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[eu_members at aclweb dot org] Information Processing & Management Journal: Special Issue on Question Answering -- CFP

Call for papers

Special Issue on Question Answering.
Information Processing & Management Journal

Guest Editors:
Patrick Saint-Dizier, IRIT, France
Marie-Francine Moens, Katholieke Universiteit Leuven, Belgium.

Important dates:
Submissions of articles: April 1, 2009
Notification to authors: June 20, 2009
Final version of accepted papers: September 13, 2009

Question answering is a sophisticated form of information
retrieval characterized by information needs that are expressed as
natural language statements or questions. In contrast to classical
information retrieval where complete documents are considered
relevant to the information need, in question answering specific
pieces of information are returned as an answer. Often, automated
reasoning is needed to identify correct answers.

Question answering has its roots decades ago when natural
language interfaces to data or knowledge bases were researched.
Today, such older technologies are blown in a new life, when we
witness the growing power of, for instance, searching multimedia
data (i.e., images, video, text, audio) combined with natural
language expressions, and making inferences over content
recognized in text or in the other media.

In this special issue we would like to compose a collection of state
of the art question answering papers which address the problem
from different angles, but are united by the recent technologies for
automatically recognizing content in the textual sources or the
semi-automatic recognition in other media sources, and by the
knowledge representation and reasoning paradigms used. Some
more practical issues such as presentation of answers, scalability
issues and indexing structures for question answering might also be

We particularly welcome submissions on, but not limited to, the
following topics:

Natural language processing for question analysis:
- Question analysis, semantic role labeling
- How to deal with complex questions

Natural language processing for document analysis:
- Information extraction, semantic role labeling, coreference
resolution and content linking
- Discourse analysis

Multimedia processing for question answering:
- Content recognition in images, video, audio and text
- Recognition and resolution of spatial and temporal
- Applications of multimedia question answering

Knowledge representations and reasoning strategies:
- Formal content representations
- Reasoning and matching strategies
- Constraint processing and relaxation
- Textual inference
- Handling incompleteness and uncertainty
- Probabilistic inference
- Data fusion

Speech interfaces and interactive question answering:
- Improved user models through speech interaction
- Dealing with noisy and uncertain question transcripts
- Interaction design
- Dialogue and question answering

Text and multimedia answer generation:
- Response production: summarization, fusion, co-operativity
Data indexing structures and scalability

Submissions for the special topic issue should be high-quality
manuscripts on the theoretical, empirical and methodological issues
surrounding question answering information retrieval. Submissions
should describe original research and not be under consideration in
any other forum.

All submissions should be formatted according to the Information
Processing & Management guidelines for papers, references, and
citations and should be submitted using the Elsevier Editorial
System for Information Processing and Management.

To ensure that all manuscripts are correctly identified for inclusion
into the special issue, it is important that authors select Special
Issue: Question Answering when they reach the "Article Type" step
in the submission process.

Submitted articles will be reviewed according to the Information
Processing & Management reviewing criteria and appropriateness to
the special topic issue.

Contact Patrick Saint-Dizier (stdizier at irit.fr) or Marie-Francine
Moens (sien.moens at cs.kuleuven.be) for further information on
the CFP. The program committee will be composed of experts who
served on the program committees of the past and current KRAQ