On Alleviation of New User Problem in Collaborative Filtering using SNA Theory
نویسندگان
چکیده
منابع مشابه
On Alleviation of New User Problem in Collaborative Filtering using SNA Theory
Collaborative filtering is the most used personalized recommendation technology. However, the traditional collaborative filtering faces the cold start problem and data sparsity, which deteriorates user experience and reduces the prediction accuracy. This paper presents a novel solution of new user problem with social network analysis (SNA) theory. First, the user relationship network is built b...
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Collaborative filtering is based on the assumption that “similar users have similar preferences”. In other words, by finding users that are similar to the active user and by examining their preferences, the recommender system can (i) predict the active user’s preferences for certain items and (ii) provide a ranked list of items which active user will most probably like. Collaborative filtering ...
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Cold start is one of the main challenges in recommender systems. Solving sparsechallenge of cold start users is hard. More cold start users and items are new. Sine many general methods for recommender systems has over fittingon cold start users and items, so recommendation to new users and items is important and hard duty. In this work to overcome sparse problem, we present a new method for rec...
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Recommender systems base their operation on past user ratings over a collection of items, for instance, books, CDs, etc. Collaborative Filtering (CF) is a succesful recommendation technique. User ratings are not expected to be independent, as users follow trends of similar rating behavior. In terms of Text Mining, this is analogous to the formation of higher-level concepts from plain terms. In ...
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ژورنال
عنوان ژورنال: International Journal of u- and e- Service, Science and Technology
سال: 2013
ISSN: 2005-4246,2005-4246
DOI: 10.14257/ijunesst.2013.6.6.13