Generating Corpus for Evaluating Performance of Process Matching Techniques
DOI:
https://doi.org/10.21015/vtcs.v15i3.525Abstract
Business process management (BPM) plays a vital role in organizations management. A central piece to that is the collection of business process models. Depending upon the size of the organization, the collection may have many process models in the process repository. A key feature to such a repository is searching of process models which requires computing similarity between a pair of process models. For a given pair of process models, similarity refers to finding whether the two process models that form the pair are similar or not. To compute the similarity between process models, several techniques have been established however a rigorous evaluation of these techniques has either not been conducted on numerous occasions or the evaluation has not been sufficiently rigorous. A key reason to that is the absence of a benchmark set of queries and their relevant process models, as a judge by human experts. In this study, we argue, the fewer queries used for evaluation may not have the necessary diversity to challenge the abilities of the matching techniques. This work is usually not done due to a large number of manual comparisons. It is thus required a pool of queries. A related challenge is to identify a pool of process models that are declared as relevant to the query models. To address these challenges, we have suggested a technique.References
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