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Business Process Intelligence

Grigori, Daniela; Casati, Fabio; Castellanos, Malu; Dayal, Umeshwar; Sayal, Mehmet; Shan, Ming-Chien (2004), Business Process Intelligence, Computers in Industry, 53, 3, p. 321-343. http://dx.doi.org/10.1016/j.compind.2003.10.007

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HPL-2002-119.pdf (306.7Kb)
Type
Article accepté pour publication ou publié
Date
2004
Journal name
Computers in Industry
Volume
53
Number
3
Publisher
Elsevier
Pages
321-343
Publication identifier
http://dx.doi.org/10.1016/j.compind.2003.10.007
Metadata
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Author(s)
Grigori, Daniela
Casati, Fabio
Castellanos, Malu
Dayal, Umeshwar
Sayal, Mehmet
Shan, Ming-Chien
Abstract (EN)
Business Process Management Systems (BPMSs) are software platforms that support the definition, execution, and tracking of business processes. BPMSs have the ability of logging information about the business processes they support. Proper analysis of BPMS execution logs can yield important knowledge and help organizations improve the quality of their business processes and services to their business partners. This paper presents a set of integrated tools that supports business and IT users in managing process execution quality by providing several features, such as analysis, prediction, monitoring, control, and optimization. We refer to this set of tools as the Business Process Intelligence (BPI) tool suite. Experimental results presented in this paper are very encouraging. We plan to investigate further enhancements on the BPI tools suite, including automated exception prevention, and refinement of process data preparation stage, as well as integrating other data mining techniques.
Subjects / Keywords
Business Process Intelligence; Workflow mining; Process execution analysis and prediction; Data warehouse

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