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Article

A Visual Data Mining Framework for Convenient Identification of Useful Knowledge

Authors:

Thomas M. Tirpak,

Weimin XiaoAuthors Info & Claims

ICDM '05: Proceedings of the Fifth IEEE International Conference on Data Mining

Pages 530 - 537

https://doi.org/10.1109/ICDM.2005.16

Published: 27 November 2005 Publication History

Abstract

Data mining algorithms usually generate a large number of rules, which may not always be useful to human users. In this project, we propose a novel visual data-mining framework, called Opportunity Map, to identify useful and actionable knowledge quickly and easily from the discovered rules. The framework is inspired by the House of Quality from Quality Function Deployment (QFD) in Quality Engineering. It associates discovered rules, related summarized data and data distributions with the application objective using an interactive matrix. Combined with drill down visualization, integrated visualization of data distribution bars and rules, visualization of trend behaviors, and comparative analysis, the Opportunity Map allows users to analyze rules and data at different levels of detail and quickly identify the actionable knowledge and opportunities. The proposed framework represents a systematic and flexible approach to rule analysis. Applications of the system to large-scale data sets from our industrial partner have yielded promising results.

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Cited By

Rohde DHuang RCorcoran JWhite G(2013)Visual Data Mining Methods for Kernel Smoothed Estimates of Cox ProcessesRevised Selected Papers of PAKDD 2013 International Workshops on Trends and Applications in Knowledge Discovery and Data Mining - Volume 786710.1007/978-3-642-40319-4_8(83-94)Online publication date: 14-Apr-2013
https://dl.acm.org/doi/10.1007/978-3-642-40319-4_8
Mohammed NFung BHung PLee C(2010)Centralized and Distributed Anonymization for High-Dimensional Healthcare DataACM Transactions on Knowledge Discovery from Data10.1145/1857947.18579504:4(1-33)Online publication date: 1-Oct-2010
https://dl.acm.org/doi/10.1145/1857947.1857950
Zhao KLiu BBenkler JXiao WEliassi-Rad TUngar LCraven MGunopulos D(2006)Opportunity mapProceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining10.1145/1150402.1150524(892-901)Online publication date: 20-Aug-2006
https://dl.acm.org/doi/10.1145/1150402.1150524
Show More Cited By

Index Terms

A Visual Data Mining Framework for Convenient Identification of Useful Knowledge
1. Human-centered computing
  1. Human computer interaction (HCI)
    1. Interactive systems and tools
2. Information systems
  1. Information systems applications
    1. Data mining

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cover image Guide Proceedings

ICDM '05: Proceedings of the Fifth IEEE International Conference on Data Mining

November 2005

837 pages

ISBN:0769522785

Publisher

IEEE Computer Society

United States

Publication History

Published: 27 November 2005

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Cited By

Rohde DHuang RCorcoran JWhite G(2013)Visual Data Mining Methods for Kernel Smoothed Estimates of Cox ProcessesRevised Selected Papers of PAKDD 2013 International Workshops on Trends and Applications in Knowledge Discovery and Data Mining - Volume 786710.1007/978-3-642-40319-4_8(83-94)Online publication date: 14-Apr-2013
https://dl.acm.org/doi/10.1007/978-3-642-40319-4_8
Mohammed NFung BHung PLee C(2010)Centralized and Distributed Anonymization for High-Dimensional Healthcare DataACM Transactions on Knowledge Discovery from Data10.1145/1857947.18579504:4(1-33)Online publication date: 1-Oct-2010
https://dl.acm.org/doi/10.1145/1857947.1857950
Zhao KLiu BBenkler JXiao WEliassi-Rad TUngar LCraven MGunopulos D(2006)Opportunity mapProceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining10.1145/1150402.1150524(892-901)Online publication date: 20-Aug-2006
https://dl.acm.org/doi/10.1145/1150402.1150524
Liu BZhao KBenkler JXiao WEliassi-Rad TUngar LCraven MGunopulos D(2006)Rule interestingness analysis using OLAP operationsProceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining10.1145/1150402.1150437(297-306)Online publication date: 20-Aug-2006
https://dl.acm.org/doi/10.1145/1150402.1150437

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