SLPMiner: An Algorithm for Finding Frequent Sequential Patterns Using Length-Decreasing Support Constraint

Over the years, a variety of algorithms for finding frequent sequential patterns in very large sequential databases have been developed. The key feature in most of these algorithms is that they use a constant support constraint to control the inherently exponential complexity of the problem. In general, patterns that contain only a few items will tend to be interesting if they have a high support, whereas long patterns can still be interesting even if their support is relatively small. Ideally, we desire to have an algorithm that finds all the frequent patterns whose support decreases as a function of their length. In this paper we present an algorithm called SLPMiner, that finds all sequential patterns that satisfy a length-decreasing support constraint. SLPMiner combines an efficient database-projection-based approach for sequential pattern discovery with three effective database pruning methods that dramatically reduce the search space. Our experimental evaluation shows that SL...

• Type: Conference
• Year: 2002
• Where: ICDM
• Authors: Masakazu Seno, George Karypis
• Keywords: Data Mining, Frequent Sequential Patterns, ICDM 2002, Sequential Pattern, Support Constraint