Article

JRV: an interactive tool for data mining visualization

Authors:

Upender ManneAuthors Info & Claims

ACMSE '04: Proceedings of the 42nd annual ACM Southeast Conference

Pages 442 - 447

https://doi.org/10.1145/986537.986649

Published: 02 April 2004 Publication History

Abstract

In this paper, we demonstrate JRV, a new data mining visualization tool for the knowledge discovery process where the user and computer can cooperate with each other. First, the computer can be instructed by the user interactively to compute values of several evaluation functions. Then, the user can take advantage of domain knowledge and assess the intermediate results obtained. Furthermore, by providing effective and efficient data visualization, the pattern recognition capacities of users can be greatly improved. Instead of being limited to two attributes at a given time in independence diagrams, this novel tool will allow simultaneous analyses of multiple attribute dependencies using four different drawing panels. Also, by utilizing the existing techniques of data visualization, we design a general model which can handle both categorical and numerical attributes in an intuitive way. With this model, we can identify patterns of interests efficiently. Through actual examples, we show that it might help users to find novel attribute relationships. This work is supported by NIH grant #RO1-CA98932-01.

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Cited By

Haghighi PGillick BKrishnaswamy SGaber MZaslavsky A(2008)Situation-Aware adaptive visualization for sensory data stream miningProceedings of the Second international conference on Knowledge Discovery from Sensor Data10.1007/978-3-642-12519-5_3(43-58)Online publication date: 24-Aug-2008
https://dl.acm.org/doi/10.1007/978-3-642-12519-5_3

Index Terms

JRV: an interactive tool for data mining visualization

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Published In

cover image ACM Conferences

ACMSE '04: Proceedings of the 42nd annual ACM Southeast Conference

April 2004

485 pages

ISBN:1581138709

DOI:10.1145/986537

General Chair:
Seong-Moo Yoo
The University of Alabama in Huntsville, Huntsville, AL
,
Program Chair:
Letha Hughes Etzkorn
The University of Alabama in Huntsville, Huntsville, AL

Copyright © 2004 ACM.

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Published: 02 April 2004

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ACM SE04: ACM Southeast Regional Conference 2004

April 2 - 3, 2004

Alabama, Huntsville

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Overall Acceptance Rate 502 of 1,023 submissions, 49%

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Cited By

Haghighi PGillick BKrishnaswamy SGaber MZaslavsky A(2008)Situation-Aware adaptive visualization for sensory data stream miningProceedings of the Second international conference on Knowledge Discovery from Sensor Data10.1007/978-3-642-12519-5_3(43-58)Online publication date: 24-Aug-2008
https://dl.acm.org/doi/10.1007/978-3-642-12519-5_3

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