摘要： 针对传统协同过滤方法难以准确确定目标用户的最近邻居且推荐质量不高的问题，提出综合兴趣度的概念。综合兴趣度是对用户兴趣的完整描述，在此基础上给出一种新颖的基于综合兴趣度的协同过滤算法。实验结果表明，该算法可以提高最近邻居计算的准确性，进而提高推荐质量。

关键词: 推荐系统, 协同过滤, 综合兴趣度, 推荐算法

Abstract: To address the low accuracy of identifying nearest neighbors and bad recommendation performance in traditional collaborative filtering algorithms, the concept of comprehensive interest measure which is a full description of user interest is proposed. Based on this, a novel collaborative filtering algorithm is introduced. Experimental results suggest that this algorithm can efficiently improve the accuracy of computing nearest neighbors and provid better recommendation results than traditional collaborative filtering algorithm.

Key words: recommendation system, collaborative filtering, comprehensive interest measure, recommendation algorithm

中图分类号: 

• TP311.12