DMCA
Minimal Commitment and Full Lexical Disambiguation: Balancing Rules and Hidden Markov Models (2000)
| Venue: | In Proceedings of the 5 th CoNLL Conference |
BibTeX
@INPROCEEDINGS{Robert00minimalcommitment,
author = {Patrick Ruch Robert and Robert Baud and Pierrette Bouillon and Gilbert Robert},
title = {Minimal Commitment and Full Lexical Disambiguation: Balancing Rules and Hidden Markov Models},
booktitle = {In Proceedings of the 5 th CoNLL Conference},
year = {2000},
pages = {111--114}
}
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Abstract
In this paper we describe the construction of a part-of-speech tagger both for medical document retrieval purposes and XP extraction. Therefore we have designed a double system: for retrieval purposes, we rely on a rule-based architecture, called minimal commitment, which is likely to be completed by a data-driven tool (HMM) when full disambiguation is necessary. 1 Introduction Nowadays, most medical information is stored in textual documents 1 , but such large amount of data may remain useless if retrieving the relevant information in a reasonable time becomes impossible. Although some large-scale information retrieval (IR) evaluations, made on unrestricted corpora (Hersh and al., 1998), and on medical texts (Hersh, 1998), are quite critical towards linguistic engineering, we believe that natural language processing is the best solution to face two major problems of text retrieval engines: expansion of the query and lexical disambiguation. Disambiguation can be separated between M...
Keyphrases
minimal commitment full lexical disambiguation balancing rule hidden markov model text retrieval engine medical information rule-based architecture reasonable time relevant information medical text xp extraction double system unrestricted corpus natural language processing major problem retrieval purpose large-scale information retrieval medical document retrieval purpose introduction nowadays full disambiguation data-driven tool critical towards linguistic engineering part-of-speech tagger lexical disambiguation large amount textual document
