• 제목/요약/키워드: Knowledge based systems

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소셜 네트워크 서비스 기반의 4세대 지식관리시스템 설계 방안 (Design of Fourth Generation Knowledge Management System based on Social Network Service)

  • 안길승;권민성;강창욱;허선
    • 정보과학회 논문지
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    • 제43권5호
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    • pp.579-589
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    • 2016
  • 오늘날 여러 기업에서 조직 구성원들의 지식을 활용하여 핵심역량을 강화할 목적으로 효과적으로 기업 내부의 지식을 관리하는 지식관리시스템을 도입하였다. 그러나 기존의 지식관리시스템은 기업 구성원의 적극적인 참여를 독려할만한 요소가 부족하여 고품질의 지식콘텐츠를 공유하지 못하고 있다. 이에 본 연구에서는 소셜 네트워크 서비스(Social Network Service, SNS)의 구조를 차용한 집단지성 기반 지식관리 시스템을 설계하여 기능에 따른 화면구조, 사용자의 편의 향상과 융합적인 지식콘텐츠 생산을 위한 추천알고리즘을 제시한다. 본 연구에서 제안하는 소셜 네트워크 서비스 기반의 지식관리시스템은 기존 지식관리시스템보다 구성원의 참여를 독려하고 수준 높은 지식콘텐츠를 생산 및 공유할 수 있을 것으로 기대된다.

Neural Network-based Decision Class Analysis with Incomplete Information

  • Kim, Jae-Kyeong;Lee, Jae-Kwang;Park, Kyung-Sam
    • 한국데이타베이스학회:학술대회논문집
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    • 한국데이타베이스학회 1999년도 춘계공동학술대회: 지식경영과 지식공학
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    • pp.281-287
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    • 1999
  • Decision class analysis (DCA) is viewed as a classification problem where a set of input data (situation-specific knowledge) and output data (a topological leveled influence diagram (ID)) is given. Situation-specific knowledge is usually given from a decision maker (DM) with the help of domain expert(s). But it is not easy for the DM to know the situation-specific knowledge of decision problem exactly. This paper presents a methodology fur sensitivity analysis of DCA under incomplete information. The purpose of sensitivity analysis in DCA is to identify the effects of incomplete situation-specific frames whose uncertainty affects the importance of each variable in the resulting model. For such a purpose, our suggested methodology consists of two procedures: generative procedure and adaptive procedure. An interactive procedure is also suggested based the sensitivity analysis to build a well-formed ID. These procedures are formally explained and illustrated with a raw material purchasing problem.

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A Design of K-XMDR Search System Using Topic Maps

  • Jialei, Zhang;Hwang, Chi-Gon;Jung, Gye-Dong;Choi, Young-Keun
    • Journal of information and communication convergence engineering
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    • 제9권3호
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    • pp.287-294
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    • 2011
  • This paper proposes a search system using the topic maps that it extends XMDR into Knowledge based XMDR for solving of the problems of the heterogeneity of distributed data on a network and integrate data by an efficient way. The proposed system combined Topic Maps and the extended metadata registry effectively. The Topic Maps represent related knowledge and reasoning relationship by associations of topic. And the extended metadata registry standards and manages the metadata of the local systems through registration and certification on the distributed environment. We also proposed a meta layer, include the meta topic and meta association to achieve semantic classification grouping of topics and to define relationship between Topic Maps and extended metadata registry.

Neural Network-based Decision Class Analysis with Incomplete Information

  • 김재경;이재광;박경삼
    • 한국지능정보시스템학회:학술대회논문집
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    • 한국지능정보시스템학회 1999년도 춘계공동학술대회-지식경영과 지식공학
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    • pp.281-287
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    • 1999
  • Decision class analysis (DCA) is viewed as a classification problem where a set of input data (situation-specific knowledge) and output data(a topological leveled influence diagram (ID)) is given. Situation-specific knowledge is usually given from a decision maker (DM) with the help of domain expert(s). But it is not easy for the DM to know the situation-specific knowledge of decision problem exactly. This paper presents a methodology for sensitivity analysis of DCA under incomplete information. The purpose of sensitivity analysis in DCA is to identify the effects of incomplete situation-specific frames whose uncertainty affects the importance of each variable in the resulting model. For such a purpose, our suggested methodology consists of two procedures: generative procedure and adaptive procedure. An interactive procedure is also suggested based the sensitivity analysis to build a well-formed ID. These procedures are formally explained and illustrated with a raw material purchasing problem.

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A Study on the Application of Spatial-Knowledge-Tags using Human Motion in Intelligent Space

  • Jin, Tae-Seok;Morioka, Kazuyuki;Niitsuma, Mihoko;Sasaki, Takeshi;Hashimoto, Hideki
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2005년도 ICCAS
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    • pp.31-36
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    • 2005
  • Intelligent Space (iSpace) is the space where many intelligent devices, such as computers and sensors, are distributed. According to the cooperation of many intelligent devices, the environment comes to have intelligence. In iSpace, the locations of multiple humans and other objects are obtained and tracked by using multiple camera and color-based method. In addition, we describe a context-aware information system which is based on Spatial-Knowledge-Tags (SKT). SKT system enables humans to access information and data by using spatial location of human and stored information in storage. The proposed tracking method is applied to the intelligent environment and its performance is verified by the experiments.

