then input into the Waikato Environment for Knowledge Analysis (Weka) to compare the performance of multiple machine learning algorithms in classifying whether or not the song was written by a suicidal lyricist. The algorithm that proved to have the highest classification rate was SimpleCart, with an overall accuracy of 70.6%. Pajak and Trzebiński [START_REF] Pająk | Escaping the world: Linguistic indicators of suicide attempts in poets[END_REF] used LIWC to analyze Polish poems from six separate poets. Afterwards, ANOVA and logistic regression were used to extract the most prevalent features in identifying suicidal predisposition. They drew conclusions similar to those of previous works.

Perhaps one of the most influential contributions in the text analysis of poets is that of Stirman and Pennebaker [START_REF] Stirman | Word use in the poetry of suicidal and nonsuicidal poets[END_REF], considering their results have been the basis of many different studies, such as [START_REF] Lightman | Using computational text analysis tools to compare the lyrics of suicidal and non-suicidal songwriters[END_REF][START_REF] Mulholland | Suicidal tendencies: The automatic classification of suicidal and non-suicidal lyricists using nlp[END_REF][START_REF] Pająk | Escaping the world: Linguistic indicators of suicide attempts in poets[END_REF]]. The methodology they followed was the collection of 300 poems, and the study, with the aid of LIWC, of linguistic characteristics that could be distinguished between suicidal and non-suicidal poets. Furthermore, they investigated how such characteristics accord with the two most dominant suicide models, namely Durkheim's model [START_REF] Durkheim | Suicide: A study in sociology[END_REF], where suicide rate is linked to a society's integration level, and the hopelessness model [START_REF] Petrie | Sense of coherence, self-esteem, depression and hopelessness as correlates of reattempting suicide[END_REF], where an individual is overcome with negative emotions, such as hopelessness and helplessness, which ultimately drive them to suicide. These characteristics were then examined as to how they varied in different stages of the poets' careers. It was concluded that suicide can in fact be predicted by their language use, finding stronger support for the social integration suicide model, and that there's no significant variation over time.

The purpose of this study is to train a machine learning model, which classifies a poem by the poet's proclivity towards suicide, based on textual features.

In contrast to previous research in this area, the study will be focusing on Greek poetry of the 20th century, and aims to examine whether preceding results, derived mostly from English language works, can be verified. These include higher use of the first-person singular form, compared to the first-person plural form, more frequent use of death and sexual-related words, as well as fewer overall positive emotion words [START_REF] Stirman | Word use in the poetry of suicidal and nonsuicidal poets[END_REF]. Overall, the methodology followed differs compared to previous efforts, given the lack of available tools for Greek, which resulted in the investigation of verb suffixes as features, as well as measuring in a novel manner the emotion of a poem's lyrics set in the range of [0, 2], in hopes of increasing the overall reliability of the corpus' annotation. The algorithms used were for the most part examined in previous research, and have been shown to perform relatively well in these kinds of tasks.

The rest of this paper is organized as follows. Section 2 describes the collected data, as well as the process and criteria for gathering it. Section 3 presents the feature vector that represents each poem, and why the respective values were selected. In Section 4, the classification experiments are described in detail, including the algorithms used and their results. Section 5 illustrates some of the difficulties faced during the process of classifying a poet's suicidal ideation by their poem, especially in a language with a scarcity of processing tools. Finally, Section 6 presents future improvements that could be made and a conclusion of what was accomplished in this study.

Data Collection

A corpus of 90 poems was constructed, consisting of poems from 7 poets who committed suicide and 6 who did not. The number of poems is equally distributed between the two groups. Moreover, the number of poems from each poet ranges from 5 to 9. The vast majority of poets are male (with the exception of two female poets in the suicidal group), who lived in approximately the same period of time, i.e. in the early to mid 1900s. The rationale behind this requirement was for the poets to belong to the same phase of the Greek language history, as the writing style of Greek changed significantly during the second half of the 20th century. Specifically, Katharevousa was abolished as the official Greek language in 1976 and was replaced by Modern Greek.

It was of significant importance that the poets in the suicide group undoubtedly took their own life. Similarly, special attention was paid so that poets in the non-suicide group did not have a history of self-harm or suicide attempts. All of the above is illustrated in Table 1. The size of the poems varies between 80-300 words, with an average size of 155.35. For each poet, all poems were randomly selected, with no distinction as to the nature of their content, e.g. a poem particularly high in negative emotion was not specifically selected for a poet who committed suicide. The above criteria, combined with the overall low suicide rates of Greek poets, significantly restricted the size of the corpus. The poems were stripped of all punctuation marks and accentuation using a Python script. This was required by certain parts of the annotation process described next, so that they could be automated.

Feature Description

Every poem is represented as a feature-value learning vector. The features that were selected for designing the vector are presented below. Some of these were based on the work of Kao and Jurafsky [START_REF] Kao | A computational analysis of style, affect, and imagery in contemporary poetry[END_REF] as well as Stirman and Pennebaker [START_REF] Stirman | Word use in the poetry of suicidal and nonsuicidal poets[END_REF], whereas others are novel, which are mostly applicable to the Greek language. A large number of features selected represent sums of occurence of linguistic characteristics of interest throughout the entire poem, which were normalized by the poem's length. These sum values for each poem were then normalized across the entire corpus using the well known normalization transformation of Equation 1, where v is the initial feature value, v min and v max are the minimum and maximum values of the feature across all poems, and v norm is the resulting normalized value.

V norm = v -v min v max -v min (1)
Overall, the number of features that were explored reached 37 in total.

Vocabulary Features

The vocabulary feature that was chosen is the type to token ratio (TTR), which is used as an indicator of the poem's richness in vocabulary [START_REF] Kao | A computational analysis of style, affect, and imagery in contemporary poetry[END_REF].

Morphosyntactic Features

The social integration model suggests that individuals who commit suicide have failed to integrate with society, so they are expected to be more self-centered, which seems to be manifested through the use of more first-person singular words, as opposed to first-person plural words [START_REF] Stirman | Word use in the poetry of suicidal and nonsuicidal poets[END_REF]. Based on that observation, the two morphosyntactic features that were selected were the count of occurrences of first-person singular and first-person plural verbs. Due to the lack of reliable morphological analysis tools for Greek, especially for the historical phase of the language targeted herein, these counts were obtained using a set of predefined verb suffixes (Table 2), that constitute person and number morphemes. The core set of these suffixes was found in [START_REF] Wictionary | [END_REF], and was subsequently enriched by the authors of this paper. Afterwards, a Python script was used to identify them in the poems. When any tense of a base suffix is found, it counts towards the base's occurrence, e.g. the occurrence of suffix ειρω is equivalent to that of ερνω. These bases are also used as features, to examine whether a subset of them are more prevalent in the process of the classification. All in all, these constitute 32 of the 37 features that were examined, 30 of which are the aforementioned suffixes.

Semantic Class Features

Suicidal poets are expected to deal more with negative emotion than with positive feelings, according to the hopelessness suicide model [START_REF] Petrie | Sense of coherence, self-esteem, depression and hopelessness as correlates of reattempting suicide[END_REF]. To test this, each verse was assigned a number ranging from 0 to 2 for the positive emotion it expressed, and 0 to 2 for the negative emotion. The range is overall lower than ones used in previous studies, as [-5, 5] has been used for example in [START_REF] Nielsen | A new ANEW: evaluation of a word list for sentiment analysis in microblogs[END_REF]. This was done to increase the overall reliability of the manual annotation. These numbers were then summed up for all verses of a poem, resulting in two features: one sum reflecting the positive, and one reflecting the negative emotion.

