Academic & Scientific Articles
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Item Networked Wireless Sensors, Active RFID, and Handheld Devices for Modern Car Park Management: WSN, RFID, and Mob Devs for Car Park Management(IGI Global, 2015-07-01) Djenouri, Djamel; Karbab, Elmouatezbillah; Boulkaboul, Sahar; Bagula, AntoineNetworked wireless sensors, actuators, RFID, and mobile computing technologies are explored in this paper on the quest for modern car park management systems with sophisticated services over the emerging internet of things (IoT), where things such as ubiquitous handheld computers, smart ubiquitous sensors, RFID readers and tags are expected to be interconnected to virtually form networks that enable a variety of services. After an overview of the literature, the authors propose a scalable and lowcost car parking framework (CPF) based on the integration of aforementioned technologies. A preliminary prototype implementation has been performed, as well as experimentation of some modules of the proposed CPF. The results demonstrate proof of concept, and particularly reveal that the proposed approach for WSN deployment considerably reduces the cost and energy consumption compared to existing solutions.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 A genetic algorithm feature selection based approach for Arabic Sentiment Classification(IEEE Computer Society, 2016-11-29) Aliane, Hassina; Aliane, A.A; Ziane, M.; Bensaou, N.With the recently increasing interest for opinion mining from different research communities, there is an evolving body of work on Arabic Sentiment Analysis. There are few available polarity annotated datasets for this language, so most existing works use these datasets to test the best known supervised algorithms for their objectives. Naïve Bayes and SVM are the best reported algorithms in the Arabic sentiment analysis literature. The work described in this paper shows that using a genetic algorithm to select features and enhancing the quality of the training dataset improve significantly the accuracy of the learning algorithm. We use the LABR dataset of book reviews and compare our results with LABR’s authors’ results.Item Automatic Construction of Ontology from Arabic Texts(Université Djillali LIABES Sidi-Bel-Abbès, 2012-04-29) Mazari, Ahmed Cherif; Aliane, Hassina; Alimazighi, ZaiaThe work which will be presented in this paper is related to the building of an ontology of domain for the Arabic linguistics. We propose an approach of automatic construction that is using statistical techniques to extract elements of ontology from Arabic texts. Among these techniques we use two; the first is the "repeated segment" to identify the relevant terms that denote the concepts associated with the domain and the second is the "co-occurrence" to link these new concepts extracted to the ontology by hierarchical or non- hierarchical relations. The processing is done on a corpus of Arabic texts formed and prepared in advance.Item A Graph Approach for Enhancing Process Models Matchmaking(IEEE, 2015-06-27) Belhoul, Yacine; Yahiaoui, Saïd; Haddad, Mohammed; Gater, Ahmed; Kheddouci, Hamamache; Bouzeghoub, MokraneRecent attempts have been done to measure similarity of process models based on graph matching. This problem is known to be difficult and its computational complexity is exponential. Thus, heuristics should be proposed to obtain approximations. Spectral graph matching methods, in particular eigenvalue-based projections, are know to be fast but they lost some quality in the obtained matchmaking. In this paper, we propose a graph approach for the problem of inexact matching of process models. Our approach combines a spectral graph matching method and a string comparator based algorithm in order to improve the quality of process models matchmaking. The proposed method performs the matchmaking at both structural and semantic levels. Experimentation is provided to show the performance of our method to rank a collection of process models according to a particular user query, compared to previous work.Item Coloring based approach for matching unrooted and/or unordered trees(Elsevier, 2013-04) Yahiaoui, Saïd; Haddad, Mohammed; Effantin, Brice; Kheddouci, HamamacheWe consider the problem of matching unrooted unordered labeled trees, which refers to the task of evaluating the distance between trees. One of the most famous formalizations of this problem is the computation of the edit distance defined as the minimum-cost sequence of edit operations that