Yahya Slimani Web Site

N°	Thesis	Year	Defense date	Doctoral Student's Name	Title
1	-	2022	2022	Nour El Houda Bouzerzour	Standardizing Service Descriptions to Enable Cloud Service Interoperability.
2	-	2024	2024	Ameni Belkahla	Exploitation de processeurs graphiques pour l'optimisation des systèmes de recommandation.

N°	Thesis	Year	Defense date	Doctoral Student's Name	Title
1	-	1999	26/06/1999	Faïza Najjar	Contribution à l'optimisation de requêtes de jointures pour bases de données distribuées
2	Thèse d'état Algérie	2007	novembre 2007	Ghalem Belalem	Contributions à la gestion de la cohérence de répliques de fichiers dans les systèmes à grande échelle
3	Thèse d'état Algérie	2007	novembre 2007	Belabass Yagoubi	Equilibrage de charge dans les grilles de calcul.
4	-	2008	04/10/2008	Cherif Haddad	Placement de bases de données dans les architectures à large échelle.
5	Thèse d'état Algérie	2010	26/10/2010	Zohra Slama	Localisation d’Utilisateurs Mobiles dans un Réseau Cellulaire sans Fils.
6	-	2012	05/12/2012	Moez Ben Haj Hmida	Deployment of data mining methods on Grid Computing.
7	-	2012	01/12/2012	Ines Bouzouita	Extraction de règles associatives de classification en classification supervisée.
8	-	2012	09/06/2012	Ibrahim Bounhas	Construction et intégration d'ontologies pour la cartographie socio-sémantique de fonds documentaires arabe guidée par la fiabilité de l'information.
9	-	2012	27/11/2012	Brahim Douar	Fouille de sous-graphes fréquents à base d'arc consistance.
10	Thèse de Doctorat Sénégal	2012	23/06/2012	Fodé Camara	Proposition et mise en œuvre d’un protocole de sécurité dans un processus de datamining.
11	-	2013	15/01/2013	Ghada Gasmi	Inférence de dépendances fonctionnelles en utilisant les techniques de la fouille de données.
12	-	2013	18/01/2013	Rim Mghirbi	Agrégation des résultats dans les systèmes de recherche d'information Pair-à-Pair non structurés.
13	-	2013	07/03/2013	Hassanet Slimani	A Voronoi-based index for the processingt of the location-dependent queries.
14	-	2014	10/06/2014	Raja Tlili	Strategies for high performance datamining on Grid platforms.
15	-	2014	15/01/2014	Taoufik Yeferny	Proposition d'approches de routage de requêtes dans les systèmes Pair-à-Pair non structurés.
16	Thèse de Doctorat Algérie	2015	21/10/2015	Mohammed Rebbah	Tolérance aux fautes dans les grilles de calcul.
17	Thèse de Doctorat Algérie	2015	19/04/2015	Bakhta Amrane	Méthode de recherche de services web basée sur l'analyse formelle de concepts.
18	Thèse de Doctorat Sénégal	2015	11/06/2015	Mohamed Mahmoud Ould Deye	Gestion de la qualité de services pour les applications et les services dans une infrastructure de type Cloud.
19	-	2015	17/09/2015	Saloua Zammali	Recherche d'information contextuelle: intégration du contexte dans un système de recherche d'information distribué.
20	Thèse de Doctorat Algérie	2016	24/01/2016	Hayat Bendoukha	Une approche workflow pour la définition et la composition des services dans une grille de calcul.
21	-	2016	11/06/2016	Manel Zekri	Automatisation de la conception et de la mise en oeuvre d'un entrepôt de données générique.
22	-	2018	08/03/2018	Meriem Amina Zingla	Vers un nouveau modèle de recherche d'information dans les réseaux sociaux basé sur la fouille de textes.
23	-	2018	28/03/2018	Chedi Bechikh Ali	Termes complexes pour l'indexation textuelle monolingue et inter-langues.
24	-	2018	10/03/2018	Amna Dridi	Levraging social information for personalized search.
25	-	2019	28/09/2019	Ameni Meskini	Auto-adaptation inter-coucges de services web tolérants aux fautes.
26	-	2020	25/01/2020	Wiem Lahbib	Extraction et structuration de terminologies pour la recherche d'information en langue Arabe.
27	-	2020	27/01/2020	Nadia Soudani	Fouille de textes arabes pour la construction de ressources morpho-sémantiques et la recherche d'information.
28	-	2020	05/10/2020	Souad Ghazouani	Service composition in multi-cloud environment.
29	-	2020	08/02/2020	Wiem Fekih Hassen	A ubiquitous navigation service on smartphones.
30	-	2021	19/12/2021	Narimene Dakiche	Contribution à la Détection et la Prédiction de l'Évolution des Communautés dans les Réseaux Sociaux.
31	-	2021	30/11/2021	Billel Aklouche	Proposition et expérimentation d'un modèle probabiliste d'expansion de requêtes.
32	-	2021	07/01/2021	Souheila Ben Guirat	Morphological levels combining approaches for Arabic Information retrieval.
33	-	2021	16/12/2021	Rim Dridi	Contextuel recommender system based on multi-criteria preferences.
34	-	2021	09/12/2021	Hamda Slimi	Toward Automatic Tweet And User.

