彭泽环,孙 乐,韩先培,石 贝. 基于排序学习的微博用户推荐[J]. 中文信息学报, 2013, 27(4): 96-103.
PENG Zehuan, SUN Le, HAN Xianpei, SHI Bei. Micro-blog User Recommendation Using Learning to Rank. , 2013, 27(4): 96-103.
基于排序学习的微博用户推荐
彭泽环,孙 乐,韩先培,石 贝
中国科学院 软件研究所 基础软件中心,北京 100190
Micro-blog User Recommendation Using Learning to Rank
PENG Zehuan, SUN Le, HAN Xianpei, SHI Bei
NFS, Institute of Software Technology, Chinese Academy of Sciences, Beijing 100190, China
Abstract：This paper summarized four types of recommendation-related user information from micro-blog systemthe user content(UC), the personal information(PI), the interaction(IA) and the social topological information(ST). Based on the four types of information, a user recommendation framework using learning-to-rank technology is built in the paper. Experiment results show(1) using several features to recommend usually get a better result than using a single feature; (2) recommendation performance based on UC, PI, IA respectively is better than that based on UC. Key wordslearning to rank; user recommendation; micro-blog.
[1] Zhou T, Ma H, Lyu, M., King, I. UserRec: A User Recommendation Framework in Social Tagging Systems[C]//Proceedings of the 24th AAAI Conference on Artificial Intelligence, 2010: 1486-1491. [2] Jilin Chen, Werner Geyer, Casey Dugan. Make new friends, but keep the old: recommending people on social networking sites[C]//Proceedings of CHI11: Proceedings of the 27th international conference on human factors in computing systems ACM New York, 2009. [3] Hiroyuki Koga, Tadahiro Taniguchi. Developing a User Recommendation Engine on Twitter Using Estimated Latent Topics[C]//Proceedings of HCI (1) 2011: 461-470. [4] Geyer W, Dugan C, Millen D, et al. Recommending topics for self-descriptions in online user profiles[C]//Proceedings of RecSys08, 2008: 59-66. [5] Sinha R, Swearingen K. Comparing recommendations made by online systems and friends[C]//Proceedings of DELOS-NSF Workshop on Personalization and Recommender Systems in Digital Libraries. 2001. [6] Guy I, Zwerdling N, Carmel D, et al. Personalized recommendation of social software items based on social relations[C]//Proceedings of RecSys, 2009: 53-60. [7] TY Liu. Learning to Rank for Information Retrieval[J]. Foundations and Trends in Information Retrieval, 2009. [8] K Dindia and D Canary. Definitions and Theoretical Perspectives on Maintaining Relationships. Journal of Social and Personal Relationships[J], 1993, 10(2):163-173. [9] Malone T, Grant K, Turbak F, et al. Intelligent information sharing systems[J]. Communications of the ACM , 1987, 30(5): 390-402. [10] J Hu, B Wang, Y Liu. Personalized Tag Recommendation Using Social Contacts[C]//Proceedings of SRS Workshops, 2011. [11] Ralf Herbrich,Thore Graepel, and Klaus Obermayer. Large Margin rank boundaries for ordinal regression[J]. MIT Press, Cambridge, MA, 2000.
2013, Vol. 27 
