Automating the extraction of data from HTML tables with unknown structure

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 understandi...

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Bibliographic Details
Published in:Data & knowledge engineering Vol. 54; no. 1; pp. 3 - 28
Main Authors: Embley, David W., Tao, Cui, Liddle, Stephen W.
Format: Journal Article
Language:English
Published: Elsevier B.V 01.07.2005
Subjects:
Data integration
Document-independent extraction ontologies
Table understanding
Wrapper creation
Table understanding
Document-independent extraction ontologies
Data integration
Wrapper creation
ISSN:0169-023X, 1872-6933
Online Access:Get full text
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Summary: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.
ISSN:0169-023X
1872-6933
DOI:10.1016/j.datak.2004.10.004