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Categorization of Constraints

  • Constraints on instances: specifies how a pair or a set of instances should be grouped in the cluster analysis
    • Must-link vs. cannot link constraints
      • must-link(x, y): x and y should be grouped into one cluster
    • Constraints can be defined using variables, e.g.,
      • cannot-link(x, y) if dist(x, y) > d
  • Constraints on clusters: specifies a requirement on the clusters
    • E.g., specify the min # of objects in a cluster, the max diameter of a cluster, the shape of a cluster (e.g., a convex), # of clusters (e.g., k)
  • Constraints on similarity measurements: specifies a requirement that the similarity calculation must respect
    • E.g., driving on roads, obstacles (e.g., rivers, lakes)
  • Issues: Hard vs. soft constraints; conflicting or redundant constraints

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