Process mining techniques in business environments : theoretical aspects, algorithms, techniques and open challenges in process mining / Andrea Burattin.

By:

Burattin, Andrea

Material type:

TextSeries: Lecture notes in business information processing ; 207Publication details: Switzerland : Springer, 2015.Description: XII, 220 p. : ill. b&w ; 24 cmContent type:

text

ISBN:

9783319174815

Subject(s):

DDC classification:

658.4

Contents:

1. Introduction -- Pt. 1. 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 -- Pt. 3. 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 -- Pt. 4. A New Challenge in Process Mining -- 17. Process Mining for Stream Data Sources -- Pt. 5. 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."

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Holdings
Item type	Current library	Call number	Status	Barcode
Books	Marbella International University Centre Library	658.4 BUR pro (Browse shelf(Opens below))	Available	11616

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.

Includes bibliographical references.

1. Introduction --
Pt. 1. 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 --
Pt. 3. 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 --
Pt. 4. A New Challenge in Process Mining --
17. Process Mining for Stream Data Sources --
Pt. 5. Conclusions and Future Work --
18. Conclusions and Future Work.

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."

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