• Title/Summary/Keyword: Knowledge based systems

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Human Indicator and Information Display using Space Human Interface in Networked Intelligent Space

  • Jin Tae-Seok;Niitsuma Mihoko;Hashimoto Hideki
    • Journal of the Korean Institute of Intelligent Systems
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    • v.15 no.5
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    • pp.632-638
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    • 2005
  • This paper describes a new data-handing, based on a Spatial Human Interface as human indicator, to the Spatial-Knowledge-Tags (SKT) in the spatial memory the Spatial Human Interface (SHI) is a new system that enables us to facilitate human activity in a working environment. The SHI stores human activity data as knowledge and activity history of human into the Spatial Memory in a working environment as three-dimensional space where one acts, and loads them with the Spatial-Knowledge-Tags(SKT) by supporting the enhancement of human activity. To realize this, the purpose of SHI is to construct new relationship among human and distributed networks computers and sensors that is based on intuitive and simultaneous interactions. In this paper, the specified functions of SKT and the realization method of SKT are explained. The utility of SKT is demonstrated in designing a robot motion control.

Efficient Knowledge Base Construction Mechanism Based on Knowledge Map and Database Metaphor

  • Kim, Jin-Sung;Lee, Kun-Chang;Chung, Nam-Ho
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 2004.05a
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    • pp.9-12
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    • 2004
  • Developing an efficient knowledge base construction mechanism as an input method for expert systems (ES) development is of extreme importance due to the fact that an input process takes a lot of time and cost in constructing an ES. Most ES require experts to explicit their tacit knowledge into a form of explicit knowledge base with a full sentence. In addition, the explicit knowledge bases were composed of strict grammar and keywords. To overcome these limitations, this paper proposes a knowledge conceptualization and construction mechanism for automated knowledge acquisition, allowing an efficient decision. To this purpose, we extended traditional knowledge map (KM) construction process to dynamic knowledge map (DKM) and combined this algorithm with relational database (RDB). In the experiment section, we used medical data to show the efficiency of our proposed mechanism. Each rule in the DKM was characterized by the name of disease, clinical attributes and their treatments. Experimental results with various disease show that the proposed system is superior in terms of understanding and convenience of use.

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Knowledge-based Semantic Meta-Search Engine (지식기반 의미 메타 검색엔진)

  • Lee, In-K.;Son, Seo-H.;Kwon, Soon-H.
    • Journal of the Korean Institute of Intelligent Systems
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    • v.14 no.6
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    • pp.737-744
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    • 2004
  • Retrieving relevant information well corresponding to the user`s request from web is a crucial task of search engines. However, most of conventional search engines based on pattern matching schemes to queries have a limitation that is not easy to provide results corresponding to the user`s request due to the uncertainty of queries. To overcome the limitation in this paper, we propose a framework for knowledge-based semantic meta-search engines with the following five processes: (i) Query formation, (ii) Query expansion, (iii) Searching, (iv) Ranking recreation, and (v) Knowledge base. From simulation results on english-based web documents, we can see that the Proposed knowledge-based semantic meta-search engine provides more correct and better searching results than those obtained by using the Google.

Decision Making Framework for Achieving Successful Knowledge Management (지식경영의 성공적인 실행을 위한 전략적 의사결정 프레임워크 구축)

  • Lee, Young-Chan;Kwon, Kee-Taec
    • The Journal of Information Systems
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    • v.18 no.3
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    • pp.135-154
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    • 2009
  • As the knowledge is recognized as a core factor of organization's competitiveness and creation of value added, the importance of knowledge management is also increased. To achieve the successful knowledge management, it is important to establish strategy that consider essential purpose of knowledge management such as creating and sharing of knowledge resource, improving performance, and continuing organizational innovation within the organization and influence factor inside and outside of organization. Until now, however, the research for knowledge management strategy was mostly limited to the statistical analysis based on the unilinear causality model, and systematic access and analysis that consider interaction and feedback structure between factors. In this paper, we developed the novel decision-making framework for successful strategy establishment by applying the analytic network process(ANP). Specifically. we derive clusters and components to decide the interaction and feedback structure between the elements of knowledge management by literature studies. And we produced relative importance and preference of clusters, components and alternatives dealing with feedback structure through the survey of experts in the field or related one of knowledge management. In result of this study, we expect that it will help the knowledge officer to decide establishing knowledge management strategy.

Development of a Knowledge-Based Job Shop Scheduler Applying the Attribute-Oriented Induction Method and Simulation (속성지향추론법과 시뮬레이션을 이용한 지식기반형 Job Shop 스케쥴러의 개발)

  • 한성식;신현표
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.21 no.48
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    • pp.213-222
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    • 1998
  • The objective of this study is to develop a knowledge-based scheduler applying simulation and knowledge base. This study utilizes a machine induction to build knowledge base which enables knowledge acquisition without domain expert. In this study, the best job dispatching rule for each order is selected according to the specifications of the order information. And these results are built to the fact base and knowledge base using the attribute-oriented induction method and simulation. When a new order enters in the developed system, the scheduler retrieves the knowledge base in order to find a matching record. If there is a matching record, the scheduling will be carried out by using the job dispatching rule saved in the knowledge base. Otherwise the best rule will be added to the knowledge base as a new record after scheduling to all the rules. When all these above steps finished the system will furnish a learning function.

