Transactions of the Japanese Society for Artificial Intelligence
Online ISSN : 1346-8030
Print ISSN : 1346-0714
ISSN-L : 1346-0714
Original Paper
Consumer Trend Prediction System Using Web Mining
Jun HozumiShuhei IitsukaKotaro NakayamaMasakazu TakasuEriko ShimadaChizuru SugaKeita NishiyamaYutaka Matsuo
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2014 Volume 29 Issue 5 Pages 449-459

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Abstract

The Ministry of Economy, Trade and Industry and the corporate world in Japan have recently embraced the ‘Cool Japan’ policy. They have assisted Japanese content industries in exporting Japanese media contents, such as manga (comics), to foreign countries, especially in Asia. However, this overseas expansion has not been successful in producing profits to the expected degree. The main reason for this shortfall is that companies are unable to perceive local consumer consumption trends in those countries easily and at low cost. Consequently, they are unable to select media contents that might be popular in such areas in the future. Herein, we design a consumption trend calculating system that incorporates web mining. It is readily applicable to many countries and contents. Specifically, we use web mining of data elicited from search counts on search engines, tweet counts from Twitter, and article data from Wikipedia to calculate consumption trends based on weekly manga sales data in Japan. Results show that this model can predict consumption trends for six months with high accuracy and that it can be adapted to calculate consumption trends of other contents effectively, such as anime (animation) in Japan and manga in France. Moreover, we establish the ASIA TREND MAP web service to inform industries about these calculated consumption trends for Asian countries.

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© The Japanese Society for Artificial Intelligence 2014
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