scholarly journals Process Mining in Supply the Need for Rule-Based Knowledge Abstraction

Organizations struggle to achieve insight in however their business processes square measure conducted actually. Method mining allows organizations to extract this data} by analyzing business events recorded in their information systems. However, the business events recorded in these systems don't forever mirror constant level of abstraction because the desired method model that's employed by the business. Current method mining approaches offer light attention to the current gap. This paper proposes many information preparation strategies that apply provision domain information for method mining the fabric movements among a corporation additionally, associate degree custom-made method mining project methodology is bestowed that expressly includes these preparation strategies.

Author(s):  
S. A. Roshchektaev ◽  
U. Yu. Roshchektaeva

The article discusses the methodological basis and practice of using Process mining technology to improve the efficiency of business processes of Russian companies. The challenges of the digital economy and prerequisites for the development of Process mining methods are identified. The directions of transformation of approaches to process management in the conditions of application of Process mining methods are established. The main synergy effects of internal audit and Process mining are identified. The stages of implementation of the Process mining project and quality criteria for corporate data logs are considered. An algorithm of actions is proposed to prepare for the introduction of Process mining technology in Russian companies; to obtain the identified synergy effects by internal audit.There is no conflict of interests.


Author(s):  
Mohamed Boukhebouze ◽  
Youssef Amghar ◽  
Aïcha Nabila Benharkat ◽  
Zakaria Maamar

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Shabnam Shahzadi ◽  
Xianwen Fang ◽  
David Anekeya Alilah

For exploitation and extraction of an event’s data that has vital information which is related to the process from the event log, process mining is used. There are three main basic types of process mining as explained in relation to input and output. These are process discovery, conformance checking, and enhancement. Process discovery is one of the most challenging process mining activities based on the event log. Business processes or system performance plays a vital role in modelling, analysis, and prediction. Recently, a memoryless model such as exponential distribution of the stochastic Petri net SPN has gained much attention in research and industry. This paper uses time perspective for modelling and analysis and uses stochastic Petri net to check the performance, evolution, stability, and reliability of the model. To assess the effect of time delay in firing the transition, stochastic reward net SRN model is used. The model can also be used in checking the reliability of the model, whereas the generalized stochastic Petri net GSPN is used for evaluation and checking the performance of the model. SPN is used to analyze the probability of state transition and the stability from one state to another. However, in process mining, logs are used by linking log sequence with the state and, by this, modelling can be done, and its relation with stability of the model can be established.


2020 ◽  
Author(s):  
Yaghoub rashnavadi ◽  
Sina Behzadifard ◽  
Reza Farzadnia ◽  
sina zamani

<p>Communication has never been more accessible than today. With the help of Instant messengers and Email Services, millions of people can transfer information with ease, and this trend has affected organizations as well. There are billions of organizational emails sent or received daily, and their main goal is to facilitate the daily operation of organizations. Behind this vast corpus of human-generated content, there is much implicit information that can be mined and used to improve or optimize the organizations’ operations. Business processes are one of those implicit knowledge areas that can be discovered from Email logs of an Organization, as most of the communications are followed inside Emails. The purpose of this research is to propose an approach to discover the process models in the Email log. In this approach, we combine two tools, supervised machine learning and process mining. With the help of supervised machine learning, fastText classifier, we classify the body text of emails to the activity-related. Then the generated log will be mined with process mining techniques to find process models. We illustrate the approach with a case study company from the oil and gas sector.</p>


Algorithms ◽  
2020 ◽  
Vol 13 (7) ◽  
pp. 161
Author(s):  
Ghada Elkhawaga ◽  
Mervat Abuelkheir ◽  
Sherif I. Barakat ◽  
Alaa M. Riad ◽  
Manfred Reichert

Business processes evolve over time to adapt to changing business environments. This requires continuous monitoring of business processes to gain insights into whether they conform to the intended design or deviate from it. The situation when a business process changes while being analysed is denoted as Concept Drift. Its analysis is concerned with studying how a business process changes, in terms of detecting and localising changes and studying the effects of the latter. Concept drift analysis is crucial to enable early detection and management of changes, that is, whether to promote a change to become part of an improved process, or to reject the change and make decisions to mitigate its effects. Despite its importance, there exists no comprehensive framework for analysing concept drift types, affected process perspectives, and granularity levels of a business process. This article proposes the CONcept Drift Analysis in Process Mining (CONDA-PM) framework describing phases and requirements of a concept drift analysis approach. CONDA-PM was derived from a Systematic Literature Review (SLR) of current approaches analysing concept drift. We apply the CONDA-PM framework on current approaches to concept drift analysis and evaluate their maturity. Applying CONDA-PM framework highlights areas where research is needed to complement existing efforts.


2020 ◽  
Vol 16 (3) ◽  
pp. 127-147
Author(s):  
Kingsley Okoye

Semantics has been a major challenge when applying the process mining (PM) technique to real-time business processes. The several theoretical and practical efforts to bridge the semantic gap has spanned the advanced notion of the semantic-based process mining (SPM). Fundamentally, the SPM devotes its methods to the idea of making use of existing (semantic) technologies to support the analysis of PM techniques. In principle, the semantic-based process mining method is applied through the acquisition and representation of abstract knowledge about the domain processes in question. To this effect, this paper demonstrates how the semantic concepts and process modelling (reasoning) methods are used to improve the outcomes of PM techniques from the syntactic to a more conceptual level. To do this, the study proposes an SPM-based framework that shows to be intelligent with a high level of semantic reasoning aptitudes. Technically, this paper introduces a process mining approach that uses information (semantics) about different activities that can be found in any given process to make inferences and generate rules or patterns through the method for annotation, semantic reasoning, and conceptual assertions. In turn, the method is theoretically applied to enrich the informative values of the resultant models. Also, the study conducts and systematically reviews the current tools and methods that are used to support the outcomes of the process mining as well as evaluates the results of the different methods to determine the levels of impact and its implications for process mining.


Author(s):  
Gustavo Bernardi Pereira ◽  
Eduardo Alves Portela Santos ◽  
Marcell Mariano Corrêa Maceno

Author(s):  
Kerstin Gerke ◽  
Konstantin Petruch ◽  
Gerrit Tamm

The inherent quality of business processes and their support through information technology (IT) increasingly plays a significant role in the economic success of an organization. More and more business processes are supported through IT services. In order to provide IT services with the required quality and at minimum costs, the importance of effective and efficient IT service management (ITSM) processes is crucial. In this contribution, the authors present a new approach, which allows the continual process improvement by the interconnection of the ITIL reference model, the 7-step improvement process, and process mining. On the basis of the reference model, to-be processes are set and key indicators are determined. As-is processes and their key indicators derived by process mining are subsequently compared to the to-be processes. This new approach enables the design, control, and improvement of ITIL based customer support processes, which will be trialed in practice.


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