Advances In Probabilistic And Other Parsing Technologies

Parsing technology is concerned with finding syntactic structure in language. In parsing we have to deal with incomplete and not necessarily accurate formal descriptions of natural languages. Robustness and efficiency are among the main issuesin parsing. Corpora can be used to obtain frequency information about language use. This allows probabilistic parsing, an approach that aims at both robustness and efficiency increase. Approximation techniques, to be applied at the level of language description, parsing strategy, and syntactic representation, have the same objective. Approximation at the level of syntactic representation is also known as underspecification, a traditional technique to deal with syntactic ambiguity. In this book new parsing technologies are collected that aim at attacking the problems of robustness and efficiency by exactly these techniques: the design of probabilistic grammars and efficient probabilistic parsing algorithms, approximation techniques applied to grammars and parsers to increase parsing efficiency, and techniques for underspecification and the integration of semantic information in the syntactic analysis to deal with massive ambiguity. The book gives a state-of-the-art overview of current research and development in parsing technologies. In its chapters we see how probabilistic methods have entered the toolbox of computational linguistics in order to be applied in both parsing theory and parsing practice. The book is both a unique reference for researchers and an introduction to the field for interested graduate students.

Parsing can be defined as the decomposition of complex structures into their constituent parts, and parsing technology as the methods, the tools, and the software to parse automatically. Parsing is a central area of research in the automatic processing of human language. Parsers are being used in many application areas, for example question answering, extraction of information from text, speech recognition and understanding, and machine translation. New developments in parsing technology are thus widely applicable. This book contains contributions from many of today's leading researchers in the area of natural language parsing technology. The contributors describe their most recent work and a diverse range of techniques and results. This collection provides an excellent picture of the current state of affairs in this area. This volume is the third in a series of such collections, and its breadth of coverage should make it suitable both as an overview of the current state of the field for graduate students, and as a reference for established researchers.

In Marcus (1980), deterministic parsers were introduced. These are parsers which satisfy the conditions of Marcus's determinism hypothesis, i.e., they are strongly deterministic in the sense that they do not simulate non determinism in any way. In later work (Marcus et al. 1983) these parsers were modified to construct descriptions of trees rather than the trees them selves. The resulting D-theory parsers, by working with these descriptions, are capable of capturing a certain amount of ambiguity in the structures they build. In this context, it is not clear what it means for a parser to meet the conditions of the determinism hypothesis. The object of this work is to clarify this and other issues pertaining to D-theory parsers and to provide a framework within which these issues can be examined formally. Thus we have a very narrow scope. We make no ar guments about the linguistic issues D-theory parsers are meant to address, their relation to other parsing formalisms or the notion of determinism in general. Rather we focus on issues internal to D-theory parsers themselves.

Computer parsing technology, which breaks down complex linguistic structures into their constituent parts, is a key research area in the automatic processing of human language. This volume is a collection of contributions from leading researchers in the field of natural language processing technology, each of whom detail their recent work which includes new techniques as well as results. The book presents an overview of the state of the art in current research into parsing technologies, focusing on three important themes: dependency parsing, domain adaptation, and deep parsing. The technology, which has a variety of practical uses, is especially concerned with the methods, tools and software that can be used to parse automatically. Applications include extracting information from free text or speech, question answering, speech recognition and comprehension, recommender systems, machine translation, and automatic summarization. New developments in the area of parsing technology are thus widely applicable, and researchers and professionals from a number of fields will find the material here required reading. As well as the other four volumes on parsing technology in this series this book has a breadth of coverage that makes it suitable both as an overview of the field for graduate students, and as a reference for established researchers in computational linguistics, artificial intelligence, computer science, language engineering, information science, and cognitive science. It will also be of interest to designers, developers, and advanced users of natural language processing systems, including applications such as spoken dialogue, text mining, multimodal human-computer interaction, and semantic web technology.

"This book is a comprehensive and in-depth reference to the most recent developments in the field covering theoretical developments, techniques, technologies, among others"--Provided by publisher.

The theory of formal languages is widely recognized as the backbone of theoretical computer science, originating from mathematics and generative linguistics, among others. As a foundational discipline, formal language theory concepts and techniques are present in a variety of theoretical and applied fields of contemporary research which are concerned with symbol manipulation: discrete mathematics, bioinformatics, natural language processing, pattern recognition, text retrieval, learning, cryptography, compression, etc. This volume presents the main results of some recent, quickly developing subfields of formal language theory in an easily accessible way and provides the reader with extensive bibliographical references to go deeper. Open problems are formulated too. The intended audience consists of undergraduates and graduates in computer science or mathematics. Graduates in other disciplines (linguistics, electrical engineering, molecular biology, logic) with some basic level of mathematical maturity may find the volume appealing and useful too. The book represents 'a gate to formal language theory and its applications' and a source of information in computation theory in general. This volume is complementary of the volumes in the Springer series Studies in Fuzziness and Soft Computing, number 148, and Studies in Computational Intelligence, 25.

The main topic of this volume is natural multimodal interaction. The book is unique in that it brings together a great many contributions regarding aspects of natural and multimodal interaction written by many of the important actors in the field. Topics addressed include talking heads, conversational agents, tutoring systems, multimodal communication, machine learning, architectures for multimodal dialogue systems, systems evaluation, and data annotation.

Vols. 8-10 of the 1965-1984 master cumulation constitute a title index.

This is the first comprehensive book to cover all aspects of word sense disambiguation. It covers major algorithms, techniques, performance measures, results, philosophical issues and applications. The text synthesizes past and current research across the field, and helps developers grasp which techniques will best apply to their particular application, how to build and evaluate systems, and what performance to expect. An accompanying Website extends the effectiveness of the text.