• 품질경영학회지
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• 제29권4호
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• pp.133-152
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• 2001

In order to have competitive advantage for the business firms, companies need to raise competitiveness through the effective distribution and practical use of management resources along with strategic management of integration of existing management systems such as quality and business environment. Upon resulting of questionnaires to expert group, it is definite to have an integration of quality and environment system for the better efficiency of firms, and also recommended to have either a mixture of two systems or build up new integration system through uniform of two systems. The effects of the integrated system can be summarized as an increase of company image, efficiency of system operation, simplification of system management, synergy effects on the integration.

• 동아시아경상학회지
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• 제8권1호
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• pp.21-40
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• 2020

Purpose - The labor management department is an important area in charge of the labor-management relations that affects the competitiveness of the company. This study seeks to diagnose labor management education focusing on labor manager competency strengthening curriculum that is currently being conducted domestically and propose an educational model that can contribute to the labor manager competency development by researching improvement measures. Research design, data, and methodology - In this study, the first phase is a Delphi open form survey and 15 expert panels participated. The second phase had 31 expert panels participating and in the final IPA analysis, targeting 111 on-site subjects, it conducted a survey regarding desired level of current educational level and future education requirement. Results - A final 57 subjects regarding 11 items to increase the competency of the labor managers through the first and second Delphi survey was deduced through this study. To add, regarding the current education level and desired level that the current workers are thinking with respect to analysis results of the 57 subjects through the IPA analysis, an educational model could be deduced to increase competency of the labor managers based on the result. Conclusions - Thus far, research regarding labor management has been insufficient as it was defined as a subordinate role to human resources. This study reviews the role and competency of labor managers and presented an educational model to strengthen the capabilities of internal labor managers to re-illuminate the labor manager. However, this study is limited in terms of the diversity of the types of companies participating and the small number of panels. Better data can be produced if such parts are supplemented in the future.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2005년도 추계학술대회 학술발표 논문집 제15권 제2호
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• pp.271-275
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• 2005

In this research, we propose a Unified Fuzzy rule-based knowledge Inference Systems UFIS) to help the expert in cosmetic brand detection. Users' preferred cosmetic product detection is very important in the level of CRM. To this Purpose, many corporations trying to develop an efficient data mining tool. In this study, we develop a prototype fuzzy rule detection and inference system. The framework used in this development is mainly based on two different mechanisms such as fuzzy rule extraction and RDB (Relational DB)-based fuzzy rule inference. First, fuzzy clustering and fuzzy rule extraction deal with the presence of the knowledge in data base and its value is presented with a value between $0\∼1$. Second, RDB and SQL(Structured Query Language)-based fuzzy rule inference mechanism provide more flexibility in knowledge management than conventional non-fuzzy value-based KMS(Knowledge Management Systems)

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제5권4호
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• pp.353-359
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• 2005

In this research, we propose a Unified Fuzzy rule-based knowledge Inference Systems (UFIS) to help the expert in cosmetic brand detection. Users' preferred cosmetic product detection is very important in the level of CRM. To this purpose, many corporations trying to develop an efficient data mining tool. In this study, we develop a prototype fuzzy rule detection and inference system. The framework used in this development is mainly based on two different mechanisms such as fuzzy rule extraction and RDB (Relational DB)-based fuzzy rule inference. First, fuzzy clustering and fuzzy rule extraction deal with the presence of the knowledge in data base and its value is presented with a value between 0 -1. Second, RDB and SQL (Structured Query Language)-based fuzzy rule inference mechanism provide more flexibility in knowledge management than conventional non-fuzzy value-based KMS (Knowledge Management Systems).

• 지능정보연구
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• 제9권2호
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• pp.19-38
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• 2003

In this research, we propose the mechanism to develop self-evolving expert systems (SEES) based on data mining (DM), fuzzy neural networks (FNN), and relational database (RDB)-driven forward/backward inference engine. Most researchers had tried to develop a text-oriented knowledge base (KB) and inference engine (IE). However, this approach had some limitations such as 1) automatic rule extraction, 2) manipulation of ambiguousness in knowledge, 3) expandability of knowledge base, and 4) speed of inference. To overcome these limitations, knowledge engineers had tried to develop an automatic knowledge extraction mechanism. As a result, the adaptability of the expert systems was improved. Nonetheless, they didn't suggest a hybrid and generalized solution to develop self-evolving expert systems. To this purpose, we propose an automatic knowledge acquisition and composite inference mechanism based on DM, FNN, and RDB-driven inference engine. Our proposed mechanism has five advantages. First, it can extract and reduce the specific domain knowledge from incomplete database by using data mining technology. Second, our proposed mechanism can manipulate the ambiguousness in knowledge by using fuzzy membership functions. Third, it can construct the relational knowledge base and expand the knowledge base unlimitedly with RDBMS (relational database management systems) module. Fourth, our proposed hybrid data mining mechanism can reflect both association rule-based logical inference and complicate fuzzy relationships. Fifth, RDB-driven forward and backward inference time is shorter than the traditional text-oriented inference time.

