• 한국산업정보학회논문지
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• 제17권4호
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• pp.87-97
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• 2012

지식지도는 지식 간의 상호 연관성을 기초로 전체적인 지식의 현황을 보여주는 도식으로, 상황에 따라 다양하게 해석 및 적용될 수 있는 지식의 특성을 보다 형식화되고 정형화된 방식으로 표현하기 위해 온톨로지 기술의 적용이 필요하다. 본 연구는 지식 네트워크에 나타나는 지식 간 상호참조적 네비게이션이 가능하도록 온톨로지 기술을 기반으로 지식지도를 정의하고 표현하는 방법론을 제시한다. 제시된 방법론의 타당성을 검증하기 위하여, 온톨로지 모델링 도구인 Protege-OWL을 이용하여 실제 지식지도를 모델링하고, 몇 가지 예제를 통해 구현된 온톨로지 기반 지식지도가 실제로 지식 간의 상호참조적 네비게이션을 반영하는 지식네트워크를 구성하는지 알아본다.

• 한국전자거래학회지
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• 제6권1호
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• pp.101-121
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• 2001

MOCT(Ministry of Construction St Transportation) suggested "A Plan for Implementation of Knowledge-based Economy for the Construction Industry" to add high value to a construction industry. by means of knowledge-based management. However, there is no knowledge management system which considers characteristics of a domestic construction industry. So a useful knowledge vanished the moment a company terminated a construction Uoject. Therefore, it is necessary to develop "An application method of a knowledge management system for the construction industry" which takes a real environment into consideration. This study aims to present the road map of a knowledge management system which helps the bodies of the construction industry(government, research center/university, enterprise, etc) to do a knowledge activity efficiently. To accomplish this objective, we analyzed overall knowledge management activities. In addition we suggested an implementation direction and strategy of a knowledge management system for the construction industry. As results of this study, we presented the road map of a knowledge management system for the construction industry, which is composed of policy forum, study forum, professional forum, research forum and knowledge 8t information DB. We expect that results of this study will be used as a basis for implementing the knowledge portal that brings a construction industry to a high value added industry.

• 지식경영연구
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• 제7권2호
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• pp.35-52
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• 2006

Increasing competitive pressure, the constantly accelerating transformation of the economy, and a stronger focus on value creation have initiated the search for sustainable sources of competitive advantage in organizations. In this context, the concept of treating organizational knowledge as a valuable strategic resource has become quite popular recently. Knowledge has become the most critical component in the struggle for sustained competitive advantage and knowledge management (KM) has also been described for its possible role in creating sustainable competitive advantage. In order to examine the contingency between KM resources, KM strategies, and KM performance of organizations, a contingency model of KM, which is based on resource-based theory as well as knowledge-based theory, is developed from the information systems and strategic management literature in order to assess the following questions: (i) What KM resources affect the organization's KM strategies? (ii) Is there a relationship between KM strategies and organizational performance enhanced by KM? A detailed exploratory analysis of survey responses from 79 Korean companies provides the following significant findings: (i) This study found support for the proposed contingency model of KM; (ii) The organization's KM strategies are determined by social resources and its capabilities; (iii) An organization with a culture-based KM strategy is more likely to enhance organizational KM performance than an organization with a technology-based KM strategy.

• 디지털산업정보학회논문지
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• 제6권1호
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• pp.91-103
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• 2010

This paper introduces efficient rule-based semantic search techniques to ontology-based knowledge commerce services. Primarily, the search techniques presented in this paper define rules of reasoning that are required for users to search using the concept of ontology, multiple characteristics, relations among concepts and data type. In addition, based on the defined rules, the rule-based reasoning techniques search ontology for knowledge commerce services. This paper explains the conversion rules of query which convert user's query language into semantic search words, and transitivity rules which enable users to search related tags, knowledge products and users. Rule-based sematic search techniques are also presented; these techniques comprise knowledge search modules that search ontology using validity examination of queries, query conversion modules for standardization and expansion of search words and rule-based reasoning. The techniques described in this paper can be applied to sematic knowledge search systems using tags, since transitivity reasoning, which uses tags, knowledge products, and relations among people, is possible. In addition, as related users can be searched using related tags, the techniques can also be employed to establish collaboration models or semantic communities.

