Bilel ElayebLiwa College of Technology Abu Dhabi UAE
Bilel Elayeb
Ph.D. HDR
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91
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Introduction
Dr. Bilel Elayeb is an Associate Professor of Computer Science and the Head of the College Research Unit at the Emirates College of Technology in Abu Dhabi, UAE. He obtained a HDR (2018) and a PhD (2009) in Computer Science from ENSI and the INP of Toulouse France, respectively. His research focuses on Mono-, Multi and Cross-Language IR and WSD, Analogical IR, Arabic IR and NLP, and Information Reliability. He has supervised a number of Masters and Ph.D. theses in Artificial Intelligence, IR and NLP. He has published many refereed scientific papers in many reputed international journals and conferences. He is a reviewer for many international peer-reviewed journals, and he also acts as a program committee member for several national and international conferences.
Additional affiliations
January 2013 - present
January 2012 - present
Publications
Publications (91)
Text classification is the process of labelling a given set of text documents with predefined classes or categories. Existing Arabic text classifiers are either applying classic Machine Learning algorithms such as k‐NN and SVM or using modern deep learning techniques. The former are assessed using small text collections and their accuracy is still...
We design, implement and assess in this paper a new architecture of a possibilistic mono- and cross-language information retrieval (IR/CLIR) system. The latter is useful to experiment query disambiguation, expansion and translation processes in both IR and CLIR frameworks. We take advantage of possibility theory to overcome the problems of query di...
Automatic text summarization is considered as an important task in various fields in natural language processing such as information retrieval. It is a process of automatically generating a text representation. Text summarization can be a solution to the problem of information overload. Hence, with the large amount of information available on the I...
Automatic text summarization is the process of generating or extracting a brief representation of an input text. There are several algorithms for extractive summarization in the literature tested by using English and other languages datasets; however, only few extractive Arabic summarizers exist due to the lack of large collection in Arabic languag...
Word sense disambiguation (WSD) is a specific task of computational linguistics which aims at automatically identifying the correct sense of a given ambiguous word from a set of predefined senses. In WSD the goal is to tag each ambiguous word in a text with one of the senses known a priori. In Arabic, the main cause of word ambiguity is the lack of...
Different techniques are used in text mining to analyze data, extract knowledge, information and relations. We aim in this work to extract related terms for specific keywords. In the first step, we extract Arabic keywords from news articles titles using the TF-IDF terms weighting measure. In the next step, we extract the related terms, from both ti...
In this paper, we propose a new automatic query translation disambiguation using bilingual proximity-based approach. This approach combines a traditional bilingual dictionary and parallel bilingual corpus to build a bilingual semantic dictionary of contexts (BSDC) and identify the suitable translation of a word using a proximity matching model. Bes...
La présente thèse de doctorat en informatique propose un modèle pour une recherche d'information intelligente possibiliste des documents Web et son implémentation. Ce modèle est à base de deux Réseaux Petits Mondes Hiérarchiques (RPMH) et d'un Réseau Possibiliste (RP) : Le premier RPMH consiste à structurer les documents retrouvés en zones denses d...
Different techniques are used in text mining to analyze data, extract knowledge, information and relations. We aim in this work to extract related terms for specific keywords. In the first step, we extract Arabic keywords from news articles titles using the TF-IDF terms weighting measure. In the next step, we extract the related terms, from both ti...
Le projet ANT (Arabic News Texts) vise à collecter un corpus de textes d’actualités en langue Arabe à partir de plusieurs sources d’actualités. Ce corpus peut être utilisé dans différentes tâches pour le traitement du langage naturel à savoir la classification de textes, l’extraction d’événements ainsi que la recherche d’information. Dans cet artic...
Event extraction is a common task for different applications such as text summarization and information retrieval. We propose, in this work, a TF-IDF based approach for extracting keywords from Arabic news articles’ titles. These keywords will serve to extract the main events for each month using a Part-of-Speech (POS) co-occurrence based approach....
