20.3002, FYI: Call for Book Chapters: Applied NLP

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LINGUIST List: Vol-20-3002. Tue Sep 08 2009. ISSN: 1068 - 4875.

Subject: 20.3002, FYI: Call for Book Chapters: Applied NLP

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1)
Date: 02-Sep-2009
From: Philip McCarthy < pmmccrth at memphis.edu >
Subject: Call for Book Chapters: Applied NLP
 

	
-------------------------Message 1 ---------------------------------- 
Date: Tue, 08 Sep 2009 11:22:43
From: Philip McCarthy [pmmccrth at memphis.edu]
Subject: Call for Book Chapters: Applied NLP

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Applied Natural Language Processing and Content Analysis:
Identification, Investigation, and Resolution
Edited by Dr. Philip McCarthy and Dr. Chutima Boonthum
Full Chapters Due: November 30, 2009
Planned for completion August 2010
Accepted for publication by IGI Global: 
http://www.igi-global.com/requests/details.asp?ID=708

Introduction
The amount of information that humans have gathered and made available to
other humans is, of course, phenomenal. And however large this repository
of knowledge is, we know that by this time tomorrow, it will be larger
still. But perhaps what is most relevant about this information is that
most of it appears in textual form. If we are ever to manage it, understand
it, assess it, evaluate it, summarize it, or even find it, then a broad
range of natural language processing tools, systems, algorithms, models,
theories, and techniques will have to be applied to it. The field of
Applied Natural Language Processing (ANLP) is dedicated to this venture. As
such, ANLP is not only interested in the creation of natural language
processing approaches (i.e., tools, systems, algorithms, models, theories,
and techniques), 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. In many ways then, ANLP can be
distinguished from NLP, not so much by its content, form, or span, but by
its focus. For ANLP, less time is spent describing the approach, which has
presumably been described elsewhere, as is spent describing the issue, the
investigation, and the resolution. This is not to say that the mechanics of
the approach can be ignored (they cannot), but it is to say that the
mechanics are relegated to being, as it were, a guest at the party, as
opposed to the host. 

Objective 
The main objective of our book is to offer a description of ANLP: what it
is, what it does; and where it's going. This description includes defining
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. 

We believe that by offering readers a broad, yet guided, picture of ANLP in
the first decade of the 21st century that we will be able to better shape
its success and development for the coming decades. In sum, this book will
contain state-of-the-art Applied Natural Language Processing techniques as
well as their applications. The descriptions and research will be the
product of established researchers in fields relating to ANLP. Such a book
will be relevant to teachers, students, and materials developers in fields
spanning linguistics, computer science, and cognitive science.

Target Audience
This book will be addressed to researchers, teachers, and students
interested in any level of textual analysis. More specifically, the book
will be addressed to researchers, teachers, and students interested in
studies focusing on the interaction between human and computer languages.
More specifically still, the book will be addressed to researchers,
teachers, and students interested in descriptions and examples of the
identification, investigation, and resolution of issues as they relate to
those interactions.
The book will be appropriate for the disciplines of computer science,
linguistics, cognitive science, and discourse psychology. Courses for which
the proposed book may be of interest as a primary or supplementary text
include introductory NLP and AI courses, computational linguistics, text
and data mining, discourse analysis, issues in corpus linguistics,
empirical research methodology, psychology of language, psycholinguistics,
and psychometrics. In addition, the book will be relevant to topics such as
natural language interfaces to databases, the use of linguistic tools and
electronic dictionaries, speech and language processing, conceptual
modeling, text preparation, categorization, natural language understanding
and assessment, text classification, information extraction, summarization,
question answering, topic segmentation, and machine translation.

Suggested Topics
While the focus of ANLP might contrast with NLP, the areas of interest do
not: anywhere NLP goes, ANLP must surely follow (and often arrive first).
Thus, the topics of interest for ANLP include (but, by definition, are not
limited to) summarization; text mining; categorization; authorship
recognition; genre recognition; word sense disambiguation; first/second
language acquisition; text and discourse analysis; paraphrasing;
entailment; anaphora resolution; co-reference resolution; text cohesion and
coherence; dialogue management and systems; language generation; language
models; human computer interfaces; multilingual processing; standardization
issues; language resources; corpora; learning environments; semantics;
ontologies; machine translation; intelligent tutoring; question answering;
parsing, tagging, annotating, tokenization, morphology, stemming,
information extraction, syntax, English for specific purposes; humor
analysis; user language understanding and assessment; web assessment; blog
analysis; grammar checking; speech recognition; speech production; data
mining; and any and all other areas that involve computation and text.	

Submissions will be considered for Part II and Part III of the book. 

Part I - Introduction to NLP. Part I will describe the major areas and
topics of interest in ANLP. However, unlike many computer science texts,
these chapters will not delve ever more deeply into these areas, so much as
they will broaden out, demonstrating current applications, and speculating
on future applications. Part I includes such areas as Parsing,
Summarization, Text Classification, and Question Answering.

Part II: Existing ANLP Applications - Part II will feature successful ANLP
applications or systems. Chapters will begin with a brief three-part
summary in the form of Identification, Investigation, and Resolution, and
will be approximately 10-15 pages in length. The object of Part II is to
better situate the role of ANLP as a field relating to the identification,
investigation, and resolution of issues as they relate to approaches in
human/computer language interaction. Part II already includes chapters on
such systems as AutoTutor, iSTART, and LIWC; however, more chapters will be
added through this call. 

Part III: Future ANLP - Part III will feature new research in ANLP. These
chapters will focus on either state of the art research in ANLP or reasoned
discussion for future directions in ANLP. Part III will feature
approximately 10 - 15 chapters, with each chapter 5-15 pages. ALL chapters
for Part III are open. Those wishing to make a submission for Part III
should email their chapter to the editors by the deadline given. Note that
any paper submitted to the special track in ANLP for FLAIRS-23
(http://tinyurl.com/kwwzs8) will automatically be considered for the book.

A template for chapters can be downloaded at http://tinyurl.com/lfvz24
An extended version of the call for papers can be downloaded at
http://tinyurl.com/m6enqx

Important Dates:
Chapter Submission:  November 30, 2009
Review Process Notification:  January 15, 2010
Chapter Revision and resubmission:  April 1, 2010
Final Acceptance Notifications:  April 30, 2010

Enquiries can be sent to 
Philip M. McCarthy: pmmccrth at memphis.edu and/or
Chutima Boonthum: chutima.boonthum at gmail 



Linguistic Field(s): Applied Linguistics
                     Computational Linguistics
                     Discourse Analysis
                     General Linguistics
                     Text/Corpus Linguistics





 




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