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Visual Data Mining [electronic resource] : Theory, Techniques and Tools for Visual Analytics / edited by Simeon Simoff, Michael H. Böhlen, Arturas Mazeika.

Contributor(s): Simoff, Simeon [editor.] | Böhlen, Michael H [editor.] | Mazeika, Arturas [editor.] | SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Information Systems and Applications, incl. Internet/Web, and HCI: 4404Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2008Edition: 1st ed. 2008.Description: X, 407 p. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783540710806.Subject(s): Data mining | Computer graphics | Database management | Information storage and retrieval systems | Data Mining and Knowledge Discovery | Computer Graphics | Database Management | Information Storage and RetrievalAdditional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification: 006.312 Online resources: Click here to access online
Contents:
Visual Data Mining: An Introduction and Overview -- Visual Data Mining: An Introduction and Overview -- 1 - Theory and Methodologies -- The 3DVDM Approach: A Case Study with Clickstream Data -- Form-Semantics-Function - A Framework for Designing Visual Data Representations for Visual Data Mining -- A Methodology for Exploring Association Models -- Visual Exploration of Frequent Itemsets and Association Rules -- Visual Analytics: Scope and Challenges -- 2 - Techniques -- Using Nested Surfaces for Visual Detection of Structures in Databases -- Visual Mining of Association Rules -- Interactive Decision Tree Construction for Interval and Taxonomical Data -- Visual Methods for Examining SVM Classifiers -- Text Visualization for Visual Text Analytics -- Visual Discovery of Network Patterns of Interaction between Attributes -- Mining Patterns for Visual Interpretation in a Multiple-Views Environment -- Using 2D Hierarchical Heavy Hitters to Investigate Binary Relationships -- Complementing Visual Data Mining with the Sound Dimension: Sonification of Time Dependent Data -- Context Visualization for Visual Data Mining -- Assisting Human Cognition in Visual Data Mining -- 3 - Tools and Applications -- Immersive Visual Data Mining: The 3DVDM Approach -- DataJewel: Integrating Visualization with Temporal Data Mining -- A Visual Data Mining Environment -- Integrative Visual Data Mining of Biomedical Data: Investigating Cases in Chronic Fatigue Syndrome and Acute Lymphoblastic Leukaemia -- Towards Effective Visual Data Mining with Cooperative Approaches.
In: Springer Nature eBookSummary: The importance of visual data mining, as a strong sub-discipline of data mining, had already been recognized in the beginning of the decade. In 2005 a panel of renowned individuals met to address the shortcomings and drawbacks of the current state of visual information processing. The need for a systematic and methodological development of visual analytics was detected. This book aims at addressing this need. Through a collection of 21 contributions selected from more than 46 submissions, it offers a systematic presentation of the state of the art in the field. The volume is structured in three parts on theory and methodologies, techniques, and tools and applications.
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Visual Data Mining: An Introduction and Overview -- Visual Data Mining: An Introduction and Overview -- 1 - Theory and Methodologies -- The 3DVDM Approach: A Case Study with Clickstream Data -- Form-Semantics-Function - A Framework for Designing Visual Data Representations for Visual Data Mining -- A Methodology for Exploring Association Models -- Visual Exploration of Frequent Itemsets and Association Rules -- Visual Analytics: Scope and Challenges -- 2 - Techniques -- Using Nested Surfaces for Visual Detection of Structures in Databases -- Visual Mining of Association Rules -- Interactive Decision Tree Construction for Interval and Taxonomical Data -- Visual Methods for Examining SVM Classifiers -- Text Visualization for Visual Text Analytics -- Visual Discovery of Network Patterns of Interaction between Attributes -- Mining Patterns for Visual Interpretation in a Multiple-Views Environment -- Using 2D Hierarchical Heavy Hitters to Investigate Binary Relationships -- Complementing Visual Data Mining with the Sound Dimension: Sonification of Time Dependent Data -- Context Visualization for Visual Data Mining -- Assisting Human Cognition in Visual Data Mining -- 3 - Tools and Applications -- Immersive Visual Data Mining: The 3DVDM Approach -- DataJewel: Integrating Visualization with Temporal Data Mining -- A Visual Data Mining Environment -- Integrative Visual Data Mining of Biomedical Data: Investigating Cases in Chronic Fatigue Syndrome and Acute Lymphoblastic Leukaemia -- Towards Effective Visual Data Mining with Cooperative Approaches.

The importance of visual data mining, as a strong sub-discipline of data mining, had already been recognized in the beginning of the decade. In 2005 a panel of renowned individuals met to address the shortcomings and drawbacks of the current state of visual information processing. The need for a systematic and methodological development of visual analytics was detected. This book aims at addressing this need. Through a collection of 21 contributions selected from more than 46 submissions, it offers a systematic presentation of the state of the art in the field. The volume is structured in three parts on theory and methodologies, techniques, and tools and applications.

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