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计算机工程 ›› 2007, Vol. 33 ›› Issue (24): 57-59. doi: 10.3969/j.issn.1000-3428.2007.24.019

• 软件技术与数据库 • 上一篇    下一篇

基于概念层次树的个性化推荐算法

张晓敏,王 茜   

  1. 重庆大学计算机科学与技术学院,重庆 400030
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2007-12-20 发布日期:2007-12-20

Personalized Recommendation Algorithm Based on Concept Hierarchy Tree

ZHANG Xiao-min, WANG Qian   

  1. School of Computer Science & Technology, Chongqing University, Chongqing 400030
  • Received:1900-01-01 Revised:1900-01-01 Online:2007-12-20 Published:2007-12-20

摘要: 改进了传统的协同过滤算法,提出了基于概念层次树的用户模型,利用该模型进行协同运算,使系统在用户共同评分项极其稀疏时也能产生推荐。在相似性计算和产生推荐阶段引入了概念分层思想,分别在商品种类上产生推荐,避免了推荐的单一现象。MovieLens数据集实验表明,改进后的算法在推荐质量上有了明显的提高。

关键词: 个性化推荐, 协同过滤, 概念层次树

Abstract: This paper improves traditional collaborative filtering algorithm, proposes a new user profile based on concept hierarchy tree, which can make recommender systems still work even when users have no common rating items. In the process of similarity calculation and recommendation formation, it also uses concept hierarchy thought to generate recommendation lists by different categories, avoiding recommendation lack of diversity. Experimental results on MovieLens dataset show that the improved algorithm can provide better prediction in either accuracy or diversity aspect.

Key words: personalized recommendation, collaborative filtering, concept hierarchy tree

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