CALL FOR PAPERS (BOOK)

	       ADVANCES IN SCALABLE TEXT SUMMARIZATION
	       Inderjeet Mani and Mark Maybury, editors

With the explosion in the quantity of on-line information in recent
years, demand for text summarization technology appears to be
growing. Commercial companies are starting to offer text summarization
capabilities, often bundled with information retrieval tools. Further,
there is considerable interest in mining information from large
databases, many of which have text content. These recent developments
offer opportunities as well as substantial challenges for research in
text summarization. In general, such developments have created a
practical need for summarization systems which scale up when applied
to large volumes of unrestricted text.

In response to this challenge, a number of new approaches have
emerged. Traditionally, shallower techniques have been leveraged to
achieve the desired levels of scalability and domain-independence, but
recent advances in robust information extraction as well as approaches
integrating statistical and symbolic techniques have opened up
possibilities for more powerful yet scalable summarization techniques.

With the renewed interest in text summarization, another challenge is
to develop rigorous criteria to help evaluate different methodologies,
in order to better advise investors and the interested public on
technology choices.  This state-of-the-art collection will bring
together research aimed at advancing the scientific frontiers of text
summarization to meet these new practical challenges and
opportunities. **The principal aim of this book is to collect some
of the key results to date and to identify promising research issues
for the benefit of students, corporate researchers, and research
program managers interested in learning more about this field.**

Submissions are invited on original research in all aspects of text
summarization, including, but not limited to:

TECHNIQUES
   * Statistical, linguistic, and knowledge-based techniques in intelligent
     summarization
   * Text summary generation 
   * Capturing cohesion and coherence relations in text
   * Exploiting advances in information extraction in summarization
   * Exploiting domain knowledge in scalable text summarization
   * Combining scalability with abstraction in summarization
   * Tailoring summaries to particular users, tasks, and contexts

NEW PROBLEMS
   * Multilingual summarization
   * Multimodal summarization 
   * Multi-document/multi-source summarization 

FUNDAMENTAL ISSUES in THEORY AND PRACTICE
   * Classification of summarization systems
   * Theoretical foundations, including cognitive models
   * Evaluation methods and metrics
   * Summarization in operational contexts: requirements, architectures,
     lessons learned

Criteria for selection will include clarity, originality, relevance,
and significance of results. The papers will be reviewed by a
committee of experts. In addition, authors will be asked to relate the
content of their papers to other related papers in the book. In
addition to new contributions, the book will also include reprints of
classic papers in the field.

Submission Information

DEADLINE FOR SUBMISSION: December 30, 1997
PAPERS REVIEWED BY:      March 15, 1997
DRAFT TO PUBLISHERS:     July 15, 1997

Interested authors should submit to the address below three copies of
a previously unpublished paper no more than 20 pages long,
single-spaced, addressing a specific text summarization issue or
reporting novel methods and results. Authors should indicate whether
the paper is being submitted elsewhere. Please include your name and
address on the first page.

For more information, please contact:

Dr. Inderjeet Mani
The MITRE Corporation, W640
11493 Sunset Hills Road
Reston, Virginia 22090, USA
Internet: imani@mitre.org
Phone: (703) 883-6149
Fax: (703) 883-1379