• Journal of applied mathematics & informatics
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• 제41권5호
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• pp.1129-1143
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• 2023

Social media platforms have become an integral part of our daily lives, and they generate vast amounts of data that can be analyzed for various purposes. However, the quality of the data obtained from social media is often questionable due to factors such as noise, bias, and incompleteness. Enhancing data quality is crucial to ensure the reliability and validity of the results obtained from such data. This paper proposes an enhanced decision-making framework based on Business Decision Management Systems (BDMS) that addresses these challenges by incorporating a data quality enhancement component. The framework includes a backtracking method to improve plan failures and risk-taking abilities and a steep optimized strategy to enhance training plan and resource management, all of which contribute to improving the quality of the data. We examine the efficacy of the proposed framework through research data, which provides evidence of its ability to increase the level of effectiveness and performance by enhancing data quality. Additionally, we demonstrate the reliability of the proposed framework through simulation analysis, which includes true positive analysis, performance analysis, error analysis, and accuracy analysis. This research contributes to the field of business intelligence by providing a framework that addresses critical data quality challenges faced by organizations in decision-making environments.

• 한국전자거래학회지
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• 제15권4호
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• pp.79-99
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• 2010

e-비즈니스의 활성화로 기업과 조직에서 이해당사자 간의 데이터 교환이 활발해 짐에 따라, 신뢰성 있는 데이터의 확보 및 관리가 시급한 과제로 떠오르고 있다. 이러한 문제를 해결하기 위해, 본 논문은 데이터의 품질을 체계적으로 관리할 수 있는 프레임워크를 시나리오와 함께 제시한다. 데이터 품질 관리 프레임워크는 데이터 품질 모니터링, 데이터 품질 개선, 데이터 활용의 3단계로 구분되어 있으며 각 단계마다 3개씩, 총 9개의 프로세스로 구성되어 있다. 각 프로세스에는 필요성, 기능, 역할, 프로세스간의 관계가 명시되어 있다. 또한, 본 프레임워크를 현장에 직접 적용할 수 있도록, e-비즈니스에서 많이 사용되는 상품식별 및 분류 코드체계의 사례를 이용하여 업무 시나리오를 제시하였다.

• Journal of Information Technology Applications and Management
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• 제10권4호
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• pp.103-118
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• 2003

This study presents a database quality evaluation framework. As a way to build a framework, this study expands data quality management to include data transformation processes as well as data. Further, an information structure graph is applied to represent data transformations processes. An information structure graph is absed on a relational database scheme. Thus, data transformation processes may be stored in a relational database. This kind of integration of data transformation metadata with technical metadata eases evaluation of database qualities and their causes.

• 간호행정학회지
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• 제18권2호
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• pp.222-233
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• 2012

Purpose: This study was conducted to develop an evaluation framework for QI activity in medical institutions and to analyze QI activity cases by applying the developed evaluation framework. Method: A four-phase process was employed to develop the evaluation framework, and a descriptive survey was used for the QI case study. Data were collected in April, 2010 by examining 157 QI activity cases presented at conferences and published in Journal of Korean Society of Quality Assurance in Health Care over the past three years. Developed QI activity evaluation instruments were used for data collection. Data were analyzed using the SPSS 18.0 for Windows program. Result: A QI Activity Evaluation Framework was developed. This framework consisted of 45 items. The department with the highest level of QI participation was the nursing department. The most frequent QI activity theme was patient safety. QI activity levels in Korean medical institutions are relatively equalized without significant differences according to institution characteristics. Conclusions: From the quality aspect of QI activity, more systematic and scientific approaches are required to upgrade QI activity. This study could provide methodological guidelines for QI activity and be useful in setting goals and directions for QI activity in medical institutions in Korea.

• 반도체디스플레이기술학회지
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• 제20권2호
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• pp.121-125
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• 2021

Cloud service has the characteristic that it must be always available and that it must be able to respond immediately to user requests. This study suggests a method for constructing a proactive and autonomous quality and performance management system to meet these characteristics of cloud services. To this end, we identify quantitative measurement factors for cloud service quality and performance management, define a structure for applying a time series framework to cloud service application quality and performance management for proactive management, and then use big data and artificial intelligence for autonomous management. The flow of data processing and the configuration and flow of big data and artificial intelligence platforms were defined to combine intelligent technologies. In addition, the effectiveness was confirmed by applying it to the cloud service quality and performance management system through a case study. Using the methodology presented in this study, it is possible to improve the service management system that has been managed artificially and retrospectively through various convergence. However, since it requires the collection, processing, and processing of various types of data, it also has limitations in that data standardization must be prioritized in each technology and industry.

