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| Format: | Artículo científico |
| Sprache: | en |
| Veröffentlicht: |
Instituto Politécnico Nacional
2016
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| Online-Zugang: | https://www.redalyc.org/articulo.oa?id=402650526005 |
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Inhaltsangabe:
- Business Process Models Clustering Based on Multimodal Search, K-means, and Cumulative and No-Continuous N-Grams Hugo Ordoñez Luis Merchán Armando Ordoñez Carlos Cobos Computación grams Clustering continuous n multimodal search cumulative and no 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 nocontinuous 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. 2016 artículo científico 1870-9044 https://www.redalyc.org/articulo.oa?id=402650526005 en http://www.redalyc.org/revista.oa?id=4026 Polibits application/pdf Instituto Politécnico Nacional Polibits (México) Vol.54