Hajer Baazaoui Zghal

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HAJER BAAZAOUI ZGHAL, MARIE-AUDE AUFAURE , NESRINE BEN MUSTAPHA Riadi-GDL Laboratory, ENSI Campus Universitaire de la Manouba, Tunis, Tunisia {Hajer.baazaouizghal, nesrine.benmustapha}@riadi.rnu.tn Supelec, Computer Science Department, Plateau du Moulon, 91 192 Gif sur Yvette, France Marie-Aude.Aufaure@Supelec.fr Inria Paris-Rocquencourt, Axis project,(More)
In this paper, we present a semantic search approach based on Case-based reasoning and modular Ontology learning. A case is defined by a set of similar queries associated with its relevant results. The case base is used for ontology learning and for contextualizing the search process. Modular ontologies are designed to be used for case representation and(More)
In the context of the semantic Web, ontologies improve the exploitation of Web resources by adding a consensual piece of knowledge. The need for using domain ontology for information retrieval (IR) has been explored by some approaches to better answer users’ queries. However, ontology in IR system requires a regular updating, especially the addition of new(More)
In this paper, we focus on modularization aspects for query reformulation in ontology-based question answering on the Web. The main objective is to automatically learn ontology modules that cover search terms of the user. Indeed, the main problem is that current approaches of ontology modularization consider only the input existant ontologies, instead of(More)
In this paper, we present a semantic search approach based on Case-based modular Ontology. Our work aims to improve ontology-based information retrieval by the integration of the traditional information retrieval, the use of ontology and the case based reasoning (CBR). In fact, our recommender approach uses the CBR with ontology for case representation and(More)
The huge number of available documents on the Web makes finding relevant ones a challenge. Thus, searching for information becomes more and more complex because of the growing volume of data and of its lack of structure. The quality of results that traditional full-text search engines provide is still not optimal for many types of user queries. Especially,(More)
In the enterprise context, an important amount of information is stored in relational databases. Therefore, relational database can be a rich source to extract social network. Moreover, it is not very suitable to present and store a social network. On the other hand, a graph database canmodel data in natural way and facilitates the query of data using graph(More)
Data mining is an extraordinarily demanding field referring to extraction of implicit knowledge and relationships, which are not explicitly stored in databases. A wide variety of methods of data mining have been introduced (classification, characterization, generalization...). Each one of these methods includes more than algorithm. A system of data mining(More)