LEADER 04177nam 2200625 450 001 996465631603316 005 20211007192103.0 010 $a3-540-71080-9 024 7 $a10.1007/978-3-540-71080-6 035 $a(CKB)1000000000491076 035 $a(SSID)ssj0000320647 035 $a(PQKBManifestationID)11232600 035 $a(PQKBTitleCode)TC0000320647 035 $a(PQKBWorkID)10249732 035 $a(PQKB)10264794 035 $a(DE-He213)978-3-540-71080-6 035 $a(MiAaPQ)EBC3063088 035 $a(MiAaPQ)EBC6351720 035 $a(PPN)127055185 035 $a(EXLCZ)991000000000491076 100 $a20210215d2008 uy 0 101 0 $aeng 135 $aurnn#008mamaa 181 $ctxt 182 $cc 183 $acr 200 00$aVisual data mining $etheory, techniques and tools for visual analytics /$fSimeon J. Simoff, Michael H. Bo?hlen, Arturas Mazeika (editors) 205 $a1st ed. 2008. 210 1$aBerlin, Heidelberg :$cSpringer,$d[2008] 210 4$dİ2008 215 $a1 online resource (X, 407 p.) 225 1 $aLecture Notes in Computer Science ;$v4404 300 $aBibliographic Level Mode of Issuance: Monograph 311 $a3-540-71079-5 320 $aIncludes bibliographical references and index. 327 $aVisual 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. 330 $aThe importance of visual data mining, as a strong sub-discipline of data mining, had already been recognized in the beginning of the decade. In 2005 a panel of renowned individuals met to address the shortcomings and drawbacks of the current state of visual information processing. The need for a systematic and methodological development of visual analytics was detected. This book aims at addressing this need. Through a collection of 21 contributions selected from more than 46 submissions, it offers a systematic presentation of the state of the art in the field. The volume is structured in three parts on theory and methodologies, techniques, and tools and applications. 410 0$aLecture notes in computer science ;$v4404. 606 $aComputer graphics 606 $aData mining 606 $aInformation storage and retrieval systems 615 0$aComputer graphics. 615 0$aData mining. 615 0$aInformation storage and retrieval systems. 676 $a006.6869 702 $aSimoff$b Simeon J.$f1962- 702 $aBo?hlen$b Michael H.$f1964- 702 $aMazeika$b Arturas 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996465631603316 996 $aVisual Data Mining$9774377 997 $aUNISA