A brief introduction to natural language processing for non-linguists

Authors:
Cynthia A. Thompson
Affiliations:
Stanford Univ., Stanford, CA
Venue:
Learning language in logic
Year:
2001

Citing 12
Cited 0

Natural language understanding (2nd ed.)

Natural language understanding (2nd ed.)
Word sense disambiguation using a second language monolingual corpus

Computational Linguistics
Guest Editors‘ Introduction: Machine Learning and Natural Language

Machine Learning - Special issue on natural language learning
Foundations of statistical natural language processing

Foundations of statistical natural language processing
Automatic sense disambiguation using machine readable dictionaries: how to tell a pine cone from an ice cream cone

SIGDOC '86 Proceedings of the 5th annual international conference on Systems documentation
Statistical Language Learning

Statistical Language Learning
A Maximum-Entropy-Inspired Parser

A Maximum-Entropy-Inspired Parser
Introduction to the special issue on word sense disambiguation: the state of the art

Computational Linguistics - Special issue on word sense disambiguation
Distributional part-of-speech tagging

EACL '95 Proceedings of the seventh conference on European chapter of the Association for Computational Linguistics
Word-sense disambiguation using statistical methods

ACL '91 Proceedings of the 29th annual meeting on Association for Computational Linguistics
Automatic grammar induction and parsing free text: a transformation-based approach

ACL '93 Proceedings of the 31st annual meeting on Association for Computational Linguistics
Word-sense disambiguation using statistical models of Roget's categories trained on large corpora

COLING '92 Proceedings of the 14th conference on Computational linguistics - Volume 2

Quantified Score

Hi-index	0.00

Visualization

Abstract

This chapter introduces the field of natural language processing to the computer scientist or logician outside of the field. We first discuss some concepts from the field of linguistics, which focuses on the language half of the NLP equation, then move on to some of the common computational methods used to process and understand language. No previous knowledge of NLP is assumed.