Parallel Natural Language Processing

Parallel processing is not only a general topic of interest for
computer scientists and researchers in artificial intelligence, but
it is gaining more and more attention in the community of scientists
studying natural language and its processing (computational
linguists, AI researchers, psychologists). The growing need to
integrate large divergent bodies of knowledge in natural language
processing applications, or the belief that massively parallel
systems are the only ones capable of handling the complexities and
subtleties of natural language, are just two examples of the reasons
for this increasing interest. This volume offers 13 contributions by
outstanding scientists from the fields of computer science,
artificial intelligence, and computational linguistics. The chapters
provide an extensive introduction to the field, as well as articles
that deal with both coarse grained (symbolic) and fine-grained
(connectionist) approaches. Along another axis, theoretical and
methodological, as well as empirical and implementational issues are
treated, and both language analysis and language generation are
covered.

Contents

* Parallel Natural Language Processing:Background and Overview *
Parallel Approaches to Context-Free Language Parsing * Parallel
Parsers for Context-Free Grammars--Two Actual Implementations
Compared * Object-Oriented Parallel Parsing for Context-Free Grammars
* Context-Free Parsing in Connectionist Networks * Getting Structure
from Subsymbolic Interactions * Parsing as an Energy Minimization
Problem/Process Independence and Concurrency in a Model of Sentence
Understanding * An Actor Model of Distributed Natural Language
Parsing * The Parallel Expert Parser * A Parallel Model of
Compositional Similarity of Natural Language Concepts/A Connectionist
Approach to Generation of Simple Sentences and Word Choice *
Parallelism in Incremental Sentence Generation * Author Index *
Subject Index