计算机科学 ›› 2011, Vol. 38 ›› Issue (Z10): 175-177.

• CRSSC-CWI-CGrC2015 • 上一篇    下一篇

基于个性化情境和项目类别的资源推荐研究

杨畅,李华   

  1. (重庆大学计算机学院 重庆400044)
  • 出版日期:2018-11-16 发布日期:2018-11-16

Personalize Context and Item Class Based Resource Recommendation

YANG Chang,LI Hua   

  • Online:2018-11-16 Published:2018-11-16

摘要: 传统的协同过滤推荐技术没有考虑影响用户评分的用户情境信息,但最近研究发现用户个性化情境信息直接影响着用户评分,因此在传统的协同过滤技术基础上引入用户个性化情境后推荐效果有所提高。此外可以将用户个性化情境和项目类别相结合起来。先对项目进行分类,然后再确定用户在每个项目类别下的个性化情境,同一项目类别下所有项目的用户个性化情境是相同的。在为目标项目预测评分时,先确定目标项目所在的类别,进而确定计算目标项目预测评分所用到的用户个性化情境。实验结果表明,改进后的算法较Slope one有较大提高。

关键词: 协同过滤,个性化情境,项目类别,推荐

Abstract: The conditional collaborative filtering technology does not consider the user's context information which affect user's rating. 13ut recent research show that user's personalized context directly affect rating, so the result of recommendation can be improved if personalize context is incorporated into conditional collaborative filtering technology.Besides, the personalized context and item class are can be combined, Firstly classifying the items, and then making sure user's personalize context under every item class. When predicting the rating of target item,Firstly make sure which item class the target item is belong to, and then identify the user's personalized context used to compute the rating of the target item. hhe experimental results show that the recommendation accuracy of proposed approach is better than Slope One.

Key words: Collaborative filtering, Personalized context, Item class, Recommendation

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