A neural network model of lexical organization

Sample

Amy Neustein, Judith A. Markowitz

Where Humans Meet Machines: Innovative Solutions for Knotty Natural-Language Problems brings humans and machines closer together by showing how linguistic complexities that confound the speech systems of today can be handled effectively by sophisticated natural-language technology. Some of the most vexing natural-language problems that are addressed in this book entail recognizing and processing idiomatic expressions, understanding metaphors, matching an anaphor correctly with its antecedent, performing word-sense disambiguation, and handling out-of-vocabulary words and phrases. This fourteen-chapter anthology consists of contributions from industry scientists and from academicians working at major universities in North America and Europe. They include researchers who have played a central role in DARPA-funded programs and developers who craft real-world solutions for corporations. These contributing authors analyze the role of natural language technology in the global marketplace; they explore the need for natural language mapping-tools that can cull important data from the vast array of social-media postings; they describe innovative Natural Language Processing (NLP) methods and applications; and they offer NLP tools for physicians, educators, and translators. Their contributions constitute diverse and multifaceted solutions for the knotty natural-language problems that permeate everyday human communications. Where Humans Meet Machines: Innovative Solutions for Knotty Natural-Language Problems is designed for speech engineers, system developers, computer scientists, AI researchers, and others interested in utilizing natural-language technology in both spoken and text-based applications.

Sample

Nils J. Nilsson

Intelligent agents are employed as the central characters in this introductory text. Beginning with elementary reactive agents, Nilsson gradually increases their cognitive horsepower to illustrate the most important and lasting ideas in AI. Neural networks, genetic programming, computer vision, heuristic search, knowledge representation and reasoning, Bayes networks, planning, and language understanding are each revealed through the growing capabilities of these agents. A distinguishing feature of this text is in its evolutionary approach to the study of AI. This book provides a refreshing and motivating synthesis of the field by one of AI's master expositors and leading researches.

Sample

Raffaele Simone

Since the spectrum of possibilities in linguistic theory construction is much broader and more variegated than students of linguistics have perhaps been led to believe, the Current Issues in Linguistic Theory (CILT) series has been established in order to provide a forum for the presentation and discussion of linguistic opinions of scholars who do not necessarily accept the prevailing mode of thought in linguistic science. CILT is a theory-oriented series which welcomes contributions from scholars who have significant proposals to make towards the advancement of our understanding of language, its structure, functioning, and development. Current Issues in Linguistic Theory is especially designed, by offering an alternative outlet for meaningful contributions to the current linguistic debate, to furnish the community of linguists the diversity of opinion which a healthy discipline must have.

Sample

Andrea Mayr

A comprehensive introduction to language and power for upper level undergraduates and postgraduates, this title covers all the important issues within language and power, and the different approaches to analysing these issues.