Approaches of query translation in Cross-Language Information Retrieval (CLIR) have frequently used dictionaries which suffer from translation ambiguity. Besides, a word-by-word query translation is not sufficient. In this paper, we propose, evaluate and compare a new possibilistic approach for query translation in order to improve the previous dic...
We propose in this paper a new online Arabic corpus of news articles, named ANT Corpus, which is collected from RSS Feeds. Each document represents an article structured in the standard XML TREC format. We use the ANT Corpus for Text Classification (TC) by applying the SVM and Naive Bayes (NB) classifiers to assign to each article its accurate pred...
We propose in this paper a new online Arabic corpus of news articles, named ANT Corpus, which is collected from RSS Feeds. Each document represents an article structured in the standard XML TREC format. We use the ANT Corpus for Text Classification (TC) by applying the SVM and Naive Bayes (NB) classifiers to assign to each article its accurate pred...
We propose, assess and compare in this paper a new discriminative possibilistic query translation (QT) disambiguation approach using both a bilingual dictionary and a parallel text corpus in order to overcome some drawbacks of the dictionary-based techniques. In this approach, the translation relevance of a given source query term is modeled by two...
Cross-language information retrieval (CLIR) deals with retrieving relevant documents in one language using queries expressed in another language. As CLIR tools rely on translation techniques, they are challenged by the properties of highly derivational and flexional languages like Arabic. Much work has been done on CLIR for different languages incl...
We show in this paper how Semantic Query Disambiguation (SQD) combined with Semantic Query Expansion (SQE) can improve the effectiveness of intelligent information retrieval. Firstly, we propose and assess a possibilistic-based approach mixing SQD and SQE. This approach is based on corpus analysis using co-occurrence graphs modeled by possibilistic...
Morphological ambiguity is an important phenomenon affecting several tasks in Arabic text analysis, indexing and mining. Nevertheless, it has not been well studied in related works. We investigate, in this paper, new approaches to disambiguate the morphological features of non-vocalized Arabic texts, combining statistical classification and linguis...
The literature on information retrieval shows the importance of information reliability as a key criterion for relevance judgment. However, information reliability evaluation is discussed in many disciplines such as history, Arabic storytelling, and computer science. Although these disciplines share common principles, they differ in many aspects, w...
In this paper, we experiment a discriminative possibilistic classifier with a reweighting model for morphological disambiguation of Arabic texts. The main idea is to provide a possibilistic classifier that acquires automatically disambiguation knowledge from vocalized corpora and tests on non-vocalized texts. Initially, we determine all the possibl...
Domain terminology extraction is an important step in many applications such as ontology building and information retrieval. Analyzing a corpus to automatically extract key terms is a difficult task, especially in the case of Arabic language. The complexity of spelling, morphology and semantics of Arabic makes natural language processing tasks quit...
In this paper, we propose an approach for constructing Arabic Ontology based on normalized dictionaries. This approach mainly consists in transforming non structured Arabic dictionaries into LMF (Lexical Markup Framework) based-normalized ones. We are basically exploiting Arabic dictionaries of Hadith for experimentation. Then, from an Arabic norma...
Résumé. La désambiguïsation morphologique d'un mot arabe consiste à identifier l'analyse morphologique appropriée correspondante à ce mot. Dans cet article, nous présentons trois modèles de désambiguïsation morphologique de textes arabes non voyellés basés sur la classification possibiliste. Cette approche traite les données imprécises dans les pha...
We propose in this paper a new standard Arabic test collection for mono- and cross-language Information Retrieval (CLIR). To do this, we exploit the “Hadith” texts and we provide a portal for sampling and evaluation of Hadiths’ results listed in both Arabic and English versions. The new called “Kunuz” standard Arabic test collection will promote an...
Morphological ambiguity is an important problem that has been studied through different approaches. We investigate, in this paper, some classification methods to disambiguate Arabic morphological features of non-vocalized texts. A possibilistic approach is improved and proposed to handle imperfect training and test datasets. We introduce a data tra...
