1 |
Busch M , Gade K , Larson B , et al. Earlybird; real-time search at Twitter. Proceedings of IEEE the 28th International Conference on Data , Washington, USA, 2012: 185~193
|
2 |
Chen C , Li F , Ooi B C , et al. TI: an efficient indexing mechanism for real-time search on tweets. Proceedings of the ACM International Conference on Management of Data, Athens, Greece, 2011: 649~660
|
3 |
Duan Y , Jiang L , Qin T , et al. An empirical study on learning to rank of tweets. Proceedings of the 23rd International Conference on Computational Linguistics, Beijing, China, 2010: 295~303
|
4 |
Chen K , Chen T , Zheng G , et al. Collaborative personalized tweet recommendation. Proceedings of the 35th International ACM SIGIR Conference on Research and Development in Information Retrieval, Portland, USA, 2012: 661~670
|
5 |
Chirita P , Nejdl W , Paiu R , et al. Using ODP metadata to personalize search. Proceedings of the 28th Annual Interational ACM SIGIR Conference on Research and Development in Information Retrieval, Salvador, Brazil, 2005: 178~185
|
6 |
Ramage D , Dumais S , et al. Characterizing microblogs with topic models. Proceedings of the International AAAI Conference on Weblogs and Social Media, Washington, USA, 2010: 130~137
|
7 |
Navee N , Gottron T , Kunegis J , et al. Bad news travel fast: a content-based analysis of interestingness on twitter. Proceedings of the ACM WebSci'11, Koblenz, Germany, 2011: 1~7
|
8 |
Kapanipathi P , Orlandi F , Sheth A , et al. Personalized filtering of the twitter stream. Proceedings of Semantic Personalized Information Management Workshop, Bonn, Germany, 2011: 6~13
|
9 |
Chen L , Nayak R , Xu Y . A recommendation method for online dating networks based on social relations and demographic information. Proceedings of International Conference on Advances in Social Networks Analysis and Mining(ASONAM), Kaohsiung, Taiwan, China, 2011: 407~411
|
10 |
Nayak R , Zhang M , Chen L . A social matching system for an online dating network: a preliminary study. 2010 Proceedings of IEEE International Conference on Data Mining Workshops, Sydney, Australia, 2010: 352~357
|
11 |
Newman M E J . Communities, modules and large-scale structure in networks. Nature Physics, 2012, 8(1): 25~31
|
12 |
Newman M E J . Fast algorithm for detecting Community structure in networks. Physical Review E, 2004, 69(6): 66~133
|
13 |
Girvan M , Newman M E J . Community structure in social and biological networks. Proceedings of the National Academy of Sciences, 2002, 99(12): 7821~7826
|
14 |
Zhao Z D , Shang M S . User-based collaborative-filtering recommendation algorithms on Hadoop. Proceedings of the Third International Conference on Knowledge Discovery and Data Mining(WKDD'10), Portland, USA, 2010: 478~481
|
15 |
陈可寒, 韩盼盼, 吴健 . 基于用户聚类的异构社交网络推荐算法. 计算机学报, 2013,36(2): 349~359 Chen K H , Han P P , Wu J . User clustering based social network recommendation. Chinese Journal of Computers, 2013,36(2): 349~359
|
16 |
罗奇, 余英, 赵呈领 等 自适应推荐算法在电子超市个性化服务系统中的应用研究. 通信学报, 2006,27(11): 183~186 Luo Q , Yu Y , Zhao C L , et al. Research on personalized service system in E-supermarket by using adaptive recommendation algorithm. Journal on Communications, 2006,27(11): 183~186
|
17 |
邓爱林, 朱扬勇, 施伯乐 . 基于项目评分预测的协同过滤推荐算法. 软件学报, 2003,14(9): 1621~1628 Deng A L , Zhu Y Y , Shi B L . A collaborative filtering recommendation algorithm based on item rating prediction. Journal of Software, 2003,14(9): 1621~1628.
|