Relative density estimation using Self-Organizing Maps

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Organizations need knowledge of change, such as changes in customer purchasing behaviour, to adapt business strategies in response to changing circumstances. To understand what has changed, analysts have to be able to relate new knowledge acquired from a newer dataset to that acquired from an earlier dataset. This paper presents a method to detect changes in clustering structure over time. Discovering clustering changes can also be applied in other contexts, such as fraud detection and customer attrition analysis. The key contribution of this paper is the enhancement of the measurement of relative density using SOM. This measurement is used in the visualization method called Relative Density Self-Organizing Map (ReDSOM) to compare clustering structures from two snapshot datasets. This visualization provide means for analysts to visually identify and analyze various changes in the clustering structure, such as emerging clusters, disappearing clusters, splitting clusters, and merging clusters. These contributions have been evaluated using synthetic datasets, as well as real-life datasets from the World Bank. Experiments showed that the new measure is more sensitive in detecting changes in density.

Original languageEnglish
Title of host publicationProceedings - ICACSIS 2014
Subtitle of host publication2014 International Conference on Advanced Computer Science and Information Systems
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages233-238
Number of pages6
ISBN (Electronic)9781479980758
DOIs
Publication statusPublished - 23 Mar 2014
Event2014 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2014 - Jakarta, Indonesia
Duration: 18 Oct 201419 Oct 2014

Publication series

NameProceedings - ICACSIS 2014: 2014 International Conference on Advanced Computer Science and Information Systems

Conference

Conference2014 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2014
CountryIndonesia
CityJakarta
Period18/10/1419/10/14

Keywords

  • self-organizing map
  • temporal clustering

Fingerprint Dive into the research topics of 'Relative density estimation using Self-Organizing Maps'. Together they form a unique fingerprint.

Cite this