Ontology-based WOM extraction service from weblogs

Authors:
Takahiro Kawamura;Shinichi Nagano;Yumiko Mizoguchi;Masumi Inaba;Tomohiro Yamasaki;Masayuki Okamoto
Affiliations:
Corporate Research & Development Center, Toshiba Corp.;Corporate Research & Development Center, Toshiba Corp.;Corporate Research & Development Center, Toshiba Corp.;Toshiba Corp.;Toshiba Corp.;Toshiba Corp.
Venue:
Proceedings of the 2008 ACM symposium on Applied computing
Year:
2008

Citing 6
Cited 0

Mining the peanut gallery: opinion extraction and semantic classification of product reviews

WWW '03 Proceedings of the 12th international conference on World Wide Web
Automatically collecting, monitoring, and mining japanese weblogs

Proceedings of the 13th international World Wide Web conference on Alternate track papers & posters
Thumbs up or thumbs down?: semantic orientation applied to unsupervised classification of reviews

ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Opinion sentence search engine on open-domain blog

IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Collecting evaluative expressions for opinion extraction

IJCNLP'04 Proceedings of the First international joint conference on Natural Language Processing
Detecting search engine spam from a trackback network in blogspace

KES'05 Proceedings of the 9th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part IV

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper, we introduce a web-based service that extracts reputations of a product from the internet. If a user inputs the product name, the service first collects articles reviewing the product from weblogs, bbs, and so on. Also, it analyzes their contents using metadata and ontologies with conventional NLP techniques. Then, it indicates the reputations (positive or negative) from the overall and several pre-defined aspects, and other related products that are the subject of much discussion in the articles. This paper illustrates two technical points regarding use of metadata and ontologies with NLP, and summarizes evaluations in a case that we applied it to a market research for a vehicle.