A recommender system for tourism industry using cluster ensemble and prediction machine learning techniques

Recommender systems have emerged in the e-commerce domain and are developed to actively recommend the right items to online users. Traditional Collaborative Filtering (CF) recommender systems recommend the items to users based on their single-rating feedback which are used to match similar users. In...

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Bibliographic Details
Main Authors: Nilashi, M., Bagherifard, K., Rahmani, M., Rafe, V.
Format: Article
Published: Elsevier Ltd 2017
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Online Access:http://eprints.utm.my/id/eprint/75950/
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85019901894&doi=10.1016%2fj.cie.2017.05.016&partnerID=40&md5=321c4be84c193cb3a7323bf8c44bebd3
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Institution: Universiti Teknologi Malaysia
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