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Unsupervised Information Extraction by Text Segmentation

A new unsupervised approach to the problem of Information Extraction by Text Segmentation (IETS) is proposed, implemented and evaluated herein. The authors’ approach relies on information available on pre-existing data to learn how to associate segments in the input string with attributes of a given...

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Bibliographic Details
Main Authors: Cortez, Eli. (Author, http://id.loc.gov/vocabulary/relators/aut), da Silva, Altigran S. (http://id.loc.gov/vocabulary/relators/aut)
Corporate Author: SpringerLink (Online service)
Format: Electronic eBook
Language:English
Published: Cham : Springer International Publishing : Imprint: Springer, 2013.
Edition:1st ed. 2013.
Series:SpringerBriefs in Computer Science,
Subjects:
Database management.
Data mining.
Information storage and retrieval.
Database Management.
Data Mining and Knowledge Discovery.
Information Storage and Retrieval.
Online Access:https://doi.org/10.1007/978-3-319-02597-1
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https://doi.org/10.1007/978-3-319-02597-1

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