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Data Space Pruning with Data Anti-monotonicity

  • A constraint c is data anti-monotone if for a pattern p cannot satisfy a transaction t under c, p’s superset cannot satisfy t under c either
  • The key for data anti-monotone is recursive data reduction
  • Ex. 1. sum(S.Price)≥ v is data anti-monotone
  • Ex. 2. min(S.Price) ≤ v is data anti-monotone
  • Ex. 3. C: range(S.profit) ≥ 25 is data anti-monotone
    • Itemset {b, c}’s projected DB:
      • T10’: {d, f, h}, T20’: {d, f, g, h}, T30’: {d, f, g}
    • since C cannot satisfy T10’, T10’ can be pruned


Speaker notes:

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