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Information Visualization in Data Mining and Knowledge Discovery

  • 1st Edition - August 20, 2001
  • Latest edition
  • Authors: Usama Fayyad, Georges Grinstein, Andreas Wierse
  • Language: English

Mainstream data mining techniques significantly limit the role of human reasoning and insight. Likewise, in data visualization, the role of computational analysis is relatively sm… Read more

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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.

Key features

  • Details advances made by leading researchers from the fields of data mining, data visualization, and statistics.
  • 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.
  • Presents the findings of recent international KDD workshops as formal chapters that together comprise a complete, cohesive body of research.
  • Offers a 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.

Readership

Professionals and researchers in data mining, information visualisation and statisticians responsible for analysis of business and scientific data.

Table of contents

Information Visualization in Data Mining and Knowledge Discovery: An OverviewUsama Fayyad and Georges G. GrinsteinData VisualizationIntroduction to Data VisualizationGeorges G. Grinstein and Matthew O. WardA Survey of Visualizations for High Dimensional Data MiningPatrick E. Hoffman and Georges G. GrinsteinEvaluation of Visualization SystemsRonald M. Pickett and Georges G. GrinsteinThe Data Visualization EnvironmentMike Foster and Alexander G. GeeVisualizing Massive Multivariate Time-Series DataDennis DeCostePortable Document IndexesJohn LightCharacter-Based Data Visualization for Data MiningMichel Pilote and Madeleine FillionKDD and Model VisualizationVisualization in the Knowledge Discovery ProcessKen Collier, Muralidhar Medidi and Donald SautterWhat can Visualization do for Data Mining?Andreas WierseMultidimensional Information Visualizations for Data Mining with Applications to Machine Learning ClassifiersPatrick E. Hoffman and Georges G. GrinsteinBenchmark Development for the Evaluation of Visualization for Data MiningGeorges G. Grinstein, Patrick E. Hoffman, Sharon J. Laskowski, and Ronald M. PickettData Visualization for Decision Support ActivitiesHenry S. GertzmanA Visualization-Driven Approach for Strategic Knowledge DiscoveryDavid Law Yuh FoongA Visual Metaphor for Knowledge Discovery: An Integrated Approach to Visualizing the Task, Data and ResultsPeter Docherty and Allan BeckVisualizing Data Mining ModelsKurt Thearling, Barry Becker, Dennis DeCoste, Bill Mawby, Michel Pilote, and Dan SommerfieldModel VisualizationWesley JohnstonIssues in Time Series and Categorical Data ExplorationNancy Grady, Raymond Flanery, Jr., June Donato and Jack SchryverVisualizing the Simple Bayesian ClassifierBarry Becker, Ronny Kohavi and Dan SommerfieldVisualizing Data Mining Results with Domain Generalization GraphsRobert J. Hilderman, Liangchun Li and Howard J. HamiltonAn Adaptive Interface Approach for Real-time Data ExplorationMartin R. Stytz and Sheila B. BanksIntegrating KDD and Visualization in Exploration EnvironmentsDiscovering New Relationships: A Brief Overview of Data Mining and Knowledge DiscoveryPhilip J. RhodesA Taxonomy for Integrating Data Mining and Data VisualizationThomas H. Hinke and Timothy S. NewmanIntegrating Data Mining and Visualization ProcessesNancy Grady, Loretta Auvill, Allen Beck, Peter R. Bono, Mary Dimmock, and Claudio J. MenesesMultidimensional Education, Visual and Algorithmic Data Mining Domains and SymbiosisTed W. MihalisinRobust Beta MiningR. Douglas Martin and Tim SiminUse of the Manifold Concept in Model VisualizationWilliam D. MawbyData Warfare and Multidimensional EducationTed W. MihalisinDocument Mining and VisualizationAlexander G. Gee and John LightResearch Issues in the Analysis and Visualization of Massive Data SetsClaudio J. Meneses and Georges G. GrinsteinTowards Smarter Databases: A Case Building ToolkitMarc RinguetteThe NASD Regulation Advanced Detection System: Integrating Data Mining and Visualization for Break Detection in the NASDAQ Stock MarketTed E. Senator, Henry G. Goldberg, Ping Shyr, Scott Bennett, Steve Donoho, and Craig Lovell

Product details

  • Edition: 1
  • Latest edition
  • Published: August 20, 2001
  • Language: English

About the authors

UF

Usama Fayyad

Usama Fayyad is co-founder, president, and CEO of digiMine, a data warehousing and data mining ASP. Prior to digiMine, he founded and led Microsoft's Data Mining and Exploration Group, where he developed data mining prediction components for Microsoft Site Server and scalable algorithms for mining large databases.

GG

Georges Grinstein

Georges G. Grinstein is a professor of computer science, director of the Institute for Visualization and Perception Research, and co-director of the Center for Bioinformatics and Computational Biology at the University of Massachusetts, Lowell. He is currently the chief technologist for AnVil Informatics, a data exploration company.

AW

Andreas Wierse

Andreas Wierse is the managing director of VirCinity, a spin-off company of the Computing Centre of the University of Stuttgart. Previously, he worked at the Computer Centre, where he designed and implemented distributed data management for the COVISE visualization system and maintained a wide range of graphics workstations.