• Journal of KIISE:Computing Practices and Letters
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• v.16 no.3
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• pp.301-315
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• 2010

Recently, competition between companies has intensified and so has the necessity of creating a new business value inventions has increased. A numbers of Business organizations are beginning to realize the importance of business process management. Processes however can often not go the way they were initially designed or non-efficient performance process model could be designed. This can be due to a lack of cooperation and understanding between business analysts and system developers. To solve this problem, business process mining which can be used as the basis of the business process re-engineering has been recognized to an important concept. Current process mining research has only focused their attention on extracting workflow-based process model from competed process logs. Thus there have a limitations in expressing various forms of business processes. The disadvantage in this method is process discovering time and log scanning time in itself take a considerable amount of time. This is due to the re-scanning of the process logs with each new update. In this paper, we will presents a modified FP-Tree algorithm for FP-Tree based business processes, which are used for association analysis in data mining. Our modified algorithm supports the discovery of the appropriate level of process model according to the user's need without re-scanning the entire process logs during updated.

• Journal of Information Technology and Architecture
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• v.11 no.1
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• pp.25-32
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• 2014

Web mining techniques are often used to discover useful patterns from data log generated by Web servers for the purpose of web usage analysis. Yet traditional Web mining techniques do not reflect sufficiently sequential properties of Web log data. To address such weakness, we introduce a framework for analyzing Web access log data by using process mining techniques. To illustrate the proposed framework, we show the analysis of Web access log in a campus information system based on the framework and discuss the implication of the analysis result.

• Information Systems Review
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• v.20 no.1
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• pp.81-98
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• 2018

ERP supports the automation and integration of business processes of enterprises and records voluminous data about the business activities of enterprises. The academe and business enterprises are focusing on process mining, which improves the performance of business processes and strengthens compliance. However, these studies focused on analysis of the business process of large companies, which adopts foreign ERP, such as SAP ERP or Oracle ERP. In comparison with foreign ERP, domestic ERP lags behind in terms of logging and managing of event data. Therefore, the application of process mining to domestic ERP is a challenging task. The present study aims to analyze domestic ERP based on process mining to overcome this challenge. This study discusses the lessons learned from a case study in a Korean cosmetics manufacturing company. Our results are expected to strengthen the competitiveness of Korean small and medium-sized enterprises that adopt domestic ERP and realize the outcomes of the large investment of the Korean government on the ERP implementation of enterprises.

• The Journal of Bigdata
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• v.1 no.2
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• pp.65-78
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• 2016

In the rapid change of business environment, it is crucial that several companies with core competence cooperate together in order to deliver competitive products to the market faster. Thus a lot of companies are participating in supply chains and SCM (Supply Chain Management) become more important. To efficiently manage supply chains, the analysis of data from SCM systems is required. In this paper, we explain how to analyze SCM related data with process mining techniques. After discussing the data requirement for process mining, several process mining techniques for the data analysis are explained. To show the applicability of the techniques, we have performed a case study with a company in South Korea. The case study shows that process mining is useful tool to analyze SCM data. On specifically, an overall process, several performance measures, and social networks can be easily discovered and analyzed with the techniques.

• Proceedings of the Korean Information Science Society Conference
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• 2005.07b
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• pp.109-111
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• 2005

비즈니스 프로세스를 연구하는데 있어 최근의 이슈는 비즈니스 프로세스가 복잡화되고 대량화됨에 따라, 비즈니스 프로세스를 좀더 효율적으로 개선하고자 하는 데에 맞춰져 있으며, 이러한 동향에 힘입어 워크플로우 마이닝이라는 연구분야가 생겨나게 되었다. 이에, 본 논문에서는 워크플로우 패턴을 기반으로 한 워크플로우 마이닝 기법에 관하여 연구하고, 기술한다. 첫째로, 기본적으로 워크플로우 마이닝 기술과 그의 근원이 되는 워크플로우 로그에 관하여 간략히 설명한다. 그리고, 패턴기반 워크플로우 마이닝을 하기 위한 기본적인 워크플로우 패턴에 관하여 기술하고, 패턴 기반 워크플로우 마이닝을 하기 위한 기법으로 몇 가지 알고리즘을 제시한다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.12B
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• pp.1509-1521
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• 2011