• 한국산학기술학회:학술대회논문집
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• 한국산학기술학회 2003년도 Proceeding
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• pp.99-104
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• 2003

In this research, we proposed the mechanism to develop self evolving expert systems (SEES) based on data mining (DM), fuzzy neural networks (FNN), and relational database (RDB)-driven forward/backward inference engine. Most former researchers tried to develop a text-oriented knowledge base (KB) and inference engine (IE). However, thy have some limitations such as 1) automatic rule extraction, 2) manipulation of ambiguousness in knowledge, 3) expandability of knowledge base, and 4) speed of inference. To overcome these limitations, many of researchers had tried to develop an automatic knowledge extraction and refining mechanisms. As a result, the adaptability of the expert systems was improved. Nonetheless, they didn't suggest a hybrid and generalized solution to develop self-evolving expert systems. To this purpose, in this study, we propose an automatic knowledge acquisition and composite inference mechanism based on DM, FNN, and RDB-driven inference. Our proposed mechanism has five advantages empirically. First, it could extract and reduce the specific domain knowledge from incomplete database by using data mining algorithm. Second, our proposed mechanism could manipulate the ambiguousness in knowledge by using fuzzy membership functions. Third, it could construct the relational knowledge base and expand the knowledge base unlimitedly with RDBMS (relational database management systems). Fourth, our proposed hybrid data mining mechanism can reflect both association rule-based logical inference and complicate fuzzy logic. Fifth, RDB-driven forward and backward inference is faster than the traditional text-oriented inference.

• Asia pacific journal of information systems
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• 제24권2호
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• pp.191-210
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• 2014

As mobile devices that can be connected to the Internet have spread and networking has become possible whenever/wherever, the Internet has become central in the dissemination and consumption of news. Accordingly, the ways news is gathered, disseminated, and consumed have changed greatly. In the traditional news media such as magazines and newspapers, expert editors determined what events were worthy of deploying their staffs or freelancers to cover and what stories from newswires or other sources would be printed. Furthermore, they determined how these stories would be displayed in their publications in terms of page placement, space allocation, type sizes, photographs, and other graphic elements. In turn, readers-news consumers-judged the importance of news not only by its subject and content, but also through subsidiary information such as its location and how it was displayed. Their judgments reflected their acceptance of an assumption that these expert editors had the knowledge and ability not only to serve as gatekeepers in determining what news was valuable and important but also how to rank its value and importance. As such, news assembled, dispensed, and consumed in this manner can be said to be expert-based recommended news. However, in the era of Internet news, the role of expert editors as gatekeepers has been greatly diminished. Many Internet news sites offer a huge volume of news on diverse topics from many media companies, thereby eliminating in many cases the gatekeeper role of expert editors. One result has been to turn news users from passive receptacles into activists who search for news that reflects their interests or tastes. To solve the problem of an overload of information and enhance the efficiency of news users' searches, Internet news sites have introduced numerous recommendation techniques. Recommendations based on popularity constitute one of the most frequently used of these techniques. This popularity-based approach shows a list of those news items that have been read and shared by many people, based on users' behavior such as clicks, evaluations, and sharing. "most-viewed list," "most-replied list," and "real-time issue" found on news sites belong to this system. Given that collective intelligence serves as the premise of these popularity-based recommendations, popularity-based news recommendations would be considered highly important because stories that have been read and shared by many people are presumably more likely to be better than those preferred by only a few people. However, these recommendations may reflect a popularity bias because stories judged likely to be more popular have been placed where they will be most noticeable. As a result, such stories are more likely to be continuously exposed and included in popularity-based recommended news lists. Popular news stories cannot be said to be necessarily those that are most important to readers. Given that many people use popularity-based recommended news and that the popularity-based recommendation approach greatly affects patterns of news use, a review of whether popularity-based news recommendations actually reflect important news can be said to be an indispensable procedure. Therefore, in this study, popularity-based news recommendations of an Internet news portal was compared with top placements of news in printed newspapers, and news users' judgments of which stories were personally and socially important were analyzed. The study was conducted in two stages. In the first stage, content analyses were used to compare the content of the popularity-based news recommendations of an Internet news site with those of the expert-based news recommendations of printed newspapers. Five days of news stories were collected. "most-viewed list" of the Naver portal site were used as the popularity-based recommendations; the expert-based recommendations were represented by the top pieces of news from five major daily newspapers-the Chosun Ilbo, the JoongAng Ilbo, the Dong-A Daily News, the Hankyoreh Shinmun, and the Kyunghyang Shinmun. In the second stage, along with the news stories collected in the first stage, some Internet news stories and some news stories from printed newspapers that the Internet and the newspapers did not have in common were randomly extracted and used in online questionnaire surveys that asked the importance of these selected news stories. According to our analysis, only 10.81% of the popularity-based news recommendations were similar in content with the expert-based news judgments. Therefore, the content of popularity-based news recommendations appears to be quite different from the content of expert-based recommendations. The differences in importance between these two groups of news stories were analyzed, and the results indicated that whereas the two groups did not differ significantly in their recommendations of stories of personal importance, the expert-based recommendations ranked higher in social importance. This study has importance for theory in its examination of popularity-based news recommendations from the two theoretical viewpoints of collective intelligence and popularity bias and by its use of both qualitative (content analysis) and quantitative methods (questionnaires). It also sheds light on the differences in the role of media channels that fulfill an agenda-setting function and Internet news sites that treat news from the viewpoint of markets.

