scholarly journals Applied Sequence Clustering Techniques for Process Mining

2011 ◽  
pp. 481-502 ◽  
Author(s):  
Diogo R. Ferreira
Keyword(s):  
Business Processes ◽  
Process Mining ◽  
Behavioral Patterns ◽  
Daily Work ◽  
Sequence Clustering ◽  
Event Logs ◽  
Common Trend ◽  
First Case ◽  
Insight Into

This chapter introduces the principles of sequence clustering and presents two case studies where the technique is used to discover behavioral patterns in event logs. In the first case study, the goal is to understand the way members of a software team perform their daily work, and the application of sequence clustering reveals a set of behavioral patterns that are related to some of the main processes being carried out by that team. In the second case study, the goal is to analyze the event history recorded in a technical support database in order to determine whether the recorded behavior complies with a predefined issue handling process. In this case, the application of sequence clustering confirms that all behavioral patterns share a common trend that resembles the original process. Throughout the chapter, special attention is given to the need for data preprocessing in order to obtain results that provide insight into the typical behavior of business processes.

scholarly journals Discovering Business Processes from Email Logs using fastText and Process Mining

2020 ◽  
Author(s):  
Yaghoub rashnavadi ◽  
Sina Behzadifard ◽  
Reza Farzadnia ◽  
sina zamani
Keyword(s):  
Machine Learning ◽  
Business Processes ◽  
Oil And Gas ◽  
Process Mining ◽  
The Body ◽  
Process Models ◽  
Supervised Machine Learning ◽  
Implicit Information ◽  
Oil And Gas Sector

<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>

Talking Technologically in Preschool and School: Three Case Examples

1996 ◽  
Vol 21 (2) ◽  
pp. 1-6 ◽  
Author(s):  
Marilyn Fleer
Keyword(s):  
Early Childhood ◽  
Young Children ◽  
Technology Education ◽  
Early Childhood Teacher ◽  
Case Examples ◽  
The Third ◽  
Very Young Children ◽  
First Case ◽  
Insight Into

This paper details three examples of technology education in process. The first case study highlights how an early childhood teacher comes to think about and plan for technology education. A series of diary entries are included to show the progression in thinking. In the second case study, a preschool teacher shows how very young children can participate in technology education. In the third case study a Year 3 teacher reveals how young children can become investigators in a simulated architects studio. The focus is on following the children's technological questions. All three case studies provide some insight into the sort of technological language that can be fostered in early childhood.

scholarly journals Database-Less Extraction of Event Logs from Redo Logs

2021 ◽  
pp. 73-82
Author(s):  
Dorina Bano ◽  
Tom Lichtenstein ◽  
Finn Klessascheck ◽  
Mathias Weske
Keyword(s):  
Performance Analysis ◽  
Real World ◽  
Business Processes ◽  
Process Mining ◽  
Detailed Knowledge ◽  
System Failure ◽  
Conformance Checking ◽  
Event Logs ◽  
Event Log ◽  
And Performance

Process mining is widely adopted in organizations to gain deep insights about running business processes. This can be achieved by applying different process mining techniques like discovery, conformance checking, and performance analysis. These techniques are applied on event logs, which need to be extracted from the organization’s databases beforehand. This not only implies access to databases, but also detailed knowledge about the database schema, which is often not available. In many real-world scenarios, however, process execution data is available as redo logs. Such logs are used to bring a database into a consistent state in case of a system failure. This paper proposes a semi-automatic approach to extract an event log from redo logs alone. It does not require access to the database or knowledge of the databaseschema. The feasibility of the proposed approach is evaluated on two synthetic redo logs.

scholarly journals Process Modelling Based on Event Logs

2018 ◽  
Vol 1 (1) ◽  
pp. 385-392
Author(s):  
Edyta Brzychczy
Keyword(s):  
Process Management ◽  
Process Mining ◽  
Process Analysis ◽  
Process Modelling ◽  
Process Models ◽  
Sources Of Information ◽  
Event Logs ◽  
It Systems ◽  
Many Sources

Abstract Process modelling is a very important stage in a Business Process Management cycle enabling process analysis and its redesign. Many sources of information for process modelling purposes exist. It may be an analysis of documentation related directly or indirectly to the process being analysed, observations or participation in the process. Nowadays, for this purpose, it is increasingly proposed to use the event logs from organization’s IT systems. Event logs could be analysed with process mining techniques to create process models expressed by various notations (i.e. Petri Nets, BPMN, EPC). Process mining enables also conformance checking and enhancement analysis of the processes. In the paper issues related to process modelling and process mining are briefly discussed. A case study, an example of delivery process modelling with process mining technique is presented.

Auditor Choices during Event Log Building for Process Mining

2019 ◽  
Vol 16 (2) ◽  
pp. 59-67
Author(s):  
Mieke Jans
Keyword(s):  
Analytical Procedure ◽  
Process Mining ◽  
Current Event ◽  
Dual Purpose ◽  
Event Logs ◽  
Event Log ◽  
Audit Evidence ◽  
Mining Projects ◽  
Made In

ABSTRACT Applying process mining as an analytical procedure is a relatively young stream of thought in auditing. This paper examines the first step of such process-mining projects, which involves extracting and structuring the data in the required format for analysis. The article has a dual purpose: (1) to provide an overview of the choices to be made in this phase, and (2) to provide insights into the current event log preferences of auditors. These insights are valuable for a better understanding of how event logs are currently structured, along with the consequences of this structure for the analytical procedure. This matter is important because different preparation steps could lead to varying analytical procedures and consequently, to other audit evidence. This study also aims to reveal what data are perceived as most valuable to the auditor for further analysis. To address this goal, a case study has been conducted.

