JOURNAL ARTICLE

Dependency parsing for information retrieval

Douglas P. MetzlerTerry NoreaultLauren RicheyBryan Heidorn

Year: 1984 Journal:   International ACM SIGIR Conference on Research and Development in Information Retrieval Pages: 313-324

Abstract

This paper describes the development of a parser based on the Moulton and Robinson (1981) dependency theory of syntax, and several strategies by which we are attempting to apply the outputs of this parser to the processes of Information Retrieval. We first discuss the limits of present Information Retrieval theory and the potential benefits of linguistic analysis for Information Retrieval. Next we briefly present the Moulton and Robinson theory, contrast it to rewrite rule based theories, and outline its general advantages as an approach to natural language processing. Next we describe the parser we have implemented based on the Moulton and Robinson theory, and some of the implementation issues we have addressed. Finally, we discuss several strategies by which this parser could be applied to Information Retrieval, and the problems involved in this application.

Keywords:
Computer science Parsing Natural language processing Syntax Artificial intelligence Dependency (UML) Dependency grammar Question answering Information retrieval Programming language

Metrics

8
Cited By
0.79
FWCI (Field Weighted Citation Impact)
5
Refs
0.70
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Natural Language Processing Techniques
Physical Sciences →  Computer Science →  Artificial Intelligence
Semantic Web and Ontologies
Physical Sciences →  Computer Science →  Artificial Intelligence

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