Title: A visual framework to understand similarity queries and explore data in Metric Access Methods

Authors: Marcos R. Vieira, Fabio J.T. Chino, Caetano Traina Jr., Agma J.M. Traina

Addresses: Computer Science Department, University of Sao Paulo at Sao Carlos, Av. Trabalhador Sao-carlense, 400, Sao Carlos 13566-590, Brazil. ' Computer Science Department, University of Sao Paulo at Sao Carlos, Av. Trabalhador Sao-carlense, 400, Sao Carlos 13566-590, Brazil. ' Computer Science Department, University of Sao Paulo at Sao Carlos, Av. Trabalhador Sao-carlense, 400, Sao Carlos 13566-590, Brazil. ' Computer Science Department, University of Sao Paulo at Sao Carlos, Av. Trabalhador Sao-carlense, 400, Sao Carlos 13566-590, Brazil

Abstract: This paper presents the MAMView framework to help users and developers in understanding the data organisation in Metric Access Methods (MAM). Users and developers can explore and share dynamic and interactively 2- or 3-dimensional representations of a MAM. Such representations can be the steps of a similarity query or the insertion of an object, or the data organisation in a MAM. MAMView was developed as a practical tool that has been successfully applied in studying existing MAM, helping novice users to better understand the behaviour and properties of such structures, as well developers to verify and drill-down their new proposed structures.

Keywords: data visualisation; visual exploration; MAMView; metric access methods; similarity queries; visual frameworks; 2-dimensional representations; 3-dimensional representations; two-dimensional representations; three-dimensional representations; object insertions; data organisation; novice users; proposed structures; structural properties; structural behaviour; Brazil; multimedia; XML streams; querying; extensible markup language; data mining; business intelligence.

DOI: 10.1504/IJBIDM.2010.036125

International Journal of Business Intelligence and Data Mining, 2010 Vol.5 No.4, pp.370 - 397

Published online: 22 Oct 2010 *

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