N°	Projets	Période
1	Projet CMCU (France-Tunisie)	2014/2017
2	Projet DGRS/CNRS (France-Tunisie)	2014/2016
3	Projet scientifique Tunisie-Maroc	2016/2017
4	Accord de coopération pédagogique et scientifique entre l’ISAMM et la Faculté des Nouvelles Technologies et de la Communication de l’université de Constantine 2 (Algérie)	Projet en cours

Name	Institute	Level
Parallel and Distributed Systems	ISAMM, University of Manouba	TunisiaEngineer 2nd year
Problem Complexity	ISAMM, University of Manouba, Tunisia	Engineer 2nd year
Virtualization and Cloud Computing	ISAMM, University of Manouba, Tunisia	Engineer 2nd year
Calculability and Complexity	ISAMM, University of Manouba, Tunisia	Master of research
Advanced Architectures and Systems	ISAMM, University of Manouba, Tunisia	Master of research
Dependability	ISAMM, University of Manouba, Tunisia	Master of research
Parallel and Distributed Data Mining	ISAMM, University of Manouba, Tunisia	Master of research
Data Privacy	ISAMM, University of Manouba, Tunisia	Master of research
Distributed Systems	National School of Computer Science, Algiers, Algeria	Doctorate
Grid and Cloud Computing	University of Dakar, Senegal	Master of research
Distributed Systems	ESC, Manouba university	Master of Research

Name	Institute	Level
Operating Systems	FST, University of Tunis El Manar, Tunisia	Engineer 1st year
Advanced Operating Systems	FST, University of Tunis El Manar, Tunisia	Engineer 2nd year
Operating Systems (levels 1 and 2)	FST, University of Tunis El Manar, Tunisia	Bachelor’s degree
Advanced Architectures and Systems	FST, University of Tunis El Manar, Tunisia	Master of research
Dependability	FST, University of Tunis El Manar, Tunisia	Master of research
Parallel and Distributed Data Mining	FST, University of Tunis El Manar, Tunisia	Master of research
Data Mining	FSEG, University of Sfax, Tunisia	Master of research
Data Mining	UCAD, University of Dakar, Senegal	Master of research
Parallel and Distributed Systems	UCAD, University of Dakar, Senegal	Master of research
Data Mining	UGB, University of St Louis, Senegal	Master of research
Distributed Systems	UGB, University of St Louis, Senegal	Master of research
Data Mining	University of Mascara, Algeria	Master of research
Data Mining	USTO University, Algeria	Master of research
Parallel and Distributed Systems	University of Oran, Algeria	Master of research
Parallel and Distributed Systems	University of Constantine 2, Algeria	Master of research
Parallel and Distributed Systems	ESI Alger, Algeria	Master of research
Data Mining	FSEG, University of Jendouba, Tunisia	Master of research
Data Mining	ISIG Kairouan, Tunisia	Master of research

Narimene Dakiche, Fatima Benbouzid-Si Tayeb, Yahya Slimani, Karima Benatchba: Community evolution prediction in dynamic social networks using community features' change rates. SAC 2019: 2078-2085.
Souheila Ben Guirat, Ibrahim Bounhas, Yahya Slimani: Pre-indexing Techniques in Arabic Information Retrieval. ICAART (2) 2019: 237-246.
B. Aklouche, Bounhas, I., and Slimani, Y., “Pseudo-Relevance Feedback Based on Locally-Built Co-occurrence Graphs”, in 23rd European Conference on Advances in Databases and Information Systems (ADBIS 2019), Bled, Slovenia, 2019, pp 105-119.
Billel Aklouche, Ibrahim Bounhas, Yahya Slimani : BM25 Beyond Query-Document Similarity. SPIRE 2019: 65-79.
Hamda Slimi, Ibrahim Bounhas, Yahya Slimani : URL-Based Tweet Credibility Evaluation. AICCSA 2019: 1-6.
Hamda Slimi, Ibrahim Bounhas, Yahya Slimani : L'exploitation des techniques de régression pour l'évaluation de la crédibilité des tweets. EGC 2019: 327-332-occurrence Graphs”, in 23rd European Conference on Advances in Databases and Information Systems (ADBIS 2019), Bled, Slovenia, 2019, pp 105-119.
Rim Dridi, Lynda Tamine, Yahya Slimani. Context-Aware Multi-criteria Recommendation Based on Spectral Graph Partitioning. In: Hartmann S., Küng J., Chakravarthy S., Anderst-Kotsis G., Tjoa A., Khalil I. (eds) Database and Expert Systems Applications. DEXA 2019. Lecture Notes in Computer Science, vol 11707. Springer, pp. 211-221.