Additionally, sexual and death-related references were included as features, as has been suggested, in an ad-hoc analysis, that they can contribute to identifying suicidal tendencies [START_REF] Stirman | Word use in the poetry of suicidal and nonsuicidal poets[END_REF]. For these features, the number of verses for each poem that were deemed to contain sexual or death references were summed up for each poem.

Each poem was annotated with the aforementioned semantic information by two Greek language native speakers. When a verse led to contrasting annotators' decisions, the feature value was decided upon by the majority vote of the authors of the present work.

Prediction Results

Each poem was represented using the aforementioned features. The Weka machine learning workbench [START_REF]Weka 3 -Data Mining with Open Source Machine Learning Software in Java[END_REF] was used for running prediction experiments pertaining to poets' suicidal tendencies. The baseline for our comparisons is the prediction accuracy of 50%, as the two groups are evenly split. Since the corpus was not divided into different sets for training and testing, Weka's k-fold cross validation functionality was used, for k=5. A variety of tree and rule-based algorithms were compared as to their performance at accomplishing this task. The parameters used, which achieved the best results when running these tests, are described below. These are well-established algorithms in dealing with such tasks, JRIPPER was used in [START_REF] Pestian | Suicide note classification using natural language processing: A content analysis[END_REF], C4.5 was used in [START_REF] Pestian | Suicide note classification using natural language processing: A content analysis[END_REF] and [START_REF] Burnap | Machine classification and analysis of suicide-related communication on twitter[END_REF] and finally Simple CART was used in [START_REF] Mulholland | Suicidal tendencies: The automatic classification of suicidal and non-suicidal lyricists using nlp[END_REF].

The rule-based classifier tested was JRIPPER. This algorithm was run using 50 optimization runs, achieving a classification rate of 84.4% when making use of pruning. Afterwards, three different tree classifiers were tested, the first one being Simple CART. This resulted in an accuracy of 82.8%. Another tree based classifier used was RandomForest, which had a classification rate of 82.2%, after having performed 10,000 iterations. The last algorithm tested was C4.5 (known as J48 in Weka) classifying 84.5% of the instances correctly, with 0.25 as the confidence factor, performing pruning.

The algorithm that eventually achieved the highest classification rate was C4.5, reaching 84.5%. Various statistics are presented in Table 3 detailing some of the tests done, and the models derived from C4.5 are presented in Fig 1 The resulting models indicate that the overall classification result is largely based on the positive and negative emotion scores. At a first glance, and considering the researchers' lack of a professional literary background, the suffixes don't Fig. 2. The decision tree generated by C4.5 without pruning seem to form some clear pattern which could help identify suicidal ideation. However, it is evident that the results do differ based on the occurence of singular, as opposed to plural, verb suffixes, which does support Durkheim's model.

Tree and rule-based classifiers perform fairly well and result in simple models, which is in part attributed to the manual nature of the annotation process, as a result of the lack of reliable processing tools for the Greek language, as well as to the nature of the semantic features, which are of high-level linguistic knowledge. They have proven to perform fairly well in similar research conducted in the past as well. As a basis for comparison, the results of previous studies are presented in this paragraph. Pestian et al. [START_REF] Pestian | Suicide note classification using natural language processing: A content analysis[END_REF] managed to accurately distinguish between elicited and genuine suicide notes 78% of the time. Litvinova et al [START_REF] Litvinova | Identification of suicidal tendencies of individuals based on the quantitative analysis of their internet texts[END_REF] reached a 71.5% classification rate of deciding whether Russian internet texts were suicidal or not. Mulholland and Quinn [START_REF] Mulholland | Suicidal tendencies: The automatic classification of suicidal and non-suicidal lyricists using nlp[END_REF] achieved a performance of 70.6% in identifying suicidal tendencies of songwriters through their lyrics.

Discussion

Tackling the task of identifying suicidal ideation in poetry, particularly for a language where no previous research has been conducted, is certain to pose many difficulties. The construction of the corpus was largely difficult due to the strict criteria described in Section 2. It was hard to determine whether someone did not at least attempt to commit suicide in their lifetime, as it may not have necessarily become known to people outside their close social circle. Furthermore, in the case where it was ambiguous whether the cause of death was actually suicide, as is the case with Maria Polydouri, the poet was left out, which further shortened the number of candidate poems. Perhaps, one solution to this would have been to focus more on the few poets that have written a lot of poems. This does, however, introduce the risk of the classifier learning the patterns of those particular poets and being unable to accurately classify poems by others.

Additionally, and perhaps most importantly, the process of annotating the corpus was especially demanding, since the most prevalent tools used in previous research were not available for Greek. Such tools include LIWC, the UAM CorpusTool, various word-lists, such as AFINN and ANEW, used in sentiment analysis tasks, as well as corpora used in previous studies, which could have been used for comparison. This resulted in the manual annotation of a significant portion of the selected features. It was also a major restriction in the selection of the features, as the more sophisticated a feature is, the more rigorous the process of identifying it in the text needs to be. Not adhering to the appropriate level of rigorousness introduces further potential bias into the data, and given the annotators' lack of a professional literary background, this would have been an increasingly precarious task.

Conclusion and Future Work

In conclusion, a corpus of poems was composed to identify suicidal ideation in Greek poetry of the 20th century. This proved to be a challenging task, since there has not been any previous work done on the language that was selected. Nonetheless, the resulting classifier, C4.5, reached an accuracy of 84.4%. The features explored were mostly semantic in nature, while also utilizing morphosyntactic features, such as verb suffixes which are language specific and have not been investigated before. The results are overall promising and the features selected are easily portable across different strategies, which should allow future studies to confirm how successful our methodology was.

The construction of a properly annotated corpus proved to be the most challenging part of this task. Therefore, the development of such a corpus would be worth looking into, as it would greatly aid future efforts in studying NLP related topics for Greek texts. It is of critical importance, as has been showcased by the attempts in this study, to pay special attention when manually annotating data, and to adhere to best practices which have been studied extensively before, for example by Janyce et al. [START_REF] Wiebe | Annotating expressions of opinions and emotions in language[END_REF].

There's also a scarcity of available tools, which are often required in NLP related tasks, due to the complex structure of the Greek language. For example, tools for lemmatization and stemming are somewhat difficult to implement, partly due to punctuation and grammar rules. This indicates it would be meaningful to spend time developing such tools, before further progress into more intensive NLP tasks is made. Considering the above, any future advancements in the area will be interesting to behold, after this first attempt has been made, to keep track of how such difficulties are handled.

Fig. 1 .

 1 Fig. 1. The decision tree generated by C4.5 with pruning

Table 1 .

 1 Composition of Corpus

	Poet	Poems Year of Death Suicide
	Giorgos Makris	7	1968	Yes
	Kostas Karyotakis	5	1928	Yes
	Alexis Traianos	5	1980	Yes
	Minas Dimakis	5	1980	Yes
	Katerina Gogou	8	1993	Yes
	Napoleon Lapathiotis	7	1944	Yes
	Koralia Andreadis	8	1976	Yes
	George Seferis	9	1971	No
	Tellos Agras	7	1944	No
	Constantine P. Cavafy	7	1933	No
	Kostis Palamas	8	1943	No
	Nikolaos Kavvadias	7	1975	No
	Odysseus Elytis	7	1996	No

Table 2 .

