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dc.contributor.authorGrigori, Daniela
dc.contributor.authorCasati, Fabio
dc.contributor.authorDayal, Umeshwar
dc.contributor.authorShan, Ming-Chien
dc.date.accessioned2012-04-04T15:41:59Z
dc.date.available2012-04-04T15:41:59Z
dc.date.issued2001
dc.identifier.urihttps://basepub.dauphine.fr/handle/123456789/8757
dc.language.isoenen
dc.subjectdata warehousingen
dc.subjectService Level Agreementen
dc.subjectweb servicesen
dc.subjectbusiness process managementen
dc.subject.ddc005en
dc.titleImproving Business Process Quality through Exception Understanding, Prediction, and Preventionen
dc.typeCommunication / Conférence
dc.description.abstractenBusiness process automation technologies are being increasingly used by many companies to improve the efficiency of both internal processes as well as of e-services offered to customers. In order to satisfy customers and employees, business processes need to be executed with a high and predictable quality. In particular, it is crucial for organizations to meet the Service Level Agreements (SLAs) stipulated with the customers and to foresee as early as possible the risk of missing SLAs, in order to set the right expectations and to allow for corrective actions. In this paper we focus on a critical issue in business process quality: that of analyzing, predicting and preventing the occurrence of exceptions, i.e., of deviations from the desired or acceptable behavior. We characterize the problem and propose a solution, based on data warehousing and mining techniques. We then describe the architecture and implementation of a tool suite that enables exception analysis, prediction, and prevention. Finally, we show experimental results obtained by using the tool suite to analyze internal HP processes.en
dc.identifier.citationpages159-168en
dc.relation.ispartoftitleProceedings of the 27th International Conference on Very Large Data Basesen
dc.relation.ispartofeditorSnodgrass, Richard Thomas
dc.relation.ispartofeditorRamamohanarao, Kotagiri
dc.relation.ispartofeditorParaboschi, Stefano
dc.relation.ispartofeditorCeri, Stefano
dc.relation.ispartofeditorAtzeni, Paolo
dc.relation.ispartofeditorApers, Peter M. G.
dc.relation.ispartofpublnameMorgan Kaufmann Publishers Inc.en
dc.relation.ispartofpublcitySan Franciscoen
dc.relation.ispartofdate2011
dc.relation.ispartofpages727en
dc.description.sponsorshipprivateouien
dc.subject.ddclabelProgrammation, logiciels, organisation des donnéesen
dc.relation.ispartofisbn1-558-60804-4en
dc.relation.conftitle27th International Conference on Very Large Databases (VLDB 2001)en
dc.relation.confdate2001-09
dc.relation.confcityRomeen
dc.relation.confcountryItalieen


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