• The KIPS Transactions:PartD
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• v.18D no.6
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• pp.501-508
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• 2011

A knowledge map, which has been recently applied in various fields, is discovering characteristics hidden in a large amount of information and showing a tangible output to understand the meaning of the discovery. In this paper, we suggested a knowledge map for research trend analysis based on keyword-relation networks which are constructed by using a database of the domestic journal articles in the computer engineering field from 2000 through 2010. From that knowledge map, we could infer influential changes of a research topic related a specific keyword through examining the change of sizes of the connected components to which the keyword belongs in the keyword-relation networks. In addition, we observed that the size of the largest connected component in the keyword-relation networks is relatively small and groups of high-similarity keyword pairs are clustered in them by comparison with the random networks. This implies that the research field corresponding to the largest connected component is not so huge and many small-scale topics included in it are highly clustered and loosely-connected to each other. our proposed knowledge map can be considered as a approach for the research trend analysis while it is impossible to obtain those results by conventional approaches such as analyzing the frequency of an individual keyword.

• Journal of the Korean Society for Library and Information Science
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• v.49 no.3
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• pp.393-412
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• 2015

The purpose of this study is to suggest development plan of the Regional knowledge information services through the case study analysis between Korea and Japan public libraries. For this purpose, we analyzed literature related to the Regional knowledge information services, performed case study, and carried out a investigation which focuses on a public libraries webpage. According to the analysis, the development plan for the Regional knowledge information services was suggested as follow; that is user-friendly service, internal cooperation, external network cooperative strategy, visible public relations and recognition improvement. This study has aimed to prepare for the basic data which will help Korea public libraries to make better Regional knowledge information services in the future.

• Journal of Information Management
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• v.36 no.4
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• pp.199-215
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• 2005

Experts participating in the knowledge expert network externalize their implicit knowledge by providing information or writing reports. Almost all the members of the network share externalized knowledge and the network facilitate the dissemination and diffusion of knowledge. Individuals reproduce another implicit knowledge by internalizing shared knowledge through the network and re-created knowledge is externalized, establishing knowledge circulation. In this paper, we analyze the expert groups of the Global Network of Korean Scientists & Engineers(KOSEN, www.kosen21.org), the Korea's No. 1 science and engineering knowledge expert community, with the application of the theory of policy network proposed by Marsh & Rhodes. According to the principal standards of policy network classification such as the number of participants, interaction among participants, consistency, distribution of resources and dependency, we categorize the KOSEN expert groups as closed policy network and opened issue network, and divide closed policy network into core community and periphery community.

• Knowledge Management Research
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• v.22 no.4
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• pp.1-26
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• 2021

Measuring the intangible asset has been vigorously studied for its importance. Especially, the value of character in media industry is difficult to quantitatively evaluate in spite of the industry's rapid growth. Recently, the Social Network Analysis (i.e., SNA) has been actively applied to understand human usage patterns in a media field. By using SNA methodology, this study attempts to investigate how the character network characteristics of media works are linked to human search behaviors. Our analysis reveals the positive correlation and causality between character network centralities and character search data. This result implies that the character network can be used as a clue for the valuation of character assets.

• The Journal of the Korea Contents Association
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• v.10 no.9
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• pp.348-362
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• 2010

In the Knowledge-based economy, it is inevitable for companies to implement knowledge management(KM in short) to improve management performance. In order to better understand the KM, it is necessary to examine the relationship between success factors of KM and KM performance in agribusiness sector. This study empirically analyzes the impact of success factors of Knowledge Management on companies' management performance in agribusiness cluster. From the survey data of 43 companies located in Sunchang fermented soybean products Industrial cluster, the study finds that four factors- learning culture, network, knowledge sharing and knowledge creating- influence management performance in a positive way. It also examines whether Industrial cluster strategy functions as a moderator between KM success factors and companies' performance. Furthermore, this study concludes that Sunchang fermented soybean Industrial cluster has not reached to the final stage of KM and suggests elements for further improvements.

• Journal of Digital Convergence
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• v.8 no.1
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• pp.71-79
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• 2010

Impact of online social network to cyber community has increased much attention recently. The biggest challenge in fostering a social network is to the extent whether it helps to build human capital network or social community. We propose what critical factors influence the formation of online capital network. The study uses three independent factors as motivation, self disclosure, and interactivity and two dependent factors as knowledge sharing and strengthening relationships to create virtual capital connection. Data collected from 256 university students to test the proposed model. The results of the study shows that all hypothesis are supported except one with strengthening relationship. Implications and limitations of this research are discussed.

