Publications

Conference paper, To appear
O. Ben Khiroun, B. Elayeb, and N. Bellamine Ben Saoud.
"Towards a Query Translation Disambiguation Approach using Possibility Theory",

In the 10th International Conference on Agents and Artificial Intelligence (ICAART 2018), pp. xx-xx, Funchal, Madeira, Portugal, 16-18 January 2018.

Abstract

Keywords

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Conference paper
A. Chouigui, O. Ben Khiroun, and B. Elayeb.
"ANT Corpus : An Arabic News Text Collection for Textual Classification",

In proceedings of the 14th ACS/IEEE International Conference on Computer Systems and Applications (AICCSA 2017), pp. 135-142, Hammamet, Tunisia, October 30 – November 3, 2017.

Project Web site: 🐜 https://antcorpus.github.io/

Abstract

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 predefined category. We study also in this work the contribution of terms weighting, stop-words removal and light stemming on Arabic TC. The experimental results prove that the text length affects considerably the TC accuracy and that titles words are not sufficiently significant to perform good classification rates. As a conclusion, the SVM method gives the best results of classification of both titles and texts parts.

Keywords

Arabic language, standard Arabic corpus, text classification, RSS crawling, TREC format, SVM, NB.
Book chapter
B. Elayeb, I. Bounhas, O. Ben Khiroun, and N. Bellamine Ben Saoud.
"Combining Semantic Query Disambiguation and Expansion to Improve Intelligent Information Retrieval",

In Duval B., van den Herik J., Loiseau S., and Filipe J. (eds.), ICAART 2014 Revised Selected papers, LNAI 8946, Springer International Publishing Switzerland, pp. 280-295, 2015.

Download paper: Springer | Download proceedings: Springer

 

Abstract

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 networks. Indeed, our model for relevance judgment uses possibility theory to take advantage of a double measure (possibility and necessity). Secondly, we propose and evaluate a probabilistic circuit-based approach combining SQD and SQE in an intelligent information retrieval context. In this approach, both SQD and SQE tasks are based on a graph data model, in which circuits between its nodes (words) represent the probabilistic scores for their semantic proximities. In order to compare the performance of these two approaches, we perform our experiments using the standard ROMANSEVAL test collection for the SQD task and the CLEF-2003 benchmark for the SQE process in French monolingual information retrieval evaluation. The results show the impact of SQD on SQE based on the recall/precision standard metrics for both the possibilistic and the probabilistic circuit-based approaches. Besides, the results of the possibilistic approach outperform the probabilistic ones, since it takes into account of imprecision cases.

Keywords

Semantic Query Disambiguation, Semantic query expansion, Word sense disambiguation, Information retrieval, Possibility theory, Probability theory, Semantic graph, Semantic proximity.
@inbook {EBBKB2014, title = {Combining Semantic Query Disambiguation and Expansion to Improve Intelligent Information Retrieval}, booktitle = {Duval B., van den Herik J., Loiseau S., and Filipe J. (eds.), ICAART 2014 Revised Selected papers, LNAI 8946, Springer International Publishing Switzerland, pp. 280-295.}, year = {2015}, abstract = {
}, author = {Bilel Elayeb and Ibrahim Bounhas and Ben Khiroun, Oussama and Narj{\`e}s Ben Saoud} }
Conference paper
O. Ben Khiroun, R. Ayed, B. Elayeb, I. Bounhas, N. Bellamine Ben Saoud, and F. Evrard.
"Towards a New Standard Arabic Test Collection for Mono- and Cross-Language Information Retrieval",

In the 19th International Conference on Application of Natural Language to Information Systems (NLDB 2014), Springer-Verlag Berlin, Germany, pp. 168-171, Montpellier, France, 18-20 June 2014 .

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Abstract

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 restart the development of Arabic mono retrieval and CLIR systems blocked since the earlier TREC-2001 and TREC-2002 editions.

Keywords

Mono- and Cross-Language Information Retrieval, Arabic Language, Standard Test Collection, Sampling Evaluation.
Journal article
B. Elayeb, I. Bounhas, O. Ben Khiroun, F. Evrard, and N. Bellamine Ben Saoud.
"A Comparative Study between Possibilistic and Probabilistic Approaches for Monolingual Word Sense Disambiguation",

In Knowledge and Information Systems, Springer London, 44(1): 91-126, DOI : 10.1007/s10115-014-0753-z, July 2015.

Abstract

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 learning could be trained. For these multiple reasons, it became important to use a semantic dictionary of contexts (SDC) ensuring the machine learning in a semantic platform of WSD. Our approach combines traditional dictionaries and labeled corpora to build a SDC and identify the sense of a word by using a possibilistic matching model. Besides, we present and evaluate a second new probabilistic approach for automatic monolingual WSD. This approach uses and extends an existing probabilistic semantic distance to compute similarities between words by exploiting a semantic graph of a traditional dictionary and the SDC. To assess and compare these two approaches, we performed experiments on the standard ROMANSEVAL test collection and we compared our results to some existing French monolingual WSD systems. Experiments showed an encouraging improvement in terms of disambiguation rates of French words. These results reveal the contribution of possibility theory as a mean to treat imprecision in information systems.

