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Full Description
Mainstream data mining techniques significantly limit the role of human reasoning and insight. Likewise, in data visualization, the role of computational analysis is relatively small. The power demonstrated individually by these approaches to knowledge discovery suggests that somehow uniting the two could lead to increased efficiency and more valuable results. But is this true? How might it be achieved? And what are the consequences for data-dependent enterprises? "Information Visualization in Data Mining and Knowledge Discovery" is the first book to ask and answer these thought-provoking questions. It is also the first book to explore the fertile ground of uniting data mining and data visualization principles in a new set of knowledge discovery techniques. Leading researchers from the fields of data mining, data visualization, and statistics present findings organized around topics introduced in two recent international knowledge discovery and data mining workshops.
Collected and edited by three of the area's most influential figures, these chapters introduce the concepts and components of visualization, detail current efforts to include visualization and user interaction in data mining, and explore the potential for further synthesis of data mining algorithms and data visualization techniques. This incisive, groundbreaking research is sure to wield a strong influence in subsequent efforts in both academic and corporate settings. It details advances made by leading researchers from the fields of data mining, data visualization, and statistics. It provides a useful introduction to the science of visualization, sketches the current role for visualization in data mining, and then takes a long look into its mostly untapped potential. It presents the findings of recent international KDD workshops as formal chapters that together comprise a complete, cohesive body of research.
It offers compelling and practical information for professionals and researchers in database technology, data mining, knowledge discovery, artificial intelligence, machine learning, neural networks, statistics, pattern recognition, information retrieval, high-performance computing, and data visualization.
Contents
Information Visualization in Data Mining and Knowledge Discovery: An Overview Usama Fayyad and Georges G. Grinstein Data Visualization Introduction to Data Visualization Georges G. Grinstein and Matthew O. Ward A Survey of Visualizations for High Dimensional Data Mining Patrick E. Hoffman and Georges G. Grinstein Evaluation of Visualization Systems Ronald M. Pickett and Georges G. Grinstein The Data Visualization Environment Mike Foster and Alexander G. Gee Visualizing Massive Multivariate Time-Series Data Dennis DeCoste Portable Document Indexes John Light Character-Based Data Visualization for Data Mining Michel Pilote and Madeleine Fillion KDD and Model Visualization Visualization in the Knowledge Discovery Process Ken Collier, Muralidhar Medidi and Donald Sautter What can Visualization do for Data Mining? Andreas Wierse Multidimensional Information Visualizations for Data Mining with Applications to Machine Learning Classifiers Patrick E. Hoffman and Georges G. Grinstein Benchmark Development for the Evaluation of Visualization for Data Mining Georges G. Grinstein, Patrick E. Hoffman, Sharon J. Laskowski, and Ronald M. Pickett Data Visualization for Decision Support Activities Henry S. Gertzman A Visualization-Driven Approach for Strategic Knowledge Discovery David Law Yuh Foong A Visual Metaphor for Knowledge Discovery: An Integrated Approach to Visualizing the Task, Data and Results Peter Docherty and Allan Beck Visualizing Data Mining Models Kurt Thearling, Barry Becker, Dennis DeCoste, Bill Mawby, Michel Pilote, and Dan Sommerfield Model Visualization Wesley Johnston Issues in Time Series and Categorical Data Exploration Nancy Grady, Raymond Flanery, Jr., June Donato and Jack Schryver Visualizing the Simple Bayesian Classifier Barry Becker, Ronny Kohavi and Dan Sommerfield Visualizing Data Mining Results with Domain Generalization Graphs Robert J. Hilderman, Liangchun Li and Howard J. Hamilton An Adaptive Interface Approach for Real-time Data Exploration Martin R. Stytz and Sheila B. Banks Integrating KDD and Visualization in Exploration Environments Discovering New Relationships: A Brief Overview of Data Mining and Knowledge Discovery Philip J. Rhodes A Taxonomy for Integrating Data Mining and Data Visualization Thomas H. Hinke and Timothy S. Newman Integrating Data Mining and Visualization Processes Nancy Grady, Loretta Auvill, Allen Beck, Peter R. Bono, Mary Dimmock, and Claudio J. Meneses Multidimensional Education, Visual and Algorithmic Data Mining Domains and Symbiosis Ted W. Mihalisin Robust Beta Mining R. Douglas Martin and Tim Simin Use of the Manifold Concept in Model Visualization William D. Mawby Data Warfare and Multidimensional Education Ted W. Mihalisin Document Mining and Visualization Alexander G. Gee and John Light Research Issues in the Analysis and Visualization of Massive Data Sets Claudio J. Meneses and Georges G. Grinstein Towards Smarter Databases: A Case Building Toolkit Marc Ringuette The NASD Regulation Advanced Detection System: Integrating Data Mining and Visualization for Break Detection in the NASDAQ Stock Market Ted E. Senator, Henry G. Goldberg, Ping Shyr, Scott Bennett, Steve Donoho, and Craig Lovell