R. Tlili, K. ElBedoui, Y. Slimani. A Scalable Strategy for Mining Association Rules Under Grids. IKE - World Congress in Computer Science, Computer Engineering and Applied, vol. 15, http://worldcomp-proceedings.com/proc/p2015/IKE_contents.html.
Meriem Amina Zingla, Chiraz Latiri, Yahya Slimani: Tweet Contextualization Using Association Rules Mining and DBpedia. CLEF 2015: 318-323.
Ameni Meskini, Yehia Taher, Rafiqul Haque, Yahya Slimani: Cross-layer Service Adaptation - State-of-the-Art, Shortcoming Analysis, and Future Research Directions. CLOSER 2015 : 260-267.
Belhaj Rhouma Sourour, Cherif Chiraz Latiri, Yahya Slimani: Vers des méta-règles de contexte appréciées par la IIE pour la RI. CORIA 2015: 205-220.
Meriem Amina Zingla, Mohamed Ettaleb, Chiraz Latiri, Yahya Slimani : Nouvelle approche de contextualisation de tweets basée sur les règles d'association inter-termes. EGC 2015: 487-488.
Wiem Lahbib, Ibrahim Bounhas, Yahya Slimani : Arabic Terminology Extraction and Enrichment Based on Domain-Specific Text Mining. ICTAI 2015: 340-347.
Meriem Amina Zingla, Chiraz Latiri, Yahya Slimani, Catherine Berrut : Statistical and Semantic Approaches for Tweet Contextualization. KES 2015: 498-507.
Balla W. Diack, Samba Ndiaye, Yahya Slimani: Consistency tradeoffs on distributed multi-datacentric systems : SCOLCH theorems. ICIT 2015, The 7th International Conference on Information Technology. doi:10.15849/icit.2015.0031 ICIT 2015 (http://icit.zuj.edu.jo/ICIT15).

R. Tlili, Y. Slimani. Executing association rule mining algorithms under a Grid computing environment. Proceedings of the 9th Workshop on Parallel and Distributed Systems : Testing, Analysis, and Debugging, PADTAD 2011, Toronto, ON, Canada, July 17-21, PADTAD 2011, pp. 53-61.
G. Gasmi, Y. Slimani, L. Lakhal. Towards a Parallel Approach for Incremental Mining of Functional Dependencies on Multi-core Systems. Knowledge-Based and Intelligent Information and Engineering Systems - 15th International Conference, KES 2011, Kaiserslautern, Germany, September 12-14, 2011, pp. 590-598.
B. Douar, M. Liquiere, C. Latiri, Y. Slimani. Nouvelle approche de fouille de graphes AC-réduits fréquents. Extraction et gestion des connaissances (EGC'2011), 25-29 janvier 2011, Brest, France, Editions Hermann, pp. 473-478.
B. Douar, M. Liquiere, C. Latiri, Y. Slimani. FGMAC : Frequent subgraph mining with Arc Consistency. Proceedings of the IEEE Symposium on Computational Intelligence and Data Mining, CIDM 2011, part of the IEEE Symposium Series on Computational Intelligence 2011, April 11-15, 2011, Paris, pp. 112-119.
Brahim Douar, Michel Liquiere, Cherif Chiraz Latiri, Yahya Slimani : Graph-Based Relational Learning with a Polynomial Time Projection Algorithm. ILP 2011: 98-112.
B. Gueye, Niang, I., Gueye, B., Ould Deye, M. Mahmoud, and Slimani, Y., "Constraints-based response time for efficient QoS in Web Services Composition". In NWeSP, 2011 IEEE 7th International Conference on Next Generation Web Services Practices, 19-21 October 2011, Salamanca.
Ghada Gasmi, Amira Beji, Yahya Slimani, Lotfi Lakhal. Functional Dependency Mining : Harnessing Multicore Systems. 10th IEEE/ACIS International Conference on Computer and Information Science, 2011.

