Statistically-Based Natural Language Programming Techniques Papers from the 1992 Workshop (Technical Reports) by Carl Weir

Cover of: Statistically-Based Natural Language Programming Techniques | Carl Weir

Published by AAAI Press .

Written in English

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Subjects:

  • Natural Language Processing,
  • Computer Bks - General Information,
  • Computer Books: Languages

Book details

The Physical Object
FormatPaperback
Number of Pages114
ID Numbers
Open LibraryOL11470967M
ISBN 100929280334
ISBN 109780929280332
OCLC/WorldCa35543812

Download Statistically-Based Natural Language Programming Techniques

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Hearst, M., and Grefenstette, G. Refining automatically-discovered lexical relations: Combining weak techniques for stronger results.

AAAI Workshop on Statistically-Based Natural Language Programming Techniques, Stanford University, pdf; G. Grefenstette and M.A. Hearst. Method for refining automatically-discovered lexical relations: Combining weak techniques for stronger results. In Weir (ed.) Statistically based natural language programming techniques, Proc.

AAAI Workshop, Google ScholarCited by: First, the text features a new chapter on statistically-based methods using large corpora. Second, it includes an appendix on speech recognition and spoken language understanding. Also, the information on semantics that was covered in the first edition has been largely expanded in this edition to include an emphasis on compositional interpretation.

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Download for offline reading, highlight, bookmark or take notes while 5/5(1). Natural Language Processing (or: Natural Language Programming, in short: NLP) is a technology that enables computers and people to communicate with each other at eye level.

NLP combines linguistic findings with the latest methods of computer science and artificial intelligence. Introduction to natural language processing R. Kibble CO Undergraduate study in Computing and related programmes This is an extract from a subject guide for an undergraduate course offered as part of the University of London International Programmes in Computing.

Materials for these programmes are developed by academics at Size: KB. Grefenstette, G., Hearst, M.A.: Method for Refining Automatically-Discovered Lexical Relations: Combining Weak Techniques for Stronger Results.

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Develop a naïve Bayesian classifier to determine if an email is spam, based only on its text. the role of NLP techniques, and made access to NLP resources, such as lexicons seems natural and obvious, as is shown in work like Gollins and Sanderson's () cross-language retrieval by what Author: Yorick Wilks.

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Jones, Mark. A., and Jason M. Eisner, "A Probabilistic Parser and Its Application" (), in Statistically-Based Natural Language Programming Techniques, Papers from the AAAI Workshop, Technical Report W, Menlo Park CA: AAAI Press, pp.

A bracketed corpus is used to train a probabilistic context-free grammar. In Proceedings of the AAAI Workshop on Statistically-Based Natural Language Processing Techniques, San Jose, CA. 39 Aravind K. Joshi, B. Srinivas, Disambiguation of super parts of speech (or supertags): almost parsing, Proceedings of the 15th conference on Computational linguistics, August, Kyoto, Japan [doi> / ]Cited by:   First, the text features a new chapter on statistically-based methods using large corpora.

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