 2 Suffixes used for the morphosyntactic features

	Base Suffix		Different Tenses
		Singular Active Construction
	αβω	αβω	αβα	αψα	αψω
	αζω	αζω	αζα	ασα	ασω
	αινω	αινω	αινα	ηνω
	εινω	εινω	εινα	εισα εισω
	ερνω	ερνω	ερνα	ειρα	ερα	ειρω
	ευω	ευω	ευα	εψα	εψω
	ηνω	ηνω	ηνα	ησα	ησω
	ιζω	ιζω	ιζα	ισα	ισω
	ινω	ινω	ινα	ωσα ωσω
	λλω	λλω	λλα	ιλα	ιλω
	ττω	ττω	ττα	ξα	ξω
	ωνω	ωνω	ωνα	ωσα ωσω
	ω
		Plural Active Construction
	αβουμε	αβουμε αβαμε αψαμε αψουμε
	αζουμε	αζουμε αζαμε ασαμε ασουμε
	αινουμε	αινουμε αιναμε ησαμε ησουμε
	εινουμε	εινουμε ειναμε εισαμε εισουμε
	ευουμε	ευουμε ευαμε εψαμε εψουμε
	ηνουμε	ηνουμε ηναμε ησαμε ησουμε
	ιζουμε	ιζουμε ιζαμε ισαμε ισουμε
	ινουμε	ινουμε ιναμε σαμε σαμεν σουμε
	λλουμε	λλουμε λλαμε λαμε λουμε
	ττουμε	ττουμε τταμε ξαμε ξουμε
		Singular Passive Construction
	αμαι	αμαι
	ουμαι	ουμαι ουμουν
	ιεμαι	ιεμαι ιομουν
	ομαι	ομαι	ομουν
	μαι	μαι	μουν μουνα ηκα	ηθω
		Plural Passive Construction
	ομαστε	ομαστε ομασταν
	μαστε	μαστε μασταν ουμε ηκαμε

Table 3 .

 3 and Fig 2. Detailed accuracy for both classes by each algorithm

	Algorithm	Precision Recall F-Measure Class
	JIPPER (without pruning)	0.739	0.756	0.747	TRUE
		0.750	0.733	0.742	FALSE
	JRIPPER (with pruning)	0.830	0.867	0.848	TRUE
		0.860	0.822	0.841	FALSE
	Random Forest	0.800	0.800	0.800	TRUE
		0.800	0.800	0.800	FALSE
	Simple CART (with pruning)	0.784	0.889	0.833	TRUE
		0.872	0.756	0.810	FALSE
	Simple CART (without pruning)	0.848	0.867	0.857	TRUE
		0.864	0.844	0.854	FALSE
	C4.5 (with pruning)	0.830	0.867	0.848	TRUE
		0.860	0.822	0.841	FALSE
	C4.5 (without pruning)	0.787	0.822	0.804	TRUE
		0.801	0.800	0.800	FALSE


Vassiliki Gkantouna

Vaios Papaioannou

Giannis Tzimas

Zlatan Sabic

An approach for Domain-specific Design Pattern Identification based on Domain Ontology

Keywords: Domain ontologies, Domain-specific design patterns, Content Management Systems

In this work, we present an approach for supporting the identification of domain-specific design patterns based on domain's ontology, since the latter encapsulates the knowledge about the problem domain. More specifically, the proposed approach automatically analyzes the designs of a collection of domainspecific websites in terms of all the recurrent patterns occurring among them, both in the organization of their content and the front-end interface of their pages, resulting in a set of reusable design solutions which are commonly used in them by designers as building blocks for addressing typical domain problems. Then, evaluation is performed according to a number of inspection steps. At a first level, the recurrent patterns occurring at content organization, i.e., the common configurations of domain concepts occurring among website pages are evaluated by matching them against the domain's ontology and selecting the ones which are in alignment with the domain's context. At a second level, the recurrent patterns occurring at front-end organization (i.e., the common configurations of front-end design elements) are evaluated towards their consistent and effective use in designs of the collected websites. Finally, the approach categorizes the various reusable design solutions and recommends the ones with the best evaluation results as candidate domain-specific design patterns.

Introduction

Domain-specific design patterns [START_REF] Pree | Essential Framework Design Patterns[END_REF]) are a powerful conceptual tool for designing web applications of high quality in a certain application domain. By using them, developers can gain a number of important advantages, such as increased design quality, reduced development and maintenance costs, and better communication since they provide a common vocabulary to discuss the various design alternatives. However, despite their numerous advantages, there is still an absence of techniques to systematically assist domain designers with their identification. To this end, we here propose an approach which automatically supports the identification of domain-specific design patterns, by providing designers with recommendations about candidate patterns. More specifically, we propose an approach that automatically analyzes the designs of domain-specific websites in terms of the various reusable design solutions which are used in them by designers as building blocks for addressing common domain problems. Then, in order to verify and validate that the identified design solutions truly lie and are applicable in the target domain, we evaluate them against the domain ontology and also apply a number of evaluation metrics on them. Finally, the approach categorizes the various reusable design solutions and recommends the ones with the best evaluation results as candidate domain-specific design patterns.

In order to automate the process of capturing the designs of domain-specific websites, we have narrowed down the scope of the approach to the area of Content Management Systems (CMSs) and illustrate its potential on websites built on top of Joomla! CMS. To explain the concepts of the proposed methodology, we focus on the domain of academic websites and refer to various instances of real Greek academic websites. The remaining of this paper is organized as follows: Section 2 provides an overview of the related work and discusses the contribution of this work. Section 3 presents in detail the approach, while section 4 discusses conclusions and future work.

Related Work & Contribution

The main objective of this work is to assist domain designers with the identification of domain-specific web design patterns. Therefore, we have developed an approach to provide them with automatically identified recommendations about candidate patterns based on the domain's ontology. By reviewing the literature for studies concerning the identification of domain-specific design patterns, one can find out that the research in the field is still not mature enough. To begin with, despite the fact that there are many catalogues of web design patterns [START_REF] Tidwell | Designing interfaces[END_REF]; Van Welie, 2019; Toxboe, 2019), we noticed that only a small percentage of the patterns included in them are domainspecific and the domains explored are very few. Another issue is that the identification of domain-specific design patterns relies on a completely manual process (Van Welie and Klaasse, 2004; [START_REF] Pontico | Organizing User Interface Patterns for e-Government Applications[END_REF][START_REF] Cremonesi | User interface patterns in recommendationempowered content intensive multimedia applications[END_REF] and the whole burden of the process is carried by designers, requiring a great amount of time and effort. Here lies the main contribution of the proposed approach, since it aims to assist domain designers by attempting to support the pattern identification process in an automated way. More specifically, the proposed approach supports the automated design analysis of various websites in a particular application domain, as well as, the automated identification of the reusable design solutions which are commonly used in them for addressing typical domain problems. As a result, by simply providing a list of URLs that belong to domain-specific websites, domain designers can have access to a set of reusable micro-architectures which are used in the website designs as building blocks for addressing recurring domain problems.

The Approach

The approach can be divided in three main steps as depicted in Fig. 1. First, we identify all the recurrent patterns occurring in the organization of content and front-end interfaces of a collection of domain-specific websites, resulting in a set of reusable design solutions revealing potential design practices which are commonly used by designers in the domain for supporting the realization of domain functionalities (common domain-specific tasks). Then, in order to verify which of them are effectively used, denoting the existence of domain-specific design patterns, we validate and match them against domain's ontology, apply a number of evaluation criteria on them, and finally, recommend the ones with best evaluation results as candidate patterns.

Fig. 1. The approach overview.

