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Using Grammatical Inference to Automate Information Extraction from the Web

  • Theodore W. Hong
  • Keith L. Clark
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2168)

Abstract

The World-Wide Web contains a wealth of semistructured information sources that often give partial/overlapping views on the same domains, such as real estate listings or book prices. These partial sources could be used more effectively if integrated into a single view; however, since they are typically formatted in diverse ways for human viewing, extracting their data for integration is a difficult challenge. Existing learning systems for this task generally use hardcoded ad hoc heuristics, are restricted in the domains and structures they can recognize, and/or require manual training. We describe a principled method for automatically generating extraction wrappers using grammatical inference that can recognize general structures and does not rely on manually-labelled examples. Domain-speci.c knowledge is explicitly separated out in the form of declarative rules. The method is demonstrated in a test setting by extracting real estate listings from web pages and integrating them into an interactive data visualization tool based on dynamic queries.

Keywords

Real Estate Inference Algorithm Inductive Logic Programming Book Price Grammatical Inference 
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 2001

Authors and Affiliations

  • Theodore W. Hong
    • 1
  • Keith L. Clark
    • 1
  1. 1.Department of ComputingImperial College of Science, Technology, and MedicineLondonUK

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