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Contents Popularity Prediction by Vector Representation Learned from User Action History

Authors:
Naoki Nonaka
Kotaro Nakayama
Yutaka Matsuo

Keywords: Popularity prediction, Wikipedia, Vector representation, MLP

Abstract:
The anime and manga industry is important in Japan, and its popularity has been increasing overseas in recent years. Under such circumstances, predicting the popularity of media contents is important for content holding companies. Popularity prediction research has, so far, rarely considered the multifaceted information of media contents based on consumer preferences. In this study, we extracted users’ preferences from Wikipedia and obtained a vector representation with multifaceted content information. We qualitatively analyzed learned vector representations and showed that accuracy is improved by 2 to 3 % in a popularity prediction task.

Pages: 15 to 22

Copyright: Copyright (c) IARIA, 2017

Publication date: November 12, 2017

Published in: conference

ISSN: 2308-4464

ISBN: 978-1-61208-603-3

Location: Barcelona, Spain

Dates: from November 12, 2017 to November 16, 2017