Scalable Uncertainty-tolerant Business Rules

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https://riunet.upv.es/handle/10251/50389

Cita bibliográfica

Cuzzocrea, A.; Decker, H.; Muñoz-Escoí, FD. (2014). Scalable Uncertainty-tolerant Business Rules. En Hybrid Artificial Intelligence Systems: 9th International Conference, HAIS 2014, Salamanca, Spain, June 11-13, 2014. Proceedings. Springer Verlag (Germany). 179-190. https://doi.org/10.1007/978-3-319-07617-1_16

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Resumen

Business rules are of key importance for maintaining the correctness of business processes and the reliability of business data. When they take the form of integrity constraints, business rules also can help to contain the amount of uncertainty associated to business data and decisions based on those data. However, business rule enforcement may not scale up easily to systems with concurrent transactions. To a large extent, the problem is due to two common exigencies: the postulates of total and of isolated business rule satisfaction. In order to limit the accumulation of business rule violations, and thus of uncertainty, we are going to outline how a measure-based uncertainty-tolerant approach to business rules maintenance scales up to concurrent transactions. The scale-up is achieved by refraining from the postulates of total and isolated business rule satisfaction.

Descripción

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-07617-1_16

Fuente

Hybrid Artificial Intelligence Systems: 9th International Conference, HAIS 2014, Salamanca, Spain, June 11-13, 2014. Proceedings isbn: 978-3-319-07616-4 issn: 0302-9743

Editorial

Springer Verlag (Germany)

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