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Computational Intelligence for Recommender SystemsContents of the sessionRecommender Systems (RS) are software applications that suggest useful and interesting items to users in their decision-making while interacting with large information spaces. They recommend items of interest to users based on preferences they have expressed, either explicitly or implicitly. The ever-expanding volume and increasing complexity of information on the Web has therefore made such systems essential tools for users in a variety of information seeking or various e-applications. RS help overcome the information overload problem by exposing users to the most interesting items, and by offering novelty, surprise, and relevance. Recommender technology is hence the central piece of the information seeking puzzle. Computational Intelligence (CI) paradigms reveal to be potential tools to face the Web uncertainty. In particular, CI techniques may be properly exploited to handle Web usage data and develop Web-based applications tailored on users' preferences. Recommended topics include but are not limited to the following:
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ProceedingsHAIS'10 proceedings will be published by Springer in its series of Lecture Notes in Computer Science. (Tentative) All accepted papers must be presented by one of the authors who must register for the conference and pay the fee.[top] |
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