Identification of recurrent patterns in domain-specific designs

The identification of recurrent patterns in the designs of the collected domain-specific websites is carried out in the following four phases:

Phase 1: Domain-specific websites collection & extraction of domain concepts

In the first phase, we create the collection of websites in the target application domain by employing a web crawler which, given a list containing the URLs of domainspecific websites, traverses all of their pages and makes a local copy of them on the user's computer. Subsequently, based on the semantics that is encapsulated on the pages of the collected domain-specific websites, we automatically capture domain concepts by applying a semantic similarity measurement technique on their contents. To support this task, we have developed a tool which first collects the content of every page in the website collection, and then applies a WordNet-based semantic similarity measurement technique [START_REF] Simpson | WordNet-based semantic similarity measurement[END_REF] on them in order to extract the common semantic concepts to which they refer. We consider all the computed common semantic concepts as domain concepts and store them in a database table, called domain dictionary. This way, a domain concept is assigned to every page of the collected websites.

Phase 2: Capturing the designs of domain-specific websites

In the second phase, we capture the designs of the collected domain-specific websites by automatically extracting their conceptual model at hypertext level, which specifies the organization of their front-end interfaces in terms of pages, made of a number of predefined structural and navigational design elements, called components and modules. When used in a page, all these types of components and modules, can be found in its HTML code as <div> elements, having characteristic HTML class attribute values (i.e., <div class="value">). As a result, by parsing the HTML code of the pages of the collected websites and locating the occurrences of these characteristic HTML class attribute values in them, we can retrieve the organization of the various front-end design elements that compose their hypertext. For example, Fig. 3(a) presents the hypertext organization identified for the "Faculty" page of an academic department website. This task is supported by the toolset depicted in Fig. 2, which retrieves in the reverse engineering way described above the conceptual model of the collected websites.

Next, in order to facilitate the subsequent identification of recurrent patterns in the designs of the collected websites, the conceptual model of every website is represented in the form of two directed graphs. The first graph representation captures their designs at the level of content organization in them, that is, the organization of the various domain concepts among their pages. The second graph representation captures their designs at the level of hypertext organization, that is, the organization of the various design elements in the front-end interfaces of their pages. This task is supported by the "Graph Translator" unit depicted in Fig. 2. An example can be found in Fig. 3 tual model of an academic department website. Finally, the tool produces as output two TXT files containing the two graph representations produced for the conceptual model of every website in the collection. These two graph datasets are provided as input to the graph mining algorithm utilized in the next phase, in order to perform their patternbased analysis and obtain the identification of the recurrent patterns in the organization of their content and hypertext interfaces.

Phase 3: identification of recurrent patterns in content and hypertext organization

In the third phase, we analyze the designs of the collected websites in terms of the recurrent patterns occurring in them, both at the level of content and hypertext organization. To achieve this, we reduce the problem of pattern identification in the two graph datasets produced in the previous phase to the subgraph isomorphism problem, synopsized in its general form into finding whether the isomorphic image of a subgraph exists in a larger graph. Intuitively, the isomorphic subgraphs occurring within a graph dataset is an alternative way to obtain the identification of the recurrent patterns among its graphs. Quite a few heuristics have been proposed to solve it, among which we have selected the most prominent one, that is, the gSpan algorithm [START_REF] Yan | gSpan: Graph-based substructure pattern mining[END_REF]. Thus, by applying gSpan [START_REF] Philippsen | ParSeMiS -the Parallel and Sequen-tial Mining Suite[END_REF] on the two graph datasets, we identify all the recurrent patterns occurring in the content and hypertext organization of the collected domain-specific websites. We must note that the recurrent patterns in the content organization of the websites specify information flows which determine domain functionalities, i.e., common domain-specific tasks, whereas the patterns in hypertext organization specify design fragments which are used to support the realization of these domain functionalities. For example, Fig. 4 presents two recurrent patterns identified in the designs of academic websites. Fig. 4(a) presents a recurrent pattern occurring in the content organization of various academic websites that we have used in our case study, consisting of the following configuration of domain concepts among three website pages, i.e., {Staff → Faculty → Professor}. occurring in the front-end interface organization of various academic websites, consisting of the following configuration of front-end design elements among the three involved website pages, i.e., {ACL → CCL → SC}. If the pattern in Fig. 4(b) coexists in the designs of the academic websites with the pattern of Fig. 4(a), we can assume that the front-end design elements composing the design fragment specified in Fig. 4(b) are used to support the domain functionality depicted in Fig. 4(a), that is, to allow users to find the contact details of the various professors included in the faculty staff category of an academic department. As a result, in order to identify the commonly used design practices in the collection of domain-specific websites, we examine the occurrences of the identified recurrent patterns in the two graph datasets and identify those patterns that coexist, i.e., they occur simultaneously both at content and hypertext organization level.

At the at the end of this phase, for every domain functionality (recurrent configuration of domain concepts), we identify a list of all the various recurrent design fragments which are commonly used in the designs of the collected websites in order to support its realization. Every possible combination of a design fragment in this list at the hypertext organization of the websites with the particular information flow of this domain functionality at their content organization can possibly result in a reusable design solution that is commonly used in the domain for addressing a certain domain problem. Have in mind that behind such a reusable design solution, there may be hidden a good design practice used by designers in the domain under study for addressing typical domain problems, signifying the existence of a possible domain-specific design pattern. To verify this, in the next phase, we proceed with the evaluation of the identified reusable design solutions.

Phase 4: Evaluation

In this step, we apply a number of evaluation criteria on the previously identified recurrent patterns in order to determine which of them can be considered as effective design solutions for the target application domain. Evaluation is performed in two steps. First, we evaluate the various configurations of domain concepts, captured as recurrent patterns in the content organization of the websites, by matching them against the domain's ontology. Then, we evaluate the various recurrent design fragments, captured as recurrent patterns in hypertext organization, towards (i) their consistent use in the designs of the website and (ii) the degree of their design similarity, since the underlying design reuse among them possibly reveals designers attempt to apply a certain design practice, indicating a possible domain-specific design pattern.

Evaluation based on domain ontology

Domain ontology encapsulates the knowledge about the problem domain. It is an intentional semantic structure that encodes the set of objects and terms that are presumed to exist in the semantic domain, the relationships that hold among them, and the implicit rules constraining the structure of this (piece of) reality [START_REF] Giaretta | Ontologies and knowledge bases towards a terminological clarification. Towards very large knowledge bases: knowledge building & knowledge sharing[END_REF]. Therefore, in order to validate that the identified recurrent configurations of domain concepts are actually within the context of the target domain, we cross-check the semantic concepts composing them against the concepts of domain ontology.

To define the domain ontology, we either use an already developed domain ontology as basis for domain reference or we define the domain ontology in OWL using Protégé [START_REF] Noy | Creating semantic web contents with protege-2000[END_REF]. Then, based on the domain ontology definition, we either programmatically query the ontology repository for matched terms between the ontology's concepts and the identified configurations of domain concepts with SPARQL queries (Fig. 5), or, given the output of the previous phase in OWL format, we perform an ontology matching algorithm (Fig. 6) to check the validity of the terms composing the identified configurations of domain concepts. Fig. 5 and Fig. 6 provide some relevant examples. In Fig. 5, the user validates an identified configuration of domain concepts by programmatically querying this configuration against the domain ontology of the academic domain. We can validate all terms included in an identified configuration of domain concepts one by one, such as in Fig. 5. Assuming that the concept "Professor" is one of these concepts, the toolkit validates this concept via a SPARQL query. It also suggests the concept "Lecturer", since this is also a subclass of the class Academic staff. 6, the entire configuration of domain concepts belongs to the University ontology with estimated matching value of 1.0 (ranging from 0.0 to 1.0, green color). Thus, the configuration of domain concepts is totally matched against the domain ontology. The matching results shows that this configuration lies in the semantic context of the domain and it can also be optionally enhanced. For example, the concept of "Lecturer" is missing from the original discovered domain concept configuration (no connection line) and now can be utilized.

