• 한국IT서비스학회지
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• 제11권2호
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• pp.185-196
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• 2012

The rapid evolution of ICT industry brings not only new services or products but also changes from common individual life to whole human society. Coping with these situations and survival, companies cannot help regarding R&D as the most important thing. So, discovering R&D projects which are suitable for the alternation is a big issue for many companies. To resolve the issue, KT has adopted Innovative Management Methodology developed by Strategos, which is co-founded by Gary Harmel. This paper describes this Innovative Management Methodology tailored to KT R&D. The methodology consists of five phases : focusing discovery, discovery, ideas/domains, domain elaboration & aiming point and R&D project proposal. Also, it shows some interim findings that came from the Innovative Management Process. Finally, the future plan for elaborating the methodology itself and generating new R&D projects is suggested.

• 영어어문교육
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• 제17권3호
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• pp.27-56
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• 2011

The analysis on the use of lexical discovery and consolidation strategies that have been researched within the area of vocabulary learning strategies (VLS) have not sufficiently drawn the interest of EFL practitioners with regard to vocational high school learners. The results, however, are expected to have implications for the design of vocabulary tasks and instructional materials for EFL learners. The present study investigates EFL vocational high school learners' use of lexical discovery and consolidation strategies with questionnaires, where the use of the learners' lexical discovery strategies were further validated with the think-aloud methodology by asking samples of proficient and less proficient learners to report on their reading process while reading L2 texts that had not been exposed to the learners. The results indicated that there were significant differences between the two groups of learners in the employment of 11 of the strategies which were in the categories of determination, social, memory, and metacognitive strategies, but not for cognitive strategies. The pattern of strategies indicated that different lexical discovery and consolidation strategies were employed relatively more by one proficiency group than another. The study suggests some implications for how strategy-based instruction can be implemented in EFL classrooms.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회/대한산업공학회 2003년도 춘계공동학술대회
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• pp.1128-1135
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• 2003

e-Transformation of an enterprise requires the collaboration of business processes to be suited to the business participants' purpose. To realize this collaboration, business processes should be implemented as components and the system developers could be able to reuse the components for their specific purpose. The first step of this collaboration is the discovery of exact components for business processes. A dilemma, however, is the fact that there are thousands or even millions of business processes which vary from one enterprise to another. Moreover, business processes could be decomposed into multiple levels of semantics and classified into several process areas. In general, discovery of exact business processes requires understanding of widely adopted classification schemes such as CBPC, OAGIS, or SCOR. To cope with this obstacle, business process metadata should be defined and managed regardless of specific classification schemes to support effective discovery and reuse of business processes components. In this paper, a methodology to discover business process components published in different semantic levels is proposed. The proposed methodology represents the metadata of business process components as topic maps stored in a registry and utilizes the powerful features of topic maps for process discovery. TM4J, an open-source topic map engine, is modified to support concept matching and navigation. With the implemented tool, application system developers can discover and publish the business process components effectively.

• Journal of Preventive Medicine and Public Health
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• 제49권2호
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• pp.129-133
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• 2016

Objectives: The systematic review (SR) is a research methodology that aims to synthesize related evidence. Updating previously conducted SRs is necessary when new evidence has been produced, but no consensus has yet emerged on the appropriate update methodology. The authors have developed a new SR update method called 'adaptive meta-analysis' (AMA) using the 'cited by', 'similar articles', and 'related articles' citation discovery tools in the PubMed and Scopus databases. This study evaluates the usefulness of these citation discovery tools for updating SRs. Methods: Lists were constructed by applying the citation discovery tools in the two databases to the articles analyzed by a published SR. The degree of overlap between the lists and distribution of excluded results were evaluated. Results: The articles ultimately selected for the SR update meta-analysis were found in the lists obtained from the 'cited by' and 'similar' tools in PubMed. Most of the selected articles appeared in both the 'cited by' lists in Scopus and PubMed. The Scopus 'related' tool did not identify the appropriate articles. Conclusions: The AMA, which involves using both citation discovery tools in PubMed, and optionally, the 'related' tool in Scopus, was found to be useful for updating an SR.

• 지식경영연구
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• 제1권1호
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• pp.91-107
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• 2000

This paper proposes the Organizational Knowledge Discovery Process Model (OK-DPM) as an initiative for developing a knowledge management methodology. OK-DPM is a model designed to effectively discover knowledge useful to the organization. It explains the knowledge discovery process from the conceptual level to the application level. It decomposes the organizational knowledge discovery process into 3 sub-processes; Creation, Suggestion and Validation. For each sub-process, design components are identified and possible methods for supporting each one are suggested. Also, the relationship patterns between the knowledge discovery process and knowledge type are explored. By applying OK-DPM to two real cases where the knowledge management projects are ongoing, the model was validated and revised. Even though we need to investigate with more cases to refine the OK-DPM, we found that it could provide some insights in developing the effective knowledge discovery process.

