Mining Various Patterns in Sequential Data in an SQL-like Manner

Abstract. One of the most important data mining tasks is discovery of frequently occurring patterns in sequences of events. Many algorithms for finding various patterns in sequential data have been proposed recently. Researchers concentrated on different classes of patterns, which resulted in many different models and formulations of the problem. In this paper a uniform formulation of the problem of mining frequent patterns in sequential data is provided together with an SQL-like language capable of expressing queries concerning all classes of patterns. An issue of materializing discovered patterns for further selective analysis is also addressed by introducing a concept of knowledge snapshots.

• Type: Conference
• Year: 1999
• Where: ADBIS
• Authors: Marek Wojciechowski
• Keywords: ADBIS 1999, Data Mining Tasks, Database, Mining Frequent Patterns, Sequential Data