TPWMNLP 2009 : ACL/IJCNLP-2009 Workshop on The People's Web meets NLP: Collaboratively Constructed Semantic Resources
Call For Papers
"The People's Web meets NLP:
Collaboratively Constructed Semantic Resources"
Co-located with Joint conference of the 47th Annual Meeting of the
Association for Computational Linguistics and the 4th International
Joint Conference on Natural Language Processing of the Asian
Federation of Natural Language Processing
6-7 August 2009
In recent years, online resources collaboratively constructed by ordinary
users on the Web have considerably influenced the NLP community. In many
works, they have been used as a substitute for conventional semantic
resources and as semantically structured corpora with great success.
While conventional resources such as WordNet are developed by trained
linguists , online semantic resources can now be automatically
extracted from the content collaboratively created by the users .
Thereby, the knowledge acquisition bottlenecks and coverage problems
pertinent to conventional lexical semantic resources can be overcome.
The resource that has gained the greatest popularity in this respect
so far is Wikipedia. However, other resources recently discovered in
NLP, such as folksonomies, the multilingual collaboratively
constructed dictionary Wiktionary, or Q&A sites like WikiAnswers or
Yahoo! Answers are also very promising. Moreover, new wiki-based
platforms such as Citizendium or Knol have recently emerged that
offer features distinct from Wikipedia and are of high potential
in terms of their use in NLP.
The benefits of using Web-based resources come along with new
challenges, such as the interoperability with existing resources and
the quality of the knowledge represented. As collaboratively created
resources lack editorial control, they are typically incomplete. For
the interoperability with conventional resources, the mappings have
to be investigated. The quality of collaboratively constructed
resources is questioned in many cases, and the information extraction
remains a complicated task due to the incompleteness and semi-
structuredness of the content. Therefore, the research community has
begun to develop and provide tools for accessing collaboratively
constructed resources [2,5].
The above listed challenges actually present a chance for NLP
techniques to improve the quality of Web-based semantic resources.
Researchers have therefore proposed techniques for link prediction 
or information extraction  that can be used to guide the "crowds"
to construct resources that are better suited for being used in NLP
 Christiane Fellbaum
WordNet An Electronic Lexical Database.
MIT press, 1998.
 Torsten Zesch, Christof Müller and Iryna Gurevych
Extracting Lexical Semantic Knowledge from Wikipedia and Wiktionary
Proceedings of the Conference on Language Resources and Evaluation
 Rada Mihalcea and Andras Csomai
Wikify!: Linking Documents to Encyclopedic Knowledge.
Proceedings of the Sixteenth ACM Conference on Information and
Knowledge Management, CIKM 2007.
 Daniel S. Weld et al.
Intelligence in Wikipedia.
Twenty-Third Conference on Artificial Intelligence (AAAI), 2008.
 Kotaro Nakayama et al.
Wikipedia Mining - Wikipedia as a Corpus for Knowledge Extraction.
Proceedings of the Annual Wikipedia Conference (Wikimania), 2008.
The workshop will bring together researchers from both worlds: those
using collaboratively created resources in NLP applications such as
information retrieval, named entity recognition, or keyword extraction,
and those using NLP applications for improving the resources or
extracting different types of semantic information from them. Hopefully,
this will turn into a feedback loop, where NLP techniques improved by
collaboratively constructed resources are used to improve the resources
Specific topics include but are not limited to:
* Different types of collaboratively constructed resources, such as
wiki-based platforms, Q&A sites or folksonomies;
* Using collaboratively constructed resources in NLP such as
information retrieval, text categorization, information
* Analyzing the properties of collaboratively constructed resources
related to their use in NLP;
* Interoperability of collaboratively constructed resources with
conventional semantic resources and between themselves;
* Converting unstructured information into structured lexical
semantic information; tools for mining social and collaborative
* Quality issues with respect to collaboratively constructed resources.
We also encourage the submission of short papers describing publicly
available tools for accessing or analyzing collaboratively created
resources. During the breaks, tables can be provided for demonstrations.
Rada Mihalcea, University of North Texas
Full paper submissions should follow the two-column format of ACL-IJCNLP
2009 proceedings without exceeding eight (8) pages of content plus one
extra page for references. Short paper submissions should also follow
the two-column format of ACL-IJCNLP 2009 proceedings, and should not
exceed four (4) pages, including references.
Submission will be electronic using a submission software that will be
available later at the conference website. All accepted papers will be
presented orally and published in the workshop proceedings.
Paper submission deadline (full and short): May 1, 2009
Notification of acceptance of papers: June 1, 2009
Camera-ready copy of papers due: June 7, 2009
ACL-IJCNLP 2009 Workshops: Aug 6-7, 2009
Ubiquitous Knowledge Processing Lab
Technical University of Darmstadt, Germany
Delphine Bernhard Technische Universiät Darmstadt
Paul Buitelaar DFKI Saarbruecken
Razvan Bunescu University of Texas at Austin
Pablo Castells Universidad Autónonoma de Madrid
Philipp Cimiano Karlsruhe University
Irene Cramer Dortmund University of Technology
Andras Csomai Google Inc.
Ernesto De Luca University of Magdeburg
Roxana Girju University of Illinois at Urbana-Champaign
Andreas Hotho University of Kassel
Graeme Hirst University of Toronto
Ed Hovy University of Southern California
Jussi Karlgren Swedish Institute of Computer Science
Boris Katz Massachusetts Institute of Technology
Adam Kilgarriff Lexical Computing Ltd
Chin-Yew Lin Microsoft Research
James Martin University of Colorado Boulder
Olena Medelyan University of Waikato
David Milne University of Waikato
Saif Mohammad University of Maryland
Dan Moldovan University of Texas at Dallas
Kotaro Nakayama University of Tokyo
Ani Nenkova University of Pennsylvania
Guenter Neumann DFKI Saarbruecken
Maarten de Rijke University of Amsterdam
Magnus Sahlgren Swedish Institute of Computer Science
Manfred Stede Potsdam University
Benno Stein Bauhaus University Weimar
Tonio Wandmacher University of Osnabrueck
Rene Witte Concordia University Montreal
Hans-Peter Zorn European Media Lab, Heidelberg