In both cases (either in programmatically querying ontology or in ontology mapping), the matching results can fall into three cases:

1. The identified domain concepts composing a recurrent pattern are a subset of the domain ontology's concepts, verifying that the websites composing the collection truly fall under the umbrella of the target application domain under consideration.

Web designers can either use this configuration as it has been identified or even extend it with additional concepts specified in the domain ontology. For example, if the following configurations of domain concepts have been identified in a collection of academic websites, {Professor → Associate} and {Professor → Assistant}, then by matching them against the University Ontology, a further examination of the Academic class hierarchy can reveal the concept of "Lecturer" which can be used to extend the identified configuration of domain concepts. 2. The identified domain concepts in a configuration do not belong in the set of domain ontology's concepts, denoting either that the website collection is invalid for this domain or that the semantic analysis of the contents of website pages has produced invalid results. 3. The identified domain concepts composing the recovered patterns partially belong to the set of domain ontology's concepts. In this case, web designers can decide on how to make use of the identified domain concepts and even enhance them with concepts of the domain ontology. For example, the semantic analysis of domain concepts concluded to the term Professor among other academic terms, but no other types of Academic staff were discovered. In this case, web designers might examine the academic staff class hierarchy, and finally include Associate Professor and Assistant professor in their domain concepts configuration.

This way, we validate and verify which of the identified configuration of domain concepts truly lie in the specific context of the target application domain, and select those which are in alignment with its semantics.

Evaluation based on consistent use and effectiveness

After selecting the design fragments which are used to deliver to end-users the configurations of domain concepts which are valid according to the domain ontology evaluation of the previous step, the next step is to evaluate them towards their consistent use in the designs of the collected website, as well as, towards the degree of their design similarity.

Consistent use of recurrent design fragments

To determine which of the design fragments are effectively used for the realization of the identified domain functionalities (i.e., configurations of domain concepts), we evaluate them towards their consistent use in the website designs with respect to their starting and ending variants. More specifically, in phase 3 of Section 3.1, when obtaining the identification of the recurrent patterns in the graph datasets, except from the pattern's core specification (i.e., invariant composition of design elements), we also identify its starting and ending variants, extending the core specification of the pattern with all the valid modalities in which it can start or terminate. Intuitively, these variants correspond to the various design structures with which it is connected (on its left or right side) in the collected websites in order to execute a domain functionality. Thus, to verify the consistent use of a recurrent design fragment in the various website designs, we need to consider it with respect to its starting and ending variants.

To this end, we have defined two metrics called Start-Point Metric (SPM) and End-Point Metric (EPM), respectively. Assuming that a recurrent design fragment can have N starting and M ending variants, these metrics compute the statistical variance of the occurrences of these variants in the website designs, normalized with respect to the best-case variance. They are calculated according to the following formulas:

𝑆𝑃𝑀 = 𝜎 𝑆 2 𝜎 𝑆,𝐵𝐶 2 ⁄ 𝐸𝑃𝑀 = 𝜎 𝐸 2 𝜎 𝐸,𝐵𝐶 2 ⁄ (1)
𝜎 𝑆 2 and 𝜎 𝐸 2 is the statistical variance of the N starting variants occurrences and the M ending variants occurrences respectively, calculated according to the formula (2):

𝜎 𝑆 2 = 1 𝑁 ∑ (𝑝 𝑖 - 1 𝑁 ) 2 𝑁 𝑖=1 𝜎 𝐸 2 = 1 𝑀 ∑ (𝑝 𝑖 - 1 𝑀 ) 2 𝑀 𝑖=1 (2)
where 𝑝 𝑖 is the percentage of occurrences for the i-th pattern variant. 𝜎 𝑆,𝐵𝐶 2 and 𝜎 𝐸,𝐵𝐶 2 are instead the best-case variances for the starting and ending variants, calculated by the formula [START_REF] Giaretta | Ontologies and knowledge bases towards a terminological clarification. Towards very large knowledge bases: knowledge building & knowledge sharing[END_REF] website. We have also defined a measurement scale specifying a mapping between the numerical results obtained through the calculus method and a set of (predefined) meaningful and discrete values, as defined in Table 1.

We compute the SPM and EPM metrics for all the starting and ending variants of the recurrent design fragments supporting the various domain functionalities and select only the ones having SPM and EPM values less than 0.6, and store the results in the "Results Repository". This way, we obtain a first level categorization of them based on the consistent use of their variants.

Design similarity of recurrent design fragments

Another important factor that must be taken into account in order to determine whether the identified recurrent patterns can be considered as candidate domain-specific patterns is their design similarity. This is due to the fact that high design similarity among them implies underlying design reuse which possibly occurs due to developers attempts to maintain a common design practice in the domain for the realization of a domain functionality, thus, signifying the existence of domain-specific design patterns. To this end, we perform a second level categorization of the previously selected recurrent design fragments based on the degree of their design similarity. To compute the degree of design similarity among a list of recurrent design fragments (i.e., configurations of design elements) that support a domain functionality, we adopt the vector space model. More specifically, every design fragment is represented as a vector 𝑑 𝑖 = (𝑥 1,𝑖 , 𝑥 2,𝑖 , … , 𝑥 𝑛,𝑖 ), where the compounds comprise all the distinct Joomla! design elements occurring among the various design fragments included in the list. These compounds are considered as unigrams and are weighted by the frequency of each respective unigram, that is, the number of times in which the design element (to which they correspond) occurs in the recurrent design fragment under consideration. Then, we compute the degree of design similarity between every possible pair of recurrent design fragments in the list, by calculating the cosine of the angle between their corresponding vector representations 𝑑 𝑖 and 𝑑 𝑗 . The latter is calculated according to the following formula:

𝑆𝑖𝑚𝑖𝑙𝑎𝑟𝑖𝑡𝑦(𝑑 𝑖 , 𝑑 𝑗 ) = cos(𝑑 𝑖 , 𝑑 𝑗 ) = 𝑑 𝑖 • 𝑑 𝑗 |𝑑 𝑖 | • |𝑑 𝑗 | = ∑ 𝑤 𝑡,𝑖 • 𝑤 𝑡,𝑗 𝑛 𝑡=1 √∑ 𝑤 𝑡,𝑖 2 𝑛 𝑡=1 • √∑ 𝑤 𝑡,𝑗 2 𝑛 𝑡=1 , ∈ [0,1]
where |𝑑 𝑖 | and |𝑑 𝑗 | are the norms of the two vectors. To quantify the degree of this similarity, we have defined five similarity levels, presented in Table 2. The higher the level of design similarity among the design fragments, the more possible the design reuse occurring in them to capture a common design practice in the domain for the realization of the domain functionality.

Design Similarity Level

Design fragments composed by: At the end of this step, for every identified list of recurrent design fragments that supports a domain functionality, we locate all the sets of similar design fragments in the list, and identify the various design reuse schemes occurring in them. Then, we categorize them according to their design similarity level, and present the results in descending order. This way, we manage to capture the various common design practices which are used in the domain for addressing the domain functionalities. In order to reduce the large number of the identified design fragments, we select only the ones that occur in design fragments having a design similarity above the third level. By inspecting the identified design reuse schemes, domain designers can have a global picture of the various design practices that are commonly used in the domain for realizing the various domain functionalities. By combining these results with the results concerning their consistent use in the designs of the collected websites, it becomes easier for designers to determine which of the identified reusable design solutions can be considered as good design practices for the target domain, signifying the existence of candidate domain-specific design patterns.

