Retrieving business process (BP) is a fundamental step for reusing software components within new information services and software products. Nevertheless, this step is critical in many fields and it may incur in unnecessary resources consumption due to the complexity to find services matching exactly the user’s requirements. Therefore, the development of intuitive, endowed with artificial intelligence and semantics-based methods which can recognize what the user really needs, become an important R&D area because it speeds up the deployment and configuration of new BP. In this context, this book summarizes the results of a scientific research project conduc- ted by Telematics Engineering Group of the University of Cauca (Colombia), in which a BP retrieval environment called BeMantics is defined. This environment is developed through two main modules: a repository module with pre-matching mechanisms based on behavioral semantics; and a structural, semantics and behavioral matching module which uses and error- correcting algorithm to refine the results obtained from repository. As a result the BeMantics environment provides a BP ranking according to their structural, semantics and behavioral similarity with regard to a query BP. This result is later analyzed through a pertinence eva- luation web tool which enables a group of human judges to emit relevance judgments on a set of test BPs. These relevance judgments allow obtaining a subset of BP considered as rele- vant, which let the pertinence tool to be used as basis for studying the relevance of the results achieved with the BeMantics environment.

Recuperación multinivel de procesos de negocio basado en semántica del comportamiento / FIGUEROA MARTINEZ, CRISTHIAN NICOLAS; Corrales, J. C.; Ramirez, G. A.. - STAMPA. - 1:(2012), pp. 1-109.

Recuperación multinivel de procesos de negocio basado en semántica del comportamiento

FIGUEROA MARTINEZ, CRISTHIAN NICOLAS;
2012

Abstract

Retrieving business process (BP) is a fundamental step for reusing software components within new information services and software products. Nevertheless, this step is critical in many fields and it may incur in unnecessary resources consumption due to the complexity to find services matching exactly the user’s requirements. Therefore, the development of intuitive, endowed with artificial intelligence and semantics-based methods which can recognize what the user really needs, become an important R&D area because it speeds up the deployment and configuration of new BP. In this context, this book summarizes the results of a scientific research project conduc- ted by Telematics Engineering Group of the University of Cauca (Colombia), in which a BP retrieval environment called BeMantics is defined. This environment is developed through two main modules: a repository module with pre-matching mechanisms based on behavioral semantics; and a structural, semantics and behavioral matching module which uses and error- correcting algorithm to refine the results obtained from repository. As a result the BeMantics environment provides a BP ranking according to their structural, semantics and behavioral similarity with regard to a query BP. This result is later analyzed through a pertinence eva- luation web tool which enables a group of human judges to emit relevance judgments on a set of test BPs. These relevance judgments allow obtaining a subset of BP considered as rele- vant, which let the pertinence tool to be used as basis for studying the relevance of the results achieved with the BeMantics environment.
2012
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2505164
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