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» Collaborative Filtering CAPTCHAs
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116
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KDD
2009
ACM
298views Data Mining» more  KDD 2009»
15 years 8 months ago
Mind the gaps: weighting the unknown in large-scale one-class collaborative filtering
One-Class Collaborative Filtering (OCCF) is a task that naturally emerges in recommender system settings. Typical characteristics include: Only positive examples can be observed, ...
Rong Pan, Martin Scholz
88
Voted
CIKM
2009
Springer
15 years 8 months ago
Collaborative filtering using random neighbours in peer-to-peer networks
Traditionally, collaborative filtering (CF) algorithms used for recommendation operate on complete knowledge. This makes these algorithms hard to employ in a decentralized contex...
Arno Bakker, Elth Ogston, Maarten van Steen
UM
2009
Springer
15 years 8 months ago
What Have the Neighbours Ever Done for Us? A Collaborative Filtering Perspective
Collaborative filtering (CF) techniques have proved to be a powerful and popular component of modern recommender systems. Common approaches such as user-based and item-based metho...
Rachael Rafter, Michael P. O'Mahony, Neil J. Hurle...
ICDM
2003
IEEE
142views Data Mining» more  ICDM 2003»
15 years 7 months ago
Privacy-Preserving Collaborative Filtering Using Randomized Perturbation Techniques
Collaborative Filtering (CF) techniques are becoming increasingly popular with the evolution of the Internet. E-commerce sites use CF systems to suggest products to customers base...
Huseyin Polat, Wenliang Du
EPIA
2009
Springer
15 years 5 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