Partitioning Behavioral Retrieval: An Efficient Computational Approach With Transitive Rules

The number of process models in process repositories has grown in recent years. For this reason, it is becoming increasingly important to efficiently retrieve process models from the repositories for management purposes. In fact, the method of retrieval is also essential to increase the potential of additional analysis such as similarity and behavioral analysis and compliance checking. Most retrieval methods can be classified as structural or behavioral retrieval. Behavioral retrieval considers the relationships between activities during process execution. In this paper, we introduce such a new behavior-based retrieval method called Partitioning Behavioral Retrieval. It is the first retrieval method that allows process models to contain inclusive (OR) gateways. The method is based on the dominance relation and a node-based process structure tree known from compiler theory. Although it uses instance subgraph checking as a computational basis, it derives new behavioral relations by using transitive rules. Currently, the method is limited to acyclic process models for ease of introduction. Experiments show the time advantage offered by our new method.