Text-Mining is a growing area of interest within the field of Data Mining and Knowledge Discovery. Given a collection of text documents, most approaches to Text Mining perform knowledge-discovery operations either on external tags associated with each document, or on the set of all words within each document. Both approaches suffer from limitations. This paper focuses on an intermediate approach, one that we call text mining via information extraction, in which knowledge discovery takes place on focused, relevant terms, phrases and facts, as extracted from the documents.
Description
A domain independent environment for creating information extraction modules
%0 Conference Paper
%1 502699
%A Feldman, Ronen
%A Aumann, Yonatan
%A Liberzon, Yair
%A Ankori, Kfir
%A Schler, Jonathan
%A Rosenfeld, Benjamin
%B CIKM '01: Proceedings of the tenth international conference on Information and knowledge management
%C New York, NY, USA
%D 2001
%I ACM
%K rules_language to_print
%P 586--588
%R http://doi.acm.org/10.1145/502585.502699
%T A domain independent environment for creating information extraction modules
%U http://portal.acm.org/citation.cfm?id=502585.502699
%X Text-Mining is a growing area of interest within the field of Data Mining and Knowledge Discovery. Given a collection of text documents, most approaches to Text Mining perform knowledge-discovery operations either on external tags associated with each document, or on the set of all words within each document. Both approaches suffer from limitations. This paper focuses on an intermediate approach, one that we call text mining via information extraction, in which knowledge discovery takes place on focused, relevant terms, phrases and facts, as extracted from the documents.
%@ 1-58113-436-3
@inproceedings{502699,
abstract = {Text-Mining is a growing area of interest within the field of Data Mining and Knowledge Discovery. Given a collection of text documents, most approaches to Text Mining perform knowledge-discovery operations either on external tags associated with each document, or on the set of all words within each document. Both approaches suffer from limitations. This paper focuses on an intermediate approach, one that we call text mining via information extraction, in which knowledge discovery takes place on focused, relevant terms, phrases and facts, as extracted from the documents.},
added-at = {2009-04-12T19:34:41.000+0200},
address = {New York, NY, USA},
author = {Feldman, Ronen and Aumann, Yonatan and Liberzon, Yair and Ankori, Kfir and Schler, Jonathan and Rosenfeld, Benjamin},
biburl = {https://www.bibsonomy.org/bibtex/2b7e4380bac8033e2dede353b91157029/meco},
booktitle = {CIKM '01: Proceedings of the tenth international conference on Information and knowledge management},
description = {A domain independent environment for creating information extraction modules},
doi = {http://doi.acm.org/10.1145/502585.502699},
interhash = {9f02853116baf770cb98487aa6c022d5},
intrahash = {b7e4380bac8033e2dede353b91157029},
isbn = {1-58113-436-3},
keywords = {rules_language to_print},
location = {Atlanta, Georgia, USA},
pages = {586--588},
publisher = {ACM},
timestamp = {2009-04-12T19:34:41.000+0200},
title = {A domain independent environment for creating information extraction modules},
url = {http://portal.acm.org/citation.cfm?id=502585.502699},
year = 2001
}