Exploratory hot spot profile analysis using interactive visual drill-down self-organizing maps

Graham J. Williams; Peter Christen

doi:10.1007/978-3-540-68125-0_48

Exploratory hot spot profile analysis using interactive visual drill-down self-organizing maps

Denny, Graham J. Williams, Peter Christen

Department of Computer Science

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

4 Citations (Scopus)

Abstract

Real-life datasets often contain small clusters of unusual sub-populations. These clusters, or 'hot spots', are usually sparse and of special interest to an analyst. We present a methodology for identifying hot spots and ranking attributes that distinguish them interactively, using visual drill-down Self-Organizing Maps. The methodology is particularly useful for understanding hot spots in high dimensional datasets. Our approach is demonstrated using a large real life taxation dataset.

Original language	English
Title of host publication	Advances in Knowledge Discovery and Data Mining - 12th Pacific-Asia Conference, PAKDD 2008, Proceedings
Pages	536-543
Number of pages	8
DOIs	https://doi.org/10.1007/978-3-540-68125-0_48
Publication status	Published - 2008
Event	12th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2008 - Osaka, Japan Duration: 20 May 2008 → 23 May 2008

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	5012 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	12th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2008
Country/Territory	Japan
City	Osaka
Period	20/05/08 → 23/05/08

Keywords

Attribute ranking
Hot spot analysis
Imbalanced data
Interactive drill-down visualization
Self-organizing maps

Access to Document

10.1007/978-3-540-68125-0_48

Cite this

Denny, Williams, G. J., & Christen, P. (2008). Exploratory hot spot profile analysis using interactive visual drill-down self-organizing maps. In Advances in Knowledge Discovery and Data Mining - 12th Pacific-Asia Conference, PAKDD 2008, Proceedings (pp. 536-543). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5012 LNAI). https://doi.org/10.1007/978-3-540-68125-0_48

Denny ; Williams, Graham J. ; Christen, Peter. / Exploratory hot spot profile analysis using interactive visual drill-down self-organizing maps. Advances in Knowledge Discovery and Data Mining - 12th Pacific-Asia Conference, PAKDD 2008, Proceedings. 2008. pp. 536-543 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Exploratory hot spot profile analysis using interactive visual drill-down self-organizing maps",

abstract = "Real-life datasets often contain small clusters of unusual sub-populations. These clusters, or 'hot spots', are usually sparse and of special interest to an analyst. We present a methodology for identifying hot spots and ranking attributes that distinguish them interactively, using visual drill-down Self-Organizing Maps. The methodology is particularly useful for understanding hot spots in high dimensional datasets. Our approach is demonstrated using a large real life taxation dataset.",

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Denny, Williams, GJ & Christen, P 2008, Exploratory hot spot profile analysis using interactive visual drill-down self-organizing maps. in Advances in Knowledge Discovery and Data Mining - 12th Pacific-Asia Conference, PAKDD 2008, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 5012 LNAI, pp. 536-543, 12th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2008, Osaka, Japan, 20/05/08. https://doi.org/10.1007/978-3-540-68125-0_48

Exploratory hot spot profile analysis using interactive visual drill-down self-organizing maps. / Denny; Williams, Graham J.; Christen, Peter.
Advances in Knowledge Discovery and Data Mining - 12th Pacific-Asia Conference, PAKDD 2008, Proceedings. 2008. p. 536-543 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5012 LNAI).

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

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Denny, Williams GJ, Christen P. Exploratory hot spot profile analysis using interactive visual drill-down self-organizing maps. In Advances in Knowledge Discovery and Data Mining - 12th Pacific-Asia Conference, PAKDD 2008, Proceedings. 2008. p. 536-543. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-540-68125-0_48

Exploratory hot spot profile analysis using interactive visual drill-down self-organizing maps

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