Handbook of natural language procession /
Handbook of natural language procession /
edited by Robert Dale, Hermann Moisl and Harold Somers
- New York : Marcel Dekker, Inc., c2000
- xviii, 943 pages : illustrations ; 26 cm.
Includes bibliographical references and index.
Part I Symbolic Approaches to NLP -- Part II Empirical Approaches to NLP -- Part III Artificial Neural Network Approaches to NLP.
Annotation Contributors split nearly equally between scholars of linguistics and of technical matters such as computer science and information discuss recent developments in designing and implementing computational machinery that communicates with humans using natural language. Emphasizing practical tools and techniques and minimizing speculation and polemic, they cover symbolic approaches that have their origins in generative linguistics, approaches based on empirical corpus analysis, and artificial neural network approaches. Among the topics are discourse structure and intentional recognition, generating multimedia presentations, creating a corpus for data-intensive linguistics, example-based machine translation, character recognition with syntactic neural networks, knowledge representation, and text data mining.
824790006
NATURAL LANGUAGE PROCESSING (COMPUTER SCIENCE)
QA 76.9.N38 .H36 2000
Includes bibliographical references and index.
Part I Symbolic Approaches to NLP -- Part II Empirical Approaches to NLP -- Part III Artificial Neural Network Approaches to NLP.
Annotation Contributors split nearly equally between scholars of linguistics and of technical matters such as computer science and information discuss recent developments in designing and implementing computational machinery that communicates with humans using natural language. Emphasizing practical tools and techniques and minimizing speculation and polemic, they cover symbolic approaches that have their origins in generative linguistics, approaches based on empirical corpus analysis, and artificial neural network approaches. Among the topics are discourse structure and intentional recognition, generating multimedia presentations, creating a corpus for data-intensive linguistics, example-based machine translation, character recognition with syntactic neural networks, knowledge representation, and text data mining.
824790006
NATURAL LANGUAGE PROCESSING (COMPUTER SCIENCE)
QA 76.9.N38 .H36 2000