• 한국수학사학회지
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• 제18권2호
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• pp.95-106
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• 2005

본 논문에서는 수학을 기반으로 한 데이터베이스의 지식탐사 절차를 통하여 데이터의 선택, 정제, 통합, 변환, 축소, 데이터 마이닝 기법의 선택과 적용 및 모형의 평가에 관한 개념과 방법론을 소개하고 수학의 한 분야로서 통계학의 역할과 적용방법에 관하여 연구하고자 한다. 또한 오늘날 관심이 대상이 되고 있는 데이터 마이닝의 역사와 수학적 배경, 통계 및 정보 기술을 이용한 데이터 마이닝의 주요 모델링 기법, 실용적 응용 분야 및 적용 사례 그리고 데이터 마이닝과 통계의 차이점에 관하여 조사하고 논하고자 한다.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 2000년도 춘계공동학술대회 논문집
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• pp.290-293
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• 2000

Knowledge discovery refers to the overall process of discovering useful knowledge from data. The linear programming model is a special form of useful knowledge that is embedded in a database. Since formulating models from scratch requires knowledge-intensive efforts, knowledge-based formulation support systems have been proposed in the DSS area. However, they rely on the strict assumption that sufficient domain knowledge should already be captured as a specific knowledge representation form. Hence, the purpose of this paper is to propose a methodology that finds useful knowledge on building linear programming models from a database. The methodology consists of two parts. The first part is to find s first-cut model based on a data dictionary. To do so, we applied the GPS algorithm. The second part is to discover a second-cut model by applying neural network technique. An illustrative example is described to show the feasibility of the proposed methodology.

• Journal of Information Science Theory and Practice
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• 제4권3호
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• pp.71-83
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• 2016

Purpose. The purpose of this paper is to analyze and evaluate discovery layer search tools for retrieval of legal information in Indian law libraries. This paper covers current practices in legal information retrieval with special reference to Indian academic law libraries, and analyses its importance in the domain of law.Design/Methodology/Approach. A web survey and observational study method are used to collect the data. Data related to the discovery tools were collected using email and further discussion held with the discovery layer/ tool /product developers and their representatives.Findings. Results show that most of the Indian law libraries are subscribing to bundles of legal information resources such as Hein Online, JSTOR, LexisNexis Academic, Manupatra, Westlaw India, SCC web, AIR Online (CDROM), and so on. International legal and academic resources are compatible with discovery tools because they support various standards related to online publishing and dissemination such as OAI/PMH, Open URL, MARC21, and Z39.50, but Indian legal resources such as Manupatra, Air, and SCC are not compatible with the discovery layers. The central index is one of the important components in a discovery search interface, and discovery layer services/tools could be useful for Indian law libraries also if they can include multiple legal and academic resources in their central index. But present practices and observations reveal that discovery layers are not providing facility to cover legal information resources. Therefore, in the present form, discovery tools are not very useful; they are an incomplete and half solution for Indian libraries because all available Indian legal resources available in the law libraries are not covered.Originality/Value. Very limited research or published literature is available in the area of discovery layers and their compatibility with legal information resources.

• 철학연구
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• 제148권
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• pp.157-181
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• 2018

본 논문은 뉴턴의 아이디어가 정교화되면서 뉴턴역학으로 변모하는 과정을 발견법의 요소로 고찰한다. 뉴턴이 사용한 발견법은 코헨에 의해 제안된 선행하는 여러 과학개념과 이론을 '변형재구성'하는 과정으로 집약될 수 있다. 뉴턴은 그의 역학이론을 발견하는 과정에서 아리스토텔레스, 데카르트, 갈릴레오, 케플러 등의 선행 운동이론을 구성하는 개념과 구조들을 변형재구성한다. 뉴턴의 융합은 이전 자연철학자들의 아이디어 중 적절하고 유용한 아이디어를 신중히 선택하여 변형재구성된 이후에만 가능했다. 뉴턴은 선행이론을 구성하는 개념들을 점진적으로 변형재구성하며 이들 개념들을 도약적으로 통합한다. 그 결과 이들 변형재구성된 개념들은 뉴턴의 운동법칙과 시공간 개념으로 통합되며 뉴턴역학의 체계로 완성된다. 본 논문에서는 뉴턴역학의 발견 과정을 라카토슈 연구프로그램의 구성요소로 합리적으로 재구성한다. 이렇게 재구성된 결과를 토대로 뉴턴 역학의 발견과정을 과학이론 발견법의 요소인 변형재구성의 관점에서 분석한다.

• 한국정보통신학회논문지
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• 제8권6호
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• pp.1284-1290
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• 2004

장바구니 분석에서, 가중 연관 규칙 탐사는 특정 상품에 대한 아이템의 중요도를 반영함으로써 더 많은 이익을 주는 정보를 규칙으로 탐사하였다. 그러나 트랜잭션을 구성하는 아이템들이 한 개 이상의 서로 다른 그룹으로 나누어진다면, 각 그룹의 특성을 반영하는 서로 다른 측정 방법으로 평가되어야 하므로 기존의 가중연관규칙 탐사 방법을 적용할 수가 없다. 본 논문에서는 이를 해결하기 위해서 가중 연관 규칙의 새로운 탐사 방법을 제안하였다. 먼저 각 아이템들은 유사한 특성에 따라 서브 그룹으로 나누고, 아이템 중요도(아이템 가중치)는 서브 그룹에 포함된 아이템들 단위로 계산한다 이때 적용되는 여러 가중 인자들은 아이템의 특성을 반영하는 아이템 그룹별로 재 정의하였다. 제안하는 방법은 네트워크 보안 데이터에 적용하여 위험을 일으키는 요소에 대한 위험 규칙 집합을 생성함으로써 네트워크 위험관리의 정성평가와, 규칙 생성 시 적용된 가중치와 같은 여러 통계인자들에 의해서 위험도를 계산함으로써 정량평가를 가능하게 하였다. 또한 데이터 아이템들이 상이하게 구별될 수 있는 특성을 만족하는 마켓 데이터의 새로운 응용분야에 넓게 적용될 수 있다.