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» Analysis of recommendation algorithms for e-commerce
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WWW
2005
ACM
16 years 9 days ago
Improving recommendation lists through topic diversification
In this work we present topic diversification, a novel method designed to balance and diversify personalized recommendation lists in order to reflect the user's complete spec...
Cai-Nicolas Ziegler, Sean M. McNee, Joseph A. Kons...
118
Voted
DATAMINE
2002
155views more  DATAMINE 2002»
14 years 11 months ago
Efficient Adaptive-Support Association Rule Mining for Recommender Systems
Collaborative recommender systems allow personalization for e-commerce by exploiting similarities and dissimilarities among customers' preferences. We investigate the use of a...
Weiyang Lin, Sergio A. Alvarez, Carolina Ruiz
CIKM
2008
Springer
15 years 1 months ago
SoRec: social recommendation using probabilistic matrix factorization
Data sparsity, scalability and prediction quality have been recognized as the three most crucial challenges that every collaborative filtering algorithm or recommender system conf...
Hao Ma, Haixuan Yang, Michael R. Lyu, Irwin King
WWW
2009
ACM
16 years 9 days ago
Probabilistic question recommendation for question answering communities
User-Interactive Question Answering (QA) communities such as Yahoo! Answers are growing in popularity. However, as these QA sites always have thousands of new questions posted dai...
Mingcheng Qu, Guang Qiu, Xiaofei He, Cheng Zhang, ...
KDD
2009
ACM
192views Data Mining» more  KDD 2009»
16 years 5 days ago
Learning optimal ranking with tensor factorization for tag recommendation
Tag recommendation is the task of predicting a personalized list of tags for a user given an item. This is important for many websites with tagging capabilities like last.fm or de...
Steffen Rendle, Leandro Balby Marinho, Alexandros ...