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» Explaining collaborative filtering recommendations
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RECSYS
2010
ACM
13 years 8 months ago
Multiverse recommendation: n-dimensional tensor factorization for context-aware collaborative filtering
Context has been recognized as an important factor to consider in personalized Recommender Systems. However, most model-based Collaborative Filtering approaches such as Matrix Fac...
Alexandros Karatzoglou, Xavier Amatriain, Linas Ba...
EPIA
2009
Springer
13 years 11 months ago
Item-Based and User-Based Incremental Collaborative Filtering for Web Recommendations
Abstract. In this paper we propose an incremental item-based collaborative filtering algorithm. It works with binary ratings (sometimes also called implicit ratings), as it is typi...
Catarina Miranda, Alípio Mário Jorge
SIGIR
2011
ACM
12 years 10 months ago
Collaborative competitive filtering: learning recommender using context of user choice
While a user’s preference is directly reflected in the interactive choice process between her and the recommender, this wealth of information was not fully exploited for learni...
Shuang-Hong Yang, Bo Long, Alexander J. Smola, Hon...
ICWS
2009
IEEE
13 years 5 months ago
WSRec: A Collaborative Filtering Based Web Service Recommender System
As the abundance of Web services on the World Wide Web increase, designing effective approaches for Web service selection and recommendation has become more and more important. In...
Zibin Zheng, Hao Ma, Michael R. Lyu, Irwin King
SEKE
2005
Springer
14 years 1 months ago
Javawock: A Java Class Recommender System Based on Collaborative Filtering
- Many software development platforms provide a large number of library components to make it easy to build high quality software. On the other hand, it became more and more diffic...
Masateru Tsunoda, Takeshi Kakimoto, Naoki Ohsugi, ...