Applied Natural Language Processing: Identification, Investigation and Resolution

Applied Natural Language Processing: Identification, Investigation and Resolution

Indexed In: SCOPUS
Release Date: October, 2011|Copyright: © 2012 |Pages: 659
DOI: 10.4018/978-1-60960-741-8
ISBN13: 9781609607418|ISBN10: 1609607414|EISBN13: 9781609607425
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Description & Coverage
Description:

The amount of information that humans have gathered and made available to other humans is phenomenal, yet however large this repository of knowledge is, by this time tomorrow, it will be larger still.

Applied Natural Language Processing: Identification, Investigation and Resolution is a volume dedicated to the successful application of processing tools to this information. The majority of this knowledge is expressed through textual media, which requires these tools to utilize the research in the field of Applied Natural Language Processing. This book contains state-of-the-art Applied Natural Language Processing techniques, as well as their applications. The descriptions and studies are the product of established researchers in fields relating to ANLP, and this work is relevant to teachers, students, and materials developers in fields spanning computer science, linguistics, and cognitive science.

Coverage:

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

  • Content Analysis and ANLP
  • Discourse Analysis
  • Information Extraction
  • Probabilistic approaches to ANLP
  • Programming for ANLP
  • Question Answering and Asking
  • Teaching ANLP
  • Text Classification/Clustering
  • Text Mining
  • Tokenization, Regular Expression, Morphology, and Stemming
Reviews & Statements

This volume serves to provide an overview and a survey of the state-of-the-art in ANLP. [...] The contributions to the volume come from established and recognized ANLP researchers and practitioners, with a wide range of viewpoints and skill-sets. As a result, this volume is truly comprehensive, and will be a starting point for much further work.

– Geoff Sutcliffe, University of Miami, USA
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Editor/Author Biographies
Philip M. McCarthy is an Assistant Professor at The University of Memphis. He is also a member of the Institute for Intelligent Systems. His research is in the field of Applied Natural Language Processing (ANLP). His primary interest is devising algorithms for contrastive corpus analyses, particularly where such algorithms can be informative of the relationship between language, the mind, and the world.
Chutima Boonthum-Denecke is an Assistant Professor in the Department of Computer Science at Hampton University. Dr. Boonthum-Denecke earned her Ph.D. in Computer Science from Old Dominion in 2007; MS in Applied Computer Science from Illinois State University in 2000; and BS in Computer Science from Srinakharinwirot University in 1997. Dr. Boonthum-Denecke has been involved in several NSF-funded Broadening Participation in Computing (BPC) programs: ARTSI (Advancing Robotics Technology for Societal Impact) and STARS (Students and Technology in Academia, Research and Service) Alliances. She is also a faculty member of the Hampton University Information Assurance group. Dr. Boonthum-Denecke's research interests include artificial intelligence (natural language processing, computational linguistics), information retrieval, Web development technology, and cognitive robotics.
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Editorial Advisory Board
  • Danielle McNamara, Arizona State University, USA
  • Art Graesser, University of Memphis, USA
  • Joe Magliano, Northern Illinois University, USA
  • Irwin Levinstein, Old Dominion University
  • Constantine Orasan, University of Wolverhampton, UK
  • Cristina Nicolae, University of Texas at Dallas, USA
  • Gaël Dias, University of Beira Interior, Portugal
  • Sivaji Bandyopadhyay, Jadavpur University, India
  • Asif Ekbal, University of Heidelberg, Germany
  • Sidney D’Mello, University of Memphis, USA
  • Manish Mehta, Georgia Tech, USA
  • Andrea Corradini, Syddansk University, Denmark
  • Roberto Navigli, Universita di Roma, Italy
  • Anna Feldman, Montclair State University, USA
  • Stephen Briner, Depaul University, USA
  • Charles Hall, University of Memphis, USA
  • Peter Clark, Boeing, USA
  • Gilles Richard, Institut de Reserche en Informatique de Toulouse, Francfe
  • Nick Duran, University of Memphis, USA
  • Verena Henrich, University of Tuebingen, Germany
  • Tanner Jackson, University of Memphis, USA
  • Nina Wacholder, Rutgers University, USA
  • Lorraine Khoury, University of Memphis, USA