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Automatically Extracting Ontologically Specified Data from HTML Tables of Unknown Structure

  • David W. Embley
  • Cui Tao
  • Stephen W. Liddle
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2503)

Abstract

Data on the Web in HTML tables is mostly structured, but we usually do not know the structure in advance. Thus, we cannot directly query for data of interest. We propose a solution to this problem based on document-independent extraction ontologies. The solution entails elements of table understanding, data integration, and wrapper creation. Table understanding allows us to recognize attributes and values, pair attributes with values, and form records. Data-integration techniques allow us to match source records with a target schema. Ontologically specified wrappers allow us to extract data from source records into a target schema. Experimental results show that we can successfully map data of interest from source HTML tables with unknown structure to a given target database schema. We can thus “directly” query source data with unknown structure through a known target schema.

Keywords

Target Attribute Target Schema Merge Attribute Source Schema Source Table 
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 2002

Authors and Affiliations

  • David W. Embley
    • 1
  • Cui Tao
    • 1
  • Stephen W. Liddle
    • 2
  1. 1.Department of Computer ScienceUSA
  2. 2.School of Accountancy and Information SystemsBrigham Young UniversityProvoUSA

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