9783319272429-331927242X-Data-Driven Process Discovery and Analysis: 4th International Symposium, SIMPDA 2014, Milan, Italy, November 19-21, 2014, Revised Selected Papers ... in Business Information Processing, 237)

Data-Driven Process Discovery and Analysis: 4th International Symposium, SIMPDA 2014, Milan, Italy, November 19-21, 2014, Revised Selected Papers ... in Business Information Processing, 237)

ISBN-13: 9783319272429
ISBN-10: 331927242X
Edition: 1st ed. 2015
Author: Barbara Russo, Paolo Ceravolo, Rafael Accorsi
Publication date: 2015
Publisher: Springer
Format: Paperback 132 pages
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Book details

ISBN-13: 9783319272429
ISBN-10: 331927242X
Edition: 1st ed. 2015
Author: Barbara Russo, Paolo Ceravolo, Rafael Accorsi
Publication date: 2015
Publisher: Springer
Format: Paperback 132 pages

Summary

Data-Driven Process Discovery and Analysis: 4th International Symposium, SIMPDA 2014, Milan, Italy, November 19-21, 2014, Revised Selected Papers ... in Business Information Processing, 237) (ISBN-13: 9783319272429 and ISBN-10: 331927242X), written by authors Barbara Russo, Paolo Ceravolo, Rafael Accorsi, was published by Springer in 2015. With an overall rating of 4.3 stars, it's a notable title among other books. You can easily purchase or rent Data-Driven Process Discovery and Analysis: 4th International Symposium, SIMPDA 2014, Milan, Italy, November 19-21, 2014, Revised Selected Papers ... in Business Information Processing, 237) (Paperback) from BooksRun, along with many other new and used books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $0.3.

Description

This book constitutes the thoroughly refereed proceedings of the Fourth International Symposium on Data-Driven Process Discovery and Analysis held in Riva del Milan, Italy, in November 2014. The five revised full papers were carefully selected from 21 submissions. Following the event, authors were given the opportunity to improve their papers with the insights they gained from the symposium. During this edition, the presentations and discussions frequently focused on the implementation of process mining algorithms in contexts where the analytical process is fed by data streams. The selected papers underline the most relevant challenges identified and propose novel solutions and approaches for their solution.
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