| Description |
1 online resource (xii, 220 pages) : illustrations |
| Series |
Lecture notes in business information processing, 1865-1348 ; 207 |
|
Lecture notes in business information processing ; 207. 1865-1348
|
| Contents |
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 |
| Summary |
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 |
| Bibliography |
Includes bibliographical references |
| Notes |
English |
|
Online resource; title from PDF title page (SpringerLink, viewed May 22, 2015) |
| Subject |
Data mining.
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Process control -- Data processing
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Business mathematics & systems.
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Public administration.
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Pattern recognition.
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Data mining.
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Business & Economics -- Information Management.
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Computers -- Data Processing.
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Computers -- Computer Vision & Pattern Recognition.
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Computers -- Database Management -- Data Mining.
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Data mining
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Process control -- Data processing
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| Form |
Electronic book
|
| ISBN |
9783319174822 |
|
3319174827 |
|
3319174819 |
|
9783319174815 |
|
