With the explosive growth of resources available through the Internet, information overload has become a serious issue. Especially the emergence of social media has created highly interactive platforms for users to create, share, exchange information and build social networks. Web users are commonly overwhelmed by huge volume of information and are faced with the challenge of finding the most relevant information. Recommender systems represent tools for efficient selection of the most relevant information resources, and the interest in such systems has increased dramatically over the last few years. However, web personalization has not yet been well-exploited; difficulties arise while selecting resources through recommender systems from technology perspective and social perspective; also solutions are needed for effective interaction & collaboration between users and maintain trustworthiness and reliability of information on social media. The aim of this workshop is to promote high quality research in technical and human aspects related to Web personalization, social media and resource selection through recommender systems. The workshop will provide a forum for academic and industrial researchers to exchange ideas about past, present and future trends in Web personalization, social media and resource selection, and for discussing new and innovative approaches.
征稿信息
征稿范围
Topics and areas include, but not limited to:
User behaviour modelling and personalization techniques
Collaborative and content based filtering
Clustering and classification in recommender systems
Hybrid recommender systems
Security and trust in recommen
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