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160104 ||| eng |
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|a 9783319272436
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100 |
1 |
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|a Ceravolo, Paolo
|e [editor]
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245 |
0 |
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|a Data-Driven Process Discovery and Analysis
|h Elektronische Ressource
|b 4th International Symposium, SIMPDA 2014, Milan, Italy, November 19-21, 2014, Revised Selected Papers
|c edited by Paolo Ceravolo, Barbara Russo, Rafael Accorsi
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250 |
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|a 1st ed. 2015
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260 |
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|a Cham
|b Springer International Publishing
|c 2015, 2015
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300 |
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|a IX, 123 p. 56 illus. in color
|b online resource
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505 |
0 |
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|a Discovery of Frequent Episodes in Event Logs -- Finding Suitable Activity Clusters for Decomposed Process Discovery -- History-based Construction of Alignments for Conformance Checking: Formalization and Implementation? -- Dynamic Constructs Competition Miner - Occurrence vs. Time-based Ageing -- Trustworthy Cloud Certification: A Model-Based Approach
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653 |
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|a Data mining
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653 |
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|a Application software
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653 |
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|a Computer Application in Administrative Data Processing
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653 |
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|a Data Mining and Knowledge Discovery
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653 |
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|a Business Process Management
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653 |
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|a Computer and Information Systems Applications
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653 |
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|a Information technology / Management
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700 |
1 |
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|a Russo, Barbara
|e [editor]
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700 |
1 |
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|a Accorsi, Rafael
|e [editor]
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041 |
0 |
7 |
|a eng
|2 ISO 639-2
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989 |
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|b Springer
|a Springer eBooks 2005-
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490 |
0 |
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|a Lecture Notes in Business Information Processing
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028 |
5 |
0 |
|a 10.1007/978-3-319-27243-6
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856 |
4 |
0 |
|u https://doi.org/10.1007/978-3-319-27243-6?nosfx=y
|x Verlag
|3 Volltext
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0 |
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|a 006.312
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520 |
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|a This book constitutes the thoroughly refereed proceedings of the Fourth International Symposium on Data-Driven Process Discovery and Analysis held in Riva del Milan, Italy, in November 2014. The five revised full papers were carefully selected from 21 submissions. Following the event, authors were given the opportunity to improve their papers with the insights they gained from the symposium. During this edition, the presentations and discussions frequently focused on the implementation of process mining algorithms in contexts where the analytical process is fed by data streams. The selected papers underline the most relevant challenges identified and propose novel solutions and approaches for their solution
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