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Digital Intuition: Applying Common Sense Using Dimensionality Reduction
July/August 2009 (vol. 24 no. 4)
pp. 24-35
ASCII Text
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Catherine Havasi, Robert Speer, James Pustejovsky, Henry Lieberman, "Digital Intuition: Applying Common Sense Using Dimensionality Reduction," IEEE Intelligent Systems, vol. 24, no. 4, pp. 24-35, July/August, 2009.
 
 
BibTex
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@article{ 10.1109/MIS.2009.72,
author = {Catherine Havasi and Robert Speer and James Pustejovsky and Henry Lieberman},
title = {Digital Intuition: Applying Common Sense Using Dimensionality Reduction},
journal ={IEEE Intelligent Systems},
volume = {24},
number = {4},
issn = {1541-1672},
year = {2009},
pages = {24-35},
doi = {http://doi.ieeecomputersociety.org/10.1109/MIS.2009.72},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - MGZN
JO - IEEE Intelligent Systems
TI - Digital Intuition: Applying Common Sense Using Dimensionality Reduction
IS - 4
SN - 1541-1672
SP24
EP35
EPD - 24-35
A1 - Catherine Havasi,
A1 - Robert Speer,
A1 - James Pustejovsky,
A1 - Henry Lieberman,
PY - 2009
KW - semantic networks
KW - analogies
KW - knowledge acquisition
KW - natural language processing
KW - knowledge base management
VL - 24
JA - IEEE Intelligent Systems
ER -
 
Catherine Havasi, Massachusetts Institute of Technology
Robert Speer, Massachusetts Institute of Technology
James Pustejovsky, Brandeis University
Henry Lieberman, Massachusetts Institute of Technology
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.

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Index Terms:
semantic networks, analogies, knowledge acquisition, natural language processing, knowledge base management
Citation:
Catherine Havasi, Robert Speer, James Pustejovsky, Henry Lieberman, "Digital Intuition: Applying Common Sense Using Dimensionality Reduction," IEEE Intelligent Systems, vol. 24, no. 4, pp. 24-35, July-Aug. 2009, doi:10.1109/MIS.2009.72
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