Conclusions & Future Work

In this work, we have presented an approach that recommends automatically identified candidate reusable design solutions to domain designers in order to assist them with the identification process of domain-specific design patterns. To obtain these recommendations, it automatically analyzes the designs of a collection of websites in a target application domain, identifies and evaluates all the reusable design solutions occurring among them for addressing typical domain problems. For the evaluation of the recovered design solutions, we have relied on the domain ontology in order to capture those which are in alignment with the domain's semantics, on their consistent use and on their design similarity. Finally, the approach categorizes the various reusable design solutions and recommends the ones with the best evaluation results as candidate domain-specific design patterns. By having access to the results, domain designers can have an overview of the common design practices used in the domain for addressing typical domain problems, among which they can possibly recognize best practices and capture domain-specific design patterns. In future, we plan to apply the methodology in various application and extend it, so that it can be applied in websites built on top of other popular CMS platforms, such as Drupal and WordPress.

  (b) and (c) which present an instance of the two graph representations produced for the concep-

Fig. 2 .

 2 Fig. 2. The conceptual model extraction process.

Fig. 3 .

 3 Fig. 3. (a) The organization of a page in terms of Joomla! component and modules. (b) The first graph representation of the page at the level of content organization. (c) The second graph representation of the page at the level of front-end interface organization.

Fig. 4 (Fig. 4 .

 44 Fig. 4. Recurrent patterns in the designs of academic websites. (a) A pattern occurring in the content organization of academic websites. (b) A pattern occurring in the frontend interface organization of academic websites.

Fig. 5 :

 5 Fig. 5: Querying the domain ontology.

Fig. 6 :

 6 Fig. 6: An example of ontology mapping.

Fig. 6

 6 Fig.6presents an example of ontology matching approach based on the open-source API implementation of COMA[START_REF] Massmann | Evolution of the COMA match system[END_REF]. In Fig.6, the entire configuration of domain concepts belongs to the University ontology with estimated matching value of 1.0 (ranging from 0.0 to 1.0, green color). Thus, the configuration of domain concepts is totally matched against the domain ontology. The matching results shows that this configuration lies in the semantic context of the domain and it can also be optionally enhanced. For example, the concept of "Lecturer" is missing from the original discovered domain concept configuration (no connection line) and now can be utilized.In both cases (either in programmatically querying ontology or in ontology mapping), the matching results can fall into three cases:

Table 1 .

 1 assuming that only one variant has been coherently used throughout the The measurement scale for the SPM and EPM metrics.

	SPM/EPM range	Measurement scale value
	0 ≤ SPM/EPM < 0.2	Optimum
	0.2 ≤ SPM/EPM < 0.4	Good
	0.4 ≤ SPM/EPM < 0.6	Discrete
	0.6 ≤ SPM/EPM < 0.8	Weak
	0.8 ≤ SPM/EPM ≤ 1	Insufficient

Table 2 .

 2 Design fragments categorization based on design similarity.

	1	▪ totally different configurations of design elements
	2	▪ configurations of design elements identical up to 25%
	3	▪ configurations of design elements identical up to 50%
	4	▪ configurations of design elements identical up to 75%
	5	▪ identical configurations of design elements


Dr Ioannis Neokosmidis
email: i.neokosmidis@incites.eu

Dr Theodoros Rokkas

Dimitrios Xydias

Dr Maria Rita Spada

Regulatory Considerations In the 5G era: The 5GCity Neutral Host case

Keywords: 5G Networks, Network Densification, Neutral Host, Regulation, Spectrum Sharing

The need for densification in 5G networks will necessitate the installation of large amounts of small cells in dense urban environments in order to meet future demands for capacity. The Neutral Host model has been proposed as a potential solution to this problem. This paper discusses the general regulatory considerations of 5G networks and specific considerations that relate to the Neutral Host model as this has been examined as part of the H2020 Project 5GCity.

5G and the need for densification

5G is the latest generation of mobile networks which will enable faster and more reliable mobile networks as compared to the existing ones. Initial deployments of 5G networks will depend on existing infrastructure and will be based on Non-Standalone (NSA) 5G new radio standards. NSA new radio refers to a 5G network which uses a 4G core and radio anchor with a 5G small cell mobile broadband (MBB) capacity boost, while Standalone (SA) new radio refers to a 5G network which only depends on 5G technology both for its core and radio anchor. NSA standards will enable the enhanced mobile broadband (eMBB) use case family. This type of network is expected to be very popular in the early years of 5G as mobile network operators demand backward network compatibility. Subsequently, the industry will start launching SA 5G networks to support the strictest criteria regarding the technical specifications, such as latency, data rate, capacity, spectrum efficiency and mobility, to support massive machine-type communications (mMTC) and ultra-reliable low-latency communication (URLLC) [START_REF] Elayoubi | 5G service requirements and operational use cases: Analysis and METIS II vision[END_REF].

5G will not be a revolutionary technology, but rather a fine orchestration of existing technologies, such as Software Defined Networking (SDN) [START_REF] Mosharaf | A Survey of Network Virtualization[END_REF], Network Functions Virtualisation (NFV) [START_REF] Nunes | A Survey of Software-Defined Networking: Past, Present, and Future of Programmable Networks[END_REF], Mobile Edge Computing (MEC) and Cloud Computing [START_REF] Frascolla | Millimeter-waves, MEC, and network softwarization as enablers of new 5G business opportunities[END_REF]. 5G is also going to use two new frequency bands, namely, 3.6 GHz and 26 GHz [5], which will be essential to achieve the advanced specifications it promises. Achieving the specifications in these bands will only be possible with network densification by deploying a large number of small cells. This is due to the shorter transmission range that higher frequencies can achieve. Network densification will be particularly necessary in dense urban environments where the demand for capacity will be higher. Demand for more small cell antennas, however, outpaces the supply of available sites in many cities. This creates an imbalance in the market, which could potentially drive up rental fees for those sites to the benefit of their owners. In such cases, the development of parallel small cells networks by operators will be prohibitively expensive and potentially not feasible.

An alternative to building parallel networks will be the Neutral Host (NH) model [5], whereby a single entity, the NH, deploys and operates the network (through self-operation or outsourcing) and then provides wholesale access to those interested in providing their services. The hosting aspect refers to an entity that provides a certain set of resources that are made available to clients, such as Mobile Network Operators (MNO)s, allowing them to provide uninterrupted services to their clients at the expense of reduced flexibility and complex billing relationships. The "neutrality" aspect refers to the host acting as a shared platform to multiple hosted clients. Neutrality in this context does not imply strict equality between hosted clients, as the resources offered to each client are subject to the commercial agreement between the NH and the client, and policy-based management may be applied. From a hosted client's point of view, the system behaviour and services using the resources of a NH should be available without user intervention and, ideally, they should be seamless and identical to those provided by their hosted clients' dedicated resources.

Towards this direction, 5GCity [7] architecture employs distributed cloud technologies to build its combined edge and network infrastructure, providing a multi-tenant, costeffective platform for deploying virtualized, heterogeneous services. The 5GCity architecture allows the exploitation of the NH model, employing features of the different layers:

• Application Layer: offers the tools and functions available for the infrastructure operators, customers, subcontractors, and third-party actors • Orchestration and Control Layer: allows management of a non-homogeneous set of physical resources, abstraction of physical resources, operation of horizontal slicing to provide coherence cast end-to end services tailored to a multitenant framework • Access Layer : the Neutral Host model requires network information on how to deal with the access layer (end-user devices -physical resources providing connectivity); in the Service Level Agreement (SLA) between the NH and the operator it is necessary to define how the network deals with the end-to-end chain from Radio elements and Fronthaul network to the end user devices in order to control for the availability and quality of the service.

