基于兴趣社区和信任邻居的混合推荐研究  

Hybrid Recommended Model Based on Communities of Interests and Trust Neighbors

作　　者：刘启华[1] 

机构地区：[1]江西财经大学信息管理学院,江西南昌330013

出　　处：《情报科学》2016年第2期65-69,共5页Information Science

基　　金：江西省教育厅科技项目(GJJ13290)

摘　　要：个性化推荐系统中精确性与多样性似乎是一个鱼和熊掌不可兼得之难题。本文集成基于兴趣社区的用户偏好匹配算法和基于信任邻居的多样性信息推荐算法,构建一个融合精确性和多样性的混合信息推荐模型。实验结果显示:该方法在对推荐结果准确性影响很小的情况下明显提高了推荐列表的多样性。This paper integrated user preferences matching algorithm which is based on communities of interests and diver- sity information recommendation algorithm based on trust neighbors to design hybrid information recommendation model which merge the attribution of accuracy and diversity. From experiment and evaluation, this model can increase the diversi- ty of recommendations with only a minimal accuracy loss.

关 键 词：个性化推荐系统 混合推荐 兴趣社区 信任邻居 

分 类 号：TP393.09[自动化与计算机技术—计算机应用技术]