Visual data mining : theory, techniques and tools for visual analytics / / Simeon J. Simoff, Michael H. Böhlen, Arturas Mazeika (editors)

• Pubblicazione: Berlin, Heidelberg : , : Springer, , [2008]; ©2008
• Edizione: 1st ed. 2008.
• Descrizione fisica: 1 online resource (X, 407 p.)
• Disciplina: 006.6869
• Soggetto topico: Computer graphics; Data mining; Information storage and retrieval systems
• Persona (resp. second.): SimoffSimeon J. <1962->; BöhlenMichael H. <1964->; MazeikaArturas
• Note generali: Bibliographic Level Mode of Issuance: Monograph
• Nota di bibliografia: Includes bibliographical references and index.
• Nota di contenuto: 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 Leukemia -- Towards Effective Visual Data Mining with Cooperative Approaches.
• Sommario/riassunto: 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.
• Titolo autorizzato: Visual Data Mining
• ISBN: 3-540-71080-9
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 996465631603316
• Lo trovi qui: Univ. di Salerno
• Serie: Lecture notes in computer science ; ; 4404.