Digital Intuition: Applying Common Sense Using Dimensionality Reduction
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Havasi_Digital-Intuition.pdf
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966.03 KB
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Author(s)
Havasi, Catherine
Pustejovsky, James
Speer, Robert H.
Lieberman, Henry A.
Date Issued
July 2009
Journal
IEEE Intelligent Systems
Publisher
Institute of Electrical and Electronics Engineers
Citation
Havasi, C. et al. “Digital Intuition: Applying Common Sense Using Dimensionality Reduction.” Intelligent Systems, IEEE 24.4 (2009): 24-35. © 2009 Institute of Electrical and Electronics Engineers
Version
Final published version
Abstract
Understanding the world we live in requires access to a large amount of background knowledge: the commonsense knowledge that most people have and most computer systems don't. Many of the limitations of artificial intelligence today relate to the problem of acquiring and understanding common sense. The Open Mind Common Sense project began to collect common sense from volunteers on the Internet starting in 2000. The collected information is converted to a semantic network called ConceptNet. Reducing the dimensionality of ConceptNet's graph structure gives a matrix representation called AnalogySpace, which reveals large-scale patterns in the data, smoothes over noise, and predicts new knowledge. Extending this work, we have created a method that uses singular value decomposition to aid in the integration of systems or representations. This technique, called blending, can be harnessed to find and exploit correlations between different resources, enabling commonsense reasoning over a broader domain.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Massachusetts Institute of Technology. Media Laboratory
Terms of Use
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
Persistent DSpace Link
DOI of Published Version
http://dx.doi.org/10.1109/MIS.2009.72
