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RECSYS
2010
ACM
13 years 6 months ago
Incremental collaborative filtering via evolutionary co-clustering
Collaborative filtering is a popular approach for building recommender systems. Current collaborative filtering algorithms are accurate but also computationally expensive, and so ...
Mohammad Khoshneshin, W. Nick Street
AAIM
2008
Springer
208views Algorithms» more  AAIM 2008»
13 years 8 months ago
Large-Scale Parallel Collaborative Filtering for the Netflix Prize
Many recommendation systems suggest items to users by utilizing the techniques of collaborative filtering (CF) based on historical records of items that the users have viewed, purc...
Yunhong Zhou, Dennis M. Wilkinson, Robert Schreibe...
WISE
2010
Springer
13 years 4 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
WWW
2007
ACM
14 years 7 months ago
Google news personalization: scalable online collaborative filtering
Several approaches to collaborative filtering have been studied but seldom have studies been reported for large (several million users and items) and dynamic (the underlying item ...
Abhinandan Das, Mayur Datar, Ashutosh Garg, ShyamS...
RECSYS
2010
ACM
13 years 6 months ago
Collaborative filtering via euclidean embedding
Recommendation systems suggest items based on user preferences. Collaborative filtering is a popular approach in which recommending is based on the rating history of the system. O...
Mohammad Khoshneshin, W. Nick Street