This paper proposes and assesses a new possibilistic approach for automatic monolingual word sense disambiguation (WSD). In fact, in spite of their advantages, the traditional dictionaries suffer from the lack of accurate information useful for WSD. Moreover, there exists a lack of high-coverage semantically labeled corpora on which methods of lear...
This paper proposes and assesses a new possibilistic approach for automatic monolingual word sense disambiguation (WSD). In fact, in spite of their advantages, the traditional dictionaries suffer from the lack of accurate information useful for WSD. Moreover, there exists a lack of high-coverage semantically labeled corpora on which methods of lear...
We propose in this paper a new standard Arabic test collection for mono-and cross-language Information Retrieval (CLIR). To do this, we exploit the "Hadith" texts and we provide a portal for sampling and evaluation of Hadiths' results listed in both Arabic and English versions. The new called "Kunuz" standard Arabic test collection will promote and...
Traitement Automatique du Langage Naturel 2014, Faculté Saint-Charles, Marseille, France; 07/2014
The 6th International Conference on Agents and Artificial Intelligence (ICAART 2014), Angers, Loire Valley, France.; 03/2014
19th International Conference on Application of Natural Language to Information Systems, 18-20 June 2014 - Montpellier, France; 01/2014
19th International Conference on Application of Natural Language to Information Systems, Montpellier, France; 01/2014
International Journal on Knowledge and Information Systems. 01/2014;
In this paper, we explore several statistical methods to find solutions to the problem of query translation ambiguity. Indeed, we propose and compare a new possibilistic approach for query translation derived from a probabilistic one, by applying a classical probability-possibility transformation of probability distributions, which introduces a cer...
The 24th Conference on Computational Linguistics and Speech Processing (ROCLING 2012); 09/2012
We study in this paper the impact of Word Sense Disambiguation (WSD) on Query Expansion (QE) for monolingual intelligent information retrieval. The proposed approaches for WSD and QE are based on corpus analysis using co-occurrence graphs and possibilistic networks. Indeed, our model for relevance judgment uses possibility theory to take advantages...
We study in this paper the impact of Word Sense Disambiguation (WSD) on Query Expansion (QE) for monolingual intelligent information retrieval. The proposed approaches for WSD and QE are based on corpus analysis using co-occurrence graphs modelled by possibilistic networks. Indeed, our model for relevance judgment uses possibility theory to take ad...
نقدم، في هذا المقال، مشروع "كنوز" المتمثل في مدونة مرجعية للبحث عن المعلومة باللغة العربية والإنجليزية. إن مشروع "كنوز" يرتكز على نصوص الحديثا لنبوي باللغتين المذكورتين ونقترح عبر بوابة "كنوز المصطفى" برنامجا لتقييم نتائج البحث عن إستعلامات تمت تجميعها وفق طريقة تريك. نهدف من خلال المدونة المرجعية إلى النهوض بالبحوث باللغة العربية ولغات أخرى.
We aim to build a new standard Arabic test collection for mono-and cross-language Information Retrieval (CLIR). To do this, we exploit the "Hadith" texts and we provide a portal for sampling and evaluation of Hadiths' results listed in both Arabic and English versions. The portal will also offer simple search functionality for the general public us...
In this paper, we explore several statistical methods to find solutions to the problem of query translation ambiguity. Indeed, we propose and compare a new possibilistic approach for query translation derived from a probabilistic one, by applying a classical probability-possibility transformation of probability distributions, which introduces a cer...
Information retrieval applications are essential tools to manage the huge amount of information in the Web. Ontol-ogies have great importance in these applications. The idea here is that several data belonging to a domain of interest are represented and related semantically in the ontology, which can help to navigate, manage and reuse these data. D...
Information retrieval applications are essential tools to manage the huge amount of information in the Web. Ontologies have great importance in these applications. The idea here is that several data belonging to a domain of interest are represented and related semantically in the ontology, which can help to navigate, manage and reuse these data. De...
