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Titlebook: Syntactic Wordclass Tagging; Hans Halteren Book 1999 Springer Science+Business Media B.V. 1999 Markov model.hidden markov model.learning.m

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书目名称Syntactic Wordclass Tagging
编辑Hans Halteren
视频video
丛书名称Text, Speech and Language Technology
图书封面Titlebook: Syntactic Wordclass Tagging;  Hans Halteren Book 1999 Springer Science+Business Media B.V. 1999 Markov model.hidden markov model.learning.m
描述In both the linguistic and the language engineering community, the creation and use of annotated text collections (or annotated corpora) is currently a hot topic. Annotated texts are of interest for research as well as for the development of natural language pro­ cessing (NLP) applications. Unfortunately, the annotation of text material, especially more interesting linguistic annotation, is as yet a difficult task and can entail a substan­ tial amount of human involvement. Allover the world, work is being done to replace as much as possible of this human effort by computer processing. At the frontier of what can already be done (mostly) automatically we find syntactic wordclass tagging, the annotation of the individual words in a text with an indication of their morpho syntactic classification. This book describes the state of the art in syntactic wordclass tagging. As an attempt to give an overall view of the field, this book is of interest to (at least) two, possibly very different, types of reader. The first type consists of those people who are using, or are planning to use, tagged material and taggers. They will want to know what the possibilities and impossibilities of taggin
出版日期Book 1999
关键词Markov model; hidden markov model; learning; machine learning; performance
版次1
doihttps://doi.org/10.1007/978-94-015-9273-4
isbn_softcover978-90-481-5296-4
isbn_ebook978-94-015-9273-4Series ISSN 1386-291X Series E-ISSN 2542-9388
issn_series 1386-291X
copyrightSpringer Science+Business Media B.V. 1999
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Automatic Taggers: An Introductionatic tagging software. We did not discuss in very much detail how such software works or which methods are used to arrive at an acceptable quality output. In this second part of the book, we will do just that: describe some popular techniques in detail.
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Syntactic Wordclass Tagging978-94-015-9273-4Series ISSN 1386-291X Series E-ISSN 2542-9388
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TokenizationThe linguistic annotation of naturally occurring text can be seen as a progression of transformations of the original text, with each step abstracting away surface differences. . is one of the earliest steps in this transformation during natural language processing.
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Lexicons for TaggingIn this chapter we will discuss the issue of constructing a lexicon which can be used in tagging.
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