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Applied Natural Language Processing: Identification, Investigation and Resolution

Philip M. McCarthy

Published by IGI Global
ISBN 10: 1609607414 / ISBN 13: 9781609607418
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Title: Applied Natural Language Processing: ...

Publisher: IGI Global

Binding: Hardcover

Book Condition: New

Book Type: Hardcover

Description:

Hardcover. 659 pages. Dimensions: 11.0in. x 8.9in. x 1.7in.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. This item ships from multiple locations. Your book may arrive from Roseburg,OR, La Vergne,TN. Bookseller Inventory # 9781609607418

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Synopsis:

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.

About the Author:

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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