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Big Data Process Analysis: From Data Mining to Process Mining.

Authors: GIACALONE, Massimiliano; Carlo Cusatelli; Roberto Casadei; Angelo Romano; Vito Santarcangelo;

Big Data Process Analysis: From Data Mining to Process Mining.

Abstract

Process mining is the approach that extracts real workflows by database of events (logs) and compares them to the predefined procedures estimating the process gap for process improvement. It is a different overture from Data Mining that extracts hidden information and relations from data, with whom it is often confused. The most important tool for the development of process mining is ProM, an open source suite which implements a lot of technical approaches for process mining. This paper aims to present Process Mining approach showing the differences from Data Mining, and the implementation by ProM on real logs of an Italian company, comparing the extracted workflows to ISO9001 predefined procedures.

Country
Italy
Keywords

Big Data, Process Mining, Data Mining, Big Data; Process Mining; Process Tool; Data Mining, Big Data, Process Mining, Process Tool, Data Mining., Process Tool

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green
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