Social mining, recommenders and data semantics are moving the focus of enterprise systems towards context-awareness and personalization. However, the design of these software systems needs specific architectures to support intelligent behaviors, still ensuring important non-functional properties, such as flexibility, efficiency and scalability. This paper proposes an architectural pattern that helps designers to easily identify the subsystems that characterize intelligent enterprise systems. By decoupling transactional behavior from batch processing, the pattern avoids the interference of knowledge extraction and reasoning processes with the state and the performance of the transactional subsystem. The pattern has been experimented in e-Commerce by designing an intelligent and scalable virtual mall.
An Architectural Pattern for Designing Intelligent Enteprise Systems
Zimeo E;
2013-01-01
Abstract
Social mining, recommenders and data semantics are moving the focus of enterprise systems towards context-awareness and personalization. However, the design of these software systems needs specific architectures to support intelligent behaviors, still ensuring important non-functional properties, such as flexibility, efficiency and scalability. This paper proposes an architectural pattern that helps designers to easily identify the subsystems that characterize intelligent enterprise systems. By decoupling transactional behavior from batch processing, the pattern avoids the interference of knowledge extraction and reasoning processes with the state and the performance of the transactional subsystem. The pattern has been experimented in e-Commerce by designing an intelligent and scalable virtual mall.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
