计算机应用与软件Issue(9)：98-101,205,5.DOI:10.3969/j.issn.1000-386x.2014.09.025
基于个人和社会隐含因子的社会化推荐
SOCIAL RECOMMENDATION BASED ON INDIVIDUAL AND SOCIAL LATENT FACTOR
武春岭 1胡云冰 1鲁先志1
作者信息
- 1. 重庆电子工程职业学院计算机学院 重庆401331
- 折叠
摘要
Abstract
Thesocialrecommendationbasedonusersandrelationshipoftheirhistoricalbehavioursarouseswideattention,butalmostall of the existing recommendation models ignore the heterogeneity and diversity of social relationship.In response to this deficiency,we proposed a social recommendation method with the joint model of individual and social latent factor (ISLF ).The method combines collaborative filtering and social network modelling approach,utilises the latest mixture membership stochastic block model to extract vectors of social factors for each user.Moreover,it employs an optimised expectation maximisation algorithm (EM)to optimise ISLF model so as to carry out the fast expectation computation.Finally,we made the experiments based on real dataset-DouBan,results show that the new method proposed can provide more accurate recommendations with higher quality and better effect than current social recommendation methods.关键词
推荐系统/社会化关系/社会隐含因子/协同过滤/社交网络Key words
Recommendationsystem/Socialisationrelationship/Latentfactor/Collaborativefiltering/Socialnetwork分类
信息技术与安全科学引用本文复制引用
武春岭,胡云冰,鲁先志..基于个人和社会隐含因子的社会化推荐[J].计算机应用与软件,2014,(9):98-101,205,5.
