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Information Extraction from Semi-structured Web Documents

  • Bo-Hyun Yun
  • Chang-Ho Seo
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4092)

Abstract

This paper proposes the web information extraction system that extracts the pre-defined information automatically from web documents (i.e. HTML documents) and integrates the extracted information. The system recognizes entities without labels by the probabilistic based entity recognition method and extends the existing domain knowledge semiautomatically by using the extracted data. Moreover, the system extracts the sub-linked information linked to the basic page and integrates the similar results extracted from heterogeneous sources. The experimental result shows that the global precision of seven domain sites is 93.5%. The system using the sub-linked information and the probabilistic based entity recognition enhances the precision significantly against the system using only the domain knowledge. Moreover, the presented system can extract the more various information precisely due to applying the system with flexibility according to domains. Thus, the system can increase the degree of user satisfaction at its maximum and contribute the revitalization of e-business.

Keywords

Information Source Domain Knowledge Information Extraction Learning Data Token Probability 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Bo-Hyun Yun
    • 1
  • Chang-Ho Seo
    • 2
  1. 1.Dept. of Computer EducationMokwon UniversityTaejonKorea
  2. 2.Dept. of Applied MathematicsKongju UniversityKongju-CityKorea

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