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A Comparative Study of Uncertainty Handling Methods in Knowledge-Based System (지식기반시스템에서 불확실성처리방법의 비교연구)

  • 송수섭
    • Journal of the military operations research society of Korea
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    • v.23 no.2
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    • pp.45-71
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    • 1997
  • There has been considerable research recently on uncertainty handling in the fields of artificial intelligence and knowledge-based system. Various numerical and non-numerical methods have been proposed for representing and propagating uncertainty in knowledge-based system. The Bayesian method, the Dempster-Shafer's Evidence Theory, the Certainty Factor model and the Fuzzy Set Theory are most frequently appeared in the knowledge-based system. Each of these four methods views uncertainty from a different perspective and propagates it differently. There is no single method which can handle uncertainty properly in all kinds of knowledge-based systems' domain. Therefore a knowledge-based system will work more effectively when the uncertainty handling method in the system fits to the system's environment. This paper proposed a framework for selecting proper uncertainty handling methods in knowledge-based system with respect to characteristics of problem domain and cognitive styles of experts. A schema with strategic/operational and unstructured/structured classification is employed to differenciate domain. And a schema with systematic/intuitive and preceptive/receptive classification is employed to differenciate experts' cognitive style. The characteristics of uncertainty handling methods are compared with characteristics of problem domains and cognitive styles respectively. Then a proper uncertainty handling method is proposed for each category.

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The Effects of Learning Organization, Learner's Characteristics on Organizational Knowledge Creation: The Role of Perceived Organizational Support as A Moderator (조직의 지식창출에 대한 학습조직의 구조적 특성 및 학습자 특성의 효과 : 인지된 조직지원의 조절효과)

  • Cho, Yoonhyung;Choi, Woojae
    • Knowledge Management Research
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    • v.12 no.1
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    • pp.17-37
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    • 2011
  • This paper is aimed at investigating the influence of the learning organization's structural characteristics, learner's characteristics, and perceived organizational support (POS) on organizational knowledge creation. also the POS is tested as a moderator on the relationship between learner's characteristics including learning goal orientation and learning self-efficacy and organizational knowledge creation. the results are as follows. for main effect hypotheses, both connecting the organization to its environment and establishing systems to capture and share learning system representing learning organization's structural characteristics have significant positive impact on organizational knowledge creation. the POS also has a significant impact on organizational knowledge creation. However, learning goal orientation and learning self-efficacy have not significant impact on organizational knowledge creation. for moderating effect hypothesis, POS moderates the relationship between learning goal orientation and organizational knowledge creation, which means if the POS is high then learning goal orientation has more significant positive impact on it. Based on our findings, we conclude that structural characteristics of learning organization provide organizations with an opportunity of knowledge creation. in particular, interconnectedness of organization with environment and organizational knowledge sharing systems determine the ways of behaving that are related to learning within organizations. however, learner's characteristics did not have a significant effect on organizational knowledge creation, which could be interpreted due to the fact that employees are not motivated to create new knowledge if they are rarely required to involve challenging works, generate new knowledge, or share preexisted knowledge with others.

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Effects of Learning Expectation and Perceived Knowledge Sharing on User Satisfaction and IS Continuance (학습기대와 지식공유 지각이 사용자 만족과 지속사용에 미치는 영향)

  • Kim, In Chan;Baek, Seung Nyoung
    • The Journal of Information Systems
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    • v.28 no.4
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    • pp.377-401
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    • 2019
  • Purpose The purpose of this study is to investigate the effects of learning expectation and perceived knowledge sharing on user satisfaction and IS continuance in the Korean Army which is currently using the Regiments' Information System to help their Integrated Administration Management. Based on both the Information System(IS) Continuance Model and IS Success Model, this study also examine the role of system quality on user satisfaction. We develop a research model(structural equation model) and its hypotheses that learning expectation, perceived knowledge sharing, and system quality increase users' satisfaction, which leads to IS continuance. The effect of learning expectation on perceived knowledge sharing is also hypothesized. Design/methodology/approach Online Survey using e-mails was administered to test our research model and associated hypotheses. Among the 360 e-mail letters including our survey questionnaire, 285 responses were collected via e-mails. Meaningful 225 cases were analyzed for our study. SPSS Statistics 24.0 and SmartPLS 3.0 were used to analyze both measuremant test and hyotheses test by using the data set. Findings Survey results show that learning expectation(confirmation variable), learning expectation, perceived knowledge sharing(a perceived usefulness variable), and system quality(a system characteristic) each increases user satisfaction, which leads to IS continuance, under the control of the effect of habit to use information systems. Learning expectation also has a positive influence on perceived knowledge sharing. Theoretical and practical implications are presented.