Y. Slimani, M. Ben Haj Hmida., "Data Mining parallèle et distribué". Tutoriel 10ème Journées Francophones Extraction et Gestion des Connaissances, EGC10, 26-29 Janvier 2010, Hammamet, Tunisie.
C. Latiri, Y. Slimani, C. Nasri, K. Smaïli. Extraction des séquences fermées fréquentes à partir de corpus parallèles : Application à la traduction automatique. 10ème Journées Francophones Extraction et Gestion des Connaissances, EGC10, 26-29 Janvier 2010, Hammamet, Tunisie, pp. 55-60.
R. Mghirbi, K. Arour, Y. Slimani, B. Defude. A Profile-Based Aggregation Model in a Peer-To-Peer Information Retrieval System. Data Management in Grid and Peer-to-Peer Systems, Third International Conference, Globe 2010, Bilbao, Spain, September 1-2, 2010, pp. 148-159.
M.A Esseghir, G. Goncalves, Y. Slimani. Memetic Feature Selection: Benchmarking Hybridization Schemata. Hybrid Artificial Intelligence Systems, 5th International Conference, HAIS 2010, San Sebastian, Spain, June 23-25, 2010, pp. 351-358.
M.A Esseghir, G. Goncalves, Y. Slimani. Adaptive Particle Swarm Optimizer for Feature Selection. Intelligent Data Engineering and Automated Learning IDEAL 2010, 11th International Conference, Paisley, UK, September 1-3, 2010, pp. 226-233.
R. Mghirbi, K. Arour, Y. Slimani, B. Defude. Un modèle comportemental d'interclassement de résultats dans un système de recherche d'information pair-à-pair. Actes du XXVIII Congrès INFORSID, Marseille, France, 25-28 mai 2010, pp. 95-110.
Ibrahim Bounhas, Yahya Slimani. A hierarchical approach for semi-structured document indexing and terminology extraction. International Conference on Information Retrieval & Knowledge Management (CAMP), 2010.

T. Hamrouni, I. Denden, S. Ben Yahia, E. Mephu Nguifo, and Y. Slimani., "Les itemsets essentiels fermés : une nouvelle représentation concise". In Actes des 7ème Journées Francophones Extraction et Gestion de Connaissances, Namur, Belgique, RNTI, 23-26 Janvier 2007.
S. Zghal, K. Kamoun, S. Ben Yahia, E. Mephu Nguifo, Y. Slimani., "EDOLA : Une nouvelle méthode d'alignement d'ontologies OWL-Lite". CORIA 2007: 351-367.
S. Zghal, E. Mephu Nguifo, K. Kamoun, S. Ben Yahia, Y. Slimani., "A new alignment method for OWL-Lite ontologies using propagation of similarity over the graph". DEXA Workshops 2007: 524-528.
C. Haddad, Y. Slimani., "Economic model for replicated database placement in grid". in the 7th IEEE International Symposium on Cluster Computing and the Grid (CCGrid’07), Rio de Janeiro, Brazil, May 2007, pp 283-289.
S. Zghal, S. Ben Yahia, E. Mephu Nguifo, Y. Slimani., "SODA: an OWL-DL based Ontology Matching System". The Second International Workshop on Ontology Matching (OM 2007), November 11, 2007, BEXCO, Busan, Korea.
M. A. Esseghir, T. Hsu, G. Goncalves, Y. Slimani., "A Cooperative feature selection approach based on island model". Colloque sur l'Optimisation et les Systèmes d'Information, COSI 2007, Oran, Algérie, Juin, 2007.
G. Belalem, Y. Slimani., "Consistency Management for Data Grid in OptorSim Simulator". MUE 2007: 554-560.
S. Saïdi, Y. Slimani, K. Arour., "Webview selection from user access patterns". PIKM 2007: 171-176.
A. Hamdadou, B. Bouziane, Y. Slimani., "Proposal for a Spatial Decision Support System in Territory Planning : A Hybrid Approach : Linear Programming, Fuzzy Measurement, Multicriterion Methods and GIS". ACIT 2007, Syria.

