Ontology-Based Topic Extraction Service from Weblogs

  • Authors:
  • Shinichi Nagano;Masumi Inaba;Yumiko Mizoguchi;Takayuki Iida;Takahiro Kawamura

  • Affiliations:
  • -;-;-;-;-

  • Venue:
  • ICSC '08 Proceedings of the 2008 IEEE International Conference on Semantic Computing
  • Year:
  • 2008

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Abstract

Consumer Generated Media (CGM) has a significant impact on on campanies' product marketing strategies. This paper illustrates development of opinion analysis servce for marketing research,WOM Scouter. Then we present an algorithm of associated topic extraction, which is one of main features in WOM Scouter. Associated topic extraction finds out competitive products from blog entries commenting on a specified product. The main feature is to apply product ontology in addition to natural language processing. By looking up a term on product ontology, the product domain is identified in blog entries, and general nouns are excluded. Another feature is to evaluate an importance of each product by means of two kinds of smoothing functions based on link popularity and document frequency. The experimental evaluation shows that the proposed algorithm is closer to blog readers' impression than TF-IDF.