|
|
|
|
LEADER |
02889nmm a2200349 u 4500 |
001 |
EB001034083 |
003 |
EBX01000000000000000827605 |
005 |
00000000000000.0 |
007 |
cr||||||||||||||||||||| |
008 |
150601 ||| eng |
020 |
|
|
|a 9783319174822
|
100 |
1 |
|
|a Burattin, Andrea
|
245 |
0 |
0 |
|a Process Mining Techniques in Business Environments
|h Elektronische Ressource
|b Theoretical Aspects, Algorithms, Techniques and Open Challenges in Process Mining
|c by Andrea Burattin
|
250 |
|
|
|a 1st ed. 2015
|
260 |
|
|
|a Cham
|b Springer International Publishing
|c 2015, 2015
|
300 |
|
|
|a XII, 220 p. 101 illus
|b online resource
|
505 |
0 |
|
|a 1 Introduction -- Part I: State of the Art: BPM, Data Mining and Process Mining -- 2 Introduction to Business Processes, BPM, and BPM Systems -- 3 Data Generated by Information Systems (and How to Get It) -- 4 Data Mining for Information System Data -- 5 Process Mining -- 6 Quality Criteria in Process Mining -- 7 Event Streams -- Part II: Obstacles to Process Mining in Practice -- 8 Obstacles to Applying Process Mining in Practice -- 9 Long-term View Scenario -- Part III: Process Mining as an Emerging Technology -- 10 Data Preparation -- 11 Heuristics Miner for Time Interval -- 12 Automatic Configuration of Mining Algorithm -- 13 User-Guided Discovery of Process Models -- 14 Extensions of Business Processes with Organizational Roles -- 15 Results Interpretation and Evaluation -- 16 Hands-On: Obtaining Test Data -- Part IV: A New Challenge in Process Mining -- 17 Process Mining for Stream Data Sources -- Part V: Conclusions and Future Work -- 18 Conclusions and Future Work
|
653 |
|
|
|a Computer Appl. in Administrative Data Processing
|
653 |
|
|
|a Management information systems
|
653 |
|
|
|a Pattern recognition
|
653 |
|
|
|a Pattern Recognition
|
653 |
|
|
|a Data mining
|
653 |
|
|
|a Application software
|
653 |
|
|
|a Data Mining and Knowledge Discovery
|
653 |
|
|
|a Business Process Management
|
653 |
|
|
|a Industrial management
|
041 |
0 |
7 |
|a eng
|2 ISO 639-2
|
989 |
|
|
|b Springer
|a Springer eBooks 2005-
|
490 |
0 |
|
|a Lecture Notes in Business Information Processing
|
856 |
4 |
0 |
|u https://doi.org/10.1007/978-3-319-17482-2?nosfx=y
|x Verlag
|3 Volltext
|
082 |
0 |
|
|a 006.312
|
520 |
|
|
|a After a brief presentation of the state of the art of process-mining techniques, Andrea Burratin proposes different scenarios for the deployment of process-mining projects, and in particular a characterization of companies in terms of their process awareness. The approaches proposed in this book belong to two different computational paradigms: first to classic "batch process mining," and second to more recent "online process mining." The book encompasses a revised version of the author's PhD thesis, which won the "Best Process Mining Dissertation Award" in 2014, awarded by the IEEE Task Force on Process Mining
|