Visualization of topology representing networks

Agnes Vathy-Fogarassy, Agnes Werner-Stark, Balazs Gal, Janos Abonyi

Research output: Conference contribution

7 Citations (Scopus)

Abstract

As data analysis tasks often have to face the analysis of huge and complex data sets there is a need for new algorithms that combine vector quantization and mapping methods to visualize the hidden data structure in a low-dimensional vector space. In this paper a new class of algorithms is defined. Topology representing networks are applied to quantify and disclose the data structure and different nonlinear mapping algorithms for the low-dimensional visualization are applied for the mapping of the quantized data. To evaluate the main properties of the resulted topology representing network based mapping methods a detailed analysis based on the wine benchmark example is given.

Original languageEnglish
Title of host publicationIntelligent Data Engineering and Automated Learning - IDEAL 2007 - 8th International Conference, Proceedings
Pages557-566
Number of pages10
Publication statusPublished - dec. 1 2007
Event8th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2007 - Birmingham, United Kingdom
Duration: dec. 16 2007dec. 19 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4881 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other8th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2007
CountryUnited Kingdom
CityBirmingham
Period12/16/0712/19/07

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ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Vathy-Fogarassy, A., Werner-Stark, A., Gal, B., & Abonyi, J. (2007). Visualization of topology representing networks. In Intelligent Data Engineering and Automated Learning - IDEAL 2007 - 8th International Conference, Proceedings (pp. 557-566). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4881 LNCS).