Title: Enriching folksonomy for online videos

Authors: Hiroki Sakaji; Masaki Kohana; Akio Kobayashi; Hiroyuki Sakai

Addresses: The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, 113-8656, Tokyo, Japan ' The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, 113-8656, Tokyo, Japan ' The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, 113-8656, Tokyo, Japan ' The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, 113-8656, Tokyo, Japan

Abstract: We propose a method that enriches folksonomy by using user comments on online videos. Folksonomy is a process in which users tag videos so that they can be searched for easily. On some videos, users can post tags and comments. A tag corresponds to folksonomy. One such online sharing website is Nico Nico Douga; however, users cannot post more than 12 tags on a video. Therefore, there are some important tags that could be posted but are sometimes not. We present a method for acquiring some of these missing tags by choosing new tags that score well in a scoring method developed by us. The method is based on information theory and a novel algorithm for estimating new tags by using distributed databases constructed by us.

Keywords: text mining; distributed database; information extraction.

DOI: 10.1504/IJGUC.2019.099664

International Journal of Grid and Utility Computing, 2019 Vol.10 No.3, pp.258 - 264

Received: 13 May 2017
Accepted: 22 Oct 2017
Published online: 20 May 2019 *

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