Computer Science ›› 2018, Vol. 45 ›› Issue (2): 276-279.doi: 10.11896/j.issn.1002-137X.2018.02.047

Previous Articles     Next Articles

Important Micro-blog User Recommendation Algorithm Based on Label and PageRank

WANG Rong-bing, AN Wei-kai, FENG Yong and XU Hong-yan   

  • Online:2018-02-15 Published:2018-11-13

Abstract: Massive micro-blog information makes it difficult for new users to obtain the content they are interested in.Important micro-blog user recommendation provides an effective way for new users to access information.At present,inadequate consideration of the relationship between users and the lack of user personalized label processing make the recommendation accuracy of important micro-blog user be not high.Therefore, an important micro-blog user recommendation algorithm based on label and PageRank was proposed.Firstly,the personalized label is processed by word segmentation,de-noising and setting weight,and the processed result is used as the representative of user interest.Se-condly,the relationship between users is analyzed by PageRank calculation model.Finally,important micro-blog users are recommended to new users with similar interests by label similarity calculation.The experiment shows that the proposed algorithm improves the recommendation accuracy of important micro-blog users compared with the recommendation algorithm based on label and collaborative filtering,because the analysis of the importance of micro-blog user relationship and user’s personalized label is integrated into this algorithm.

Key words: Personalized recommendation,PageRank,Label,Micro-blog

[1] ZHANG R,JIN Z G,WANG Y.Recommendation Model of Microblog User Tags Based on Hybrid Grain[J].Computer Scien-ce,2016,43(4):192-196.(in Chinese) 张瑞,金志刚,王颖.一种基于混合粒度的微博用户标签推荐模型[J].计算机科学,2016,43(4):192-196.
[2] WEI S,ZHENG X,CHEN D,et al.A Hybrid Approach forMovie Recommendation via Tags and Ratings[J].Electronic Commerce Research & Applications,2016,18(C):83-94.
[3] YANG A T,TANG Y,WANG J B,et al.Personalized Friends Recommendation System Based on Game Theory in Social Network[J].Computer Science,2015,42(9):191-194.(in Chinese) 杨阿祧,汤庸,王江斌,等.基于博弈的社会网络个性化好友推荐算法研究[J].计算机科学,2015,42(9):191-194.
[4] XING Q L,LIU L,LIU Y Q,et al.Study on User Tags in Weibo[J].Journal of Software,2015,26(7):1626-1637.(in Chinese) 邢千里,刘列,刘奕群,等.微博中用户标签的研究[J].软件学报,2015,26(7):1626-1637.
[5] LI R M,LIN H F,YAN J.Mining Latent Semantic on User-Tag-Item for Personalized Music Recommendation[J].Journal of Computer Research and Development,2014,51(10):2270-2276.(in Chinese) 李瑞敏,林鸿飞,闫俊.基于用户-标签-项目语义挖掘的个性化音乐推荐[J].计算机研究与发展,2014,51(10):2270-2276.
[6] CAI Q,HAN D M,LI H S,et al.Personalized Resource Recommendation Based on Tags and Collaborative Filtering[J].Computer Science,2014,41(1):69-71.(in Chinese) 蔡强,韩东梅,李海生,等.基于标签和协同过滤的个性化资源推荐[J].计算机科学,2014,41(1):69-71.
[7] WANG X Y,REN G S.Improved PageRank Algorithm Based on User Behavior and PageAnalysis[J].Computer Engineering,2016,42(2):164-168.(in Chinese) 王旭阳,任国盛.基于用户行为与页面分析的改进PageRank算法[J].计算机工程,2016,42(2):164-168.
[8] REN X Y,SONG M N,SONG J D.Context-Aware Point-of-Interest Recommendation in Location-Based Social Networks[J].Chinese Journal of Computers,2017,40(4):824-841.(in Chinese) 任星怡,宋美娜,宋俊德.基于位置社交网络的上下文感知的兴趣点推荐[J].计算机学报,2017,40(4):824-841.
[9] LIANG T T,LI C Q,LI H S.Top-k Learning Resource Matching Recommendation Based on Content Filtering PageRank[J].Computer Engineering,2017,43(2):220-226.(in Chinese) 梁婷婷,李春青,李海生.基于内容过滤PageRank的Top-k学习资源匹配推荐[J].计算机工程,2017,43(2):220-226.
[10] OLVERA E P,GODOY D.Evaluating Term Weighting Schemesfor Content-based Tag Recommendation in Social Tagging Systems[J].IEEE Latin America Transaction,2012,0(4):1973-1980.
[11] LIU J,ZHANG K,CHEN X.Personalized Recommendation Algorithm Based on Tags and Collaborative Filtering[J].Compu-ter & Modernization,2016(2):62-65.(in Chinese) 刘健,张琨,陈旋.基于标签和协同过滤的个性化推荐算法[J].计算机与现代化,2016(2):62-65.
[12] SONG Y,ZHANG L,GILES C L.Automatic Tag Recommendation Algorithms for Social Recommender Systems[J].ACM Transactions on the Web,2011,5(1):4.
[13] DU W H,RAN J W,HUANG J W,et al.Improving the Quality of Tags Using State Transition on Progressive Image Search and Recommendation System[C]∥IEEE International Confe-rence on Systems,Man,and Cybernetics.IEEE,2012:3233-3238.
[14] JIANG S,WANG Z Q,XIU Y,et al.Collaborative FilteringRecommendation Method Based on Dynamic Social Behavior and Users’ Background Information[J].Computer Science,2015,42(3):252-255.(in Chinese) 蒋胜,王忠群,修宇,等.基于动态社会行为和用户背景的协同推荐方法[J].计算机科学,2015,42(3):252-255.

No related articles found!
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!