Collaborative Filtering Recommendation Algorithm Based on Users’ Behavior and Roles
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    Abstract:

    There are sparse ratings problem in the traditional CF recommendation algorithm, and based on this sparse ratings will lead to the fact that the similarity may not be accurate. For this reason, a CF algorithm based on fixed I-U ratings matrix, which is given by a certain ratings of user behavior instead of vacancies rating, and weighted coefficient K bases on users’ role to constrain the similarity calculation is proposed. Experiments show that the improved algorithm has better recommendation quality.

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李幼平,尹柱平.基于用户行为与角色的协同过滤推荐算法.计算机系统应用,2011,20(11):103-106

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  • Received:March 17,2011
  • Revised:April 11,2011
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