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KDD
2002
ACM
196views Data Mining» more  KDD 2002»
14 years 8 months ago
Comparing Two Recommender Algorithms with the Help of Recommendations by Peers
Abstract. Since more and more Web sites, especially sites of retailers, offer automatic recommendation services using Web usage mining, evaluation of recommender algorithms has bec...
Andreas Geyer-Schulz, Michael Hahsler
AAAI
2006
13 years 9 months ago
Mixed Collaborative and Content-Based Filtering with User-Contributed Semantic Features
We describe a recommender system which uses a unique combination of content-based and collaborative methods to suggest items of interest to users, and also to learn and exploit it...
Matthew Garden, Gregory Dudek
AAAI
2006
13 years 9 months ago
Model-Based Collaborative Filtering as a Defense against Profile Injection Attacks
The open nature of collaborative recommender systems allows attackers who inject biased profile data to have a significant impact on the recommendations produced. Standard memory-...
Bamshad Mobasher, Robin D. Burke, Jeff J. Sandvig
DEBU
2008
186views more  DEBU 2008»
13 years 7 months ago
A Survey of Collaborative Recommendation and the Robustness of Model-Based Algorithms
The open nature of collaborative recommender systems allows attackers who inject biased profile data to have a significant impact on the recommendations produced. Standard memory-...
Jeff J. Sandvig, Bamshad Mobasher, Robin D. Burke
DMS
2010
229views Multimedia» more  DMS 2010»
13 years 6 months ago
Image Annotation System Using Visual and Textual Features
We present an automated Image Annotation system called I-Tag which uses both visual and textual information of the images and recommends relevant tags for them. The automatic gene...
Swapnil Barai, Alfonso F. Cardenas