Multilevel Mining Association Rules:

• Items often form hierarchy.
• Items of the lower level are expected to have lower support.
• A common form of background knowledge as that an attribute may be generated or specialized according to a hierarchy of concepts.
• Rules which contain associations with hierarchy of concepts are called Multilevel Association Rules.

Support and confidence of Multilevel association rules:

• Generalizing / specializing values of attributes affects support and confidence.
• Support of rules increases from specialized to general.
• Support of rules decreases from general to specialized.

• Confidence is not affected for general or specialized.

  Two Approaches of Multilevel Association Rules:

  I. Using uniform support level for all levels:

  • The same minimum support for all levels.
  • There is only one minimum support threshold so no need to examine itemsets
  • If support threshold is too high ⇒ miss low level associations
  • If the support threshold is too low ⇒ generate too many high level associations.

Fig: Example of uniform minimum support for all levels

II. Using reduced minimum support at lower level:

• At every level of abstraction , there is its own minimum support threshold

• So minimum support at lower levels reduces.

Fig: Example of reduced minimum support for lower level