Current Slide

Small screen detected. You are viewing the mobile version of SlideWiki. If you wish to edit slides you will need to use a larger device.

Mining Collective Outliers II: Direct Modeling of the Expected Behavior of Structure Units

  • Models the expected behavior of structure units directly
  • Ex. 1. Detect collective outliers in online social network of customers
    • Treat each possible subgraph of the network as a structure unit
    • Collective outlier: An outlier subgraph in the social network
      • Small subgraphs that are of very low frequency
      • Large subgraphs that are surprisingly frequent
  • Ex. 2. Detect collective outliers in temporal sequences
    • Learn a Markov model from the sequences
    • A subsequence can then be declared as a collective outlier if it significantly deviates from the model
  • Collective outlier detection is subtle due to the challenge of exploring the structures in data
    • The exploration typically uses heuristics, and thus may be application dependent
    • The computational cost is often high due to the sophisticated mining process


Speaker notes:

Content Tools

Sources

There are currently no sources for this slide.