Academic & Scientific Articles
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Item Minimum redundancy and maximum relevance for single and multi-document Arabic text summarization(Elsevier, 2014-12) Oufaida, Houda; Nouali, Omar; Blache, PhilippeAutomatic text summarization aims to produce summaries for one or more texts using machine techniques. In this paper, we propose a novel statistical summarization system for Arabic texts. Our system uses a clustering algorithm and an adapted discriminant analysis method: mRMR (minimum redundancy and maximum relevance) to score terms. Through mRMR analysis, terms are ranked according to their discriminant and coverage power. Second, we propose a novel sentence extraction algorithm which selects sentences with top ranked terms and maximum diversity. Our system uses minimal language-dependant processing: sentence splitting, tokenization and root extraction. Experimental results on EASC and TAC 2011 MultiLingual datasets showed that our proposed approach is competitive to the state of the art systems.Item CERIST at INEX 2015: Social Book Search Track(CERIST, 2015) Chaa, Messaoud; Nouali, OmarIn this paper, we describe our participation in the INEX 2015 Social Book Search Suggestion Track (SBS). We have exploited in our experiments only the tags assigned by users to books provided from LibraryThing (LT). We have investigated the impact of the weight of each term of the topic in the retrieval model using two methods. In the first method, we have used the TF-IQF formula to assign a weight to each term of the topic. In the second method, we have used Rocchio algorithm to expand the query and calculate the weight of the tags assigned to the example books mentioned in the book search request. Parameters of our models have been tuned using the topics of INEX 2014 and tested on INEX 2015 Social Book Search track.Item Semantic Annotations and Context Reasoning to Enhance Knowledge Reuse in E-learning(2013) Boudebza, Souad; Azouaou, Faiçal; Berkani, Lamia; Nouali, OmarWe address in this paper the need of improving knowledge reusability within online Communities of Practice of E-learning (CoPEs). Our approach is based on contextual semantic annotations. An ontological-based contextual semantic annotation model is presented. The model serves as the basis for implementing a context aware annotation system called “CoPEAnnot”. Ontological and rule-based context reasoning contribute to improving knowledge reuse by adapting CoPEAnnot’s search results, navigation and recommendation. The proposal has been experimented within a community of learners.Item Using Clustering and Modified Classification algorithm without a learning corpus for automatic text summarization(2013-02-05) Aries, Abdelkrime; Oufaida, Houda; Nouali, OmarIn this paper we describe a modified classification method destined for extractive summarization purpose. The classification in this method doesn’t need a learning corpus; it uses the input text to do that. First, we cluster the document sentences to exploit the diversity of topics, then we use a learning algorithm (here we used Naive Bayes) on each cluster considering it as a class. After obtaining the classification model, we calculate the score of a sentence in each class, using a scoring model derived from classification algorithm. These scores are used, then, to reorder the sentences and extract the first ones as the output summary. We conducted some experiments using a corpus of scientific papers, and comparing our system to another system which is UNIS system. Also, we experiment the impact of clustering threshold tuning, on the resulted summary, as well as the impact of adding more features to the classifier. We found that this method is interesting, and gives good performance, and the addition of new features (which is simple using this method) can improve summary’s accuracy.Item Réponse automatique au courriel : Architecture basé sur les SQR et classification des questions(CERIST, 2014-11-02) Said, Ahmed; Nouali, Omar; Guemraoui, LilaCet article relate une approche pour la mise en œuvre d’un système de réponse automatique au courrier électronique, qui s’appuie essentiellement sur l’utilisation de l’approche par question-réponse. Toutefois, notre étude a montré que l'analyse et la classification des questions est un élément essentiel pour chercher efficacement une réponse à la question, Ainsi, nous nous somme focalisé sur ce point, où nous avons proposé une approche de classification qui se base sur différents critères de classification. Dans cette approche nous avons introduit le sujet du courriel comme un nouveau critère pour la classification des questions. Nous avons aussi expérimenté notre approche avec le classifieur SVM et les résultats de tests obtenus ont été satisfaisants.Item Deal with multiplicity and diversity of relevance factors in XML