Full Product Details
Author: Nancy Ide ,
James Pustejovsky
Publisher: Springer
Imprint: Springer
Edition: 1st ed. 2017
Weight: 2.535kg
ISBN: 9789402408799
ISBN 10: 9402408797
Pages: 1459
Publication Date: 29 June 2017
Audience:
College/higher education
,
Postgraduate, Research & Scholarly
Format: Hardback
Publisher's Status: Active
Availability: Manufactured on demand
We will order this item for you from a manufactured on demand supplier.
Reviews
Handbook of Linguistic Annotation is worth reading in that this volume presents a spate of annotation projects ... . This book includes a detailed introduction to a wealth of linguistic annotated resources and is worthy of recommendation for researchers of Quantitative Linguistics because these resources can either be used as direct sources for future quantitative studies or offer various choices on the annotation patterns. (Peng Bi, Journal of Quantitative Linguistics, January, 2018)
Author Information
Nancy Ide is Professor of Computer Science at Vassar College in Poughkeepsie, New York, USA. She has been in the field of computational linguistics for over 30 years and made significant contributions to research in word sense disambiguation, computational lexicography, discourse analysis, and the use of semantic web technologies for language data. She is founder of the Text Encoding Initiative (TEI), the first major standard for representing electronic language data, and later developed the XML Corpus Encoding Standard (XCES). More recently, she co-developed the ISO LAF/GrAF representation format for linguistically annotated data. She has also developed major corpora for American English, including the Open American National Corpus (OANC) and the Manually Annotated Sub-Corpus (MASC), and has been a pioneer in efforts to foster open data and resources. Professor Ide is Co-Editor-in-Chief of the journal Language Resources and Evaluation and Editor of the Springer book series Text,Speech, and Language Technology. James Pustejovsky is the TJX Feldberg professor of computer science at Brandeis University in Waltham, Massachusetts, United States. His expertise includes theoretical and computational modeling of language, specifically: Computational linguistics, Lexical semantics, Knowledge representation, temporal and spatial reasoning and Extraction. His main topics of research are Natural language processing generally, and in particular, the computational analysis of linguistic meaning. He proposed Generative Lexicon theory in lexical semantics. His other interests include temporal reasoning, event semantics, spatial language, language annotation, computational linguistics, and machine learning.