This paper presents a new possibilistic information retrieval system using semantic query expansion. The work is involved in query expansion strategies based on external linguistic resources. In this case, the authors exploited the French dictionary “Le Grand Robert”. First, they model the dictionary as a graph and compute similarities between quer...
This paper presents and experiments a new approach for automatic word sense disambiguation (WSD) applied for French texts. First, we are inspired from possibility theory by taking advantage of a double relevance measure (possibility and necessity) between words and their contexts. Second, we propose, analyze and compare two different training metho...
This paper presents a new approach for Arabic non-vocalized texts disambiguation based on a possibilistic classifier. A morphological analyzer provides all the possible solutions and the values of the morphological features of words. When texts are vocalized, the number of solutions is reduced and in many cases, we can identify the correct analysis...
This paper proposes and experiments a new approach for morphological feature disambiguation of non-vocalized Arabic texts using a possibilistic classifier. The main idea is to learn contextual dependencies between features from vocalized texts and exploit this knowledge to disambiguate non-vocalized ones. We use possibility theory as a means to mod...
This paper proposes and experiments a new approach for morpholog-ical feature disambiguation of non-vocalized Arabic texts using a possibilistic classifier. The main idea is to learn contextual dependencies between features from vocalized texts and exploit this knowledge to disambiguate non-vocalized ones. We use possibility theory as a means to mo...
This paper presents a new approach for Arabic non-vocalized texts disambiguation based on a possibilistic classifier. A morphological analyzer provides all the possible solutions and the values of the morphological features of words. When texts are vocalized, the number of solutions is reduced and in many cases, we can identify the correct analysis...
This paper presents and experiments a new approach for automatic word sense disambiguation (WSD) applied for French texts. First, we are inspired from possibility theory by taking advantage of a double relevance measure (possibility and necessity) between words and their contexts. Second, we propose, analyze and compare two different training metho...
This paper presents a new possibilistic information retrieval system using semantic query expansion. The work is involved in query expansion strategies based on external linguistic resources. In this case, the authors exploited the French dictionary "Le Grand Robert". First, they model the dictionary as a graph and compute similarities between quer...
This paper presents a new possibilistic approach for semantic query expansion in an information retrieval system. The approach fall into the category of query expansion strategies based on external linguistic resources. In our case, we exploited the French dictionary "Le Grand Robert". We are inspired from the possibilistic networks theory by takin...
He presented a master's thesis entitled "Un analyseur de contenu des documents scientifiques du Web." His current research interests are: ontology engineering, document analysis, and Arabic text processing. Bilel Elayeb is an assistant professor at the National School of Computer Science of La Manouba in Tunisia. He obtained his PhD in computer sci...
Ontologies are useful for modelling and retrieving knowledge in complex information systems. Ontology construction environments use statistical and linguistic information to extract knowledge from corpora. Within the great improvement in this field, there is a need to introduce the Arabic language in these environments. We present the ArabOnto arch...
This paper presents a new possibilistic approach for semantic query expansion in an information retrieval system. The approach fall into the category of query expansion strategies based on external linguistic resources. In our case, we exploited the French dictionary "Le Grand Robert". We are inspired from the possibilistic networks theory by takin...
Ontologies have an important role in knowledge organization and information retrieval. Domain ontologies are composed of concepts represented by domain relevant terms. Existing approaches of ontology construction make use of statistical and linguistic information to extract domain relevant terms. The quality and the quantity of this information inf...
Ontologies are useful for modelling and retrieving knowledge in complex information systems. Ontology construction environments use statistical and linguistic information to extract knowledge from corpora. Within the great improvement in this field, there is a need to introduce the Arabic language in these environments. We present the ArabOnto arch...
The Arabic storytelling methodology provides solutions to the problem of information reliability. The reliability of a story depends on the credibility of its narrators. To insure reliability verification, the narrators' names are explicitly cited at the head of the story, which constitute its chain of narrators. Stories were reported from a genera...
