• Title/Summary/Keyword: Data-driven Management

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Implementation of Management System for Contamination Vulnerability Calibration of the Ground Water by an Object-oriented Geographic Data Model (객체지향 지리 데이터 모델에 의한 지하수의 오취약성 분석을 위한 관리시스템 구현)

  • Lee, Hong-Ro
    • Journal of the Korean Association of Geographic Information Studies
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    • v.6 no.2
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    • pp.101-112
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    • 2003
  • This paper designs and implements the management system that can calibrate the contamination vulnerability of the ground water, using an object oriented data model. Geographic-objects are specified by features extracted from an applicable geographic domain, and geographic-fields are defined by chemical factors extracted from each driven water. To show the topological relationships among the geographic-objects and the geographic-fields, this paper attach the weight and the ratio of the drastic model to chemical factors represented on the land use digital map and the ground water digital map. The geographic feature class, administrative boundary class, land use class and driven water class consist of a class composition hierarchy for evaluating the convenient contamination vulnerability calibration with spatial relationships among the well objects. Therefore, this management system for evaluating the contamination vulnerability can also contribute to the application of other natural environments.

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A study on strategic use of MyData: Focused in Financial Services (금융 마이데이터의 전략적 활용에 관한 사례 연구)

  • Lee, Ju-Hee
    • Journal of Digital Convergence
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    • v.20 no.3
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    • pp.181-189
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    • 2022
  • The purpose of this study is to investigate the innovation of business model and the effectiveness of the data-driven model. the main concepts and policies related to the data economy are reviewed, and implications are drawn through the analysis of data-based convergence service creation cases. This study identified the existing data-driven business model of the creation of MyData service industry in the financial industry and concept of the data economy. According to the empirical analysis result, this study confirmed that t considering the mobile environment and consumer acceptance of data portability, the ripple effect of the implementation of My Data on the financial industry is expected to be significant.

Compromising Multiple Objectives in Production Scheduling: A Data Mining Approach

  • Hwang, Wook-Yeon;Lee, Jong-Seok
    • Management Science and Financial Engineering
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    • v.20 no.1
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    • pp.1-9
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    • 2014
  • In multi-objective scheduling problems, the objectives are usually in conflict. To obtain a satisfactory compromise and resolve the issue of NP-hardness, most existing works have suggested employing meta-heuristic methods, such as genetic algorithms. In this research, we propose a novel data-driven approach for generating a single solution that compromises multiple rules pursuing different objectives. The proposed method uses a data mining technique, namely, random forests, in order to extract the logics of several historic schedules and aggregate those. Since it involves learning predictive models, future schedules with the same previous objectives can be easily and quickly obtained by applying new production data into the models. The proposed approach is illustrated with a simulation study, where it appears to successfully produce a new solution showing balanced scheduling performances.

Development of knapsack problem solver using relational DBMS (관계형 데이터베이스를 이용한 배낭문제 해법기의 구현)

  • 서창교;송구선
    • Korean Management Science Review
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    • v.13 no.2
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    • pp.73-94
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    • 1996
  • Knapsack problems represent many business application such as cargo loading, project selection, and capital budgeting. In this research we developed a knapsack problem solver based on Martello-Toth algorithm using a relational database management system on the PC platform. The solver used the menu-driven user interface. The solver can be easily integrated with the database of decision support system because the solver can access the database to retrieve the data for the model and to store the result directly.

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Context-Driven Framework for High Level Configuration of Virtual Businesses (가상기업의 형성을 위한 컨텍스트 기반 프레임워크)

  • Lee, Kyung-Huy;Oh, Sang-Bong
    • Journal of Information Technology Applications and Management
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    • v.14 no.2
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    • pp.11-26
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    • 2007
  • In this paper we suggest a context-driven configuration model of virtual businesses to form a business network model consisting of role-based, interaction-centered business partners. The model makes use of the subcontext concept which explicitly represents actors and interactions in virtual business (VB) context. We separate actors who have capacities on tasks in a specific kind of role and actor subcontext which models requirements in specific interaction subcontext. Three kinds of actors are defined in virtual service chains, service user, service provider, and external service supporter. Interaction subcontext models a service exchange process between two actor subcontexts with consideration of context dependencies like task and quality dependencies. Each subcontext may be modeled in the form of a situation network which consists of a finite set of situation nodes and transitions. A specific situation is given in a corresponding context network of actors and interactions. It is illustrated with a simple example.