retrieval(2010-07-05) Bal, Kamal; Nouali, OmarIn this paper, we are interested in content oriented XML information retrieval whose aim is to retrieve not a list of relevant documents, but only fragments of document (XML element) relevant to the user information need. Retrieved XML elements must not only contain relevant information but also be at good level of granularity. The coexistence of content and structural information in XML documents makes that multiple and diverse relevance sources condition the selection and the rank of relevant XML element. It is admitted that the consideration of several relevance sources will surely improve quality of results. However, actual XML retrieval approaches consider just some relevance sources and neglect others due to relevance sources heterogeneity. In this paper, we try to identify and classify theses relevance sources and to propose a way to exploit multiple and diverse relevance sources in retrieval process.Item Towards a Dynamic Evacuation System for Disaster Situations(IEEE, 2014-03) Benssam, Ali; Bendjoudi, Ahcène; Yahiaoui, Saïd; Nouali-Taboudjemat, Nadia; Nouali, OmarMedical evacuation is one of the most important modules in the emergency plans activated during disaster situations. It aims at evacuating victims to the most appropriate health-care facilities. Evacuation plans were for a long time performed approximatively and passively rather than optimally and proactively between the disposal site and the targeted hospital and they often lacked visibility on the evolution of the events that may change data and leading to a revision of the plans. However, thanks to the proliferation of information and communication technologies (ICTs) in all aspects of life, the evacuation operations in disaster situations had known a great enhancement. In fact, critical operations such as real-time monitoring of the state of resources used during the evacuation process, detecting the occurring changes and reflecting them on the global process to provide dynamic and optimal evacuation plans become possible. In this paper, we propose a framework for dynamic evacuation operations in disaster situations. We design a system that takes into consideration the above challenges such as detecting changes and using them in an intelligent way to enable dynamic, optimal and up-to-date evacuation plans. The provided prototype is called DEvacuS (Dynamic Evacuation System).Item Metadata’s Protection in CKMS-As-A-Security Services(CERIST, 2014-02-20) Fehis, Saad; Nouali, Omar; Bentayeb, SarahTo ensure the confidentiality and integrity of data, it is necessary to use encryption techniques; the safety of these techniques is based on the pro- tection of keys and algorithms used by those techniques. Indeed, the estab- lishment of an encryption key management system (creation, storage, distribu- tion, etc...) is paramount. However, the safety of this type of system in the context of Cloud Computing is based on the protection of the data dictionary (metadata). The protection of this dictionary is a real challenge in a no-trust context. This paper describes the implementation of a protection technique for the Cryptographic Key Management System’s metadata, which provides handling (Consulting / Editing) data without offending the confidentiality and integrity of the dictionary.Item Improvement of a retrieval and f iltering systems by an automatic multi words extraction tool(Ghassan Issa, General Chair, 2006-04) Nouali, Omar; Krinah, AbdelghaniThe role of all retrieval systems consists in finding documents (or document excerpts) that best answer an information need. This need, whether precise and instant (a request) or general and long term (a profile), is most often expre ssed by a list of entities called terms. The goal of this article is to present an automatic mu lti words recognition and extraction tool, compiled from text extracts, in order to build a thesaurus, or terminological basis, useful by search engines and filtering systems in order to boost their performances.Item Filtrage cognitif de l’information électronique(ECIG 2007, 2007-10-19) Nouali, Omar; Toursel, B.L'objectif des travaux de recherche présentés dans cet article est l’automatisation du processus de filtrage de l’information en prenant en compte l’importance relative de l'information et les besoins en ressources linguistiques pour son traitement. Nous proposons une solution ouverte, dynamique et évolutive qui offre au processus de filtrage la possibilité d’apprendre, d’exploiter ces connaissances apprises et de s’adapter à la nature de l’application. Nous l’avons modélisé à l’aide d’agents pour offrir un gain de temps par rapport à une solution algorithmique séquentielle. Pour la validation de notre approche de filtrage, nous avons mené un ensemble d’expériences pour évaluer les performances des techniques et outils proposés et développés.