Novel centroid selection approaches for KMeans-clustering based recommender systems

Information Sciences

Volumn 320, Issue , 2015, Pages 156-189

  Zahra, Sobia ^a   Ghazanfar, Mustansar Ali ^a   Khalid, Asra ^a   Azam, Muhammad Awais ^a   Naeem, Usman ^b   Prugel Bennett, Adam ^c  

^a UNIVERSITY OF ENGINEERING AND TECHNOLOGY   (Pakistan)

^b UNIVERSITY OF EAST LONDON   (United Kingdom)

^c UNIVERSITY OF SOUTHAMPTON   (United Kingdom)

Author keywords

Centroid (seed) selection clustering; Collaborative filtering; K means clustering; Recommender systems

Indexed keywords

COLLABORATIVE FILTERING; DATA MINING; FILTRATION; LEARNING SYSTEMS; RECOMMENDER SYSTEMS; SCALABILITY;

CENTROID (SEED) SELECTION CLUSTERING; IMPROVE PERFORMANCE; MACHINE LEARNING TECHNIQUES; OFF-LINE TRAINING; RECOMMENDATION ALGORITHMS; ROBUST APPLICATION; SCALABILITY ISSUE; SELECTION METHODS;

K-MEANS CLUSTERING;

EID: 84937510254     PISSN: 00200255     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ins.2015.03.062     Document Type: Article

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