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Learning Rules for Conceptual Structure on the Web

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Abstract

This paper presents an infrastructure and methodology to extract conceptual structure from Web pages, which are mainly constructed by HTML tags and incomplete text. Human beings can easily read Web pages and grasp an idea about the conceptual structure of underlying data, but cannot handle excessive amounts of data due to lack of patience and time. However, it is extremely difficult for machines to accurately determine the content of Web pages due to lack of understanding of context and semantics. Our work provides a methodology and infrastructure to process Web data and extract the underlying conceptual structure, in particular relationships between ontological concepts using Inductive Logic Programming in order to help with automating the processing of the excessive amount of Web data by capturing its conceptual structures.

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Authors and Affiliations

  1. Colledge of Information Science and Technology, Drexel Univeristy, USA

    Hyoil Han & Ramez Elmasri

  2. Department of Computer Science and Engineering, The University of Texas at, Arlington

    Hyoil Han & Ramez Elmasri

Authors
  1. Hyoil Han
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  2. Ramez Elmasri
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Han, H., Elmasri, R. Learning Rules for Conceptual Structure on the Web. Journal of Intelligent Information Systems 22, 237–256 (2004). https://doi.org/10.1023/B:JIIS.0000019278.84222.b7

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  • DOI: https://doi.org/10.1023/B:JIIS.0000019278.84222.b7

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