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Volumn 9, Issue 3, 2015, Pages 233-242

Tuning machine learning algorithms for content-based movie recommendation

Author keywords

content based movie recommendation; continuous attributes; decisiontrees; k means clustering; machine learning; multi valued attributes; na ve Bayes classifier; Recommendation systems

Indexed keywords

COLLABORATIVE FILTERING; DECISION TREES; K-MEANS CLUSTERING; LEARNING SYSTEMS; MACHINE LEARNING; MOTION PICTURES; RECOMMENDER SYSTEMS; TREES (MATHEMATICS);

EID: 84941791421     PISSN: 18724981     EISSN: 18758843     Source Type: Journal    
DOI: 10.3233/IDT-140219     Document Type: Article
Times cited : (5)

References (19)
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    • 84941798550 scopus 로고    scopus 로고
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    • GroupLens Research at the University of Minnesota: Movie-Lens Datasets, http://www.grouplens.org/node/73.
  • 10
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    • Toward the next generation of recommender systems: A survey of the state-of-the-art and possible extensions
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    • Hybrid recommender systems: Survey and experiments
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    • Burke, R.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.