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» Methods for boosting recommender systems
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SIGIR
2009
ACM
14 years 2 months ago
Temporal collaborative filtering with adaptive neighbourhoods
Recommender Systems, based on collaborative filtering (CF), aim to accurately predict user tastes, by minimising the mean error achieved on hidden test sets of user ratings, afte...
Neal Lathia, Stephen Hailes, Licia Capra
UAI
2000
13 years 9 months ago
Collaborative Filtering by Personality Diagnosis: A Hybrid Memory and Model-Based Approach
The growth of Internet commerce has stimulated the use of collaborative filtering (CF) algorithms as recommender systems. Such systems leverage knowledge about the known preferenc...
David M. Pennock, Eric Horvitz, Steve Lawrence, C....
ECIR
2009
Springer
14 years 4 months ago
Active Sampling for Rank Learning via Optimizing the Area under the ROC Curve
Abstract. Learning ranking functions is crucial for solving many problems, ranging from document retrieval to building recommendation systems based on an individual user’s prefer...
Pinar Donmez, Jaime G. Carbonell
JDCTA
2010
688views more  JDCTA 2010»
13 years 2 months ago
Hand Mouse: Real Time Hand Motion Detection System Based on Analysis of Finger Blobs
Hand detection is a fundamental step in many practical applications as gesture recognition, video surveillance, and multimodal machine interface and so on. The aim of this paper i...
Ibrahim Furkan Ince, Manuel Socarras-Garzon, Tae-C...
JMLR
2006
132views more  JMLR 2006»
13 years 7 months ago
Learning to Detect and Classify Malicious Executables in the Wild
We describe the use of machine learning and data mining to detect and classify malicious executables as they appear in the wild. We gathered 1,971 benign and 1,651 malicious execu...
Jeremy Z. Kolter, Marcus A. Maloof