5GCity will offer an infrastructure dashboard providing operators and verticals the ability to create slices according to their needs. 5GCity goes one step further by providing a Software Development Kit (SDK) that allows developers to create network functions and services, and service providers to combine pre-existing functions in order to develop new services.

Moreover, both infrastructure and services dashboards will also provide advanced functionalities, such as billing, offering increased flexibility to mobile operators and other interested parties and motivating them to adopt the NH model.

Regulatory considerations in the 5G era

Past regulatory practice was generally based on the requirements of physically larger high-power macrocells. This approach will likely not be appropriate in the case of networks with smaller cells, such as the NH model. Enabling the deployment of small cell networks requires streamlined federal, state and local permitting, rights-of-way, application submission timelines, application fees, application review timelines and appeals processes to make it economically feasible for operators to deploy 5G across communities. Some of the issues that need to be addressed by regulatory authorities to facilitate the smooth transition to 5G networks are as follow.

Network equipment certification and permits

To enable the deployment of a large number of new antennas, a simplified and easilyreplicable certification process could be considered. For instance, the height of the installed antenna and the Effective Isotropic Radiation Power (EIRP) metric are already being used in many countries as criteria for certification exemption or process simplification. The enforcement of the simplification should be done at a national level, though specific local considerations should be taken into account. This would allow for a flexible regulatory agenda which also respects local laws, given that the latter do not impede the development of new networks.

Indicative examples of metrics used as thresholds for the need for declaration or installation permission are:

• Antenna height: Canada (15m), Germany (10m), the Netherlands (5m), France (12m), United Kingdom (4m/15m) • Power level: Chile (low power), France (up to 5W simple declaration is needed), Japan (low power type approved, 20mW), Malaysia (EIRP of 2W), Germany (10W)

• A combination of height and power: United States • Regional-based simplified procedures: Spain Before overhauling the certification and permitting procedures, considerations such as street furniture aesthetics should also be taken into account. In particular it could be examined if the installation of multiple small cells can be facilitated at once, taking into account their relatively small size and visual impact.

Some additional recommendations made by the Small Cells Forum [8] and GSMA [9] in order to accelerate the deployment of small cell networks are as follow: In the United States (US), according to Federal Communications Commission (FCC) rules, small cells can be exempt from environmental assessment in case they meet certain size and visibility criteria. In addition, the FCC has set time limits for the authorities to decide on permit applications in case of collocation (90 days) and new installations (150 days). The United Kingdom (UK), in a radical move for European standards, has removed all restrictions for placing small cell antennas on commercial buildings/structures to support mobile network rollout. This has simplified network investment considerations for the MNOs which now can expand their 4G mobile networks and better prepare for 5G.

During the site identification phase, a site owner might be reluctant to provide access to all interested parties that want to install equipment and instead sign an exclusive agreement with only one of the operators. Such anticompetitive practices should also be taken care of by regulatory authorities to ensure a level playing field for all players.

The relevant public authorities should, therefore, work closely together with a view to simplify administrative procedures, reduce delays and lower the cost for operators, while protecting public interests.

Site availability

Regulating access to existing sites raises significant challenges for National Regulatory Authorities (NRAs), both in dense urban areas where the site availability is limited and some site owners might have significant negotiating power over the contract terms, as well as in rural areas where it is uneconomic to develop parallel networks. An alternative solution to alleviate some of the regulatory challenges is to increase the number of available sites for network installation. To achieve that, the NRA must collaborate with local municipalities or the relevant state authority to reconsider planning rules which should accommodate the small size and radiation impact of small cell antennas in both indoor and outdoor environments. What is more, the public authorities should enable the cost-effective access to street furniture elements, such as lamp posts and masts, to ensure that the supply of sites suitable for antenna installations is enough to counter any market cornering or market power concentration incidents.

Electrical power

One of the biggest challenges that the industry is likely to face with 5G installations is the need for electrical power on each cell site. To tackle this problem, the authorities could facilitate the deployment of small cells near sites with electrical power like bus stops, street-lamps or ducts. To address this potential problem, operators are investigating off-grid network deployments including power over Ethernet, the construction of power generators or the use of renewable sources, suitable for installations in remote areas. In some countries, such as Luxembourg, on top of the above-mentioned problems, 5G stakeholders have highlighted that the necessity to deploy an electricity meter for each small cell antenna would increase both the complexity and deployment costs considering the number of small cells needed to be installed.

Access to public furniture and fiber networks

Depending on the use case that 5G networks need to support, this might include installing a large number of macrocells, small cells or line-of-sight connections. The need to deploy more antennas and new network equipment will be accompanied by issues associated with gaining access to sites, public and private infrastructure as well as with backhauling. These issues should be addressed from an early stage, during the network planning phase, to avoid impeding 5G network deployments.

Very high on the 5G ecosystem stakeholders' agenda are issues related to locating new available installation sites and agreeing on the contract terms with landlords, which apparently is a very lengthy and cumbersome process. Thus, easy access to public buildings, street furniture and street-lamps can significantly accelerate the deployment of 5G networks and especially small cells networks. Access to passive infrastructure, however, such as ducts and masts will also be required.

Addressing the need for backhauling will also be important. Although an alternative solution with microwaves has been suggested, this technology depends on weather conditions, as it can be impacted by heavy rainfall. Thus, access to fibre, depending on availability, will be necessary to address the need for backhauling. Hence, fibre sharing will need to be facilitated and regulated in order to accelerate 5G deployment.

Spectrum

Timely availability and price of spectrum will be critical factors for the deployment of 5G. Hence, it is essential to set up a roadmap for the grant of spectrum as early as possible and to investigate solutions beneficial for both the regulator and interested spectrum buyers. A 'spectrum fee holiday', that is to provide free access to spectrum for a predefined period provided that spectrum owners allocates pre-defined capital resources in 5G, could be among the potential regulatory considerations to lower the cost burden for operators. For instance, Italy auctioned 5G spectrum frequencies in October 2018, raising an astounding 6.5 billion euro, over a 14-days long bidding process, raising concerns regarding the operators' capacity to further invest in infrastructure over the coming years. Taking Italy as counter-example, the French regulator, ARCEP (Autorité de régulation des communications électroniques et des Postes), committed to working out a way to keep spectrum prices low, to encourage healthy competition and the much-needed investments in next generation infrastructure.

Another consideration related to spectrum, has to do with the active sharing of a future small cells network, whereby regulation permitting, or even obliging, spectrum sharing between the network operators and small cell operators, should be in place. This would allow the more efficient usage of spectrum, one of the main regulatory concerns as we move to 5G. Here, the use of a Licensed Shared Access (LSA) agreement could be in place, whereby the spectrum owner (mobile network operator) allows the small cell operator to use their spectrum in areas where it is unused by the MNO. Another alternative is for the small cell networks to use unlicensed spectrum though this solution runs the risk of causing interference with other equipment which could impair the small cell network's ability to deliver the specifications of a 5G network, such as low latency and high reliability.

Spectrum licensing for private indoor 5G networks that will be deployed in the future should also be considered. Regulators need to ensure that the spectrum bands used for private 5G networks should ideally be compatible across all European Union (EU) member states. Apart from the spectrum bands used, the way of licensing spectrum for private networks should also be considered. Spectrum sharing on an unprotected basis, raises concerns regarding the reliability of using such spectrum given the potential interference from existing users of unlicensed spectrum. Hence, there appears to be a need for private 5G networks to use spectrum bands that are distinct from existing uses of shared spectrum. However, given the potential limited interference that indoor private networks could have to outdoor spectrum users, there could be considerations to licence private networks as secondary spectrum users. This would ensure that the spectrum is shared on a non-interfering basis with network operators being the primary spectrum users. More specifically, the propagation characteristics of millimeter Wave (mmWave) bands limit any potential for interference while beamforming and massive MIMO techniques could also assist in reducing interference with other users.

