Quantitative common sense estimation system and its application to automatic membership function generation

Yuta Igawa, Masafumi Hagiwara

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Systems capable of autonomous thinking and estimation have been required to cope with unknown situations. One of the important issues is knowledge, especially common sense, acquisition. This paper proposes new quantitative common sense estimation methods and applies them to an automatic membership function generation system. The proposed system estimates threshold values corresponding to large and small for various kinds of object-attribute sets to make membership functions. Here, the proposed system tries to relate each object and the impression. Two methods are proposed in this paper. The method-1 obtains data from top 1,000 snippets by Web search and estimates the global and local tendencies by clustering. The method-2 uses the number of hits in Web search together with parts of the results obtained by the method-1. In addition, several techniques are devised to eliminate unnecessary information from the retrieved Web pages. We carried out evaluation experiments: the effectiveness of the proposed methods has been shown and effectiveness of the combined method is indicated.

Original languageEnglish
Title of host publication6th International Conference on Soft Computing and Intelligent Systems, and 13th International Symposium on Advanced Intelligence Systems, SCIS/ISIS 2012
Pages1335-1340
Number of pages6
DOIs
Publication statusPublished - 2012
Event2012 Joint 6th International Conference on Soft Computing and Intelligent Systems, SCIS 2012 and 13th International Symposium on Advanced Intelligence Systems, ISIS 2012 - Kobe, Japan
Duration: 2012 Nov 202012 Nov 24

Other

Other2012 Joint 6th International Conference on Soft Computing and Intelligent Systems, SCIS 2012 and 13th International Symposium on Advanced Intelligence Systems, ISIS 2012
CountryJapan
CityKobe
Period12/11/2012/11/24

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Membership functions
Websites
Experiments

Keywords

  • knowledge acquisition
  • membership function
  • quantitative common sense
  • Web

ASJC Scopus subject areas

  • Artificial Intelligence
  • Software

Cite this

Igawa, Y., & Hagiwara, M. (2012). Quantitative common sense estimation system and its application to automatic membership function generation. In 6th International Conference on Soft Computing and Intelligent Systems, and 13th International Symposium on Advanced Intelligence Systems, SCIS/ISIS 2012 (pp. 1335-1340). [6505176] https://doi.org/10.1109/SCIS-ISIS.2012.6505176

Quantitative common sense estimation system and its application to automatic membership function generation. / Igawa, Yuta; Hagiwara, Masafumi.

6th International Conference on Soft Computing and Intelligent Systems, and 13th International Symposium on Advanced Intelligence Systems, SCIS/ISIS 2012. 2012. p. 1335-1340 6505176.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Igawa, Y & Hagiwara, M 2012, Quantitative common sense estimation system and its application to automatic membership function generation. in 6th International Conference on Soft Computing and Intelligent Systems, and 13th International Symposium on Advanced Intelligence Systems, SCIS/ISIS 2012., 6505176, pp. 1335-1340, 2012 Joint 6th International Conference on Soft Computing and Intelligent Systems, SCIS 2012 and 13th International Symposium on Advanced Intelligence Systems, ISIS 2012, Kobe, Japan, 12/11/20. https://doi.org/10.1109/SCIS-ISIS.2012.6505176
Igawa Y, Hagiwara M. Quantitative common sense estimation system and its application to automatic membership function generation. In 6th International Conference on Soft Computing and Intelligent Systems, and 13th International Symposium on Advanced Intelligence Systems, SCIS/ISIS 2012. 2012. p. 1335-1340. 6505176 https://doi.org/10.1109/SCIS-ISIS.2012.6505176
Igawa, Yuta ; Hagiwara, Masafumi. / Quantitative common sense estimation system and its application to automatic membership function generation. 6th International Conference on Soft Computing and Intelligent Systems, and 13th International Symposium on Advanced Intelligence Systems, SCIS/ISIS 2012. 2012. pp. 1335-1340
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