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GAO Ying, QI Hong, LIU Yabo, LIU Dayou
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Abstract: A user gradebased collaborative filtering recommendation algorithm is presented in this paper. It solves the scalability problem of traditional collaborative filtering algorithm. It defines a user grade function firstly, which determines users’ grade according to the number of their rating items, and by means of finding neighbors for a target user, it only considers the candidates in his near grade, so the efficiency increases. Both theory and experimental results show that this algorithm improves recommendation efficiency greatly compared with traditional collaborative filtering, and at the same time the recommendation quality does not decrease.
Key words: collaborative filtering, user grade, recommendation algorithm
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GAO Ying, QI Hong, LIU Yabo, LIU Dayou. A User Gradebased Collaborative Filtering Recommendation Algorithm[J].J4, 2008, 46(03): 489-493.
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http://xuebao.jlu.edu.cn/lxb/EN/Y2008/V46/I03/489
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