Titlebook: Visual Data Mining; Theory, Techniques a Simeon J. Simoff,Michael H. B?hlen,Arturas Mazeika Book 2008 Springer-Verlag Berlin Heidelberg 200

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0302-9743 1 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..978-3-540-71080-6Series ISSN 0302-9743 Series E-ISSN 1611-3349

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The 3DVDM Approach: A Case Study with Clickstream Data a comprehensive description of behaviors of users. Clickstreams, however, are large and raise a number of unique challenges with respect to visual data mining. At the technical level the huge amount of data requires scalable solutions and limits the presentation to summary and model data. Equally c

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A Methodology for Exploring Association Modelsion of association rule models. One aim is to provide the user with a tool that enables the exploration of a large set of association rules. The method is inspired by the hypertext metaphor. The initial set of rules is dynamically divided into small comprehensible sets or pages, according to the int

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Visual Mining of Association Rulesluable information for many application fields such as marketing, credit scoring, business, etc. The counterpart is that a massive effort is required (due to the large number of rules usually mined) in order to make actionable the retained knowledge. In this framework vizualization tools become esse

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