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An expert system for hazard identification in chemical processes

  • Chae, Heeyeop;Yoon, Yeo-Hong;Yoon, En-Sup
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 19-21 Oct. 1992
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    • pp.430-435
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    • 1992
  • Hazard identification is one of the most important task in process design and operation. This work has focused on the development of a knowledge-based expert system for HAZOP (Hazard and Operability) studies which are regarded as one of the most systematic and logical qualitative hazard identification methodologies but which require a multidisciplinary team and demand much time-consuming, repetitious work. The developed system enables design engineers to implement existing checklists and past experiences for safe design. It will increase efficiency of hazard identification and be suitable for educational purposes. This system has a frame-based knowledge structure for equipment failures/process material properties and rule networks for consequence reasoning which uses both forward and backward chaining. To include wide process knowledge, it is open-ended and modular for future expansion. An application to LPG storage and fractionation system shows the efficiency and reliability of the developed system.

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Exploring the Determinants of MOOCs continuance intention

  • Jo, Donghyuk
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제12권8호
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    • pp.3992-4005
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    • 2018
  • In our current information-based society in which knowledge is a fundamental asset to production, the capability to utilize information and produce knowledge with the use of information technology (IT) has become essential to learning. Massive Open Online Courses (MOOCs) have recently been introduced in light of such changes and are recognized as an alternative to open education. MOOCs' capabilities are being acknowledged in lifelong education in terms of reeducation and knowledge sharing, and also in terms of improving teaching quality, and improving university students' levels of creativity and integrated thinking by supporting high-level content and teaching. Therefore, this study presents an extended research model that combines information system (IS) continuance and task-technology fit models. Our study researches previous literature, revealing factors of continuous use after accepting MOOCs from the learner's perspective, and analyzes the model empirically. The ideal environment for MOOCs learners is evaluated, and a strategic approach to the successful settlement and diffusion of MOOCs is presented based on this study's findings.

Product Variety Modeling Based on Formal Concept Analysis

  • Kim, Tai-Oun
    • Industrial Engineering and Management Systems
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    • 제9권1호
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    • pp.1-9
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    • 2010
  • Increasing product variety based on product family and product platform provides a company with a competitive advantage over its competitors. As products become more complex, short-life cycled and customized, the design efforts require more knowledge-intensive, collaborative and coordinating efforts for information sharing. By sharing knowledge, information, component and process across different families of products, the product realization process will be more efficient, cost-effective and quick-responsive. Formal Concept Analysis (FCA) is used for analyzing data and forming semantic structures that are formal abstractions of concepts of human thoughts. A Web Ontology Language (OWL) is designed for applications that need to process the content of information instead of simply presenting information to humans. OWL also captures the evolution of different components of the product family. The purpose of this paper is to develop product variety modeling to increase the usefulness of common platform. In constructing and analyzing product ontology, FCA is adopted for conceptual knowledge processing. For the selected product family, product variety Ontology is constructed and implemented using prot$\'{e}$g$\'{e}$-2000.

프로세스 중심의 진료의사결정 지원 시스템 구축 (Development of process-centric clinical decision support system)

  • 민영빈;김동수;강석호
    • 산업공학
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    • 제20권4호
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    • pp.488-497
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    • 2007
  • In order to provide appropriate decision supports in medical domain, it is required that clinical knowledge should be implemented in a computable form and integrated with hospital information systems. Healthcare organizations are increasingly adopting tools that provide decision support functions to improve patient outcomes and reduce medical errors. This paper proposes a process centric clinical decision support system based on medical knowledge. The proposed system consists of three major parts - CPG (Clinical Practice Guideline) repository, service pool, and decision support module. The decision support module interprets knowledge base generated by the CPG and service part and then generates a personalized and patient centered clinical process satisfying specific requirements of an individual patient during the entire treatment in hospitals. The proposed system helps health professionals to select appropriate clinical procedures according to the circumstances of each patient resulting in improving the quality of care and reducing medical errors.

Comparison of Alternative knowledge Acquisition Methods for Allergic Rhinitis

  • Chae, Young-Moon;Chung, Seung-Kyu;Suh, Jae-Gwon;Ho, Seung-Hee;Park, In-Yong
    • 지능정보연구
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    • 제1권1호
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    • pp.91-109
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    • 1995
  • This paper compared four knowledge acquisition methods (namely, neural network, case-based reasoning, discriminant analysis, and covariance structure modeling) for allergic rhinitis. The data were collected from 444 patients with suspected allergic rhinitis who visited the Otorlaryngology Deduring 1991-1993. Among four knowledge acquisition methods, the discriminant model had the best overall diagnostic capability (78%) and the neural network had slightly lower rate(76%). This may be explained by the fact that neural network is essentially non-linear discriminant model. The discriminant model was also most accurate in predicting allergic rhinitis (88%). On the other hand, the CSM had the lowest overall accuracy rate (44%) perhaps due to smaller input data set. However, it was most accuate in predicting non-allergic rhinitis (82%).

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