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» Language Models of Collaborative Filtering
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GFKL
2005
Springer
114views Data Mining» more  GFKL 2005»
14 years 1 months ago
Attribute-aware Collaborative Filtering
One of the key challenges in large information systems such as online shops and digital libraries is to discover the relevant knowledge from the enormous volume of information. Rec...
Karen H. L. Tso, Lars Schmidt-Thieme
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
ITRUST
2005
Springer
14 years 1 months ago
Alleviating the Sparsity Problem of Collaborative Filtering Using Trust Inferences
Collaborative Filtering (CF), the prevalent recommendation approach, has been successfully used to identify users that can be characterized as “similar” according to their logg...
Manos Papagelis, Dimitris Plexousakis, Themistokli...
ICCBR
2001
Springer
14 years 10 days ago
A Case-Based Reasoning View of Automated Collaborative Filtering
From some perspectives Automated Collaborative Filtering (ACF) appears quite similar to Case-Based Reasoning (CBR). It works on data organised around users and assets that might be...
Conor Hayes, Padraig Cunningham, Barry Smyth
RECSYS
2009
ACM
14 years 2 months ago
Context-based splitting of item ratings in collaborative filtering
Collaborative Filtering (CF) recommendations are computed by leveraging a historical data set of users’ ratings for items. It assumes that the users’ previously recorded ratin...
Linas Baltrunas, Francesco Ricci