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Constituent object parsing for information retrieval and similar text processing problems

Metzler, DP and Haas, SW and Cosic, CL and Wheeler, LH (1989) Constituent object parsing for information retrieval and similar text processing problems. UNSPECIFIED. UNSPECIFIED.

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The architecture and functioning of the Constituent Object Parser are described. This system has been developed specifically for text processing applications such as information retrieval, which can benefit from structural comparisons between elements of text such as a query and a potentially relevant abstract. The general way in which the system performs these matches, and the ways in which this objective influenced the design of the system are described. The parsing architecture incorporates several interesting features including: (1) an unusual combination of declarative and procedural representation techniques, (2) a monotonic discipline which permits useful heuristic approaches to difficult linguistic problems such as ellipsis, conjunction, ambiguity, and ill‐formed and incomplete input, and (3) an attempt to minimize the level of syntactic detail required in both the grammar and the lexicon. © 1989 John Wiley & Sons, Inc. Copyright © 1989 John Wiley & Sons, Inc.


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Item Type: Monograph (UNSPECIFIED)
Status: Published
CreatorsEmailPitt UsernameORCID
Metzler, DP
Haas, SW
Cosic, CL
Wheeler, LH
Date: 1 January 1989
Date Type: Publication
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Journal or Publication Title: Journal of the American Society for Information Science
Volume: 40
Number: 6
Page Range: 398 - 423
DOI or Unique Handle: 10.1002/(sici)1097-4571(198911)40:6<398::aid-asi3>;2-l
Institution: University of Pittsburgh
Department: School of Library and Information Science
Schools and Programs: School of Information Sciences > Library and Information Science
Refereed: No
ISSN: 0002-8231
University of Pittsburgh Series: iSchool Research Report Series
Other ID: LIS012/IS88012
Date Deposited: 11 Apr 2013 17:32
Last Modified: 01 Sep 2018 11:55


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