JACIII Vol.18 No.2 pp. 166-174
doi: 10.20965/jaciii.2014.p0166


Detection of Affectively Comparable Term Using Hierarchical Knowledge and Blog Snippets

Ryosuke Yamanishi*, Junichi Fukumoto*, and Fumito Masui**

*Department of Media Technology, Ritsumeikan University, 1-1-1 Nojihigashi, Kusatsu, Shiga 525-8577, Japan

**Department of Computer Science, Kitami Institute of Technology, 165 Kouen-cho, Kitami, Hokkaido 090-8577, Japan

September 18, 2013
February 3, 2014
March 20, 2014
natural language processing, affective computing, knowledge discovery, web intelligence

This paper describes a method for detecting affectively comparable terms. Comparable terms are often handled as sample objects instance in order to enrich linguistic expression, and using such terms explains and describes descriptions well. Coordinate terms in hierarchical knowledge are potentially comparable terms. Hierarchical coordinate terms are however sometimes affectively inappropriate as comparable term, because hierarchical knowledge is constructed by using only semantics without affections. We obtained the affections of terms obtained from blog and innovated them into hierarchical knowledge in order to detect affectively comparable terms. We conduct experiments to detect affectively comparable terms and discuss results, from which, we confirmed that affectively comparable terms could be detected by our proposed method. We deem detected affectively comparable terms to be applicable to creating artificial intelligence realizing intuitive interaction.

Cite this article as:
R. Yamanishi, J. Fukumoto, and F. Masui, “Detection of Affectively Comparable Term Using Hierarchical Knowledge and Blog Snippets,” J. Adv. Comput. Intell. Intell. Inform., Vol.18, No.2, pp. 166-174, 2014.
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Last updated on Nov. 16, 2018