A new collaborative filtering approach for increasing the aggregate diversity of recommender systems

Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

Volumn Part F128815, Issue , 2013, Pages 955-963

  Niemann, Katja ^a   Wolpers, Martin ^a  

^a FRAUNHOFER INSTITUTE FOR APPLIED INFORMATION TECHNOLOGY FIT   (Germany)

Author keywords

Aggregate diversity; Item item similarity; Long tail; Niche items; Recommender systems; Usage context

Indexed keywords

AGGREGATES; COLLABORATIVE FILTERING; DATA MINING; ONLINE SYSTEMS;

ITEM SIMILARITY; LONG TAIL; NICHE ITEMS; ONLINE STORE; USAGE CONTEXT; USAGE DATA;

RECOMMENDER SYSTEMS;

EID: 84949088547     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2487575.2487656     Document Type: Conference Paper

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