M. Ben Hadj Hamida, Y. Slimani., "A Patricia-Tree Approach for Frequent Closed Itemsets". WEC(2), 2005, pp. 253-256.
S. Ben Yahia, Y. Slimani, J. Rezgui., "A divide and conquer approach for deriving partially ordered sub-structures". In Proceedings of the Intl. Ninth Pacific-Asia Conference on Knowledge Data Discovery (PAKDD'05), LNCS, vol. 3120, Hanoi, Vietnam, May, 18-20, 2005, pp. 91-96.
G. Gasmi, S. Ben Yahia, E. Mephu Nguifo, Y. Slimani., "IGB : A new informative generic base of association rules". In Proceedings of the Intl. Ninth Pacific-Asia Conference on Knowledge Data Discovery (PAKDD'05), LNAI, vol. 3518, Vietnam, May 18-20, 2005, pp.81-90.
T. Hamrouni, S. Ben Yahia and Y. Slimani., "Prince : Extraction optimisée des bases génériques de règles sans calcul de fermetures". In Proceedings of the Intl. INFORSID Conference, Editions Hermès, Grenoble, France, pp. 353-368, 24-27 May 2005.
G. Gasmi, S. Ben Yahia, E. Mephu Nguifo, and Y. Slimani., "Discovering 'Factual' and 'Implicative' generic association rules". In Proceedings of the Intl. Conference CAP'05, Nice, France. Presses Universitaires de Grenoble, pp. 329-344, 30 Mai-3 Juin 2005.
T. Hamrouni, S. Ben Yahia and Y. Slimani., "Avoiding the itemset closure computation pitfall". In Proceedings of the Intl. Conf. on Concept Lattices and their Applications, CLA 2005, Olomouc, Czech Republic, pp. 46-59, September 7-9, 2005.
H. Bendoukha, Y. Slimani., "Approche d’Intégration du Modèle Workflow dans une Grille de Calcul : Application à la Production Numérique de Films". COSI 2005.
Sondess Ben Tekaya, Sadok Ben Yahia, Yahya Slimani : GenAll Algorithm: Decorating Galois lattice with minimal generators. CLA 2005.
T. Hamrouni, S. Ben Yahia and Y. Slimani., "Prince: An algorithm for generating rule bases without closure computations". In Proceedings of the 7th Intl. Conference on Data Warehousing and Knowledge Discovery (DaWak 2005), Springer-Verlag, LNCS 3589, Copenhagen, Denmark, pp. 346-355, August 2005.

Knowledge Discovery refers to the overall process of discovering useful knowledge from data. In this process, data mining is an important step where we apply specific algorithms for extracting useful information (knowledge). There are various types of data mining techniques such as association rules, classifications and clustering. Association rule mining, one of the most important and well techniques of data mining. Algorithms for extracting association rules explore large item spaces to identify all items that satisfy some user-specified criteria. Then, these items are used to generate association rules. These algorithms suffer from two drawbacks:

The size of the search space to explore;
The multiple accesses to physical databases.

A known challenge (and always an open research issue) is how to constrain the search space to prevent an exponential explosion of rules while minimizing information loss. Our contributions to this challenge are twofold :

Data representation and algorithmic : We study more suitable data to represent the search space in order to reduce its exploration. For example, we used intensively Formal Concept Analysis that can be used as an unsupervised clustering technique. In addition, FCA is particularly suited for exploratory data analysis because of its human-centeredness. The generation of knowledge is promoted by the FCA representation that makes the inherent logical structure of the information transparent. We used this representation for different types of data like text (text mining), web (web mining) and web services (web services discovery).
Performance : To reduce the effect of size space on data mining algorithms performance, we proposed and developed parallel and distributed versions of sequential data mining algorithms (parallel and distributed generation of association rules, parallel and distributed classification, etc.).

Research Staff

Name	Position	University	Email
Yahya Slimani	Full Professor, Head of the group	ISAMM Manouba, Tunisia	yahya.slimani@fst.rnu.tn
Chiraz Latiri	Full Professor, Research team leader	ISAMM Manouba, Tunisia	chiraz.latiri3@gmail.com
Ghada Gasmi	Assistant Professor, Research team leader	INSAT, Tunis	ghada.gasmi@gmail.com
Brahim Bounhas	Assistant Professor, Research team leader	ISD Manouba, Tunisia	bounhas.ibrahim@gmail.com
Hatem Haddad	Assistant Professor, Research team leader	ISAMM Manouba, Tunisia	haddad.hatem@gmail.com

External Collaborators

Name	Position	University	Email
Samba Ndiaye	Professor, Research Team Leader	UCAD University, Sénégal	samba.ndiaye@ucad.edu.sn
Fode Camara	Associate Professor, Research team leader	Bambay university (Senegal)	fode.camara@uadb.edu.sn
Mohamed El Hadi Benelhadj	Associate Professor	University of Constantine 2, Algeria	benelhadj@gmail.com
Dame Samb	Assistant Professor	Thies university (Senegal)	dsamb@univ-thies.sn

High Performance Computing (HPC) represents any computational activity requiring more than a single computer to execute a given task. As example, we can cite supercomputers and computer clusters that are used to solve advanced computation problems. HPC has also the capacity to handle and analyze massive amounts of data at high speed. In our research, we used HPC to explore three major issues :

