• [Journal] Ahlem Kalaï, Corinne Amel Zayani, Ikram Amous Ben Amor, Abdelghani Wafa et Florence Sèdes. Social collaborative service recommendation approach based on user’s trust and domain-specific expertise. , mars , 2018, Future Generation Computer Systems (FGCS), 80: 355-367, 2018
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    Abstract

    A few years ago, the Internet of (Web) Service vision came to offer services to all aspects of life and business. The increasing number of Web services make service recommendation a directive research to help users discover services. Furthermore, the rapid development of social network has accelerated the development of social recommendation approach to avoid the data sparsity and cold-start problems that are not treated very well in the collaborative filtering approach. On the one hand, the pervasive use of the social media provides a big social information about the users (e.g., personnel data, social activities, relationships). Hence, the use of trust relation becomes a necessity to filter and select only the useful information. Several trust-aware service recommender systems have been proposed in literature but they do not consider the time in trust level detection among users. On the other hand, in the reality, the majority of users prefer the advice not only of their trusted friends but also their expertise in some domain-specific. In fact, the taking into account of user’s expertise in recommendation step can resolve the user’s disorientation problem. For these reasons, we present, in this paper, a Web service decentralized discovery approach which is based on two complementary mechanisms. The trust detection is the first mechanism to detect the social trust level among users. This level is defined in terms of the users’ interactions for a period of time and their interest similarity which are inferred from their social profiles. The service recommendation is the second mechanism which combines the social and collaborative approaches to recommend to the active user the appropriate services according to the expertise level of his most trustworthy friends. This level is extracted from the friends’ past invocation histories according to the domain-specific which is known in advance in the target user’s query. Performance evaluation shows that each proposed mechanism achieves good results. The proposed Level of social Trust (LoT) metric gives better precision more than 50% by comparing with the same metric without taking into account the time factor. The proposed service recommendation mechanism which based on the trust and the domain-specific expertise gives, firstly, a RMSE value lower than other trust-aware recommender systems like TidalTrust, MoleTrust and TrustWalker. Secondly, it provides a better response rate than the recommendation mechanism which based only on trust with a difference equal to 4%.

  • [Conférence intertnationale] Zied Trifa, Maher Khemakhem et Jalel Eddine Hajlaoui. Pollution Attacks indentification in Structured P2P Overlay Networks. The 19th International Conference on Information and Communications Security (ICICS 2017), decembre, 2017, Chine
  • [Conférence intertnationale] jihen karoui, Benamara Zitoune Farah et Véronique Moriceau. SOUKHRIA : Towards an Irony Detection System for Arabic in Social Media. 3rd International Conference on Arabic Computational Linguistics (ACLing), novembre, 2017, Dubai, Emirats arabes unis
  • [Conférence intertnationale] Mohamed Frikha , Mohamed Mhiri et Faiez Gargouri. Ontology-based Social Interaction Between Trusted Friends to Personalize Recommendation of Medical Tourism Activities. 14th ACS/IEEE International Conference on Computer Systems and Applications (AICCSA 2017), novembre, 2017
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  • [Conférence intertnationale] Zied Trifa et Maher Khemakhem. A Framework for Monitoring and Mitigating Malicious Attacks in Structured P2P Overlay Networks. 14th ACS/IEEE International Conference on Computer Systems and Applications, novembre, 2017
  • [Conférence intertnationale] Mohamed Frikha , Mohamed Mhiri et Faiez Gargouri. An User Interest Ontology Based on Trusted Friends Preferences for Personalized Recommendation. 14th European Mediterranean & Middle Eastern Conference on Information Systems (EMCIS 2017), septembre, 2017
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  • [Journal] Mohamed Frikha , Mohamed Mhiri et Faiez Gargouri. Social Trust based Semantic Tourism Recommender System: A Case of Medical Tourism in Tunisia. European Journal of Тourism Research (EJTR Journal), septembre, 2017
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  • [Conférence intertnationale] Maryam Jallouli, Sonia Lajmi et Ikram Amous Ben Amor. Designing recommender system: conceptual framework and pratical implementation. International Conference on Knowledge Based and Intelligent Information and Engineering Systems (KES), septembre, 2017, Marseille, France
    Abstract

    A recommender system (RS) is a subclass of information systems. It aims at providing the most relevant items (music, film…) that are preferred to each user. Several recommendation algorithms have been proposed in the literature and a comparison across their experimental results is necessary to evaluate the best algorithm. This paper presents a framework for presenting, developing and evaluating a recommender system. We preserve that this approach could play a vital role in elaborating an architecture and implementation of this type of systems. The proposed model presents the process of preparing the data set, whether rating or social data. It also includes a suite of state-of-the-art algorithms. The specificity of our architecture is the possibility of developing four kinds of recommender systems that are baseline, social, contextual and socio-contextual recommender system.  

