计算机应用研究2016，Vol.33Issue(8)：2278-2281,4.DOI:10.3969/j.issn.1001-3695.2016.08.008
基于万有引力和随机行走的推荐算法研究
Study on GARW recommendation algorithm
王国霞1
作者信息
- 1. 北京科技大学 自动化学院，北京 100083
- 折叠
摘要
Abstract
This paper studied the personalized recommendation algorithm for social tags systems,and proposed a new recom-mendation algorithm based on gravitation and random walk(GARW).Aiming at the problem that the present recommendation algorithm lacked of physical explanation and heavy reliance on users’score,this new algorithm introduced into the universal law of gravitation innovatively,also gave the definition of item gravitation and the calculation method,and considered the strength of item gravitation as the similarity of items,then got the correlation graph of items.After that,using random walk method,it spreaded users’preferences on the correlation graph of items,got its’steady-state probability on nodes of the graph which reflec-ted the degree of correlation between users’preference and items.The items with higher steady-state probability were recommen-ded to the user.Experimental results show the new algorithm performs better than the other algorithm compared to.关键词
推荐算法/个性化/万有引力/随机行走/社会标签/个性化推荐Key words
recommendation algorithm/personalized/the universal law of gravitation/random walk/social tags/perso-nal recommendation分类
信息技术与安全科学引用本文复制引用
王国霞..基于万有引力和随机行走的推荐算法研究[J].计算机应用研究,2016,33(8):2278-2281,4.
