Process Mining

@article{vanderAalst2012ProcessM,
  title={Process Mining},
  author={Wil M.P. van der Aalst},
  journal={Informatik-Spektrum},
  year={2012},
  volume={35},
  pages={354-359}
}
Using real event data to X-ray business processes helps ensure conformance between design and reality. 

Using Process Mining to Analyze an Emergency Service

TLDR
Digital solutions open up advances in institutions and in the services they provide, and any possible solution to solve this problem is seen as an opportunity to obtain innovative indications for improving the functioning of the institutions.

Process Mining Put into Context

TLDR
The authors argue that analysts should take into account the context in which events occur when analyzing processes and present guiding principles and challenges for process mining.

Discovering LTL based business rules from Event Logs

TLDR
The developed application LTLMiner aims at improving the performance of an existing tool TLQC used for business rule discovery using linear temporal logic business rules from event logs.

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TLDR
It is useful to diagnose in early stages of business process analysis and it encompasses performance performance evaluation and decision making in process mining.

Exploration and Assessment of Event Data

TLDR
A categorization scheme of event dependencies is defined and a preliminary approach for exploring event data is described, combining visual exploration with pattern mining, using either a sequential or a temporal scale.

Process Modelling from Insurance Event Log

TLDR
This paper has made an attempt to convert the event logs of the insurance process in to process model using petri net.

Title: Desire Lines in Big Data Desire Lines in Big Data

TLDR
This document describes a collection of techniques to discover, monitor and improve real processes by extracting knowledge from event data by extracting process models from an event log.

On the exploitation of process mining for security audits: the process discovery case

TLDR
This paper focuses on process discovery as a means to reconstruct process-related structures from event logs, such as the process' control flow, social network and data flows, so security analysis to determine the compliance with security and privacy requirements can be automated.

A model of the process of Big Data with generalized net

TLDR
Theoretical generalized net (GN) model is presented to follow the process of data lifecycle during a data analysis using Data Science, with various inner structure and near real time input speed.
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References

SHOWING 1-10 OF 40 REFERENCES

Process Mining - Discovery, Conformance and Enhancement of Business Processes

TLDR
This book provides real-world techniques for monitoring and analyzing processes in real time and is a powerful new tool destined to play a key role in business process management.

A novel approach for process mining based on event types

TLDR
A novel approach for process mining based on two event types, i.e., START and COMPLETE, is proposed and overcomes some of the limitations of existing algorithms such as the α-algorithm and therefore enhances the applicability of process mining.

Process mining: a research agenda

Model-Based Business Process Mining

TLDR
A newly released tool for analyzing ERP system logs is used to construct the underlying business flows and to provide new insights that can be used by the company to improve the procurement process.

A Rule-Based Approach for Process Discovery: Dealing with Noise and Imbalance in Process Logs

TLDR
This work proposes a method that constructs the process model from process log data, by determining the relations between process tasks, by employing machine learning technique to induce rule sets.

Trace Clustering in Process Mining

TLDR
This paper presents an approach using trace clustering, i.e., the event log is split into homogeneous subsets and for each subset a process model is created, and demonstrates that this approach can improve process mining results in real flexible environments.

Fuzzy Mining - Adaptive Process Simplification Based on Multi-perspective Metrics

TLDR
A new process mining approach is proposed that is configurable and allows for different faithfully simplifiedviews of a particular process, just like different roadmaps provide suitable abstractions of reality.

Semantic Analysis of Business Process Executions

TLDR
This paper presents a system and a set of techniques, developed at Hewlett-Packard, that overcome limitations, enabling the use of log data for efficient business-level analysis of business processes.

An Outlook on Semantic Business Process Mining and Monitoring

TLDR
An outlook on the opportunities and challenges on semantic business process mining and monitoring is presented, thus paving the way for the implementation of the next generation of BPM analysis tools.

XES, XESame, and ProM 6

TLDR
Two tools that use the eXtensible Event Stream format are presented - XESame and ProM 6 - and the main innovations and the role of XES are highlighted.