收稿日期: 2012-11-20
修回日期: 2013-02-19
网络出版日期: 2013-03-05
基金资助
本文系中国石油大学(北京)研究生教育质量与创新工程基金项目"机构知识仓储建设及其长效服务机制研究"(项目编号:2011B008)研究成果之一。
Research on the Cold Start Recommender System of New Users Based on Seed-set Rating in the Collaborative Filtering System
Received date: 2012-11-20
Revised date: 2013-02-19
Online published: 2013-03-05
景民昌 , 张芹 , 唐弟官 . 协同过滤系统中基于种子集评分的新用户冷启动推荐研究[J]. 图书情报工作, 2013 , 57(05) : 124 -128 . DOI: 10.7536/j.issn.0252-3116.2013.05.022
This paper believes that building a seed set to guide users’ evaluation is one of the solutions to resolve the cold start problem of new users. An integrated approach based on multiple-attribute comprehensive assessment is brought up by bringing the relevance into the construction strategy of seed set. User environment of the recommender system is simulated through the experiment designed according to public data sets, in order to compare the accuracy and success rate of forecast. The result shows that the recommender effectiveness is improved by considering the relevance of seeds, if a small amount of seeds sets which are more suitable to the real recommendation system are adopted.
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