• 산업공학
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• 제14권2호
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• pp.164-171
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• 2001

We suggest a Business Performance Information System with Knowledge Discovery in Databases(KDD) as a key component of integrated information and knowledge management system. The proposed system measures business performance by considering both VA(Value-Added), which represents stakeholder's point of view and EVA(Economic Value-Added), which represents shareholder's point of view. In modeling of Business Performance Information System, we apply the following KDD processes : Data Warehouse for consistent management of a performance data, On-Line Analytic Processing(OLAP) for multidimensional analysis, Genetic Algorithms for exploring and finding dominant managing factors and Analytic Hierarchy Process(AHP) for applying expert's knowledge and experience. To demonstrate the performance of the system, we conducted a case study using financial data of Korean automobile industry over 16 years from 1981 to 1996, which is taken from database of KISFAS(Korea Investors Services Financial Analysis System).

• 한국전자거래학회지
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• 제12권2호
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• pp.233-247
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• 2007

급변하는 기업환경에 신속히 대응하기 위하여 기업의 업무는 비즈니스 프로세스 중심으로, 정보 인프라는 웹서비스 기반으로 재편되어가고 있으며, 기업의 정보시스템은 BPMS를 중심으로 다시 구축되어갈 것으로 전망된다. 이러한 배경하에 본 연구에서는 e-비즈니스 고도화의 방향으로 SOA(Service oriented architecture)를 설정하고, 전문가들을 대상으로 한 설문조사를 통해 e-비즈니스 기술과 BPM 기능요소 간의 상관도 분석을 수행하였으며, 이를 바탕으로 서비스 지향의 e-비즈니스 고도화를 위한 BPM 발전과제들의 우선순위를 제시하였다. 연구의 결과는 BPM 솔루션 업체, 도입기업 및 정책입안자들에게 중요한 참고자료로 활용될 수 있을 것이다.

• 국제학술발표논문집
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• The 6th International Conference on Construction Engineering and Project Management
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• pp.217-220
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• 2015

Because of the recession of the Korean construction market, many construction companies are expediting overseas business. Despite the rapid growth of international markets, the polarization of profit with SMCCs (Small and Medium Construction Companies) and large construction companies in the international construction market has become more serious. This problem causes competition to provide the lowest prices, which makes the future of overseas business for the SMCCs uncertain. Thus, the SMCCs require a reasonable capability evaluation system for overseas business. However, the existing evaluation methods focus on large construction companies. To address this problem, this study proposes a system to evaluate the overseas business capabilities. The 27 indicators to evaluate the overseas business capabilities are derived from a literature review and are verified through expert interviews. The indicators are classified into 4 large categories, and a questionnaire-based survey of 50 Korean SMCCs is conducted to analyze the correlation between overseas business capability and the indicators. The system expects to provide the effect of the indicators on the overseas business capability and the chance to evaluate the capability for overseas business.