HPC for large and distributed data applications : Due to the exponential growth of data, today there is an ever increasing need to process and analyze big data. The huge size of the available data and their high-heterogeneity and high-dimensionality make large-scale data mining applications computationally very demanding. Moreover, the quality of the data mining results often depends directly on the amount of computing resources available. In fact, data mining applications are poised to become the dominant consumers of supercomputing in the near future. There is a necessity to develop eﬀective parallel algorithms for various data mining techniques. However, designing such algorithms is challenging. In this research topic, we try to develop and experiment data mining algorithms that are able to benefit from the capabilities of HPC infrastructures.
HPC programming : While discussions of HPC architectures have long centered on performance gains, that is not the only measure of success of HPC. The programmability of these architectures is as important as performance. Because the high heterogeneity of HPC architectures, their programmability concerns various HPC platforms: Multiprocessors, Cluster, Grid Computing, Multicores, etc. Today’s Petascale computing algorithms and applications are not structured to take advantage of these architectures. Recent studies estimate that 80-90% of applications use a single level of parallelism. Hence, it’s important to revisit old parallel programming models and languages to define parallel programming models for HPC. One approach is to use hybrid parallelism, i.e. parallelism at multiple levels with multiple programming models (MPI, OpenMP, MapReduce, Hadoop, CUDA, etc.), will be used in many applications. Hybrid parallelism may emerge because application speedup at each level can be multiplied by future architectures.
Fault tolerance and HPC : With the emergence of Petascale systems, fault tolerance has received a lot of attention over the last decade. Most the existing fault tolerance techniques for parallel and distributed applications have been applied to high computing applications. Unfortunately, despite their relative success, existing approaches do not fit well with the challenging evolutions of large-scale systems. In a development of a fault tolerance technique for HPC architectures, scalability and performance are the most two important aspects that we need to take to our consideration. The goal of this research is to develop scalable fault tolerance techniques to help to make future high performance computing applications self-adaptive and fault survivable.

Research Staff

Name	Position	University	Email
Yahya Slimani	Full Professor, Head of the group	ISAMM Manouba, Tunisia	yahya.slimani@fst.rnu.tn
Moez Ben Haj Hmida	Assistant Professor, Research team leader	ENIT Tunis El Manar, Tunisia	moez.benhajhmida@gmail.com
Riadh Frefita	Assistant Professor	ESPRIT Tunis, Tunisia	readfrefita@gmail.com
Amani Belkahla	PhD student	ENSI, Manouba	amani.belkahla@gmail.com

External Collaborators

Name	Position	University	Email
Ibrahima Niang	Professor, Research Team Leader	UCAD, Senegal	ibrahima_niang@hotmail.com
Mohamed Rebbah	Associate Professor, Research team Leader	Mascara University, Algeria	rebbahmed@univ-mascara.dz

Information retrieval (IR) is considered as the science of searching for relevant information including documents, images, video and other forms of media across databases, unstructured data and the World Wide Web. Nowadays information retrieval is widely known and used in the context of online web search engines. But Information has also many other fields of application domains, like biomedicine, social network, social science, genomic, geographic, etc. In this research topic, we study five research thematics: contextual IR, social IR, temporal IR, Arabic IR and testbeds for IR systems.

