Symbolic hierarchical clustering for visual analogue scale data

Kotoe Katayama, Rui Yamaguchi, Seiya Imoto, Hideaki Tokunaga, Yoshihiro Imazu, Keiko Matsuura, Kenji Watanabe, Satoru Miyano

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

1 Citation (Scopus)

Abstract

We propose a hierarchical clustering in the framework of Symbolic Data Analysis(SDA). SDA was proposed by Diday at the end of the 1980s and is a new approach for analysing huge and complex data. In SDA, an observation is described by not only numerical values but also "higher-level units"; sets, intervals, distributions, etc. Most SDA works have dealt with only intervals as the descriptions. In this paper, we define "pain distribution" as new type data in SDA and propose a hierarchical clustering for this new type data.

Original languageEnglish
Title of host publicationIntelligent Decision Technologies - Proceedings of the 3rd International Conference on Intelligent Decision Technologies, IDT'2011
Pages799-805
Number of pages7
DOIs
Publication statusPublished - 2011 Dec 1
Event3rd International Conference on Intelligent Decision Technologies, IDT'2011 - Piraeus, Greece
Duration: 2011 Jul 202011 Jul 22

Publication series

NameSmart Innovation, Systems and Technologies
Volume10 SIST
ISSN (Print)2190-3018
ISSN (Electronic)2190-3026

Other

Other3rd International Conference on Intelligent Decision Technologies, IDT'2011
CountryGreece
CityPiraeus
Period11/7/2011/7/22

Keywords

  • Distribution-valued data
  • Visual analogue scale

ASJC Scopus subject areas

  • Decision Sciences(all)
  • Computer Science(all)

Cite this

Katayama, K., Yamaguchi, R., Imoto, S., Tokunaga, H., Imazu, Y., Matsuura, K., Watanabe, K., & Miyano, S. (2011). Symbolic hierarchical clustering for visual analogue scale data. In Intelligent Decision Technologies - Proceedings of the 3rd International Conference on Intelligent Decision Technologies, IDT'2011 (pp. 799-805). (Smart Innovation, Systems and Technologies; Vol. 10 SIST). https://doi.org/10.1007/978-3-642-22194-1_79