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USER-CONTRIBUTED KNOWLEDGE AND ARTIFICIAL INTELLIGENCE: AN EVOLVING SYNERGY
IJCAI 2009 Workshop, July 13, 2009, Pasadena, CA
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[edit] Overview
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.
[edit] Topics
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 well
- Integrating Wikipedia with existing ontologies (e.g. WordNet, CYC, ODP)
- Extracting annotated data from user contributions
- Enriching user contributions with new types of structural information
- 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
[edit] Workshop Format
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.
[edit] Organizing Committee
- Razvan Bunescu, Ohio University
- Evgeniy Gabrilovich, Yahoo! Research
- Rada Mihalcea, University of North Texas
- Vivi Nastase, EML Research