• Journal of Korean Society for Geospatial Information Science
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• v.18 no.4
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• pp.61-69
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• 2010

The collapse of a slope or cut embankment brings much damage to life and property. Accordingly, it is very important to analyze the spatial distribution by calculating the landslide susceptibility in the estimation of the risk of landslide occurrence. The heuristic, statistic, deterministic, and probabilistic methods have been introduced to make landslide susceptibility maps. In many cases, however, the reliability is low due to insufficient field data, and the qualitative experience and knowledge of experts could not be combined with the quantitative mechanical?analysis model in the existing methods. In this paper, new modeling method for a probabilistic landslide susceptibility analysis combined Bayesian Network with ontology model about experts' knowledge and spatial data was proposed. The ontology model, which was made using the reasoning engine, was automatically converted into the Bayesian Network structure. Through conditional probabilistic reasoning using the created Bayesian Network, landslide susceptibility with uncertainty was analyzed, and the results were described in maps, using GIS. The developed Bayesian Network was then applied to the test-site to verify its effect, and the result corresponded to the landslide traces boundary at 86.5% accuracy. We expect that general users will be able to make a landslide susceptibility analysis over a wide area without experts' help.

• The KIPS Transactions:PartB
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• v.15B no.2
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• pp.147-158
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• 2008

Fuzzy Cognitive Map (FCM) and Bayesian Belief Network (BBN) are two major frameworks for modeling, representing and reasoning about causal knowledge. Despite their extensive use in causal knowledge engineering, there is no reported work which compares their respective roles. This paper aims to fill the gap by providing a qualitative comparison of the two frameworks through a systematic analysis based on some inherent features of the frameworks. We proposed a set of comparison criteria which covers the entire process of causal knowledge engineering, including modeling, representation, and reasoning. These criteria are usability, expressiveness, reasoning capability, formality, and soundness. The results of comparison have revealed some important facts about the characteristics of FCM and BBN, which will help to determine how FCM and BBN should be used, with respect to each other, in causal knowledge engineering.

• Proceedings of the Korean Society of Disaster Information Conference
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• 2022.10a
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• pp.145-147
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• 2022

본 논문은 대규모 텍스트 데이터에서 이슈를 발굴할 때 사용되는 기존의 정보 네트워크 또는 지식 그래프 구축 방법의 한계점을 지적하고, 문장 단위로 정보 네트워크를 구축하는 새로운 방법에 대해서 제안한다. 먼저 문장을 구성하는 단어와 캐릭터수의 분포를 측정하며 의성어와 같은 노이즈를 제거하기 위한 역치값을 설정하였다. 다음으로 BERT 기반 언어모델을 이용하여 모든 문장을 벡터화하고, 코사인 유사도를 이용하여 두 문장벡터에 대한 유사성을 측정하였다. 오분류된 유사도 결과를 최소화하기 위하여 명사형 단어의 의미적 연관성을 비교하는 알고리즘을 개발하였다. 제안된 유사문장 비교 알고리즘의 결과를 검토해 보면, 두 문장은 서술되는 형태가 다르지만 동일한 주제와 내용을 다루고 있는 것을 확인할 수 있었다. 본 논문에서 제안하는 방법은 단어 단위 지식 그래프 해석의 어려움을 극복할 수 있는 새로운 방법이다. 향후 이슈 및 트랜드 분석과 같은 미래연구 분야에 적용하면, 데이터 기반으로 특정 주제에 대한 사회적 관심을 수렴하고, 수요를 반영한 정책적 제언을 도출하는데 기여할 수 있을 것이다

• Journal of the Korean Society for information Management
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• v.32 no.3
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• pp.317-340
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• 2015

This study clarified the knowledge structure of international collaboration in psychiatry based on analyzing networks in order to construct cooperation networks for international collaboration in psychiatry in South Korea. The result of analysis of knowledge structure at a state-level is as follows. First, this study found that the rate of collaboration for five years is high as 89.97%. Moreover, this study investigated the change of rate of collaboration and international collaboration according to the passage of time, and ascertained that while the rate of international collaboration has increased, Second, this study examined the trend of research on collaboration between Asian countries, and found that collaboration between Asian countries is on a low level. Third, the country (or group) that the number of papers of international collaboration and the value of centrality are the highest is EU-28. The result of analysis of knowledge structure at a research output-level is as follows. this study analyzed the correlation of centrality with research output, and found that positive correlation exists in the three indicators of centrality, and a country with high centrality has good research output.