Open AccessAn Overview of Empirical Natural Language Processing
Author(s) -
Brill Eric,
Mooney Raymond J.
Publication year - 1997
Publication title -
ai magazine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.597
H-Index - 79
eISSN - 2371-9621
pISSN - 0738-4602
DOI - 10.1609/aimag.v18i4.1318
Subject(s) - computer science , natural language processing , artificial intelligence , parsing , information extraction , natural language , question answering , machine translation , natural (archaeology) , temporal annotation , language technology , comprehension approach , archaeology , history
In recent years, there has been a resurgence in research on empirical methods in natural language processing. These methods employ learning techniques to automatically extract linguistic knowledge from natural language corpora rather than require the system developer to manually encode the requisite knowledge. The current special issue reviews recent research in empirical methods in speech recognition, syntactic parsing, semantic processing, information extraction, and machine translation. This article presents an introduction to the series of specialized articles on these topics and attempts to describe and explain the growing interest in using learning methods to aid the development of natural language processing systems.