Maximum Entropy Model In Nlp
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Introduction to Linguistic Annotation and Text Analytics
Linguistic annotation and text analytics are active areas of research and development, with academic conferences and industry events such as the Linguistic Annotation Workshops and the annual Text Analytics Summits. This book provides a basic introduction to both fields, and aims to show that good linguistic annotations are the essential foundation for good text analytics. After briefly reviewing the basics of XML, with practical exercises illustrating in-line and stand-off annotations, a chapter is devoted to explaining the different levels of linguistic annotations. The reader is encouraged to create example annotations using the WordFreak linguistic annotation tool. The next chapter shows how annotations can be created automatically using statistical NLP tools, and compares two sets of tools, the OpenNLP and Stanford NLP tools. The second half of the book describes different annotation formats and gives practical examples of how to interchange annotations between different formats using XSLT transformations. The two main text analytics architectures, GATE and UIMA, are then described and compared, with practical exercises showing how to configure and customize them. The final chapter is an introduction to text analytics, describing the main applications and functions including named entity recognition, coreference resolution and information extraction, with practical examples using both open source and commercial tools. Copies of the example files, scripts, and stylesheets used in the book are available from the companion website, located at the book website. Table of Contents: Working with XML / Linguistic Annotation / Using Statistical NLP Tools / Annotation Interchange / Annotation Architectures / Text Analytics
Natural Language Processing – IJCNLP 2005
Author: Robert Dale
language: en
Publisher: Springer Science & Business Media
Release Date: 2005-09-30
This book constitutes the thoroughly refereed proceedings of the Second International Joint Conference on Natural Language Processing, IJCNLP 2005, held in Jeju Island, Korea in October 2005. The 88 revised full papers presented in this volume were carefully reviewed and selected from 289 submissions. The papers are organized in topical sections on information retrieval, corpus-based parsing, Web mining, rule-based parsing, disambiguation, text mining, document analysis, ontology and thesaurus, relation extraction, text classification, transliteration, machine translation, question answering, morphological analysis, text summarization, named entity recognition, linguistic resources and tools, discourse analysis, semantic analysis NLP applications, tagging, language models, spoken language, and terminology mining.
Encyclopedia of Machine Learning
Author: Claude Sammut
language: en
Publisher: Springer Science & Business Media
Release Date: 2011-03-28
This comprehensive encyclopedia, in A-Z format, provides easy access to relevant information for those seeking entry into any aspect within the broad field of Machine Learning. Most of the entries in this preeminent work include useful literature references.