  • [Conférence intertnationale] Maryam Jallouli, Sonia Lajmi et Ikram Amous Ben Amor. Latent factor model applied to recommender system: A survey. 14th European Mediterranean & Middle Eastern Conference on Information Systems, septembre, 2017, Coimbra, Portugal
    Abstract

    Nowadays, internet has offer an overabundance of available information. In social networks, users confront gigantic number of items. To overcome this phenomenon, known as information overload, recommender systems are intended to filter information and help users to make their choice. Many models based collaborative filtering have been used in the literature to solve the problem of recommendation. Among these models, latent factor model has become the most popular due to his performed results of accuracy. This work is part of research into Recommender System domain and aims to present a detailed explication on works based latent factor model. We first describe a general view of this model. Its realization in field of recommendation is next presented. A detailed study on different steps is then exposed. The most important works that have been developed are then presented. To the author’s knowledge, there has been no work that tries to explain in detail how latent factor model is applied to Recommender Systems.

  • [Conférence intertnationale] Lotfi Chaari, Hadj Batatia et Jean-Yves Tourneret. A General Non-Smooth Hamiltonian Monte Carlo Scheme Using Bayesian Proximity Operator Calculation. European Signal Processing Conference (EUSIPCO), septembre, 2017, Kos, Grèce
  • Date de création : 19 Décembre 2012
    MIRADOC 2011 : Journées doctorales du laboratoire Miracl. Décembre 2011. Touzeur , Tunisie
  • Date de création : 19 Décembre 2012
    MIRADOC’2010, Rencontre Doctorale de Miracl Date : 19-22 décembre 2010. Lieu: Douz , Tunisie
  • Date de création : 19 Décembre 2012
    Les 2éme Journées sur les Réseaux Bayésiens et leurs Applications Date et lieu : octobre 2011, Sfax, Tunisie. Abstract The Bayesian Networks are graphical models that are easy to interpret and update. These models are useful if the knowledge is uncertain, but they lack some means to express ambiguity. To face this problem, we propose Fuzzy Evidence in Bayesian Networks and combine the Fuzzy Logic and Bayesian Network. This has allowed to benefit from mutual advantages of these two approaches, and to overcome the problem of data and observation ambiguity. This paper proposes an inference algorithm which uses the Bayesian Network and Fuzzy Logic reliability. This solution has been implemented, tested and evaluated in comparison with the existing methods.
  • Faiez Gargouri, Wassim Jaziri  Ontology Theory, Management and Design: Advanced Tools and Models ». IGI Global. ISBN-978-1-61520-   859-3. Mars 2010. Description Ontologies and formal representations of knowledge are extremely powerful tools for modeling and managing large applications in several domains ranging from knowledge engineering, to data mining, to the semantic web. Ontology Theory, Management and Design: Advanced Tools and Models, explores the wide range of applications for ontologies, while providing a complete view of the both the theory behind the design and the problems posed by the practical development and use of ontologies. This reference presents an in-depth and forward looking analysis of current research, illustrating the importance of this field and pointing toward to the future of knowledge engineering, management and information technology.  
  • Titre : Finite State Language Engineering Autheurs : BEN HAMADOU A., MESFAR S., SILBERZTEIN M.  ISBN : 978-9973-37602-2 Livre, Edition CPU, Tunis, 2010
  • Titre :  Les Systèmes décisionnels : Théorie et pratique Autheurs : BEN-ABDALLAH H., BOULMARKOUL A., BOUSSAID O., FEKI J., GARGOURI F. ISBN : 789973990020. Nombre des pages: 130 pages Livre, Nouha Editions, 2010.