• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.6
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• pp.643-648
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• 2003

In order to provide efficient retrieving results for user query on the web environment, the various searching algorithms have developed and considered user's preference and convenience. However, the searching algorithms are developed on the horizontal and non hierarchical web environment in general and could not apply to the complex hierarchical and functional web environments such like the enterprise network. In this paper, we purpose the multi-agent based web mining system which can provide the efficient mining results to the user on the special web environment. For doing this, we suggest the network model with the hierarchical web environment and model the multi agent based web mining system which has four corporation agents and fourteen process modules. Then, we explain the detailed functions of each agent considered the hierarchical environment according to the module. Especially, we purpose the new merging agent and improved ranking algorithm by using the graph theory.

• Journal of Internet Computing and Services
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• v.6 no.6
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• pp.57-69
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• 2005

This paper proposes a minimal workflow model as a feasible solution to the workflow process rediscovery problem. The minimal workflow model can be represented by the minimal workflow net. The process model is represented by ICN(Information Control Net) Modeling method, ICN can configure activity dependent net applying proper algorithm according to activity dependency among activities which configure the ICN, The proposed model is possible to develop with the application of minimal workflow net and with the application of the algorithm related to activity dependent net properties, Hence, it can solve the process rediscovery problem and can also be helpful on process improvement.

• Tunnel and Underground Space
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• v.32 no.1
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• pp.78-92
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• 2022

In this study, we proposed a diagnostics and assessment model for mining sites that can evaluate the smart mining technology level in a systematic and structured way. For this, the maturity of the smart mining was defined, and detailed assessment items of the diagnostics and assessment model for smart mining were derived by considering the smart factory diagnostics and assessment model (KS X 9001-3) used in the manufacturing industry. While maintaining the existing system, the existing 46 detailed assessment items were modified to be suitable for mining. As a result, a total of 29 detailed assessment items were derived in the areas of promotion strategy, process, information system and automation, and performance. Based on this, a questionnaire was designed to diagnose the level of smart mining technology, and assessment was performed by applying it to domestic iron mines. The level of smart mining technology in the study area was found to be level 2, and it could be inferred that it was about 40% lower than the average smart level of the general manufacturing industry. In addition, by using the developed model, it was possible to recognize the weak points of the mine at each stage of the introduction, operation, and advancement of smart mining, and to suggest investment and improvement directions.

• Proceedings of the Korea Database Society Conference
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• 2001.06a
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• pp.345-361
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• 2001

인터넷의 확산으로 웹 구조, 웹 로그 등을 분석하는 웹마이닝(Web Mining)에 대한 연구가 활발히 진행되고 있다. 그러나 웹에서 발생하는 데이터에 대한 분석은 아직 미약한 상태이다. 웹에서 획득된 데이터는 신뢰도가 낮아 통계와 같은 기존의 분석 방법을 적용하기에 많은 어려움이 따른다. 또한 대용량 데이터와 실제 데이터에 유연한 분석을 제공하는 데이터 마이닝은 아직까지 적용 분야가 매우 한정되어 있다. 본 논문에서는 인터넷 사이트의 실제 데이터를 이용하여 데이터마이닝 과정에 따라 데이터 정제, 데이터 선택, 데이터 변환 등 효과적인 데이터 전처리 방법을 제시한다. 또한 이렇게 전처리된 데이터로 고객 세분화, 우수 고객 분류를 위한 데이터마이닝 기법을 적용한 후 수행 결과를 분석한다. 마지막으로 분석의 한계점을 지적하고 보다 양질의 데이터마이닝을 위한 시스템 및 사이트 설계 방안을 제시한다.

• 한국방재학회:학술대회논문집
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• 2010.02a
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• pp.69.1-69.1
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• 2010

본 연구는 교량 시설물의 재난방지를 위한 정보시스템의 구축에 있어 선행되어야 하는 교량 구조계산서 항목 저장정보의 질적 향상을 위해 XML 스키마 매칭 기법을 효율적으로 활용할 방법에 대해 제시하였다. 이를 위하여 XML 스키마 매칭에 사용되는 가중치 변화에 따른 매칭 정확도를 나타내는 데이터를 구축하고, 이를 활용하여 데이터 마이닝 기법 중 하나인 의사결정나무 모델을 구현하여 교량의 형식, 문서가 포함하고 있는 항목의 수, 문서를 작성한 회사에 따라 달라질 수 있는 최적의 가중치를 지동으로 선정할 수 있는 프로세스를 제안하였다. 의사결정나무 모델을 통해 결정한 매칭 가중치는 이전에 비하여 약 10% 정확도 상승효과가 있음을 알 수 있었다.

