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Another role of Wikipedians: Guiding machines to do intelligence tasks

Author KaKan Lo (The Chinese University of Hong Kong)
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About the author
Ka Kan Lo
Ka Kan Lo

Ka Kan Lo: A research student studying Master degree (Will graduate in 2007) at Chinese University of Hong Kong, working on Natural Language Processing, Artificial Intelligence, developing new methods in utilizing the Wikipedia and Web contents for machine intelligence tasks such as Machine Reading, Natural Language Processing, Automatic Question Answering and Information Extraction and Retrieval. Previously, he got his undergraduate degree in 2004, major in computer engineering at the same University.

Previously, Mr. Lo has given talks in a number of conference and workshops, including the talk at AAAI symposium, a gathering of premier AI researchers. Details can be found at AAAI symposium 2007 - Machine Reading , AAAI - Association for the Advancement of Artificial Intelligence. In addition, he also pioneers works in integrating the web and wikipedia information for legal data retrieval where details can be found at: ICAIL 2007 - DESI workshop . He also worked on a new breed of question answering system which utilizes the structure of Wikipedia content for QA - TREC, 2006.

Mr. Lo is currently finalizing a Machine Reading prototype which extends the web and wikipedia information into actionable Semantic Web, information portfolio and Machine Reading applications.

Abstract
This presentation proposes and demonstrates that the Wikipedia can be used as a source to share knowledge with not only people, but also machines. By utilizing the structures, texts and the links within Wikipedia, the possibilities of using these concept-linking constructs to help computers to acquire concepts and knowledge are explored and presented. This would be exciting in the Wikimedia communities in which Wikipedians can share and distribute knowledge to new groups of ?audiences?. This new usage of Wikipedia would suggest an even wider spread of the Wikimedia projects to larger communities in a wider context.
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