MMIES2 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/.

The reviewing process  will  be  blind and  each  submission will  be reviewed by at least three programme committee members.

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	 This CfP was obtained from WikiCFP