Modeling user preferences using neural networks and tensor factorization model

Volume: 45, Pages: 132 - 148
Published: Apr 1, 2019
Abstract
With the expansion of information on the web, recommendation systems have become one of the most powerful resources to ease the task of users. Traditional recommendation systems (RS) suggest items based only on feedback submitted by users in form of ratings. These RS are not competent to deal with definite user preferences due to emerging and situation dependent user-generated content on social media, these situations are known as contextual...
Paper Details
Title
Modeling user preferences using neural networks and tensor factorization model
Published Date
Apr 1, 2019
Volume
45
Pages
132 - 148
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