Visualization of cluster changes by comparing self-organizing maps

David McG Squire

doi:10.1007/11430919_48

Visualization of cluster changes by comparing self-organizing maps

Denny, David McG Squire

Department of Computer Science

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

17 Citations (Scopus)

Abstract

In this paper we introduce Self-Organizing Map-based techniques that can reveal structural cluster changes in two related data sets from different time periods in a way that can explain the new result in relation to the previous one. These techniques are demonstrated using a real-world data set from the World Development Indicators database maintained by the World Bank. The results verify that the methods are capable of revealing changes in cluster strucure and membership, corresponding to known changes in economic fortunes of countries.

Original language	English
Title of host publication	Advances in Knowledge Discovery and Data Mining - 9th Pacific-Asia Conference, PAKDD 2005, Proceedings
Publisher	Springer Verlag
Pages	410-419
Number of pages	10
ISBN (Print)	3540260765, 9783540260769
DOIs	https://doi.org/10.1007/11430919_48
Publication status	Published - 2005
Event	9th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2005 - Hanoi, Viet Nam Duration: 18 May 2005 → 20 May 2005

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	3518 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	9th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2005
Country/Territory	Viet Nam
City	Hanoi
Period	18/05/05 → 20/05/05

Access to Document

10.1007/11430919_48

Cite this

Denny, & Squire, D. M. (2005). Visualization of cluster changes by comparing self-organizing maps. In Advances in Knowledge Discovery and Data Mining - 9th Pacific-Asia Conference, PAKDD 2005, Proceedings (pp. 410-419). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3518 LNAI). Springer Verlag. https://doi.org/10.1007/11430919_48

Denny ; Squire, David McG. / Visualization of cluster changes by comparing self-organizing maps. Advances in Knowledge Discovery and Data Mining - 9th Pacific-Asia Conference, PAKDD 2005, Proceedings. Springer Verlag, 2005. pp. 410-419 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "In this paper we introduce Self-Organizing Map-based techniques that can reveal structural cluster changes in two related data sets from different time periods in a way that can explain the new result in relation to the previous one. These techniques are demonstrated using a real-world data set from the World Development Indicators database maintained by the World Bank. The results verify that the methods are capable of revealing changes in cluster strucure and membership, corresponding to known changes in economic fortunes of countries.",

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Denny & Squire, DM 2005, Visualization of cluster changes by comparing self-organizing maps. in Advances in Knowledge Discovery and Data Mining - 9th Pacific-Asia Conference, PAKDD 2005, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 3518 LNAI, Springer Verlag, pp. 410-419, 9th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2005, Hanoi, Viet Nam, 18/05/05. https://doi.org/10.1007/11430919_48

Visualization of cluster changes by comparing self-organizing maps. / Denny; Squire, David McG.
Advances in Knowledge Discovery and Data Mining - 9th Pacific-Asia Conference, PAKDD 2005, Proceedings. Springer Verlag, 2005. p. 410-419 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3518 LNAI).

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

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AB - In this paper we introduce Self-Organizing Map-based techniques that can reveal structural cluster changes in two related data sets from different time periods in a way that can explain the new result in relation to the previous one. These techniques are demonstrated using a real-world data set from the World Development Indicators database maintained by the World Bank. The results verify that the methods are capable of revealing changes in cluster strucure and membership, corresponding to known changes in economic fortunes of countries.

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Denny, Squire DM. Visualization of cluster changes by comparing self-organizing maps. In Advances in Knowledge Discovery and Data Mining - 9th Pacific-Asia Conference, PAKDD 2005, Proceedings. Springer Verlag. 2005. p. 410-419. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/11430919_48

Visualization of cluster changes by comparing self-organizing maps

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