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Process mining techniques in busines...

Burattin, Andrea.

Process mining techniques in business environmentstheoretical aspects, algorithms, techniques and open challenges in process mining /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Process mining techniques in business environmentsby Andrea Burattin.
其他題名:	theoretical aspects, algorithms, techniques and open challenges in process mining /
作者:	Burattin, Andrea.
出版者:	Cham :Springer International Publishing :2015.
面頁冊數:	xii, 220 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
標題:	Data mining.
電子資源:	http://dx.doi.org/10.1007/978-3-319-17482-2
ISBN:	9783319174822 (electronic bk.)

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

Process mining techniques in business environmentstheoretical aspects, algorithms, techniques and open challenges in process mining /[electronic resource] :by Andrea Burattin. - Cham :Springer International Publishing :2015. - xii, 220 p. :ill., digital ;24 cm. - Lecture notes in business information processing,2071865-1348 ;. - Lecture notes in business information processing ;96..

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.

ISBN: 9783319174822 (electronic bk.)

Standard No.: 10.1007/978-3-319-17482-2doiSubjects--Topical Terms:

184440
Data mining.

LC Class. No.: QA76.9.D343

Dewey Class. No.: 006.312

Process mining techniques in business environmentstheoretical aspects, algorithms, techniques and open challenges in process mining /
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