Symbolic hierarchical clustering for visual analogue scale data

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

doi:10.1007/978-3-642-22194-1_79

Symbolic hierarchical clustering for visual analogue scale data

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

Faculty of Environment and Information Studies

Research output: Chapter in Book/Report/Conference proceeding › Conference 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 language	English
Title of host publication	Intelligent Decision Technologies - Proceedings of the 3rd International Conference on Intelligent Decision Technologies, IDT'2011
Pages	799-805
Number of pages	7
DOIs	https://doi.org/10.1007/978-3-642-22194-1_79
Publication status	Published - 2011 Dec 1
Event	3rd International Conference on Intelligent Decision Technologies, IDT'2011 - Piraeus, Greece Duration: 2011 Jul 20 → 2011 Jul 22

Publication series

Name	Smart Innovation, Systems and Technologies
Volume	10 SIST
ISSN (Print)	2190-3018
ISSN (Electronic)	2190-3026

Other

Other	3rd International Conference on Intelligent Decision Technologies, IDT'2011
Country/Territory	Greece
City	Piraeus
Period	11/7/20 → 11/7/22

Keywords

Distribution-valued data
Visual analogue scale

ASJC Scopus subject areas

Decision Sciences(all)
Computer Science(all)

Access to Document

10.1007/978-3-642-22194-1_79

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

Symbolic hierarchical clustering for visual analogue scale data. / Katayama, Kotoe; Yamaguchi, Rui; Imoto, Seiya et al.
Intelligent Decision Technologies - Proceedings of the 3rd International Conference on Intelligent Decision Technologies, IDT'2011. 2011. p. 799-805 (Smart Innovation, Systems and Technologies; Vol. 10 SIST).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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. Smart Innovation, Systems and Technologies, vol. 10 SIST, pp. 799-805, 3rd International Conference on Intelligent Decision Technologies, IDT'2011, Piraeus, Greece, 11/7/20. https://doi.org/10.1007/978-3-642-22194-1_79

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

@inproceedings{4338a0d712424cbd924cb7bba4522fee,

title = "Symbolic hierarchical clustering for visual analogue scale data",

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.",

keywords = "Distribution-valued data, Visual analogue scale",

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

year = "2011",

month = dec,

day = "1",

doi = "10.1007/978-3-642-22194-1_79",

language = "English",

isbn = "9783642221934",

series = "Smart Innovation, Systems and Technologies",

pages = "799--805",

booktitle = "Intelligent Decision Technologies - Proceedings of the 3rd International Conference on Intelligent Decision Technologies, IDT'2011",

note = "3rd International Conference on Intelligent Decision Technologies, IDT'2011 ; Conference date: 20-07-2011 Through 22-07-2011",

}

TY - GEN

T1 - Symbolic hierarchical clustering for visual analogue scale data

AU - Katayama, Kotoe

AU - Yamaguchi, Rui

AU - Imoto, Seiya

AU - Tokunaga, Hideaki

AU - Imazu, Yoshihiro

AU - Matsuura, Keiko

AU - Watanabe, Kenji

AU - Miyano, Satoru

PY - 2011/12/1

Y1 - 2011/12/1

N2 - 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.

AB - 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.

KW - Distribution-valued data

KW - Visual analogue scale

UR - http://www.scopus.com/inward/record.url?scp=84866309828&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84866309828&partnerID=8YFLogxK

U2 - 10.1007/978-3-642-22194-1_79

DO - 10.1007/978-3-642-22194-1_79

M3 - Conference contribution

AN - SCOPUS:84866309828

SN - 9783642221934

T3 - Smart Innovation, Systems and Technologies

SP - 799

EP - 805

BT - Intelligent Decision Technologies - Proceedings of the 3rd International Conference on Intelligent Decision Technologies, IDT'2011

T2 - 3rd International Conference on Intelligent Decision Technologies, IDT'2011

Y2 - 20 July 2011 through 22 July 2011

ER -

Symbolic hierarchical clustering for visual analogue scale data

Abstract

Publication series

Other

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this