Employing neighborhood reduction for alleviating sparsity and cold start problems in user-based collaborative filtering

Recommender system (RS) can produce personalized service to users by analyzing their historical information. User-based collaborative filtering (UBCF) approach is widely utilized in practical RSs because of its excellent performance. However, the traditional UBCF suffers from several inherent proble...

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Veröffentlicht in:	Information retrieval (Boston) 2020-08, Vol.23 (4), p.449-472
Hauptverfasser:	Zhang, Zhipeng, Zhang, Yao, Ren, Yonggong
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Cold starts Collaboration Computer Science Data Mining and Knowledge Discovery Data Structures and Information Theory Datasets Filtration Information Storage and Retrieval Natural Language Processing (NLP) Neighborhoods Pattern Recognition Recommender systems Reduction Redundancy Sparsity
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