The Arabic storytelling methodology provides solutions to the problem of information reliability.The reliability of a story depends on the credibility of its narrators. To insure reliability verification, the narrators' names are explicitly cited at the head of the story, which constitute its chain of narrators. Stories were reported from a generat...
This Ph.D. thesis proposes a new model for a multiagent possibilistic Web information retrieval and its implementation. This model is based on two Hierarchical Small-Worlds (HSW) Networks and a Possibilistic Networks (PN): The first HSW consists in structuring the founded documents in dense zones of Web pages which strongly depend on each other. We...
La présente thèse de doctorat en informatique propose un modèle pour une recherche d'information intelligente possibiliste des documents Web et son implémentation. Ce modèle est à base de deux Réseaux Petits Mondes Hiérarchiques (RPMH) et d'un Réseau Possibiliste (RP) : Le premier RPMH consiste à structurer les documents retrouvés en zones denses d...
La présente thèse de doctorat en informatique propose un modèle pour une recherche d'information intelligente possibiliste des documents Web et son implémentation. Ce modèle est à base de deux Réseaux Petits Mondes Hiérarchiques (RPMH) et d'un Réseau Possibiliste (RP) : Le premier RPMH consiste à structurer les documents retrouvés en zones denses d...
Purpose
The purpose of this paper is to make a scientific contribution to web information retrieval (IR).
Design/methodology/approach
A multiagent system for web IR is proposed based on new technologies: Hierarchical Small‐Worlds (HSW) and Possibilistic Networks (PN). This system is based on a possibilistic qualitative approach which extends the q...
As a long time as Internet will continue its evolution, we will continue to be submerged by data, without those however being structured. The search for information within this framework becomes a difficult task and the traditional methods of search on Internet or data bases prove more and more limited. The co-operative information systems based on...
As a long time as Internet will continue its evolution, we will continue to be submerged by data, without those however being structured. The search for information within this framework becomes a difficult task and the traditional methods of search on Internet or data bases prove more and more limited. The co-operative information systems based on...
This paper presents a web information retrieval system based on Hierarchical Small-Worlds (HSW) and Possibilistic Networks (PN). The first HSW consists in structuring the "Google" search results in dense zones of web pages which strongly depend on each other. We thus reveal dense clouds of pages which "speak" more or less about the same subject and...
We describe in this paper a multiagent possibilistic system for web information retrieval, called SARIPOD. This system is based on Hierarchical Small-Worlds (HSW) and Possibilistic Networks (PN). The first HSW consists in structuring the "Google" search results in dense zones of web pages which strongly depend on each other. We thus reveal dense cl...
Résumé : La problématique majeure de la Recherche d'Information (RI) consiste à extraire à partir d'une collection de documents, ceux qui répondent à un besoin utilisateur en se basant souvent sur des informations pauvres. Les différents modèles connus de la RI (booléen, vectoriel, probabiliste, bayésien) représentent les documents et les requêtes...
In this paper, we propose a reusable multiagent architecture for web information retrieval integrating new technologies. This system, called SARIPOD, is based on Hierarchical Small-Worlds (HSW) and Possibilistic Networks (PN). The first HSW consists in structuring the "Google" search results in dense zones of web pages which strongly depend on each...
Résumé : La problématique majeure de la Recherche d'Information (RI) consiste à extraire à partir d'une collection de documents, ceux qui répondent à un besoin utilisateur en se basant souvent sur des informations pauvres. Les différents modèles connus de la RI (booléen, vectoriel, probabiliste, bayésien) représentent les documents et les requêtes...
This paper presents an Internet information retrieval system based on Hierarchical Small-Worlds (HSW) and Possibilistic Networks (PN). The first HSW, for the words of the French language, is used to take account of the dependences between these words. The second HSW is devoted to the web pages required and translated in the same way the dependences...