• Agribusiness and Information Management
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• 제8권1호
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• pp.11-16
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• 2016

This paper presents how Digital Knowledge Ecosystem such as "Govi Nena" (translates as agriculture intelligence) can be used to provide a more effective and practical solution to eliminate the inefficiencies in agricultural markets and achieve higher productivity and price stability. In order to establish the framework to analyze the system, this paper uses a set of hypothetical scenarios faced by value chain actors based on a review of the literature, established knowledge and recent developing country experiences. The scenario analysis reveals that "Govi Nena" enables farmers to make effective production decisions, deepens the level of value chain integration, and enhances the level of welfare for the society as a whole.

• 지식경영연구
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• 제19권3호
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• pp.31-46
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• 2018

Despite the organizational benefits of knowledge sharing among employees, many workers are reluctant to share their knowledge with their colleagues. Most organizations have taken a lot of actions to facilitate knowledge sharing among employees, including developing reward systems, enhancing social networks and interpersonal relationships and crafting organizational cultures that support knowledge sharing. To date, however, earlier studies have demonstrated that knowledge doesn't flow easily when an organization makes a concerted effort to facilitate knowledge sharing. The issue whether or not employees are motivated to share their knowledge with others is definitely the main concern in knowledge sharing. The purpose of this study is to explore the conditions under which employees are inclined to share knowledge with other members. Specifically, we examine the effect of knowledge self-efficacy on knowledge sharing intention. In addition, we attempt to investigate medicating effects of personal outcome expectation and performance-related outcome expectation on the relationship between knowledge self-efficacy and knowledge sharing intention. To test the proposed hypotheses in our study, we collected data via a survey with a sample of 210 employees in 23 firms in Korea. The major findings of the empirical research are as follows: 1) knowledge self-efficacy was positively related with knowledge sharing intention. 2) personal outcome expectation has turned out to have a mediation effect on the relationship between knowledge self-efficacy and knowledge sharing intention. 3) performance-related outcome expectation also mediates the relationship between knowledge self-efficacy and knowledge sharing intention That is, this result indicates that knowledge self-efficacy has indirect effect on knowledge sharing intention through personal outcome expectation and performance-related outcome expectation. Based on these findings, implications of the research findings and recommendation for future research are discussed.

• 한국IT서비스학회지
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• 제8권1호
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• pp.143-163
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• 2009

The study investigates the challenge of knowledge maintenance in the KMSs. Knowledge pieces are the embodiment of structures in an organization and need to be modified tuned to environmental change over time. Since the change of knowledge in the KMS is not made automatically, it requires user's active participation which is called maintenance action. This study shows that users are not voluntary in taking maintenance action with empirical data based upon knowledge pieces that are already established in the KMS. This article shows that the intention of maintaining KMS is negatively influenced by KM-related culture, organizational culture and the authority of knowledge piece rather than the organizational demography. An organizational culture has an influence directly upon the intention of maintaining knowledge but influence upon KM-related culture or the authority of knowledge piece, the influence indirectly related to the intention of maintaining knowledge. It can be argued that the organizational demography have only meager influence upon the intention of maintaining knowledge only by KM-related culture. This research has the implication that what factors are to be considered in maintaining knowledge pieces over time for the organization managers.

• 지식경영연구
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• 제13권1호
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• pp.13-24
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• 2012

Unlike the traditional belief that knowledge flows along the formal reporting procedures, recent social network research has reported the importance of informal social networks which may play a critical role as the real knowledge conduits. In fact, as a complementary approach of utilizing knowledge management systems (KMSs), many firms have focused on managing informal knowledge flow through which to acquire and transfer valuable knowledge in a fast and effective way. In a case of global companies that have newly developed foreign branches or subsidiaries, due to cultural or institutional differences and lack of understanding of knowledge management and its benefits, they often have difficulties in activating knowledge sharing in local branches. In these situations, diagnosing organizational knowledge flow through SNA can be a first step to solve the problems. Therefore, in this paper, I report on the result of case study on a foreign branch of "A" global company by identifying organizational knowledge paths. Based on the results of the diagnosis, some implications and insights for building knowledge management (KM) strategy specified for a newly developed foreign branch will also be discussed.

