Retrieval of Similar Semantic Workflows Based on Behavioral and Structural Characteristics

Workflow reuse is an important method for modern enterprises and organizations to improve the efficiency of business process management (BPM). Semantic workflows are domain knowledge-based workflows. The retrieval of similar semantic workflows is the first step for semantic workflow reuse. Existing retrieval algorithms of similar semantic workflows only focus on semantic workflows’ structural characteristics while ignoring their behavioral characteristics, which affects the overall quality of retrieved similar semantic workflows and increases the cost of semantic workflow reuse. To address this issue, a two-phase retrieval algorithm of similar semantic workflows is put forward based on behavioral and structural characteristics. A task adjacency relations (TARs) set is used to express a semantic workflow’s behavior. A TARs trees index named TARTreeIndex and a data index named DataIndex are constructed combined with domain knowledge for the semantic workflows case base. For a given query semantic workflow, firstly, candidate semantic workflows are obtained by filtering the semantic workflows case base with the TARTreeIndex and DataIndex, then candidate semantic workflows are verified and ranked with the graph matching similarity algorithm. Experiments show that the proposed algorithm improves the retrieval performance of similar semantic workflows compared with the existing popular retrieval algorithms for similar semantic workflows, so it can provide high-quality semantic workflows for semantic workflow reuse.