Resumen

ORDONEZ, Hugo; MERCHAN, Luis; ORDONEZ, Armando  y  COBOS, Carlos. Business Process Models Clustering Based on Multimodal Search, K-means, and Cumulative and No-Continuous N-Grams. Polibits [online]. 2016, n.54, pp.25-31. ISSN 1870-9044.  https://doi.org/10.17562/PB-54-4.

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.

Palabras llave : Clustering; business process models; multimodal search; cumulative and no-continuous n-grams..