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Querying Text Databases for Efficient Information Extraction Eugene Agichtein Luis Gravano
 

Summary: ICDE 2003
Querying Text Databases for Efficient Information Extraction
Eugene Agichtein Luis Gravano
Columbia University
E-mail: {eugene,gravano}@cs.columbia.edu
Abstract
A wealth of information is hidden within unstructured text.
This information is often best exploited in structured or re-
lational form, which is suited for sophisticated query pro-
cessing, for integration with relational databases, and for
data mining. Current information extraction techniques ex-
tract relations from a text database by examining every doc-
ument in the database, or use filters to select promising doc-
uments for extraction. The exhaustive scanning approach
is not practical or even feasible for large databases, and
the current filtering techniques require human involvement
to maintain and to adopt to new databases and domains. In
this paper, we develop an automatic query-based technique
to retrieve documents useful for the extraction of user-defined
relations from large text databases, which can be adapted

  

Source: Agichtein, Eugene - Department of Mathematics and Computer Science, Emory University

 

Collections: Computer Technologies and Information Sciences