Visual Discovery of Network Patterns of Interaction between Attributes

  • Simeon J. Simoff
  • John Galloway
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4404)


Visual discovery of network patterns of interaction between attributes in a data set identifies emergent networks between myriads of individual data items and utilises special algorithms that aid visualisation of ‘emergent’ patterns and trends in the linkage. It complements conventional data mining methods, which assume the independence between the attributes and the independence between the values of these attributes. The approach complements analytical data mining techniques where the rules or definitions of what might constitute an exception are able to be known and specified ahead of time. For example, in the analysis of transaction data there are no known suspicious transactions. This chapter presents a human-centred visual data mining methodology that addresses the issues of depicting implicit relationships between data attributes and/or specific values of these attributes. Different aspects of the approach is demonstrated through the reflection of the analytical process in two cases: one looking at fraudulent activity which will be difficult, if not impossible to detect with conventional exception detection methods, and the other one looking at exploring a large data set of low level communication data. The chapter argues that for many problems, a ‘discovery’ phase in the investigative process based on visualisation and human cognition is a logical precedent to, and complement of, more automated ‘exception detection’ phases.


Data Mining Data Item Social Network Analysis Data Mining Method Network Pattern 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Simeon J. Simoff
    • 1
    • 2
  • John Galloway
    • 3
  1. 1.School of Computing and Mathematics, College of Health and ScienceUniversity of Western SydneyAustralia
  2. 2.Faculty of Information TechnologyUniversity of TechnologySydneyAustralia
  3. 3.Chief ScientistNetMap Analytics Pty LtdSt LeonardsAustralia

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