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
Affiliations:
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
Venue:
International Journal of Business Intelligence and Data Mining
Year:
2010

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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.