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A Study on the Development of a Quality-Driven CIM System (part l: Framework) (품질 지향적 CIM시스템 개발에 관한 연구 (제1부:Freamwork))

  • Kang, Mujin
    • Journal of the Korean Society for Precision Engineering
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    • v.13 no.12
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    • pp.63-69
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    • 1996
  • As the significance of quality in the sense of customer satisfaction is growing, the management of quality becomes one of the main interests in the manufacturing systems research. This paper presents the concept of quality-driven CIM(Computer Integrated Manufacturing) system which is composed of a business process domain and a quality domain. In the business process domain, business functions are integrated by conventional design and manufacturing databases on the one hand, and an integrated quality system is interlinked to them via several quality modules on the other hand. Quality information model connects the business process domain with the quality domain where various types of quality data are stored in the form of quality database. This framework helps a manufacturing enterprise to implement the quality-driven CIM system to achieve its final objective "customer satisfaction".ion".uot;.

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A Study on Developing a Provenance Conceptual Model for Data-driven Electronic Records Based on Extending W3C PROV (PROV의 확장에 기초한 데이터형 전자기록의 출처 모델 연구)

  • Hyun, Moonsoo
    • The Korean Journal of Archival Studies
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    • no.80
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    • pp.5-41
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    • 2024
  • This study was conducted to develop a provenance representation model for data-type electronic records. It supports the distinction between provenance and context for the creation and management of data-type electronic records. To express both, it aims to design an extensible provenance model. For this purpose, W3C PROV is utilized as a basic model, with P-Plan and ProvONE for designing prospective provenance area. Afterward, the provenance model was extended by mapping the record management requirements. The provenance model proposed in this study is designed to represent and connect both retrospective and prospective provenance of data-type electronic records. Based on this study, it is expected to discussing the concept of provenance in the records management and archival studies area and to extending the model in the future.

Current Status and Proposal of University Library Research Data Management Service: Focused on Science and Technology Specialized Universities (대학도서관 연구데이터 관리 서비스 현황 및 제안 - 과학기술특성화 대학을 중심으로 -)

  • Juseop Kim;Suntae Kim
    • Journal of the Korean Society for Library and Information Science
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    • v.57 no.3
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    • pp.279-301
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    • 2023
  • The data-driven research environment is rapidly changing. Accordingly, domestic university libraries are also preparing to establish and operate research data management services to support university researchers. This study was designed to propose a research data management service to support researchers in science and technology specialized university libraries. In order to propose the service, 11 universities specializing in science and technology were selected from overseas and domestic universities and their research data management services were analyzed. Key categories were derived from analysis results, research data management, electronic research notebooks, and RDM training. In particular, the 'research data management' category included DMP, data collection, data management, data preservation, data sharing and publishing, data reuse, infrastructure and tools. And it consists of RDM guides and policies. The results of this study will be helpful in introducing and operating research data management services in science and technology specialized university libraries.

A Study of Relationship between Dataveillance and Online Privacy Protection Behavior under the Advent of Big Data Environment (빅데이터 환경 형성에 따른 데이터 감시 위협과 온라인 프라이버시 보호 활동의 관계에 대한 연구)

  • Park, Min-Jeong;Chae, Sang-Mi
    • Knowledge Management Research
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    • v.18 no.3
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    • pp.63-80
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    • 2017
  • Big Data environment is established by accumulating vast amounts of data as users continuously share and provide personal information in online environment. Accordingly, the more data is accumulated in online environment, the more data is accessible easily by third parties without users' permissions compared to the past. By utilizing strategies based on data-driven, firms recently make it possible to predict customers' preferences and consuming propensity relatively exactly. This Big Data environment, on the other hand, establishes 'Dataveillance' which means anybody can watch or control users' behaviors by using data itself which is stored online. Main objective of this study is to identify the relationship between Dataveillance and users' online privacy protection behaviors. To achieve it, we first investigate perceived online service efficiency; loss of control on privacy; offline surveillance; necessity of regulation influences on users' perceived threats which is generated by Dataveillance.

Insights Discovery through Hidden Sentiment in Big Data: Evidence from Saudi Arabia's Financial Sector

  • PARK, Young-Eun;JAVED, Yasir
    • The Journal of Asian Finance, Economics and Business
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    • v.7 no.6
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    • pp.457-464
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    • 2020
  • This study aims to recognize customers' real sentiment and then discover the data-driven insights for strategic decision-making in the financial sector of Saudi Arabia. The data was collected from the social media (Facebook and Twitter) from start till October 2018 in financial companies (NCB, Al Rajhi, and Bupa) selected in the Kingdom of Saudi Arabia according to criteria. Then, it was analyzed using a sentiment analysis, one of data mining techniques. All three companies have similar likes and followers as they serve customers as B2B and B2C companies. In addition, for Al Rajhi no negative sentiment was detected in English posts, while it can be seen that Internet penetration of both banks are higher than BUPA, rarely mentioned in few hours. This study helps to predict the overall popularity as well as the perception or real mood of people by identifying the positive and negative feelings or emotions behind customers' social media posts or messages. This research presents meaningful insights in data-driven approaches using a specific data mining technique as a tool for corporate decision-making and forecasting. Understanding what the key issues are from customers' perspective, it becomes possible to develop a better data-based global strategies to create a sustainable competitive advantage.