• 융합신호처리학회논문지
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• 제3권3호
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• pp.27-35
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• 2002

지식기반 영상검색은 영상이 갖는 다양한 데이터에서 추출되어진 특징값을 지식으로 하여 질의 영상에 대한 검색 결과영상을 찾아주는 방법이다. 본 연구에서 사용한 영상자료는 자동차 전조등 영상으로 전조등 영상에 대한 입력 자료는 차량마다 다양한 패턴을 갖는 영상과 문자, 숫자 및 특수문자이다. 영상에서의 정보는 화소값들의 분포상태나 통계적 분석 및 패턴의 상태 등인데, 전조등 영상에서는 이러한 정보가 영상 검색을 위한 지식 데이터로 사용된다. 영상데이터에서 추출된 다양한 정보를 다중 지식 기반으로 하여 본 논문에서는 교통사고나 기타 차량사건의 발생 시 활용할 수 있는 영상검색 시스템을 구축하였으며, 전조등 영상의 검색에 효율적으로 적용한 다중 지식기반 검색방법을 제안하였다. 다중지식 구축을 위한 특징함수는 컬러 영상에서와 그레이레벨 영상에서 각각 필요한 성분들을 추출하여 구성하였으며, 한 개나 두 개 정도의 특징값을 사용한 기존의 방법과 달리 복합적인 특징값의 사용을 통한 다중 지식 기반의 검색방법이 컬러정보나 패턴에 대한 유사성을 높여서 용의차량의 전조등 영상 검색 효율성을 향상시켰다. 소프트웨어의 제작을 위해 비쥬얼 베이직과 크리스탈리포트 그리고 MS 액세스 데이터베이스를 사용하였다. 검색 효율성 및 특성 함수의 구성을 효과적으로 발전시키면 검색시스템은 용의 차량의 추적 및 교통사고에서 효율적인 과학수사에 일조할 것으로 기대한다.

• Human Ecology Research
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• 제58권1호
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• pp.105-120
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• 2020

This study helps infant teachers practice a constructivism-based teacher education program that supports infant mathematical inquiry activities and examines improvements in mathematical teaching knowledge, mathematical teaching initiatives, mathematical interaction, constructivism belief and mathematical teaching efficacy. Twenty two experiment group infant teachers and twenty two comparison group infant teachers were chosen at two workforce educare centers. The experiment group infant teachers participated in 18 sessions of a constructivism teacher training program for 8 weeks, but the comparison group infant teachers did not take part in the program. Pretest and post-tests were implemented for the mathematical teaching knowledge, mathematical teaching initiatives, mathematical interactions, constructivism belief and mathematical teaching efficacy in the experiment group. Independent sample t-test and ANCOVA were tested using Windows SPSS statistics 21.0. The homogeneity test for the experiment and comparison group revealed significant differences. ANCOVA was carried out after the pretest score was controlled as a co-variance. Significant differences were indicated in mathematical teaching knowledge, mathematical teaching initiative, mathematical interaction, constructivism belief and mathematical teaching efficacy. The results indicated that a constructivism-based teacher education program to support infant mathematical inquiry activities influenced improvements in mathematical teaching knowledge, mathematical teaching initiative, mathematical interaction, constructivism belief and mathematical teaching efficacy. This study proved the effects of the program based on constructivism theory content for the knowledge, skills and attitude about infant teaching of mathematical initiatives and practiced a program of exploration, investigation, application and assessment for infant teachers. The results can help infant teachers teach mathematical exploration activities and help activate infant mathematical exploration activities.

• 인터넷정보학회논문지
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• 제12권5호
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• pp.113-125
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• 2011

정보의 출처와 형식이 다양해지고 정보의 양 또한 많아짐에 따라 소셜 웹에서의 맞춤형 지식 생성은 더욱 어려워지고 있다. RSS(Really Simple Syndication)가 정보 수집 방법의 개선에 일조했으나, 웹에 산재된 정보를 찾아 필요한 정보들만으로 구성된 맞춤형 지식을 생성하는 것은 여전히 사용자들의 몫으로 남아 있다. 본 논문에서는 맞춤형 지식 생성의 용이성을 제고하기 위해 상황 기반 유사도를 이용한 맞춤형 지식생성 프레임워크를 제안하였다. 본 프레임워크는 기본적으로 사례 기반추론의 절차를 따르지만, 기존 사례 기반의 유사도 계산 방식이 문법적 추론에 기반했던 것과 달리, 온톨로지를 활용한 의미적 유사도를 이용한 사례 기반 추론을 활용한다. 또한 사용자 요구를 만족하는 유사사례의 보정을 위해 온톨로지를 활용한 정보 집적도 기반의 유사도 방법론을 제안하였다. 본 프레임워크에서는 첫째 비구조적인 웹 정보를 사례 형태의 구조적 정보로 변환하고, 둘째 사용자의 요구에 적합한 의미론적 유사사례를 찾은 후 셋째, 선택된 유사사례의 정보 집적도를 고려한 보정을 통해 맞춤형 지식을 생성하는 과정을 거친다. 본 논문에서는 유사도 계산에 일반적으로 활용되는 여러 방법론들과 비교를 통하여 제안한 온톨로지 기반 의미적 유사도 계산 방법론의 타당성을 입증하였다.