WfMC, which is one of the international standardization organizations leading the business process and workflow technologies, has been officially released the BPAF1.0 that is a standard format to record process instances' event logs according as the business process intelligence mining technologies have recently issued in the business process and workflow literature. The business process mining technologies consist of two groups of algorithms and their analysis techniques; one is to rediscover flow-oriented process-intelligence, such as control-flow, data-flow, role-flow, and actor-flow intelligence, from process instances' event logs, and the other has something to do with rediscovering relation-oriented process-intelligence like process-driven social networks and process-driven affiliation networks from the event logs. The current standardized format of BPAF1.0 aims at only supporting the control-flow oriented process-intelligence mining techniques, and so it is unable to properly support the relation-oriented process-intelligence mining techniques. Therefore, this paper tries to extend the BPAF1.0 so as to reasonably support the relation-oriented process-intelligence mining techniques, and the extended BPAF is termed BPAF2.0. Particularly, we have a plan to standardize the extended BPAF2.0 as not only the national standard specifications through the e-Business project group of TTA, but also the international standard specifications of WfMC.

• Journal of Internet Computing and Services
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• v.17 no.6
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• pp.123-131
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• 2016

Process mining in big data environment utilize a number of data were generated from the business process. It generates lots of knowledge and insights regarding implementation and improvement of the process through the event log of the company's enterprise resource planning (ERP) system. In recent years, various research activities engaged with the audit work of company organizations are trying actively by using the maximum strength of the mining process. However, domestic studies on applicable sales auditing system for the process mining are insufficient under big data environment. Therefore, we propose process-mining methods that can be optimally applied to online and traditional auditing system. In advance, we propose continuous monitoring information system that can early detect and prevent the risk under the big data environment by monitoring risk factors in the organizations of enterprise. The scope of the research of this paper is to design a pre-verification system for risk factor via practical examples in sales auditing. Furthermore, realizations of preventive audit, continuous monitoring for high risk, reduction of fraud, and timely action for violation of rules are enhanced by proposed sales auditing system. According to the simulation results, avoidance of financial risks, reduction of audit period, and improvement of audit quality are represented.

• The Journal of the Korea Contents Association
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• v.17 no.5
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• pp.221-233
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• 2017

To survive in the ever-changing environment, organizations need to improve or innovate their business processes. As a result, to attain this objective, BPM (Business Process Management) concept is widely adopted in modern enterprises. BPM life cycle consists of diagnosis, design, implementation and enactment. Conventionally, diagnosis of business process within the BPM life cycle is usually conducted by manual methods such as interviews, questionnaires and direct observations of process. And (re)designing business processes is also usually done manually under supervision of business experts from scratch. It is time-consuming and error-prone tasks. The objective of this research is to integrate the diagnosis and (re)design phase of BPM life cycle by sharing automatically generated process model and basic statistics in the diagnosis phase based on the process mining method. Eventually, this approach will lead to automate the tasks of diagnosis and design of business process. To implement and to show the usefulness of the proposed framework, two case studies were conducted in this research.

• Proceedings of the Korean Information Science Society Conference
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• 2004.10b
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• pp.127-129
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• 2004

비즈니스 프로세스의 정의 및 실행이 복잡화되고 대량화되면서, 비즈니스 프로세스를 좀더 효율적으로 개선하고자 하는 노력이 필요하게 되었다. 본 논문에서는 그러한 노력을 위해 도달가능경로를 이용한 워크플로우 마이닝 기법을 사용하여, 문제를 해결하고자 한다. 따라서, 본 논문에서는 워크플로우 마이닝을 하기 위하여, ICN(Information Control Net) 모델을 기반으로 정의된 프로세스 모델을 도달가늠경로를 찾아내기 위하여 WDN(Workflow Dependent Net)으로 구성을 한 후, MWN(Minimal Workflow Net)으로 변환하여, 도달가능경로를 구성할 수 있는 정보를 얻을 수 있도록 하는데 목적을 둔다.

• Proceedings of the Korea Information Processing Society Conference
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• 2005.05a
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• pp.113-116
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• 2005

워크플로우의 도입으로 인하여 다수의 기업은 업무의 효율성을 증대 시켰다. 하지만, 진정한 기업 업무의 효율성 증대는 워크플로우의 도입으로 인한 비즈니스 프로세스의 자동화뿐만 아니라 비즈니스 프로세스 설계의 최적화 및 개선이라고 판단된다. 이에 본 논문에서는 의존성 기반의 워크플로우 마이닝 기법에 관하여 제시 하며, 비즈니스 프로세스 설계의 최적화 및 개선을 위하여 어떠한 방법으로 접근해 나아가야 할지에 관하여 논한다.