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Requirements and Challenges

  • Scalability
    • Clustering all the data instead of only on samples
  • Ability to deal with different types of attributes
    • Numerical, binary, categorical, ordinal, linked, and mixture of these
  • Constraint-based clustering
      • User may give inputs on constraints
      • Use domain knowledge to determine input parameters
  • Interpretability and usability
  • Others
    • Discovery of clusters with arbitrary shape
    • Ability to deal with noisy data
    • Incremental clustering and insensitivity to input order
    • High dimensionality

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