Investigating the quality of different Self-Organizing Map topologies for complex data

Huajie Wu*, Tom Gedeon, Dingyun Zhu

*Corresponding author for this work

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

    Abstract

    Self-Organizing Maps (SOM) are useful tools for visualizing high dimensional data. However, conventional SOM suffer from the border effect. Therefore, Spherical Self-Organizing Maps (SSOM) have been developed to remove such negative effects. In this paper, we extend the topology of SSOM by reconstructing the neighbors to propose the concept of Concentric Spherical Self-Organizing Maps (CSSOM). The major improvement of CSSOM is that it allows using an arbitrary number of spheres and such a topology could be applied in analyzing sequential and time series data. We conducted experiments using these SOM topologies on several datasets. The display schemas and several measures for the quality of SOMs are discussed with the experimental results. The comparison of the results indicates that the quality of SOM is improved through using specified CSSOM depending on the characteristics of the dataset.

    Original languageEnglish
    Title of host publicationLINDI 2012 - 4th IEEE International Symposium on Logistics and Industrial Informatics, Proceedings
    Pages221-226
    Number of pages6
    DOIs
    Publication statusPublished - 2012
    Event4th IEEE International Symposium on Logistics and Industrial Informatics, LINDI 2012 - Smolenice, Slovakia
    Duration: 5 Sept 20127 Sept 2012

    Publication series

    NameLINDI 2012 - 4th IEEE International Symposium on Logistics and Industrial Informatics, Proceedings

    Conference

    Conference4th IEEE International Symposium on Logistics and Industrial Informatics, LINDI 2012
    Country/TerritorySlovakia
    CitySmolenice
    Period5/09/127/09/12

    Fingerprint

    Dive into the research topics of 'Investigating the quality of different Self-Organizing Map topologies for complex data'. Together they form a unique fingerprint.

    Cite this