Radiation

Organisations like the World Health Organisation (WHO) have issued recommendations and suggested limits for the allowed radio frequency exposure [11] that are also endorsed by the EU and other national governments. To meet the advanced specifications that 5G networks promise, a large number of small cell antennas and the use of intelligent beaming techniques, such as beamforming and massive Multiple Input Multiple Output (MIMO), might result in higher power levels when and where needed and lower levels once the needs are reduced. Hence, the 5G ecosystem stakeholders have raised concerns whether the existing radiation limit will still be relevant when 5G networks are introduced. Therefore, the new technology could trigger an adaptation of the existing regulatory framework, while respecting health-related laws and mandates. Italy was the first country in Europe to auction spectrum in all three frequency bands concurrently, a process which took place in September 2018. All mobile operators participated in the 5G spectrum auction where a simultaneous multi-band award procedure was running. All spectrum assignments for all the bands were part of a single award procedure, which was divided in two phases. Firstly, the 700 MHz band was awarded and subsequently the remaining lots on the other bands were auctioned. The licence duration was set in a way that it offers enough time for the operators to recoup their investments in 5G networks within a reasonable timeframe. The expiry date of the allocated licenses is 31 st December 2037 for all the assigned lots.

Spectrum Auction in Italy and the NH Model

The financial exposure taken on in the Italian auction was huge, and all telcos will be impacted in the medium term as it happened in other countries after the 3G bands were auctioned in the early 2000s. This could affect the creation of a 5G ecosystem for the different actors because of the high price the operators had to pay, which squeezed their cash reserves. Operators have to explore new opportunities based on different use cases and business models in mission critical services, in massive IoT or in other verticals like Media and Energy. Possible synergies must be explored to cooperate with regulators and policymakers to deploy 5G in a more economically-efficient way.

A reliable 5G infrastructure is fundamental to offer the benefits enabled by the new technologies for different contexts.

Telcos have to follow not only the auction obligations but also to implement a new strategy for smart deployments, such as the one described in 5GCity by:

• sharing small cells networks • prioritizing site construction according to the business models • using more information coming from the business analysis of the customers • creating smart partnerships to capture the economic benefits of the 5G technology.

Neutral Host-specific regulatory considerations

Regulating the NH model is a complex task given the various facets that need to be considered. Few considerations that NRAs should take into account are as follow:

Ensure neutrality

The NH should be obliged to provide wholesale access to all interested parties, e.g. network operators or other service providers, on a non-discriminatory basis. In other words, no operator or other party should be refused access to the NH's infrastructure, subject to regulatory approval. Neutrality doesn't necessarily mean providing the same level of service to everyone, since different bundles of services could be available to the hosted clients, but rather to provide the same level of service to those who have subscribed to the same service bundle.

No retail services

The NH should be prohibited from offering retail services that would put them in direct competition with existing MNOs, as this would defeat the purpose of the NH's very existence. Allowing a NH to exist in dense urban areas or rural areas where it is uneconomic to build individual networks ensures that MNOs have access to the NH's resources which complement their network to ensure improved coverage and service delivery. Direct competition between the two would turn operators away from trying to do business with the NH, making its existence not viable.

Price regulation

The wholesale access prices offered by the NH should be regulated to ensure transparency, reasonableness and equal treatment of all parties. The NH's significant market power in its niche market could give it the ability to charge extraordinary prices to provide wholesale access to other interested parties, squeezing their profit margins and creating distortions in the market. Hence, a transparent rate card with 'reasonable' prices for the different levels of service should be in place. Several pricing schemes could also be investigating, such as the 'pay as you grow', 'pay as you use' or one with a flat annual fee.

Spectrum ownership

Spectrum used by the NH should also be carefully regulated. Here, what needs to be clarified is who is going to be the spectrum owner in the case a NH exists. We have identified four alternative scenarios that vary in the form of the relationship between the operator and NH.

The operator owns the spectrum. The operator acquires a spectrum license from the NRA, while the NH has zero spectrum holdings. Should the operator decide to use the NH's network, the latter uses the frequency bands acquired by the former. In this scenario, the NH minimizes its expenses and avoids participating in the complex task of spectrum management.

The NH owns the spectrum. The NH acquires a local spectrum license on its own. This scenario gives the NH significant market power which needs to be regulated so that it offers competitive prices.

Both the operators and the NH own spectrum. In this case the operator will use its spectrum and NH's infrastructure. On the other hand, the NH can provide spectrum to verticals and other interesting parties that do not have their own license or complement operators' spectrum if needed.

A third entity owns the spectrum. In this case, the NH plays the role of the plays the role of the intermediary which increases the complexity since the NH undertakes the spectrum management task. A similar approach can be followed for the infrastructure.

Stakeholders opinion about NH regulatory considerations

In order to investigate stakeholders' opinion and confirm the initial NH regulatory considerations, 5GCity project conducted a survey through questionnaires during MWC19.

Regarding the need for proper regulation of the Neutral Host, 73% of respondents believe that the NH services/products should be regulated. This likely relates to the potential exhaustive pricing and potential preferential treatment of the wholesale customers that the NH would have in case its products/services were not regulated. Should the NH products/services be regulated, this would enabled fair and equal treatment of all actors requesting access, stimulating healthy competition in the market. Concerning billing, the majority of respondents believe that the billing relationship between the NH and operators should be based on the resources used from the latter. Only 13% of respondents believe in a fixed fee relationship. This is likely due to the fact that operators/verticals prefer dynamic billing systems, which are tailored to their changing needs for access. Surprisingly, more respondents believe that the NH should be the spectrum owner, in contrast to the current model in which operators are the sole owners and are subject to strict regulation for its use. This is likely due to expectations that there would be less complexity in the process, should the NH own spectrum.

Conclusions

Although Europe, USA and Asia are competing about the leadership in the 5G era, there are still several challenges that should be addressed before the deployment and the commercialization of 5G networks. In this paper, the need for the NH model in this new environment was briefly discusses. The NH model supported by the H2020 5GCity project was then described. Regulatory considerations were investigated and several guidelines that will be useful for network operators to accelerate the deployment of 5G networks and adopt the NH model were provided.

  5G development can benefit from synergies among pioneer bands in frequencies: 1. Coverage-oriented band: 2x30 MHz Frequency Division Duplex (FDD) and up to 20 MHz SDL in the 694-790 MHz band 2. Intermediate band: 400 MHz Time Division Duplex (TDD) in the 3.6-3.8 GHz band 3. Capacity-oriented band: 1 GHz TDD in the 26.5-27.5 GHz band

  1. Use of generic permits or exemptions based on internationally standardized equipment classes (e.g. IEC 62232 Ed.2.0 installation classes). 2. Harmonization of the rules and administrative processes for planning permissions across different authority domains in accordance with the Digital Single Market (DSM) strategy [10] for Europe. 3. Simplified administrative processes for small cell deployments through use 'one stop shop' application procedures, reducing the decision-making time and paperwork.

[START_REF] Frascolla | Millimeter-waves, MEC, and network softwarization as enablers of new 5G business opportunities[END_REF]

. Proving tacit approval if local authorities do not oppose an authorization request within a certain number of days or weeks. 5. Maintaining a database of qualified candidate site locations to speed-up site identification and further simplify processing of applications. 6. Incentivizing small cell deployments through revision or full exemptions of base station taxes and recurring fees originally devised for macro base stations.

Acknowledgement

We like to acknowledge the efforts of all the partners of the 5GCity project consortium. This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 761508