Modern Computational Models of Semantic Discovery in Natural Language

Modern Computational Models of Semantic Discovery in Natural Language

Jan Žižka (Mendel University in Brno, Czech Republic) and František Dařena (Mendel University in Brno, Czech Republic)
Indexed In: SCOPUS
Release Date: July, 2015|Copyright: © 2015 |Pages: 335
ISBN13: 9781466686908|ISBN10: 1466686901|EISBN13: 9781466686915|DOI: 10.4018/978-1-4666-8690-8

Description

Language—that is, oral or written content that references abstract concepts in subtle ways—is what sets us apart as a species, and in an age defined by such content, language has become both the fuel and the currency of our modern information society. This has posed a vexing new challenge for linguists and engineers working in the field of language-processing: how do we parse and process not just language itself, but language in vast, overwhelming quantities?

Modern Computational Models of Semantic Discovery in Natural Language compiles and reviews the most prominent linguistic theories into a single source that serves as an essential reference for future solutions to one of the most important challenges of our age. This comprehensive publication benefits an audience of students and professionals, researchers, and practitioners of linguistics and language discovery.

This book includes a comprehensive range of topics and chapters covering digital media, social interaction in online environments, text and data mining, language processing and translation, and contextual documentation, among others.

Topics Covered

The many academic areas covered in this publication include, but are not limited to:

  • Arab Spring and Media
  • Artificial Intelligence
  • Corpus Stylistics
  • Linguistics
  • Machine Translation
  • Natural Language Processing
  • Ontology
  • Sentiment Analysis
  • Statistics
  • Syntax

Reviews and Testimonials

Computer and information scientists address some problems related to the automated semantic processing of electronic textual data written in natural languages, including instances of possible solutions demonstrated by carefully selected typical and applicable examples. Their topics include a model of the empirical distribution law for syntactic and link words in "perfect" texts, extracting definitional contexts in Spanish by identifying hyponymy-hyperonymy relations, semantics-based document categorization employing semi-supervised learning, departing the ontology layer cake, and machine translation within commercial companies.

– ProtoView Book Abstracts (formerly Book News, Inc.)

Table of Contents and List of Contributors

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Author(s)/Editor(s) Biography

Jan Žižka is an Associate Professor at the Department of Informatics, Faculty of Business and Economics, Mendel University Brno, member of SoNet research center, editor-in-chief of International Journal of Information Sciences and Techniques (IJIST), and International Journal of Computer Science & Information Technology (IJCSIT), a member of editorial boards and program committees of several other international scientific journals and conferences. He is also an author and co-author of many journal and conference peer-reviewed articles, and co-editor of several books in the area of informatics. His research areas include artificial intelligence, machine learning, and text/data mining.
František Daøena works as an Associate Professor and head of Information systems working group at the Department of Informatics, Faculty of Business and Economics, Mendel University Brno, he is a member of SoNet research center, author of several publications in international scientific journals, conference proceedings, and monographs, member of editorial board of international journals and editor-in-chief of International Journal in Foundations of Computer Science & Technology (IJFCST). His research areas include artificial intelligence, machine learning, and text/data mining.

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