DocumentCode
2720563
Title
Recommend Items for User in Social Networking Services with CF
Author
Guan, Linting ; Lu, Hailing
Author_Institution
Collage of Math., Phys. & Inf., Zhejiang Ocean Univ., Zhoushan, China
fYear
2012
fDate
11-13 Aug. 2012
Firstpage
1347
Lastpage
1350
Abstract
In this paper we focus on the algorithm for prediction task involves predicting whether or not a user will follow an item that has been recommended to the user in social networking services. Items can be person, organizations or groups, which is sponsored by Ten cent Weibo as KDD Cup 2012. We evaluate a range of different profiling and recommendation strategies, based on a subset of large dataset from KDD Cup 2012.
Keywords
collaborative filtering; recommender systems; social networking (online); CF; KDD Cup 2012; Tencent Weibo; recommendation strategies; recommended items; social networking services; Collaboration; Filtering; Gold; Prediction algorithms; Social network services; Sparse matrices; Training; collaborative filtering; item recommendation; recommender systems;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Science & Service System (CSSS), 2012 International Conference on
Conference_Location
Nanjing
Print_ISBN
978-1-4673-0721-5
Type
conf
DOI
10.1109/CSSS.2012.340
Filename
6394578
Link To Document