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» An automatic weighting scheme for collaborative filtering
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SIGIR
2004
ACM
13 years 9 months ago
An automatic weighting scheme for collaborative filtering
Collaborative filtering identifies information interest of a particular user based on the information provided by other similar users. The memory-based approaches for collaborativ...
Rong Jin, Joyce Y. Chai, Luo Si
WISE
2010
Springer
13 years 2 months ago
Neighborhood-Restricted Mining and Weighted Application of Association Rules for Recommenders
Abstract. Association rule mining algorithms such as Apriori were originally developed to automatically detect patterns in sales transactions and were later on also successfully ap...
Fatih Gedikli, Dietmar Jannach
ICDM
2007
IEEE
147views Data Mining» more  ICDM 2007»
13 years 10 months ago
Scalable Collaborative Filtering with Jointly Derived Neighborhood Interpolation Weights
Recommender systems based on collaborative filtering predict user preferences for products or services by learning past user-item relationships. A predominant approach to collabo...
Robert M. Bell, Yehuda Koren
WEBI
2009
Springer
13 years 10 months ago
Zero-Sum Reward and Punishment Collaborative Filtering Recommendation Algorithm
In this paper, we propose a novel memory-based collaborative filtering recommendation algorithm. Our algorithm use a new metric named influence weight, which is adjusted with ze...
Nan Li, Chunping Li
ICDM
2005
IEEE
168views Data Mining» more  ICDM 2005»
13 years 9 months ago
A Scalable Collaborative Filtering Framework Based on Co-Clustering
Collaborative filtering-based recommender systems, which automatically predict preferred products of a user using known preferences of other users, have become extremely popular ...
Thomas George, Srujana Merugu