An interface for targeted collection of common sense knowledge using a mixture model

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An interface for targeted collection of common sense knowledge using a mixture model

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International Conference on Intelligent User Interfaces archive
Proceedings of the 13th international conference on Intelligent user interfaces table of contents

Sanibel Island, Florida, USA

SESSION: Information & knowledge management table of contents

Pages 137-146

Year of Publication: 2009

ISBN:978-1-60558-168-2

Authors

Robert Speer	MIT CSAIL, Cambridge, MA, USA
Jayant Krishnamurthy	MIT CSAIL, Cambridge, MA, USA
Catherine Havasi	Brandeis University, Waltham, MA, USA
Dustin Smith	MIT Media Lab, Cambridge, MA, USA
Henry Lieberman	MIT Media Lab, Cambridge, MA, USA
Kenneth Arnold	MIT Media Lab, Cambridge, MA, USA

Sponsors

SIGCHI: ACM Special Interest Group on Computer-Human Interaction
ACM: Association for Computing Machinery
SIGART: ACM Special Interest Group on Artificial Intelligence

Publisher

ACM New York, NY, USA

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ABSTRACT

We present a game-based interface for acquiring common sense knowledge. In addition to being interactive and entertaining, our interface guides the knowledge acquisition process to learn about the most salient characteristics of a particular concept. We use statistical classification methods to discover the most informative characteristics in the Open Mind Common Sense knowledge base, and use these characteristics to play a game of 20 Questions with the user. Our interface also allows users to enter knowledge more quickly than a more traditional knowledge-acquisition interface. An evaluation showed that users enjoyed the game and that it increased the speed of knowledge acquisition.

REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

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