Ateyyat El Abnoudy: Poetic Realism in Egyptian Documentaries

2017 ◽  
Author(s):  
Stefanie Van de Peer
Keyword(s):  
Young Female ◽  
The State ◽  
Political Situation ◽  
First Case ◽  
Short Films ◽  
The World ◽  
Poetic Realism ◽  
Female Filmmakers ◽  
Insight Into

The first case study deals with the ‘mother’ of Egyptian documentary making Ateyyat el Abnoudy, and traces her career as a lawyer, journalist and filmmaker. As a pioneer of politically engaged and socially preoccupied documentary, she has influenced many young female filmmakers. Since the early seventies, her films, both short and feature length, have been celebrated throughout the world at festivals and retrospectives, but remain controversial in Egypt itself. This case study looks in detail at her early short films, Horse of Mud (1971), Sad Song of Touha (1972) and The Sandwich (1975), as well as feature length documentaries Permissible Dreams (1982), Responsible Women (1994) and Days of Democracy (1996). Dealing with the lower classes, women’s issues, education and illiteracy among women, their personal status and their political situation in Egypt, the films reflect a concern with the subaltern woman. The filmmaker’s concern with the subaltern woman stems from an intellectual preoccupation with inequality and a professional insight into the unwillingness of the state to deal with women’s problems.

scholarly journals Simplified Process Model Discovery Based on Role-Oriented Genetic Mining

2014 ◽  
Vol 2014 ◽  
pp. 1-8
Author(s):  
Weidong Zhao ◽  
Xi Liu ◽  
Weihui Dai
Keyword(s):  
Process Model ◽  
Process Mining ◽  
Fitness Function ◽  
Control Flow ◽  
Process Models ◽  
Programming Approach ◽  
Event Logs ◽  
Process Complexity

Process mining is automated acquisition of process models from event logs. Although many process mining techniques have been developed, most of them are based on control flow. Meanwhile, the existing role-oriented process mining methods focus on correctness and integrity of roles while ignoring role complexity of the process model, which directly impacts understandability and quality of the model. To address these problems, we propose a genetic programming approach to mine the simplified process model. Using a new metric of process complexity in terms of roles as the fitness function, we can find simpler process models. The new role complexity metric of process models is designed from role cohesion and coupling, and applied to discover roles in process models. Moreover, the higher fitness derived from role complexity metric also provides a guideline for redesigning process models. Finally, we conduct case study and experiments to show that the proposed method is more effective for streamlining the process by comparing with related studies.

scholarly journals Generating Block-Structured Parallel Process Models by Demonstration

2021 ◽  
Vol 11 (4) ◽  
pp. 1876
Author(s):  
Julijana Lekić ◽  
Dragan Milićev ◽  
Dragan Stanković
Keyword(s):  
Business Process ◽  
Business Processes ◽  
Process Mining ◽  
Original Method ◽  
Process Models ◽  
Programming By Demonstration ◽  
Event Logs ◽  
Process Specification ◽  
Common Purpose ◽  
Block Structured

Programming by demonstration (PBD) is a technique which allows end users to create, modify, accommodate, and expand programs by demonstrating what the program is supposed to do. Although the ideal of common-purpose programming by demonstration or by examples has been rejected as practically unrealistic, this approach has found its application and shown potentials when limited to specific narrow domains and ranges of applications. In this paper, the original method of applying the principles of programming by demonstration in the area of process mining (PM) to interactive construction of block-structured parallel business processes models is presented. A technique and tool that enable interactive process mining and incremental discovery of process models have been described in this paper. The idea is based on the following principle: using a demonstrational user interface, a user demonstrates scenarios of execution of parallel business process activities, and the system gives a generalized model process specification. A modified process mining technique with the α|| algorithm applied on weakly complete event logs is used for creating parallel business process models using demonstration.

scholarly journals Discovering Business Processes from Email Logs Using fastText and Process Mining

2021 ◽  
Author(s):  
Yaghoub Rashnavadi ◽  
Sina Behzadifard ◽  
Reza Farzadnia ◽  
Sina Zamani
Keyword(s):  
Machine Learning ◽  
Text Classification ◽  
Business Processes ◽  
Process Mining ◽  
Real Life ◽  
Process Models ◽  
Supervised Machine Learning ◽  
Implicit Information

Communication is indispensable for today's lifestyle, and thanks to technology, millions of people can communicate as quickly as possible. The effect of this breakthrough has transformed organizations to the degree that they generate billions of emails daily to facilitate their operations. There is implicit information behind this vast corpus of human-generated content that can be mined and used for their benefit. This paper tries to address the opportunity that email logs can bring to organizations and propose an approach to discover process models by combining supervised text classification and process mining. This framework consists of two main steps, text classification, and process mining. First, Emails will be classified with supervised machine learning, and to mine, the processes fuzzy Miner is used. To further investigate the application of this framework, we also applied this framework over a real-life dataset from a case study organization.

scholarly journals Discovering Business Processes from Email Logs using fastText and Process Mining

2020 ◽  
Author(s):  
Yaghoub rashnavadi ◽  
Sina Behzadifard ◽  
Reza Farzadnia ◽  
sina zamani
Keyword(s):  
Machine Learning ◽  
Business Processes ◽  
Oil And Gas ◽  
Process Mining ◽  
The Body ◽  
Process Models ◽  
Supervised Machine Learning ◽  
Implicit Information ◽  
Oil And Gas Sector

<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>

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