With the workflow technology being more widely used, there are more and more workflow models. How to retrieve the similar models efficiently from a large model repository is challenging. Since dynamic behavior is the essential characteristic of workflow models, we measure the similarity between models based on their behavior. Since the number of models is large, the efficiency of similarity retrieval is very important. To improve the efficiency of similarity retrieval based on behavior, we propose a more efficient algorithm for similarity calculation and use an index named TARIndex for query processing. To make our approach more applicable, we consider the semantic similarity between labels. Analysis and experiments show that our approach is efficient. © 2012 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Jin, T., Wang, J., & Wen, L. (2012). Efficient retrieval of similar workflow models based on behavior. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7235 LNCS, pp. 677–684). https://doi.org/10.1007/978-3-642-29253-8_64
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