Cross-Disciplinary Advances in Applied Natural Language Processing: Issues and Approaches

Chutima Boonthum-Denecke (Hampton University, USA), Philip M. McCarthy (The University of Memphis, USA), and Travis Lamkin (University of Memphis, USA)

Indexed In: SCOPUS

Publication Status: E-Book and Print Version Available for Purchase

ISBN13: 9781613504475

EISBN13: 9781613504482

DOI: 10.4018/978-1-61350-447-5

Description:

Applied Natural Language Processing (ANLP) is interested in not only the creation of natural language processing approaches (i.e., tools, systems, algorithms, models, theories, and techniques), but it is also (and, arguably, more specifically) interested in how those approaches stack up against new problems, issues, identified knowledge gaps, or created data sets.

Cross-Disciplinary Advances in Applied Natural Language Processing: Issues and Approaches defines the role of ANLP within NLP, and alongside other disciplines such as linguistics, computer science, and cognitive science. The description also includes the categorization of current ANLP research, and examples of current research in ANLP. This book is a useful reference for teachers, students, and materials developers in fields spanning linguistics, computer science, and cognitive science.

Coverage:

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

ANLP Applications
Applied Linguistics
Artificial Intelligence
Cognitive Science
Computational Linguistics
Content Analysis
Human Computer Interaction
Language Engineering
Natural Language Processing
Semantic Analysis

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The current book needs to be seen not just as an inventory of what constitutes ANLP, or what researchers in ANLP are doing, it should also be seen as an opportunity for researchers and enthusiasts to consider how their work can be applied to industry, or for that matter, to any real world application.

– David Johnson, Decooda.com, USA; and Charles Wardell, Decooda.com, USA

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.

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.

Travis A. Lamkin is a graduate student at The University of Memphis, in the Applied Linguistics program. His primary research area is Applied Natural Language Processing (ANLP). He is currently involved in the Gramulator Project. He is particularly interested in applying methods and tools, such as the Gramulator, to the studies of literary criticism and genre assessment.

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