Keywords

Word sense disambiguation, Possibility theory, Probability theory, Semantic dictionary of contexts, Semantic graph.
Conference paper
O. Ben Khiroun, B. Elayeb, I. Bounhas, F. Evrard, and N. Bellamine Ben Saoud.
"Improving Query Expansion by Automatic Query Disambiguation in Intelligent Information Retrieval",

In the 6th International Conference on Agents and Artificial Intelligence (ICAART 2014), pp. 153-160, Angers, Loire Valley, France, 6-8 March 2014.

Abstract

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 advantages of a double measure (possibility and necessity). Our experiments are performed using the standard ROMANSEVAL test collection for the WSD task and the CLEF-2003 benchmark for the QE process in French monolingual Information Retrieval (IR) evaluation. The results show the positive impact of WSD on QE based on the recall/precision standard metrics.

Keywords

Semantic Query Expansion, Word Sense Disambiguation, Information Retrieval, Possibility Theory, Semantic Graph.
Conference paper
رجاء عيّاد، أسامة بن خيرون، إبراهيم بونحاس، بلال العايب، يحيى سليماني.
"كنوز: مدونة مرجعية باللغة العربية للبحث عن المعلومة",

In Proceedings of the 6th INFOL@NGUES seminar, Centre de Publication Universitaire (CPU) Eds, ISLAIB Béja, Tunisia, 24-26 April 2014.

Abstract

الخلاصة : نقدم، في هذا المقال، مشروع "كنوز" المتمثل في إنشاء مدونة مرجعية للبحث عن المعلومة باللغة العربية والإنجليزية. إن مشروع "كنوز" يرتكز على نصوص الحديث النبوي باللغتين المذكورتين ونقترح عبر بوابة "كنوز المصطفى" برنامجا لتقييم نتائج البحث عبر استعلامات تمّ تجميعها وفق منهجية تريك .(TREC) نهدف من خلال المدونة المرجعية إلى النهوض بالبحوث باللغة العربية ولغات أخرى. (CLIR)

Keywords

اللغة العربية، البحث الأحادي والترافقي عن المعلومة، نصوص الحديث النبوي، المدونة المرجعية.
Conference paper
O. Ben Khiroun, B. Elayeb, I. Bounhas, F. Evrard, and N. Bellamine Ben Saoud.
"A Possibilistic Approach for Automatic Word Sense Disambiguation",

In the 24th Conference on Computational Linguistics and Speech Processing (ROCLING 2012), pp. 261-275, Yuan Ze University, Chung-Li, Taiwan, 21-22 September 2012.

Conference web sites: ACLCLP.org & ROCLING 2012
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Abstract

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 methods: judgment and dictionary based training. Third, we summarize and discuss the overall performance of the various performed tests in a global analysis way. In order to assess and compare our approach with similar WSD systems we performed experiments on the standard ROMANSEVAL test collection.

Keywords

Word Sense Disambiguation, Semantic Dictionary of Contexts, Possibility Theory.
Journal article
B. Elayeb, I. Bounhas, O. Ben Khiroun, F. Evrard, and N. Bellamine Ben Saoud.
"Towards a Possibilistic Information Retrieval System Using Semantic Query Expansion",

In International Journal of Intelligent Information Technologies (IJIIT), IGI Global, Hershey, USA, 7(4) : 1-25, DOI : 10.4018/jiit.2011100101, October-December 2011.

Abstract

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 query terms by exploiting the circuits in the graph. Second, the possibility theory is used by taking advantage of a double relevance measure (possibility and necessity) between the articles of the dictionary and query terms. Third, these two approaches are combined by using two different aggregation methods. The authors also benefit from an existing approach for reweighting query terms in the possibilistic matching model to improve the expansion process. In order to assess and compare the approaches, the authors performed experiments on the standard ‘LeMonde94’ test collection.

Keywords

Possibilistic information retrieval, Semantic query expansion, Possibilistic networks, Dictionary modelling..
Conference paper
O. Ben Khiroun, B. Elayeb, I. Bounhas, F. Evrard, and N. Bellamine Ben Saoud.
"A Possibilistic Approach for Semantic Query Expansion",

In the 4th international conference on Internet Technologies and Applications (ITA 2011), V. Grout, D. Oram, and R. Picking (Eds), pp. 308-316, Wrexham Wales (UK), 6-9 September 2011.

Download proceedings: Lulu

Abstract

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 taking advantage of a double relevance measure (possibility and necessity) between the articles of the dictionary and the terms of the query. We also propose a new approach for reweighting query terms to improve the expansion process. In order to assess our approach we performed experiments on the "Le Monde94" test collection. Our results are compared to an existing approach modeling the dictionary as a graph and computing similarities between terms by exploiting the circuits in the graph.

Keywords

Semantic Query Expansion, Information Retrieval System, Possibilistic Networks, Dictionary modelling, reweighting query terms.
The Bibtex format.
Oussama Ben Khiroun ResearchGate
Oussama Ben Khiroun DBLP