Automating the extraction of data from HTML tables with unknown structure

David W. Embley, Cui Tao, Stephen W. Liddle

Research output: Contribution to journalConference article

54 Scopus citations

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. Our solution entails elements of table understanding, data integration, and wrapper creation. Table understanding allows us to find tables of interest within a Web page, recognize attributes and values within the table, 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 locate data of interest in tables and map the data 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.

Original languageEnglish (US)
Pages (from-to)3-28
Number of pages26
JournalData and Knowledge Engineering
Volume54
Issue number1
DOIs
StatePublished - Jul 1 2005
Event21st International Conference on Conceptual Modeling ER -
Duration: Oct 7 2002Oct 11 2002

Keywords

  • Data integration
  • Document-independent extraction ontologies
  • Table understanding
  • Wrapper creation

ASJC Scopus subject areas

  • Information Systems and Management

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