Context-based retrieval : Information retrieval can benefit from contextual information to adapt the results to a user’s current situation and personal preferences. For example, performing the same query in different contexts often leads to different result rankings. Hence, semantics-based information retrieval is especially challenging because a change in context has an impact on the knowledge base content. In the context of information retrieval, the impact of a contextual aspect on the query results determines its relevance. In this issue, we study the problem of identification of relevant contextual information and his effect (or influence) on the performance of an information retrieval system. Our goal is to achieve high recall and precision for a specific user in a specific situation.
Social-based retrieval : Recently the fields of information retrieval and social network analysis have contributed to the emergence of a new category of information retrieval systems, namely the SIR systems (Social Information Retrieval). These systems extend conventional IR to incorporate the social context of search and recommendation. A particular aspect of SIR is the modeling of the social interaction between people (social ties), which is used for enhancing recommendation systems. Our goal in this issue is to see how information retrieval systems can be enriched by analyzing these social ties, and particularly the strong and weak ties that measure the strength of relationship between people.
Temporal information retrieval systems : Temporal Information Retrieval (TPR) is an emerging research area in the field of Information Retrieval. It is a fact of modern life that an enormous volume of information is created, exchanged, and stored electronically on the Web. Much of the content of stored resources is strongly time-dependent. Hence, an electronic resource can be identifying not only by his content but also by some temporal features, like creation or update date. These temporal features can be used to increase precision of search in an information retrieval system. In fact, classical IR techniques based on topic similarity alone are not sufficient for the search in temporal document collections. To overcome this limit, temporal dimension available in electronic resources (like documents) should be incorporated with document ranking for efficient retrieval. Our objective in this issue is twofold: (i) identifying the temporal characteristics of documents; (ii) incorporating these characteristics into information retrieval techniques in order to improve the retrieval effectiveness of an information retrieval system.
Arabic information retrieval : Traditional information retrieval system was carried out essentially in English and fueled by the annual Text Retrieval Conferences (TREC) sponsored by NIST (the National Institute of Standards and Technology). NIST has accumulated large amounts of standard data (text collections, queries, and relevance judgments) so that IR researchers can compare their techniques on common data sets. More recently, IR researchers have found a real interest to study new languages other than English. Now, TREC includes multilingual data and other organizations sponsor similar annual evaluations for European languages (CLEF) and Asian languages (NTCIR) (Chinese, Japanese, and Korean). Arabic began to be included in the TREC cross-lingual track, and in the TDT (topic detection and tracking) evaluations. The availability of standard Arabic data sets from the NIST and the Linguistic Data Consortium (LDC) has in turned spurred a huge acceleration in progress in information retrieval and other natural language processing involving Arabic language. Arabic is an interesting case to study in IR, because Arabic is a highly inflected language. In this sub-topic, we study some problematic related to IR systems (lemmatization, morphological analysis, indexation) and we use the Hadith corpora as knowledge basis.
Testbed for IR systems : The central problem of information retrieval (IR) is to find test collections. The existing data sets (like those provided by TREC) have played a key role to promote progress in the IR domain. However, given the significant increase of online content over the past few years and their diversity, and of the increasing rate of search queries, the current testbeds are either too small or not representative of the real applications of IR systems.

Research Staff

Name	Position	University	Email
Yahya Slimani	Full Professor, Head of the group	ISAMM Manouba, Tunisia	yahya.slimani@fst.rnu.tn
Chiraz Latiri	Full Professor, Research team leader	ISAMM Manouba, Tunisia	chiraz.latiri3@gmail.com
Brahim Bounhas	Assistant Professor, Research team leader	ISD Manouba, Tunisia	bounhas.ibrahim@gmail.com
Moez Ben Haj Hmida	Assistant Professor, Research team leader	ENIT Tunis El Manar, Tunisia	moez.benhajhmida@gmail.com
Hatem Haddad	Assistant Professor, Research team leader	ISAMM Manouba, Tunisia	haddad.hatem@gmail.com
Meriem Zingla	Associate Professor	Univ. Mascara (Algeria)	zinglameriem@gmail.com
Chedi Bechikh	Assistant Professor	FSEG Jendouba, Tunisia	chedi.bechikh@gmail.com
Nadia Soudani	Assistant Professor	FSEG Jendouba, Tunisia	nadia.soudani@gmail.com
Wiem Lahbib	Doctoral thesis	--	wiemlahbib88@hotmail.fr
Hamda Slimi	Associate Professor	Tebessa university (Algeria)	slimi.hamda2@gmail.com
Billel Aklouche	Associate Professor	Constantine university (Algeria)	aklouche.billel@gmail.com
Rim Dridi	Assistant Professor	FST Tunis, Tunisia	dridi.rime@gmail.com
Narimene Dakiche	Associate Professor	ESI, Oued-Smar (Algeria)	an_dakiche@esi.dz
Fatima Benbouzid Si Tayeb	Professor, Research team leader	ESI, Oued-Smar (Algeria)	f_sitayeb@esi.dz

External Collaborators

Name	Position	University	Email
Kamel Smaili	Full Professor	University of Lorraine, France	Kamel.Smaili@loria.fr
Lionel Brunie	Full Professor	INSA Lyon, France	Lionel.Brunie@insa-lyon.fr
Ibrahima Niang	Professor	UCAD, Senegal	ibrahima_niang@hotmail.com
Eric Gaussier	Full Professor	IMAG Grenoble, France	eric.gaussier@imag.fr
Catherine Berrut	Full Professor	IMAG Grenoble, France	Catherine.Berrut@imag.fr
Lynda Tamine	Full Professor	IRIT Toulouse, France	Lynda.Lechani@irit.fr
Fabrice Evrard	Assistant Professor	ENSEEIHT Toulouse, France	Fabrice.Evrard@enseeiht.fr
Bakhta Amrane	Associate Professor	University of Oran, Algeria	fatema_amrane@yahoo.fr
Bilel El Ayeb	Assistant Professor	FSB Bizerte, Tunisia	elayeb_bilel@yahoo.fr

