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Record Nr. |
UNINA9910299226203321 |
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Autore |
Burattin Andrea |
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Titolo |
Process Mining Techniques in Business Environments : Theoretical Aspects, Algorithms, Techniques and Open Challenges in Process Mining / / by Andrea Burattin |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 |
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ISBN |
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Edizione |
[1st ed. 2015.] |
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Descrizione fisica |
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1 online resource (XII, 220 p. 101 illus.) |
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Collana |
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Lecture Notes in Business Information Processing, , 1865-1356 ; ; 207 |
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Disciplina |
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Soggetti |
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Data mining |
Information technology - Management |
Pattern recognition systems |
Data Mining and Knowledge Discovery |
Business Process Management |
Computer Application in Administrative Data Processing |
Automated Pattern Recognition |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Bibliographic Level Mode of Issuance: Monograph |
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Nota di contenuto |
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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. |
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Sommario/riassunto |
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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. |
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