[Corpora-List] CFP: MMIES2: Multi-source, Multilingual Information Extraction and Summarization Workshop

Tue Mar 4 12:33:26 UTC 2008

MMIES2: Multi-source, Multilingual Information Extraction and 
Summarization Workshop

Manchester, 23 August, 2008

Held in conjunction with COLING-2008 (http://www.coling2008.org.uk/),
the 22nd International Conference on Computational Linguistics, 18-22
August,  2008.

Theme:

The objective of the 2nd MMIES Workshop: Multi-source, Multilingual
Information Extraction and Summarization is to bring together researchers
and practitioners in the areas of extraction, summarization, and other
information access technologies, to discuss recent approaches to 
multi-source
and multi-lingual challenges.  Approaches to handling the idiosyncratic
nature of the new Web2.0 media are especially welcome, including: mixed 
input,
new jargon, ungrammatical and mixed-language input, and emotional discourse.

Workshop Web Site:

http://doremi.cs.helsinki.fi/mmies2/

Organisers:

* Sivaji Bandyopadhyay (Jadavpur University, India)
* Thierry Poibeau (CNRS / Universite Paris 13, France)
* Horacio Saggion (University of Sheffield, UK)
* Roman Yangarber (University of Helsinki, Finland)

Call for Papers

Information extraction (IE) and text summarization (TS) are key technologies
aiming at extracting from texts  information that is relevant to a
user's interest,   and presenting it to the user in concise form.
The on-going information explosion
makes IE and TS particularly critical for successful functioning within the
information society.  These technologies, however, face new challenges 
with the
adoption of the Web 2.0 paradigm (e.g. blogs, wikis) because of their 
inherent
multi-source nature.  These technologies must no longer only deal with 
isolated
texts or single narratives, but with large-scale repositories or sources --
possibly in several languages -- containing a multiplicity of views, 
opinions,
or commentaries on particular topics, entities or events.  There is thus 
a need
to adapt and/or develop new techniques to deal with these new phenomena.

Recognising similar information across different sources and/or in different
languages is of paramount importance in this multi-source, multi-lingual
context.  In information extraction, merging information from multiple 
sources
can lead to increased accuracy as compared with extraction from a
single source. In text summarization, similar facts found across
sources can  inform sentence scoring algorithms.
In question answering, the distribution of answers in similar contexts
can  inform answer ranking components.

Often, it is not the similarity of information that matters, but its
complementary nature. In a multi-lingual context, information extraction and
text summarization can provide solutions for cross-lingual access: key 
pieces
of information can be extracted from different texts in one or many 
languages,
merged, and then conveyed in many natural languages in concise form.
Applications need to be able to cope with the idiosyncratic nature of 
the new
Web 2.0 media: mixed input, new jargon, ungrammatical and mixed-language 
input,
emotional discourse, etc.  In this context, synthesizing or inferring 
opinions
from multiple sources is a new and exciting challenge for NLP.  On another
level, profiling of individuals who engage in the new social Web, and
identifying whether a particular opinion is appropriate/relevant in a given
context are important topics to be addressed.

It is therefore important that the research community address the following
issues:

- What methods are appropriate to detect similar/complementary/contradictory
information? Are hand-crafted rules and knowledge-rich approaches 
convenient?

- What methods are available to tackle cross-document and cross-lingual
entity and event coreference?

- What machine learning approaches are most appropriate for this task --
supervised/unsupervised/semi-supervised?  What type of corpora are 
required for
training and testing?

- What techniques are appropriate to synthesize condensed synopses of the
extracted information?  What generation techniques are useful here? What 
kind
of techniques can be used to cross domains and languages?

- What techniques can improve opinion mining and sentiment analysis through
multi-document analysis?  How do information extraction and opinion mining
connect?

- What tools exist for supporting multi-lingual/multi-source access to
information?  What solutions exist beyond full document translation to 
produce
cross-lingual summaries?

Important Dates:

* Paper submission deadline: ***  5 May ***
* Notification of acceptance of Papers: 6 June
* Camera-ready copy of papers due: 1 July
* Workshop: *** 23 August ***

Paper Submission:

Papers should describe original work and should indicate the state of
completion of the reported results. Wherever appropriate, concrete
evaluation results should be included. Submissions will be judged on
correctness, originality, technical strength, significance and
relevance to the conference, and interest to the attendees.

Submissions should follow the two-column format of ACL proceedings and
should not exceed eight (8) pages, including references. We strongly
recommend the use of the Coling 2008 LaTeX style files or Microsoft
Word Style files tailored for this year's conference
(http://personalpages.manchester.ac.uk/staff/harold.somers/coling/style.html).

Submission will be electronic (pdf format only), using the START paper
submission webpage dedicated to the workshop
https://www.softconf.com/coling08/MMIES2/.

Programme Committee:

 Javier Artiles (UNED, Spain)
 Kalina Bontcheva (U. Sheffield, UK)
 Nathalie Colineau (CSIRO, Australia)
 Nigel Collier (NII, Japan)
 Hercules Dalianis (KTH/Stockholm University, Sweden)
 Thierry Declerk (DFKI, Germany)
 Michel Généreux (LIPN-CNRS, France)
 Julio Gonzalo (UNED, Spain)
 Brigitte Grau (LIMSI-CNRS, France)
 Ralph Grishman (New York University, USA)
 Kentaro Inui (NAIST, Japan)
 Min-Yen Kan (National University of Singapore, Singapore)
 Guy Lapalme (U. Montreal, Canada)
 Diana Maynard (U. Sheffield, UK)
 Jean-Luc Minel (Modyco-CNRS, France)
 Constantin Orasan (University of Wolverhampton, UK)
 Cecile Paris (CSIRO, Australia)
 Maria Teresa Pazienza (U. of Roma tor Vergata, Italy)
 Bruno Pouliquen (European Commission - Joint Research Centre, Italy)
 Satoshi Sekine (NYU, USA)
 Patrick Saint-Dizier (IRIT-CNRS, France)
 Agnes Sandor (Xerox XRCE, France)
 Ralf Steinberger (European Commission - Joint Research Centre, Italy)
 Stan Szpakowicz (University of Ottawa, Canada)
 Lucy Vanderwende (Microsoft Research, USA)
 Jose Luis Vicedo (Universidad de Alicante, Spain)

Additional Information:

Information about the previous MMIES Workshop, at
RANLP-2007 in Borovets, Bulgaria  can be found at
(http://www-lipn.univ-paris13.fr/~poibeau/mmies/index.html)

Questions?

Sivaji Bandyopadhyay  - sivaji_cse_ju at yahoo.com
Thierry Poibeau  - Thierry.Poibeau at lipn.univ-paris13.fr
Horacio Saggion - H.Saggion at dcs.shef.ac.uk
Roman Yangarber - Roman.Yangarber at cs.helsinki.fi

-- 
Dr. Horacio Saggion
Research Fellow
Natural Language Processing Group
Department of Computer Science
211 Portobello Street
Sheffield - S1 4DP
United Kingdom
http://www.dcs.shef.ac.uk/~saggion
saggion at dcs.shef.ac.uk
Tel: +44-114-222-1947
Fax: +44-114-222-1810

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