Toward more diverse recommendations: Item re-ranking methods for recommender systems

19th Workshop on Information Technologies and Systems, WITS 2009

Volumn , Issue , 2009, Pages 79-84

  Adomavicius, Gediminas ^a   Kwon, Young Ok ^a  

^a UNIVERSITY OF MINNESOTA   (United States)

Author keywords

Collaborative filtering; Ranking functions; Recommendation diversity; Recommender systems

Indexed keywords

ALGORITHMS; COLLABORATIVE FILTERING; INFORMATION TECHNOLOGY;

DIVERSITY GAIN; PERSONALIZED RECOMMENDATION; PREDICTION TECHNIQUES; RANKING FUNCTIONS; RE-RANKING; REAL-WORLD; RECOMMENDATION ACCURACY; RECOMMENDATION DIVERSITIES;

RECOMMENDER SYSTEMS;

EID: 84903844870     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

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