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Digging in the Details: A Case Study in Network Data Mining

  • John Galloway
  • Simeon J. Simoff
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3495)

Abstract

Network Data Mining builds network linkages (network models) between myriads of individual data items and utilizes special algorithms that aid visualization of ‘emergent’ patterns and trends in the linkage. It complements conventional and statistically based data mining methods. Statistical approaches typically flag, alert or alarm instances or events that could represent anomalous behavior or irregularities because of a match with pre-defined patterns or rules. They serve as ‘exception detection’ methods where the rules or definitions of what might constitute an exception are able to be known and specified ahead of time. Many problems are suited to this approach. Many problems however, especially those of a more complex nature, are not well suited. The rules or definitions simply cannot be specified; there are no known suspicious transactions. This paper presents a human-centered network data mining methodology. A case study from the area of security illustrates the application of the methodology and corresponding data mining techniques. The paper argues that for many problems, a ‘discovery’ phase in the investigative process based on visualization and human cognition is a logical precedent to, and complement of, more automated ‘exception detection’ phases.

Keywords

Data Mining Data Item Social Network Analysis Data Mining Technique Emergent Group 
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 2005

Authors and Affiliations

  • John Galloway
    • 1
    • 2
  • Simeon J. Simoff
    • 3
    • 4
  1. 1.Complex Systems Research CentreUniversity of Technology SydneyBroadwayAustralia
  2. 2.Chief Scientist, NetMap Analytics Pty LtdSt LeonardsAustralia
  3. 3.Faculty of Information TechnologyUniversity of Technology SydneyBroadwayAustralia
  4. 4.Electronic Markets Group, Institute for Information and Communication TechnologiesUniversity of Technology SydneyBroadwayAustralia

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