Cloud Computing has attracted researchers as an alternative to supercomputers for high performance computing. Grids enable access to shared computing power and storage capacity, while Clouds enable access to leased computing power and storage capacity. Although there is a difference in the fundamental concepts of Grid and Cloud computing that does not necessarily mean that they are mutually exclusive. For example, it is quite feasible to have a Cloud within a Grid, as it is possible to have a Grid as a part of a Cloud. We use these infrastructures to revisit some problems and challenges of classical parallel and distributed systems.

Deployment of data mining algorithms on Grid’s : In this issue, we are interested by implementing and adapting parallel and distributed data mining algorithms on these architectures.
Load balancing for data mining algorithms : in these infrastructures, some computational resources are heavily loaded while others have available processing capacity. In this issue, we study the problem of load balancing for data mining algorithms running on Grid platforms. In the context of Cloud’s, we use the load balancing to enhance the QoS.
Fault tolerance for Grid’s : Fault tolerance is an important property for large scale computational grid systems, where geographically distributed nodes co-operate to execute tasks. Due to the number of components and their diversity, nodes, networks, disks and applications frequently fail, restart, disappear and behave unexpectedly. As the number of grid system components increases, the probability of failures in the grid computing environment becomes higher than that in a traditional parallel computing environment. Hence, support for the development of fault tolerant applications has been identified as one of the major technical challenges to address for the successful deployment of computational. Since the failure of resources affects job execution fatally, fault tolerance service is essential to satisfy QOS requirement in grid computing. Commonly utilized techniques for providing fault tolerance are job checkpointing, load balancing and replication. In case of complex scientific workflows where tasks can execute in well defined order reliability is another biggest challenge because of the unreliable nature of the grid resources. To study this problem, we proposed a dynamic colored graph for representing a Grid infrastructure. On the basis of this new representation, we defined and implemented a framework to tolerate failures of nodes and communication links. The same graphic representation is used to study the load balancing problem in Grid systems.
Load balancing and QoS for Cloud computing : Cloud computing has grown in popularity in recent years thanks to technical and PAYG business model (Pay As You Go) benefits. In Cloud computing environments, application requirements can be characterized by quality of service (QoS) requirements such as availability, security, reliability, load balancing, etc., as mentioned in the Service Level Agreement (SLA). To improve the efficiency of the Cloud infrastructures, system, we suggest an approach to make load balancing more dynamic to better manage the QoS of multi-instance applications in the Clouds. This approach is based on limiting the number of requests that, at a given time, can be effectively sent and stored in queues of virtual machines through a queue load balancer for incoming user requests. Our simulation-based experimental results using production workload models show that the proposed provisioning technique detects changes in workload intensity (arrival pattern, resource demands) that occur over time and allocates multiple virtualized resources to satisfy QoS constraints.

Research Staff

Name	Position	University	Email
Yahya Slimani	Full Professor, Head of the group	ISAMM Manouba, Tunisia	yahya.slimani@fst.rnu.tn
Moez Ben Haj Hmida	Assistant Professor, Research team leader	ENIT Tunis El Manar, Tunisia	moez.benhajhmida@gmail.com
Baya Chalabi	PhD student	ESI Alger, Algeria	b_chalabi@esi.dz
Nour-El-Houda Bouzerzour	PhD student	ENSI, Manouba	nounourelhouda20@gmail.com
Souad Ghazouani	Assistant Professor, Research team leader	FSEG Jendouba, Tunisia	souad.ghazouani1987@gmail.com

External Collaborators

Name	Position	University	Email
Belabass Yagoubi	Full Professor	University of Oran, Algeria	byagoubi@gmail.com
Ghalem Belalem	Full Professor	University of Oran, Algeria	ghalem1dz@gmail.com
Ibrahima Niang	Professor	UCAD, Senegal	ibrahima_niang@hotmail.com
Mohamed Rebbah	Associate Professor	University of Mascara, Algeria	rebbah_med@yahoo.fr
Mohamed Mahmoud Ould Deye	Assistant Professor	UCAD, Senegal	deyeother@yahoo.fr

Name :	SLIMANI
Last name :	Yahya
Birth date :	March 19, 1951
Birthplace :	Oujda
Citizen :	Algerian
Email :	yahya.slimani@fst.rnu.tn
Email :	yahya.slimani@gmail.com
Email :	yahya.slimani.guest@isamm.uma.tn

Yahya SLIMANI

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