Sciweavers

25 search results - page 4 / 5
» Predicting Neighbor Goodness in Collaborative Filtering
Sort
View
IR
2006
13 years 5 months ago
A study of mixture models for collaborative filtering
Collaborative filtering is a general technique for exploiting the preference patterns of a group of users to predict the utility of items for a particular user. Three different co...
Rong Jin, Luo Si, Chengxiang Zhai
ICIP
2005
IEEE
14 years 7 months ago
Lossless image compression using an edge adapted lifting predictor
Abstract- We present a novel and computationally simple prediction stage in a Daubechies 5/3 ? like lifting structure for lossless image compression. In the 5/3 wavelet, the predic...
Ömer Nezih Gerek, A. Enis Çetin
STAIRS
2008
169views Education» more  STAIRS 2008»
13 years 6 months ago
Probabilistic Association Rules for Item-Based Recommender Systems
Since the beginning of the 1990's, the Internet has constantly grown, proposing more and more services and sources of information. The challenge is no longer to provide users ...
Sylvain Castagnos, Armelle Brun, Anne Boyer
KDD
2009
ACM
162views Data Mining» more  KDD 2009»
14 years 5 months ago
TrustWalker: a random walk model for combining trust-based and item-based recommendation
Collaborative filtering is the most popular approach to build recommender systems and has been successfully employed in many applications. However, it cannot make recommendations ...
Mohsen Jamali, Martin Ester
WISE
2010
Springer
13 years 3 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