• 한국차세대컴퓨팅학회논문지
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• 제13권2호
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• pp.102-110
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• 2017

최근 자연어 처리 분야에서 단어의 모호성을 해소하기 위해서 다양한 기계 학습 방법이 적용되고 있다. 지도 학습에 사용되는 데이터는 정답을 부착하기 위해 많은 비용과 시간이 필요하므로 최근 연구들은 비지도 학습의 성능을 높이기 위한 노력을 지속적으로 시도하고 있다. 단어 모호성 해소(word sense disambiguation)를 위한 비지도 학습연구는 지식 기반(knowledge base)를 이용한 방법들이 주목받고 있다. 이 방법은 학습 데이터 없이 지식 기반의 정보을 이용하여 문장 내에서 모호성을 가지는 단어의 의미를 결정한다. 지식 기반을 이용한 방법에는 그래프 기반방식과 유사도 기반 방법이 대표적이다. 그래프 기반 방법은 모호성을 가지는 단어와 그 단어가 가지는 다양한 의미들의 집합 간의 모든 경로에 대한 의미 그래프를 구축한다는 장점이 있지만 불필요한 의미 경로가 추가되어 오류를 증가시킨다는 단점이 있다. 이러한 문제를 해결하기 위해 본 논문에서는 그래프 구축을 위해 불필요한 간선들을 배제하면서 반복적으로 그래프를 재구축하는 모델을 제안한다. 또한, 구축된 의미 그래프에서 더욱 정확한 의미를 예측하기 위해 하이브리드 유사도 예측 모델을 적용한다. 또한 제안된 모델은 다국어 어휘 의미망 사전인 BabelNet을 사용하기 때문에 특정 언어뿐만 아니라 다양한 언어에도 적용 가능하다.

• 한국정보처리학회논문지
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• 제6권11호
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• pp.2863-2874
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• 1999

Apartment auction is a system that is used for the citizens to get a house. This paper deals with the implementation of a web-based intelligent decision support system using OLAP technique and data mining technique for auction decision support. The implemented decision support system is working on a real auction database and is mainly composed of OLAP Knowledge Extractor based on data warehouse and Auction Data Miner based on data mining methodology. OLAP Knowledge Extractor extracts required knowledge and visualizes it from auction database. The OLAP technique uses fact, dimension, and hierarchies to provide the result of data analysis by menas of roll-up, drill-down, slicing, dicing, and pivoting. Auction Data Miner predicts a successful bid price by means of applying classification to auction database. The Miner is based on the lazy model-based classification algorithm and applies the concepts such as decision fields, dynamic domain information, and field weighted function to this algorithm and applies the concepts such as decision fields, dynamic domain information, and field weighted function to this algorithm to reflect the characteristics of auction database.

• 한국정보시스템학회지:정보시스템연구
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• 제21권3호
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• pp.45-70
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• 2012

Based on the usage levels of target costing systems(TCS) and information technology (IT) infrastructure, this study aims to develop a framework useful for classifying four types of knowledge management(KM) strategies in manufacturing firms: process-oriented, product-oriented, mixed and negative. We adopted a multi-methodological approach by mixing both qualitative and quantitative methods. Before developing a framework, through a case study of the H Motor Company in Korea, this paper investigated and showed the functions of TCS in the management of tacit knowledge. The results from the case study indicated that with the use of TCS, a firm can create, transfer, and share diverse kinds of tacit knowledge among employees for the facilitation of process innovation. We also empirically confirmed the four types of KM strategies, and demonstrated the characteristics(i.e., size, total sales, age, and knowledge intensity) of the organizations adopting each strategy.