RECOMMENDER SYSTEM DEVELOPMENT
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Date
2019
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
СДУ хабаршысы - 2019
Abstract
Abstract. Over the last few decades recommender systems have taken more and more place in industry. Recommender systems are algorithms aimed at suggesting relevant products to users. From suggesting to people the goods that could interest them to suggesting to users the web content matching their preferences, recommender systems are today unavoidable in our daily online journeys. Recommender systems are really important in all industries as they can bring real economic returns or can be competitive advantage. In this work we provide an approach for increasing click-through rate by suggesting relevant products to users. The algorithm behind the recommender system described in this study is based on matrix factorization.
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Keywords
recommender systems, matrix factorization, implicit feedback, explicit feedback, СДУ хабаршысы - 2019, №3
Citation
A. Kim / RECOMMENDER SYSTEM DEVELOPMENT / СДУ хабаршысы - 2019