A domain independent environment for creating information extraction modules

Authors:
Ronen Feldman;Yonatan Aumann;Yair Liberzon;Kfir Ankori;Jonathan Schler;Benjamin Rosenfeld
Affiliations:
ClearForest Corporation, NY, NY;ClearForest Corporation, NY, NY;ClearForest Corporation, NY, NY;ClearForest Corporation, NY, NY;ClearForest Corporation, NY, NY;ClearForest Corporation, NY, NY
Venue:
Proceedings of the tenth international conference on Information and knowledge management
Year:
2001

Citing 2
Cited 0

Exploiting Background Information in Knowledge Discovery from Text

Journal of Intelligent Information Systems
Description of the UMass system as used for MUC-6

MUC6 '95 Proceedings of the 6th conference on Message understanding

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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.