transform one tree into another. Unfortunately, this problem has been proved to be NP-complete. In this paper, we propose a new algorithm to measure distance between unrooted unordered labeled trees. This algorithm uses a specific graph coloring to decompose the trees into small components (stars and bistars). Then, it determines a distance between two trees by computing the edit distance between their components. We prove that the proposed distance is a pseudo-metric and we analyze its time complexity. Our experimental evaluations on large synthetic and real world datasets confirm our analytical results and suggest that the distance we propose is accurate and its algorithm is scalable.Item Information agronomique au cœur du Portail National de Signalement des Thèses(CERIST, 2016-11) Mebtouche, NawelAnalyser l’activité de recherche fondée sur les thèses réalisées dans les établissements académiques nationaux constitue un repérage valorisant de la recherche, une aide pour les chercheurs, ainsi que pour les responsables du secteur pour la mise en place des politiques et stratégies d’avenir. C’est dans cette optique que le Centre de Recherche sur L’information Scientifique et Technique (CERIST) a développé le portail national de signalement des thèses ( PNST) . Notre présente étude est une tentative d’évaluation de la production scientifique nationale, en matière de thèse, dans le domaine de l’agronomie. La réalisation de ce travail nécessite l’utilisation la base de données du portail PNST. Cette dernière est source fiable qui récence les travaux de recherche de la post-graduation (magistère, doctorat, doctorat LMD), à l’échelle nationale, durant la période 2010-2016. Cette base de données suit la chaine de réalisation de la thèse, depuis le signalement du sujet jusqu'à la diffusion de la thèse soutenue.Item Usages du web social via les sites web des bibliothèques algériennes : cas du réseau universitaire(Centre de recherche sur l'information scientifique et technique - CERIST, 2016-05-20) Loukem, Mohamed El Hadi; Aliouali, NadiaL’émergence du web 2.0, dit web social apparaît comme un nouveau bouleversement majeur. Symbolisé par quelques applications phares, comme Youtube, Wikipedia, mySpace ou encore les blogs, le web 2.0 regroupe en réalité un ensemble de pratiques considérées comme nouvelles. Toutes sont basées sur le retour de l’usager au cœur des dynamiques de production et d’échange de contenu. Celui-ci peut désormais publier lui-même du contenu, mais aussi l’enrichir, le modifier et surtout le partager avec d’autres, au sein de réseaux ou de communautés. La manifestation visible du web social en Algérie connaît des contraintes liées à ses usages en l’absence d’une sensibilisation faisant face aux insuffisances constatées par rapport à l’application de ses outils qui favorisent la participation de l’usager. Ses enjeux liés au rôle important qu’il joue dans l’évolution des services et des compétences. Un état de la question sur ses usages par les bibliothèques universitaires algériennes est établi. par ailleurs, un ensemble de recommandations est proposé afin de contribuer à la mise en oeuvre d’une démarche d’usages du web social par nos bibliothèques universitaires, selon les principes fondamentaux de ses outils pour une meilleure optimisation des services rendus et répondre au mieux aux exigences des usagers des bibliothèques du réseau académique algérien.Item A stochastic local search combined with support vector machine for web services classification(CERIST, 2016-04) Laachemi, Abdelouahab; Boughaci, DalilaIn this paper, we are interested in the Web service classification. We propose a classification method that first uses a stochastic local search (SLS) meta-heuristic for feature selection then call the Support Vector Machine (SVM) to do the classification task. The proposed method that combines SLS and SVM for Web service classification is validated on the QWS Dataset to measure its performance. We used a set of 364 Web services divided into four categories (Platinum, Gold, Silver and Bronze) in which quality is measured by 9 attributes. The experiments and the comparison show the effectiveness of our method for the classification of Web services.Item Big Data : Concepts et Cas d’utilisation(CERIST, 2015-06-15) Amrane, AbdesalamDans ce rapport nous décrivons l'écosystème Big Data, le contexte et les cas d'utilisation sont présentés. par la suite nous détaillons les technologies matérielles et logicielles nécessaires (stockage, traitement parallèle, virtualisation, …).