• 한국전자거래학회지
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• 제14권3호
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• pp.39-57
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• 2009

전자거래가 보편화 되고 전자카탈로그 데이터의 양이 증가하면서 데이터 품질을 관리할 수 있는 체계적인 접근 방법이 필요해지고 있다. 이러한 필요성에 따라 여기서는 프로세스 기반의 전자카탈로그 데이터 품질관리 프레임워크를 제시한다. 이것은 기업이나 조직 의 전자카탈로그 시스템의 기대를 만족시키기 위해 지속적으로 수행하는 데이터 관리 및 개선 활동에 대한 방법이다. 이 프레임워크에서는 품질관리를 위한 대상이 데이터, 데이터 품질관리 항목, 데이터 품질관리 프로세스의 세 가지로 구분된다. 세 가지 관리 대상은 다시 관리조직의 레벨인 총괄데이터 책임자, 데이터 관리자, 사용자에 따라 세분화 되어 제시된다.

• 품질경영학회지
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• 제50권1호
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• pp.1-19
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• 2022

Purpose: The purpose of this study is to design a system for quality management and improvement of overall public services. Methods: Literature Review, Framework Design Method, Case Studies Analysis Results: Public Service Quality Management Principles, Definition of Public Services Quality Management Areas, Quality Management Guidelines, Service Quality Management Tools Conclusion: In this study, a study case of the public service quality management framework, which is a system that supports overall quality management and continuous quality improvement of public services, is presented. The management system was designed based on the existing research results and domestic and foreign cases of public service standardization, targeting the entire public service.

• 한국빅데이터학회지
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• 제3권1호
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• pp.33-40
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• 2018

4차 산업혁명이 일어나면서 각 산업에서 새로운 개념이 탄생되었다. 각 산업의 새로운 개념은 빅데이터를 핵심 인프라로 가정하여 발전하고 있다. 따라서 빅데이터에 대한 품질관리가 점점 중요해 지고 있다. 본 논문에서는 빅데이터 품질 사례 연구를 통하여 빅데이터 품질관리 체계를 제시하고자 한다. 사례 연구를 위하여 새로운 정보기술을 활용한 법률서비스인 리걸테크 분야를 대상으로 하였다. 최근에 구현하고 있는 법무부 생활법률지식서비스를 위한 빅데이터 품질체계를 도출하였다.

• Asian Journal of Innovation and Policy
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• 제9권1호
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• pp.12-35
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• 2020

Quality performance information has been regarded as a significant step toward managing public performance. Although a correlation between the quality of information and its actual usage among managers in high-accountability policy areas has been found, quality performance information has not been properly provided to practitioners. This study takes an Institutional Analysis and Development approach to assess an appropriate institutional framework that facilitates state agencies and academics to coproduce this information. Based on a conceptual framework, we analyze a public information system of the Workforce Data Quality Initiative in Ohio and carry out a content analysis with NVIVO. It is found that arrangements that can manage the incentive dynamic in this process may help to align heterogeneous stakeholders in a mutually supportive fashion. Also, the research agenda and information resulted from being coproduced for management and academic purposes, simultaneously. This use of administrative data sheds light on how quality performance information can be coproduced under an appropriate institutional arrangement between administration and research communities. It is suggested that accessibility to the information system among various stakeholders should be improved.

• International Journal of Quality Innovation
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• 제2권2호
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• pp.93-100
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• 2001

This paper illustrates a prototyping framework of the documentation-standards retrieval system via the data mining approach for enhancing software development quality. We first present an approach for designing a retrieval algorithm based on data mining, with the three basic technologies of machine learning, statistics and database management, applied to this system to speed up the searching time and increase the fitness. This approach derives from the observation that data mining can discover unsuspected relationships among elements in large databases. This observation suggests that data mining can be used to elicit new knowledge about the design of a subject system and that it can be applied to large legacy systems for efficiency. Finally, software development quality will be improved at the same time when the project managers retrieving for the documentation standards.