• Journal of Digital Convergence
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• v.12 no.8
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• pp.377-387
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• 2014

The purpose of this study is to suggest improvement ways of outpatient process via a simulation model and to improve operational efficiency. Three experimentation scenarios were implemented into the simulation model to determine which proposed scenario provides better improvement in terms of the following performance measures: LOS(Length of Stay), patient waiting time, patient travel time, and staff utilization. The hospital medical data collection and statistical tools used to analyze the process mining tools. And the PIOS simulation tool was used and the validity of the model was verified by using t-test. The simulation results demonstrated that oupatient process of center type is most efficient. Simulation approach is a powerful technique that supports efficient decision-making compared to traditional healthcare management approach based on past experience, feelings, and intuition. Therefore, the proposed experimentation model has wide applicability in healthcare systems.

• Journal of Internet Computing and Services
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• v.10 no.3
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• pp.113-129
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• 2009

Abstract Corporate activities are composed of numerous working processes and during the working flow, various business processes are being created and completed simultaneously. Enterprise Resources Planning (ERP) makes the working process simple, yet creates more complicated work structure and therefore, there is an absolute need of efficient management for business processes. The workflow literature has been looking for efficient and effective ways of rediscovering and mining workflow intelligence and knowledge from their enactment histories and event logs. As part of studies to analyze and improve the process, the concepts of 'Process Mining', 'Process re-discovery', 'BPR (Business Process Reengineering)' have appeared and the studies for practical implementation are proactively being done. However, these studies normally follow the approach throughout data warehousing for log data of process instances. It is very hard for these approaches to reflect user's intention to the rediscovering and mining activities. The process instances designed based on the consideration of analysis can make groupings effectively and when the analysis demand of user changes within the analysis domain can also reduce the cost of analysis. Therefore, the thesis proposes a special type of workflow model, which is called a colored workflow model, that is extended from the ICN (information control net) modeling methodology by reinforcing the concept of colored token. The colored tokens represent the conceptual types of constraints and criteria that can be used to classifying and grouping the workflow intelligence and knowledge extracted from the corresponding workflow models' enactment histories and event logs. Through the runtime information of process instances, it makes possible to analyze proactive and user-oriented process with the goal of deriving business knowledge from the beginning of process definition.

• Journal of Internet Computing and Services
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• v.20 no.1
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• pp.87-96
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• 2019

In this paper, we propose a MapReduce-supported clustering technique for collecting and classifying distributed workflow enactment event logs as a preprocessing tool. Especially, we would call the distributed workflow enactment event logs as Workflow BIG-Logs, because they are satisfied with as well as well-fitted to the 5V properties of BIG-Data like Volume, Velocity, Variety, Veracity and Value. The clustering technique we develop in this paper is intentionally devised for the preprocessing phase of a specific workflow process mining and analysis algorithm based upon the workflow BIG-Logs. In other words, It uses the Map-Reduce framework as a Workflow BIG-Logs processing platform, it supports the IEEE XES standard data format, and it is eventually dedicated for the preprocessing phase of the ${\rho}$-Algorithm that is a typical workflow process mining algorithm based on the structured information control nets. More precisely, The Workflow BIG-Logs can be classified into two types: of activity-based clustering patterns and performer-based clustering patterns, and we try to implement an activity-based clustering pattern algorithm based upon the Map-Reduce framework. Finally, we try to verify the proposed clustering technique by carrying out an experimental study on the workflow enactment event log dataset released by the BPI Challenges.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.6
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• pp.681-689
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• 2019

Web usage pattern discovery is an advanced means by using web log data, and it's also a specific application of data mining technology in Web log data mining. In education Data Mining (DM) is the application of Data Mining techniques to educational data (such as Web logs of University, e-learning, adaptive hypermedia and intelligent tutoring systems, etc.), and so, its objective is to analyze these types of data in order to resolve educational research issues. In this paper, the Web log data of a university are used as the research object of data mining. With using the database OLAP technology the Web log data are preprocessed into the data format that can be used for data mining, and the processing results are stored into the MSSQL. At the same time the basic data statistics and analysis are completed based on the processed Web log records. In addition, we introduced the Apriori Algorithm of Web usage pattern mining and its implementation process, developed the Apriori Algorithm program in Python development environment, then gave the performance of the Apriori Algorithm and realized the mining of Web user access pattern. The results have important theoretical significance for the application of the patterns in the development of teaching systems. The next research is to explore the improvement of the Apriori Algorithm in the distributed computing environment.

• Journal of Information Technology Applications and Management
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• v.21 no.4
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• pp.51-64
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• 2014

The purpose of operating the main homepage of University is to provide the related information about University resources to site visitors. In this study, we analyze website browsing patterns and extract characteristics of users in order to improve its utilization. The access log files to main homepage were used to analyze the browsing patterns and converted to process log files adaptable to a process mining tool, ProM. Finally we provide useful information about user friendly homepage design and suggest plans for improving its utilization to website operators.