Efficient Retrieval of Similar Business Process Models Based on Structure
With the business process management technology being more widely used, there are more and more business process models, which are typically graphical. How to query such a large number of models efficiently is challenging. In this paper, we solve the problem of querying similar models efficiently based on structure. We use an index named TaskEdgeIndex for query processing. During query processing, we estimate the minimum number of edges that must be contained according to the given similarity threshold, and then obtain the candidate models through the index. Then we compute the similarity between the query condition model and every candidate model based on graph structure by using maximum common edge subgraph based similarity, and discard the candidate models that actually do not satisfy the similarity requirement. Since the number of candidate models is always much smaller than the size of repositories, the query efficiency is improved.
KeywordsBusiness Process Query Processing Candidate Model Query Time Business Process Model
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