Sequence Models for Automatic Highlighting and Surface Information Extraction

Abstract

With the increase of textual information available electronically, we assist to a great diversification of the demands on Information Retrieval (IR) and Information Extraction (IE) systems. In this paper we apply Machine Learning techniques of sequence analysis to the tasks of highlighting and labeling text with respect to an information extraction task. Specifically, dynamic probability models are used. Like IR systems, they use little semantics, are fully trainable and do not require any knowledge representation of the domain. Unlike IR approaches, documents are considered as a dynamic sequence of words. Furthermore, additional word information is naturally included in the representation. Models are evaluated on a sub-task of the MUC6 Scenario Template corpus. When morpho-syntactic word information is introduced into the representation, an increase in performances is observed.

Affiliations

LIP6, University of Paris 6,

case 169, 4 Place Jussieu, F-75252

Paris cedex 05, France.

Contributors

Massih-Reza Amini

Hugo Zaragoza

Patrick Gallinari

Conference

Publication date: April 1999

Publication date (Print): April 1999

Pages: 1-9

ID: 10.14236/ewic/IRSG1999.1

Copyright statement: © Massih-Reza Amini et al. Published by BCS Learning and Development Ltd. 21st Annual BCS-IRSG Colloquium on IR, Glasgow

License:

This work is licensed under a Creative Commons Attribution 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

Conference name: 21st Annual BCS-IRSG Colloquium on IR

Conference acronym: IRSG

Conference number: 21

Conference location: Glasgow

Conference date: 19-20 April 1999

Conference sponsor: Electronic Workshops in Computing (eWiC)

Conference theme: IR Research

Product

Product Information: 1477-9358 BCS Learning & Development

Self URI (article page): https://www.scienceopen.com/hosted-document?doi=10.14236/ewic/IRSG1999.1

Self URI (journal page): https://ewic.bcs.org/

Categories

Series title: Electronic Workshops in Computing