Thursday 25th of April 2024
 

From Social Network to Semantic Social Network in Recommender System


Khaled Sellami, Mohamed Ahmed-Nacer, Pierre Tiako, Rachid Chelouah and Hubert Kadima

Due the success of emerging Web 2.0, and different social network Web sites such as Amazon and movie lens, recommender systems are creating unprecedented opportunities to help people browsing the web when looking for relevant information, and making choices. Generally, these recommender systems are classified in three categories: content based, collaborative filtering, and hybrid based recommendation systems. Usually, these systems employ standard recommendation methods such as artificial neural networks, nearest neighbor, or Bayesian networks. However, these approaches are limited compared to methods based on web applications, such as social networks or semantic web. In this paper, we propose a novel approach for recommendation systems called semantic social recommendation systems that enhance the analysis of social networks exploiting the power of semantic social network analysis. Experiments on real-world data from Amazon examine the quality of our recommendation method as well as the performance of our recommendation algorithms.

Keywords: Recommender system, social network, semantic web, user profile.

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ABOUT THE AUTHORS

Khaled Sellami
Khaled Sellami is a lecturer in the Department of Computer Science, Bejaia University, Algeria. He received the MSc degree in computer science from Bejaia University, Algeria, in 2005. He is a PhD candidate in Computer Science Department at Bejaia University. His research interests include semantic web, web engineering, ontology engineering, and social information systems

Mohamed Ahmed-Nacer
Mohamed Ahmed-Nacer is a professor at the Computer Science Department of the USTHB University, Algeria. He received the PhD degree in Computer science from the Polytechnic National Institute (INPG), Grenoble (France), in 1994. He heads the informatics Systems Laboratory. His research interests include formal specifications, information management and integration, process modeling, and knowledge management.

Pierre Tiako
Pierre Tiako is the Director of the Center for Information Technology Research at Langston University, Oklahoma (USA) and a Computer Science professor. He holds a PhD in software engineering from National Polytechnic Institute (INPL), Lorraine (France). His research interests include web engineering, e-commerce trading alliances, software process modeling. He is the promoter of Tiako University under establishment in Oklahoma.

Rachid Chelouah
Rachid Chelouah is a lecturer in the EISTI, Cergy, France. He received the PhD degree in Computer science and optimization from the Cergy-Pontoise University (France), in 2000. His research interests include optimization methods, web mining.

Hubert Kadima
Hubert Kadima is a professor in the EISTI, Cergy, France. He heads the LARIS Laboratory. His research interests include formal specifications, information management integration, process modeling, knowledge management, and social information systems.


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