计算机科学 ›› 2018, Vol. 45 ›› Issue (3): 218-222.doi: 10.11896/j.issn.1002-137X.2018.03.034
肖迎元,张红玉
XIAO Ying-yuan and ZHANG Hong-yu
摘要: 随着Facebook、Twitter、微博等社交网站的迅速普及,好友推荐系统逐渐成为各大社交网站的重要组成部分。好友推荐系统通过主动为用户推荐新的潜在好友来有效地扩大用户的社交圈规模并改善用户的社交体验,因而受到了广泛关注。然而,如何针对用户的个性化需求,为用户推荐真正意义上的好友,一直是个性化好友推荐的难点之一。对此,提出一种基于用户潜在特征的社交网络好友推荐方法(SNFRLF)。首先,通过隐语义模型挖掘用户的潜在属性特征;然后,通过用户的潜在特征计算用户间的相似度;最后,将计算得到的相似度引入到随机游走模型中以获得好友推荐列表。实验结果表明,文中所提好友推荐方法较已有的好友推荐方法在性能上有显著提升。
[1] SHIH S Y,LEE M,CHEN C C.An effective friend recommendation method using learning to rank and social influence[C]∥PACIS 2015.2015. [2] CHEN J,GEYER W,DUGAN C,et al.Make New Friends,but Keep the Old:Recommending People on Social Networking Sites[C]∥Proceedings of the 27th International Conference on Human Factors in Computing Systems.2009:201-210. [3] MENG X W,LIU S D,ZHANG Y J,et al.Research on Recommender Systems[J].Journal of Software,2015,6(6):1356-1372.(in Chinese) 孟祥武,刘树栋,张玉洁,等.社会化推荐系统研究[J].软件学报,2015,6(6):1356-1372. [4] MA H,YANG H,LYU M R,et al.SoRec:social recommendation using probabilistic matrix factorization[C]∥Proceedings of the 17th ACM Conference on Information and Knowledge Ma-nagement(CIKM’08).ACM,2008:931-940. [5] RENDLE S,FREUDENTHALER C,GANTNER Z,et al.BPR:Bayesian personalized ranking from implicit feedback [C]∥Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial Intelligence(UAI’09).ACM,2009:452-461. [6] HOFMANN T.Latent SEMANTIC Models for CollaborativeFiltering[J].ACM Transactions on Information Systems,2004,22(1):89-115. [7] KOREN Y.Factorization meets the neighborhood:a multiface-ted collaborative filtering model[C]∥Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Disco-very and Data Mining.ACM,2008:426-434. [8] SHEN Y,JIN R.Learning personal+social latent factor model for social recommendation[C]∥Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining(KDD’12).ACM,2012:1303-1311. [9] YE M,LIU X,LEE W C.Exploring social influence for recommendation-a generative model approach[C]∥Proceedings of the 35th International ACM SIGIR Conference on Research and Development in Information Retrieval(SIGIR’12).2012:671-680. [10] WAN S,LAN Y,GUO J,et al.Informational friend recommendation in social media[C]∥Proceedings of the 36th International ACM SIGIR Conference on Research and Development in Information Retrieval(SIGIR’13).ACM,2013:1045-1048. [11] CHEN C C,SHIH S Y,MENG L,et al.Who should you follow? Combining learning to rank with social influence for informative friend recommendation[J].Decision Support Systems,2016,90:33-45. [12] LIBEN-NOWELL D,KLEINBERG J.The link-prediction problem for social networks[J].Journal of the American Society for Information Science and Technology,2007,58(7):1019-1031. [13] JAMALI M,ESTER M.Trustwalker:a random walk model for combining trust-based and item-based recommendation [C]∥ACM Sigkdd International Conference on Knowledge Discovery &Data Mining.2009:397-406. [14] LESKOVEC J,HUTTENLOCHER D,KLEINBERG J.Predicting positive and negative links in online social networks[C]∥Proceedings of the 19th International Conference on World Wide Web(WWW’10).ACM,2010:641-650. [15] DENG S G,HUANG L T,XU G H.Social network-based ser-vice recommendation with trust enhancement[J].Expert Systems with Applications,2014,41(18):8075-8084. [16] SARUKKAI R R.Link prediction and path analysis usingMarkov chains[J].Computer Networks,2000,33(1-6):377-386. [17] MASSA P,AVESANI P.Trust-aware recommender systems[C]∥Proceedings of the 2007 ACM Conference on Recommender Systems.2007:17-24. [18] ARMENTANO M G,GODOY D,AMANDI A.Topology-based recommendation of users in micro-blogging communities[J].Journal of Computer Science and Technology,2012,27(3):624-634. [19] WANG J,DE VRIES A P,REINDERS M J.Unifying user-based and item-based collaborative filtering approaches by similarity fusion[C]∥Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval.ACM,2006:501-508. [20] CHEN K,CHEN T,ZHENG G,et al.Collaborative personalized tweet recommendation[C]∥Proceedings of the 35th International ACM SIGIR Conference on Research and Development in Information Retrieval(SIGIR’12).ACM,2012:661-670. |
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