MultiSearchBP: Environment for Search and Clustering of Business Process Models
Hugo Ordoñez1, Juan Carlos Corrales2, Carlos Cobos3
1 Facultad de Ingeniería, Universidad de San Buenaventura, Cali, Colombia, y el Grupo de Ingeniería Telemática de la Universidad del Cauca, Colombia (correo: hugoeraso@gmail.com).
2 Departamento de Telemática, Facultad de Ingeniería Electrónica y Telecomunicaciones, Universidad del Cauca, Colombia (correo: jcorral@unicauca.edu.co).
3 Departamento de Sistemas, Facultad de Ingeniería Electrónica y Telecomunicaciones, Universidad del Cauca, Colombia (correo: ccobos@unicauca.edu.co).
]]>Manuscrito recibido el 18 de marzo de 2013
Aceptado para la publicación el 27 de julio del 2013
Versión final 16 de junio de 2014.
Resumen
El artículo presenta un entorno para búsqueda y agrupación de procesos de negocio denominado MultiSearchBP. Es basado en una arquitectura de tres niveles, que comprende el nivel de presentación, nivel de negocios (análisis estructural, la indización, búsqueda y agrupación) y el nivel de almacenamiento. El proceso de búsqueda se realiza en un repositorio que contiene 146 modelos de procesos de negocio (BP). Los procesos de indización y de consulta son similares a los del modelo de espacio vectorial utilizado en la recuperación de información, y el proceso de agrupación utiliza dos algoritmos de agrupación (Lingo y STC). MultiSearchBP utiliza una representación multimodal de los BP. También se presenta un proceso de evaluación experimental para considerar los juicios de ocho expertos evaluadores a partir de un conjunto de los valores de similitud obtenidos de comparaciones manuales efectuados con anterioridad sobre los modelos de BP almacenados en el repositorio. Las medidas utilizadas fueron la precisión gradual y el recall gradual. Los resultados muestran una precisión alta.
Palabras Clave: Procesos de negocio, recuperación de información, búsqueda multimodal, agrupamiento.
Abstract
]]> This paper presents a Business Process Searching and Grouping Environment called MultiSearchBP. It is based on a three-level architecture comprising Presentation level, Business level (Structural Analysis, Indexing, Query, and Grouping) and Storage level. The search process is performed on a repository that contains 146 Business Process (BP) models. The indexing and query processes are similar to those of the vector space model used in information retrieval and the clustering process uses two clustering algorithms (Lingo and STC). MultiSearchBP uses a multimodal representation of BPs. It also presents an experimental evaluation process to consider the judgments of eight expert evaluators from a set of similarity scores obtained from previous manual comparisons made between the BP models stored in the repository. The measures used were graded precision and graded recall. The results show high accuracy.Key words: Business processes, information retrieval, multi-modal search, clustering.
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