Discovery of Frequent DATALOG Patterns

Discovery of frequent patterns has been studied in a variety of data mining settings. In its simplest form, known from association rule mining, the task is to discover all frequent itemsets, i.e., all combinations of items that are found in a sufficient number of examples. The fundamental task of association rule and frequent set discovery has been extended in various directions, allowing more useful patterns to be discovered with special purpose algorithms. We present Warmr, a general purpose inductive logic programming algorithm that addresses frequent query discovery: a very general Datalog formulation of the frequent pattern discovery problem. The motivation for this novel approach is twofold. First, exploratory data mining is well supported: Warmr offers the flexibility required to experiment with standard and in particular novel settings not supported by special purpose algorithms. Also, application prototypes based on Warmr can be used as benchmarks in the comparison and evaluat...

• Type: Journal
• Year: 1999
• Where: DATAMINE
• Authors: Luc Dehaspe, Hannu Toivonen
• Keywords: DATAMINE 1999, Frequent, Frequent Pattern, Special Purpose Algorithms