TY  - GEN
AB  - 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.
AU  - Burattin, Andrea,
CN  - QA76.9.D343
DO  - 10.1007/978-3-319-17482-2
DO  - doi
ID  - 727261
KW  - Data mining.
KW  - Process control
LK  - https://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-319-17482-2
N2  - 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.
SN  - 9783319174822
SN  - 3319174827
T1  - Process mining techniques in business environmentstheoretical aspects, algorithms, techniques and open challenges in process mining /
TI  - Process mining techniques in business environmentstheoretical aspects, algorithms, techniques and open challenges in process mining /
UR  - https://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-319-17482-2
VL  - 207
ER  -