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Interestingness Patterns

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A data mining system has the potential to generate thousands or even millions of patterns, or rules. then “are all of the patterns interesting?” Typically, not—only a small fraction of the patterns potentially generated would be of interest to any given user.

This raises some serious questions for data mining. You may wonder,

1. What makes a pattern interesting?
2. Can a data mining system generate all the interesting patterns?
3. Can a data mining system generate only interesting patterns?

To answer the first question, a pattern is interesting if it is

1. easily understood byhumans,
2. valid on new or test data with some degree of certainty,
3. potentiallyuseful, and
4. novel.

The second question―Can a data mining system generate all the interestingpatterns?--refers to the completeness of a data mining algorithm. It is often unrealistic andinefficient for data mining systems to generate all the possible patterns. Instead, user-provided constraints and interestingness measures should be used to focus the search. A data mining algorithm is complete if it mines all interesting patterns.

Finally, the third question -- “Can a data mining system generate only interesting patterns?”— is an optimization problem in data mining. It is highly desirable for datamining systems to generate only interesting patterns.An interesting pattern represents knowledge.

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