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» On bootstrapping recommender systems
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KDD
2006
ACM
170views Data Mining» more  KDD 2006»
16 years 4 months ago
Classification features for attack detection in collaborative recommender systems
Collaborative recommender systems are highly vulnerable to attack. Attackers can use automated means to inject a large number of biased profiles into such a system, resulting in r...
Robin D. Burke, Bamshad Mobasher, Chad Williams, R...
DBSOCIAL
2011
300views Database» more  DBSOCIAL 2011»
14 years 8 months ago
Boosting video popularity through recommendation systems
While search engines are the major sources of content discovery on online content providers and e-commerce sites, their capability is limited since textual descriptions cannot ful...
Renjie Zhou, Samamon Khemmarat, Lixin Gao, Huiqian...
186
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WWW
2011
ACM
14 years 11 months ago
Ranking in context-aware recommender systems
As context is acknowledged as an important factor that can affect users’ preferences, many researchers have worked on improving the quality of recommender systems by utilizing ...
Minsuk Kahng, Sangkeun Lee, Sang-goo Lee
CIKM
2009
Springer
15 years 11 months ago
Hydra: a hybrid recommender system [cross-linked rating and content information]
This paper discusses the combination of collaborative and contentbased filtering in the context of web-based recommender systems. In particular, we link the well-known MovieLens ...
Stephan Spiegel, Jérôme Kunegis, Fang...
KAIS
2011
102views more  KAIS 2011»
14 years 11 months ago
Symbolic data analysis tools for recommendation systems
Recommendation Systems have become an important tool to cope with the information overload problem by acquiring data about the user behavior. After tracing the user behavior, throu...
Byron Leite Dantas Bezerra, Francisco de Assis Ten...