Optimal Approach for Temporal Patterns Discovery

摘要

This paper presents new technique for discovering temporal patterns when considered primitives are intervals. Apriori technique is the most used one to deal with temporal patterns using point primitives. An extension of this technique is proposed by Hoeppner to deal with interval primitives. In this paper, we show that it is not necessary to discover all patterns, instead it is sufficient to discover the set of optimum "interesting" patterns, which is smaller than the set of all significant patterns. For this task, we will introduce a new approach proposal to reduce the combinatorial explosion of generated patterns. The resulting technique, called TPGIP (Temporal Patterns Generation with Interval Primitives), is used to discover the optimal set of interesting patterns efficiently. Then, TPGIP explores some symmetric properties of interval algebra and uses partial patterns structure to propose an efficient approach to explore the patterns set in order to generate the candidate patterns. Some experimental and comparative results are shown at the end of this paper.