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

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.

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.