000 02577nam a22002657a 4500
008 240109t2016 us a||||s|||| 00| 0 eng |
020 _a9783662498507
020 _a9783662498514
040 _aUniversiti Teknologi Brunei
_beng
100 1 _aWil M. P. van der Aalst
_eauthor
245 1 0 _aProcess Mining :
_bData Science in Action /
_cWil M. P. van der Aalst
250 _aSecond edition
260 _aHeidelberg :
_bSpringer,
_c2016.
500 _aThis book is automatically accessible within the University internet network. To learn how to access it outside the campus, visit: https://www.utb.edu.bn/media/cv5fcgwb/remote-access-for-ebscohost.pdf
520 _aThis is the second edition of Wil van der Aalst's seminal book on process mining, which now discusses the field also in the broader context of data science and big data approaches. It includes several additions and updates, e.g. on inductive mining techniques, the notion of alignments, a considerably expanded section on software tools and a completely new chapter of process mining in the large. It is self-contained, while at the same time covering the entire process-mining spectrum from process discovery to predictive analytics. After a general introduction to data science and process mining in Part I, Part II provides the basics of business process modeling and data mining necessary to understand the remainder of the book. Next, Part III focuses on process discovery as the most important process mining task, while Part IV moves beyond discovering the control flow of processes, highlighting conformance checking, and organizational and time perspectives. Part V offers a guide to successfully applying process mining in practice, including an introduction to the widely used open-source tool ProM and several commercial products. Lastly, Part VI takes a step back, reflecting on the material presented and the key open challenges. Overall, this book provides a comprehensive overview of the state of the art in process mining. It is intended for business process analysts, business consultants, process managers, graduate students, and BPM researchers.
650 4 _aWorkflow
_xManagement
650 4 _aManagement
_xData processing
650 4 _aData mining
650 4 _aBusiness intelligence
856 _uhttps://search.ebscohost.com/login.aspx?direct=true&db=nlebk&AN=1203872&site=ehost-live
942 _2lc
_cEBB
_n0
998 _eReference No: 4736965 / 10.12.21 / ns277138 Date: 12 October 2021 -- (UTB) – EBSCO International, INC
999 _c21254
_d21254