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When Jul 11, 2009 - Jul 13, 2009
Where Pasadena, California, USA
Submission Deadline Mar 6, 2009
Notification Due Apr 17, 2009
Final Version Due May 8, 2009
Categories    artificial intelligence

Call For Papers

The performance of an Artificial Intelligence system often depends
on the amount of world knowledge available to it. During the last
decade, the AI community has witnessed the emergence of a number
of highly structured knowledge repositories whose collaborative
nature has led to a dramatic increase in the amount of world
knowledge that can now be exploited in AI applications. Arguably,
the best-known repository of user-contributed knowledge is
Wikipedia. Since its inception less than eight years ago, it has
become one of the largest and fastest growing online sources of
encyclopedic knowledge. One of the reasons why Wikipedia is appealing
to contributors and users alike is the richness of its embedded
structural information: articles are hyperlinked to each other and
connected to categories from an ever expanding taxonomy; pervasive
language phenomena such as synonymy and polysemy are addressed through
redirection and disambiguation pages; entities of the same type are
described in a consistent format using infoboxes; related articles are
grouped together in series templates.

Many more repositories of user-contributed knowledge exist besides
Wikipedia. Collaborative tagging in Delicious and community-driven
question answering in Yahoo! Answers and Wiki Answers are only a few
examples of knowledge sources that, like Wikipedia, can become a
valuable asset for AI researchers. Furthermore, AI methods have
the potential to improve these resources, as demonstrated recently
by research on personalized tag recommendations, or on matching user
questions with previously answered questions. Consequently,
we believe the time is ripe for a dedicated event focused on the
synergy between repositories of user-contributed knowledge and
the research in Artificial Intelligence.

The workshop is intended to be highly interdisciplinary. We encourage
participation of researchers from different perspectives, including
(but not limited to) machine learning, computational linguistics,
information retrieval, information extraction, question answering,
knowledge representation, and others. We also encourage participation
of researchers from other areas who might benefit from the use of
large bodies of machine-readable knowledge.


Topics covered by this workshop include, but are not limited to:

* Using user-contributed knowledge as a source of training data for
AI tasks
* Automatic methods for improving the quality of user contributions
* Routing tasks to people who have the expertise to perform them
* Integrating Wikipedia with existing ontologies (e.g. WordNet, CYC,
* Extracting annotated data from user contributions
* Enriching user contributions with new types of structural
* User-contributed knowledge and the Semantic Web / Web 2.0
* Automatic extraction and use of cross-lingual information
* Computerized use of satellite Wiki projects such as Wiktionary,
Wikibooks or Wikispecies


The workshop is planned as a one-day event (full day), which will
consist of an invited talk, paper and demo presentations, and
a discussion panel.


We invite the submission of regular full papers (up to 6 pages),
short papers reporting on late-breaking results (up to 3 pages), and
descriptions of system demonstrations (up to 1 page) using the IJCAI
style. Submissions that have been accepted for publication elsewhere
or are under review for another conference must clearly state so on
the front page of the paper.

Submissions should be properly anonymized to make them suitable for
double-blind review. The papers will be submitted through the following
EasyChair site:


Deadline for long paper submission March 6th, 2009
Deadline for short papers and demos March 27th, 2009
Notification of acceptance April 17th, 2009
Camera-ready papers due at IJCAI May 8th, 2009
Workshop date between July 11 and July 13, 2009
(not yet finalized)


Razvan Bunescu, Ohio University (
Evgeniy Gabrilovich (
Rada Mihalcea, University of North Texas (
Vivi Nastase, EML Research (


For additional information about the workshop, please visit the workshop
Web site at

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