• 산업경영시스템학회지
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• 제31권2호
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• pp.1-10
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• 2008

In the knowledge-based society which recognizes knowledge as a core value, knowledge management is one of the most interesting issues. The creation of knowledge within an organization occurs as a result of interactions of tacit and explicit knowledge, in process of knowledge conversion. One useful model of this process is the SECI model which stands for a process of socialization, externalization, combination and internalization of knowledge. The enterprise competitive power depends on how an organization accelerates the speed of the cycle of knowledge creation well. In this paper we introduce a knowledge management promotion system based on SECI model and proposal system to promote the cycle of knowledge creation in production fields, and study an enterprise case.

• 지식경영연구
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• 제20권4호
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• pp.75-97
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• 2019

In the rapidly changing business environment, knowledge has been recognized as a core asset for sustaining an organization's competitive advantage. In addition, knowledge sharing is one of the key elements of knowledge management, emphasizing external knowledge sharing beyond initial internal knowledge sharing. However, while knowledge management research emphasizes knowledge sharing, which is a positive aspect, research on preventing knowledge leakage that can have negative consequences is relatively lacking. Companies have tried to minimize the negative effects of knowledge management but many knowledge leakage accidents are still occurring. Therefore, this study aims to examine the effects of external factors based on deterrence theory and internal factors based on self-determination theory on knowledge leakage intention focusing on tacit knowledge. The results of the empirical analysis of 100 data sets collected through a scenario-based survey show that certainty of sanctions, social disapproval, and competence are found to have a significant effect on reducing tacit knowledge leakage intention. Furthermore, informal sanctions have a greater impact on tacit knowledge leakage intention than formal sanctions and external factors have a greater effect on tacit knowledge leakage intention than internal factors.

• 지식경영연구
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• 제15권4호
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• pp.1-14
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• 2014

This study investigates earnings management of IPO firms in knowledge-based-industry. we analyse the relation between earnings management and R&D expenses(Research and development expense)which is an important expenditure in knowledge based management. First, we found that the earnings management is the largest in the year when the firm is enrolled on the market. Second, the IPO firms have higher DA(discretionary accruals) than existing firms on the market and the size of R&D expenses is larger, too. Finally, in the IPO firms in knowledge-based-industry, the higher accounting receivable and R&D expenses are, the more happens earnings management. Our study shows that the IPO firms of knowledge-basedindustry have high R&D expenses which are core expenditure. Also, earnings management has happened frequently in the IPO firms.

• East Asian mathematical journal
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• 제38권1호
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• pp.85-94
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• 2022

Recently, an LWE-based commitment scheme is proposed. Their construction is statistically hiding as well as computationally binding. On the other hand, the construction of related zero-knowledge protocols is left as an open problem. In this paper, we present zero-knowledge protocols with hardness based on the LWE problem. we show how to instantiate efficient zero-knowledge protocols that can be used to prove linear and sum relations among these commitments. In addition, we show how the variant of LWE, spLWE problem, can be used to instantiate efficient zero-knowledge protocols.

• 한국전자거래학회:학술대회논문집
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• 한국전자거래학회 2004년도 e-Biz World Conference
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• pp.107-111
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• 2004

The purpose of the study is to develop an integrated knowledge management system for the domains of genome and nano-technology, in which terminology-based literature mining, knowledge acquisition, knowledge structuring, and knowledge retrieval are combined. The system supports integrating different types of databases (papers and patents, technologies and innovations) and retrieving different types of knowledge simultaneously. The main objective of the system is to facilitate knowledge acquisition from documents and new knowledge discovery through a terminology-based similarity calculation and a visualization of automatically structured knowledge. Implementation issue of the system is also mentioned.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권11호
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• pp.2903-2923
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• 2023

Knowledge recommendation is a type of recommendation system that recommends knowledge content to users in order to satisfy their needs. Although using graph neural networks to extract data features is an effective method for solving the recommendation problem, there is information loss when modeling real-world problems because an edge in a graph structure can only be associated with two nodes. Because one super-edge in the hypergraph structure can be connected with several nodes and the effectiveness of knowledge graph for knowledge expression, a dual-channel hypergraph convolutional neural network model (DCHC) based on hypergraph structure and knowledge graph is proposed. The model divides user data and knowledge data into user subhypergraph and knowledge subhypergraph, respectively, and extracts user data features by dual-channel hypergraph convolution and knowledge data features by combining with knowledge graph technology, and finally generates recommendation results based on the obtained user embedding and knowledge embedding. The performance of DCHC model is higher than the comparative model under AUC and F1 evaluation indicators, comparative experiments with the baseline also demonstrate the validity of DCHC model.