Business Process Models Clustering Based on Multimodal Search, K-means, and Cumulative and No-Continuous N-Grams
Abstract: Due to the large volume of process repositories, finding a particular process may become a difficult task. This paper presents a method for indexing, search, and grouping business processes models. The method considers linguistic and behavior information for modeling the business process. Behavior information is described using cumulative and no-continuous n-grams. Grouping method is based on k-means algorithm and suffix arrays to define labels for each group. The clustering approach incorporates mechanisms for avoiding overlapping and improve the homogeneity of the created groups using the K-means algorithm. Obtained results outperform the precision, recall and F-measure of previous approaches.
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| Main Authors: | , , , |
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| Format: | Digital revista |
| Language: | English |
| Published: |
Instituto Politécnico Nacional, Centro de Innovación y Desarrollo Tecnológico en Cómputo
2016
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| Online Access: | http://www.scielo.org.mx/scielo.php?script=sci_arttext&pid=S1870-90442016000200025 |
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