An Examination of Knowledge Sourcing Strategies Effects on Corporate Performance in Small Enterprises (소규모 기업에 있어서 지식소싱 전략이 기업성과에 미치는 영향 고찰)

  • Choi, Byoung-Gu
    • Asia pacific journal of information systems
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    • v.18 no.4
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    • pp.57-81
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    • 2008
  • Knowledge is an essential strategic weapon for sustaining competitive advantage and is the key determinant for organizational growth. When knowledge is shared and disseminated throughout the organization, it increases an organization's value by providing the ability to respond to new and unusual situations. The growing importance of knowledge as a critical resource has forced executives to pay attention to their organizational knowledge. Organizations are increasingly undertaking knowledge management initiatives and making significant investments. Knowledge sourcing is considered as the first important step in effective knowledge management. Most firms continue to make an effort to realize the benefits of knowledge management by using various knowledge sources effectively. Appropriate knowledge sourcing strategies enable organizations to create, acquire, and access knowledge in a timely manner by reducing search and transfer costs, which result in better firm performance. In response, the knowledge management literature has devoted substantial attention to the analysis of knowledge sourcing strategies. Many studies have categorized knowledge sourcing strategies into intemal- and external-oriented. Internal-oriented sourcing strategy attempts to increase firm performance by integrating knowledge within the boundary of the firm. On the contrary, external-oriented strategy attempts to bring knowledge in from outside sources via either acquisition or imitation, and then to transfer that knowledge across to the organization. However, the extant literature on knowledge sourcing strategies focuses primarily on large organizations. Although many studies have clearly highlighted major differences between large and small firms and the need to adopt different strategies for different firm sizes, scant attention has been given to analyzing how knowledge sourcing strategies affect firm performance in small firms and what are the differences between small and large firms in the patterns of knowledge sourcing strategies adoption. This study attempts to advance the current literature by examining the impact of knowledge sourcing strategies on small firm performance from a holistic perspective. By drawing on knowledge based theory from organization science and complementarity theory from the economics literature, this paper is motivated by the following questions: (1) what are the adoption patterns of different knowledge sourcing strategies in small firms (i,e., what sourcing strategies should be adopted and which sourcing strategies work well together in small firms)?; and (2) what are the performance implications of these adoption patterns? In order to answer the questions, this study developed three hypotheses. First hypothesis based on knowledge based theory is that internal-oriented knowledge sourcing is positively associated with small firm performance. Second hypothesis developed on the basis of knowledge based theory is that external-oriented knowledge sourcing is positively associated with small firm performance. The third one based on complementarity theory is that pursuing both internal- and external-oriented knowledge sourcing simultaneously is negatively or less positively associated with small firm performance. As a sampling frame, 700 firms were identified from the Annual Corporation Report in Korea. Survey questionnaires were mailed to owners or executives who were most erudite about the firm s knowledge sourcing strategies and performance. A total of 188 companies replied, yielding a response rate of 26.8%. Due to incomplete data, 12 responses were eliminated, leaving 176 responses for the final analysis. Since all independent variables were measured using continuous variables, supermodularity function was used to test the hypotheses based on the cross partial derivative of payoff function. The results indicated no significant impact of internal-oriented sourcing strategies while positive impact of external-oriented sourcing strategy on small firm performance. This intriguing result could be explained on the basis of various resource and capital constraints of small firms. Small firms typically have restricted financial and human resources. They do not have enough assets to always develop knowledge internally. Another possible explanation is competency traps or core rigidities. Building up a knowledge base based on internal knowledge creates core competences, but at the same time, excessive internal focused knowledge exploration leads to behaviors blind to other knowledge. Interestingly, this study found that Internal- and external-oriented knowledge sourcing strategies had a substitutive relationship, which was inconsistent with previous studies that suggested complementary relationship between them. This result might be explained using organizational identification theory. Internal organizational members may perceive external knowledge as a threat, and tend to ignore knowledge from external sources because they prefer to maintain their own knowledge, legitimacy, and homogeneous attitudes. Therefore, integrating knowledge from internal and external sources might not be effective, resulting in failure of improvements of firm performance. Another possible explanation is small firms resource and capital constraints and lack of management expertise and absorptive capacity. Although the integration of different knowledge sources is critical, high levels of knowledge sourcing in many areas are quite expensive and so are often unrealistic for small enterprises. This study provides several implications for research as well as practice. First this study extends the existing knowledge by examining the substitutability (and complementarity) of knowledge sourcing strategies. Most prior studies have tended to investigate the independent effects of these strategies on performance without considering their combined impacts. Furthermore, this study tests complementarity based on the productivity approach that has been considered as a definitive test method for complementarity. Second, this study sheds new light on knowledge management research by identifying the relationship between knowledge sourcing strategies and small firm performance. Most current literature has insisted complementary relationship between knowledge sourcing strategies on the basis of data from large firms. Contrary to the conventional wisdom, this study identifies substitutive relationship between knowledge sourcing strategies using data from small firms. Third, implications for practice highlight that managers of small firms should focus on knowledge sourcing from external-oriented strategies. Moreover, adoption of both sourcing strategies simultaneousiy impedes small firm performance.