• Journal of the Korean BIBLIA Society for library and Information Science
• /
• v.29 no.2
• /
• pp.127-148
• /
• 2018

This study defined the influence of the quality of job information websites and of user characteristic factors on the user satisfaction and on the intention of the use thereof based on the technical acceptance model to activate research on job information or job information websites in the category of Library and Information Science, amid studies on the Fourth Industrial Revolution in various disciplines emerging. 230 users experienced in job information websites were surveyed. The surveyed data were analyzed by applying the structural equation model. The results are as follows. Accuracy, security, self-efficacy, the perceived easiness of use had a positive effect on the perceived usefulness. Up-to-dateness, self-efficacy, individual innovation had a significant effect on the perceived easiness of use. The perceived usefulness and the perceived easiness of use had a positive effect on user satisfaction, and the user satisfaction had a significant effect on the intention of use.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2008.11a
• /
• pp.1284-1287
• /
• 2008

그리드는 지리적으로 분산된 다양한 컴퓨팅 자원을 초고속 네트워크로 연결하여 고속 연산, 대용량 데이터 처리를 가능케 하는 기술이다. 그리드 컴퓨팅 자원을 안정적으로 지원하기 위해서는 표준화된 그리드 기술과 그리드 네트워크 자원에 대한 관리가 요구된다. 본 논문에서는 네트워크 자원관리를 위하여 네트워크 매니저를 그리드 표준화 기구인 OGF의 WSRF 요구 사항을 기반으로 설계하였다. 또한, 단계별로 추상화된 네트워크 토폴로지 모델을 채택하여 2 단계의 자원 예약과 예약 시간에 따른 자원 할당 및 해제를 수용할 수 있도록 설계하였다. 설계된 그리드 네트워크 매니저를 이용하여 GMPLS 기반의 제어 및 전송망에서 예약 시간을 통한 자원의 예약 및 할당을 실험하였다.

• Journal of KIISE:Software and Applications
• /
• v.33 no.12
• /
• pp.1031-1051
• /
• 2006

To develop a ubiquitous system, several researches have been tried to apply multi-agent models to design a system. Even though current multi-agent models provide many benefits with ubiquitous system developments, there are still some deficiencies in completely supporting the characteristics of ubiquitous systems such as dynamic formation and termination of mission-oriented organizations and interrelationship between organizations. In addition, existing agent-based models only concern aboutananalysis and design of a system, then place a burden of implementation on developers. Therefore, in this paper, we propose the high-level abstraction model of a multi-agent based ubiquitous system and the development process concerning implementation as well as design of systems. In addition, we implemented a development toolkit, called as CDTK(Community computing system Development Tool Kit), then developed a small community computing system using the CDTK.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.14 no.11
• /
• pp.5987-5992
• /
• 2013

The authors suggest the extension IFC schema of drainage facilities for the purpose of establishment the information model standard for the roads. IFC entities, types and properties for drainage facilities are defined by the analysis of road design documents for extraction physical component and design information IFC schema is able to be extended through the result of this research. Futhermore, IFC for additional road facilities is able to be used as construction process control, quantity take off, and simulation applications with the interoperability of the IFC.

• Proceedings of the Korean Information Science Society Conference
• /
• 2000.10c
• /
• pp.44-46
• /
• 2000

본 논문은 Tertiary 저장장치를 이용한 대용량 비디오 서버의 설계와 구현에 대해서 기술한다. 서버는 서비스와 프로세스 관리 서브시스템, 자원 관리 서브시스템, 입출력 관리 서브시스템의 세 부분으로 구성된다. 입출력 대역폭이 낮은 Tertiary 저장장치의 효율적인 사용을 위해 디스크 캐쉬 풀 모델을 사용하고, 적절한 스케줄링 정책과 캐슁 알고리즘을 이용하여 가능한 많은 사용자를 수용한다. 서버는 Windows 2000에서 시스템 서비스로 구현되었으며 디스크 캐쉬의 효과적인 사용으로 Tertiary 저장장치의 낮은 대역폭을 최대한 활용하여 접속된 사용자에게 안정된 비디오 스트리밍 서비스를 제공한다.

• Management & Information Systems Review
• /
• v.35 no.2
• /
• pp.167-183
• /
• 2016

This study has recognized easy payment service as one of the new types of application of information and communication technologies and proposed a modified acceptance intention model by adding perceived risk factor based on the unified theory of acceptance and use of technology(UTAUT) and then explored those variables that effect the acceptance intention of consumers. The results of this study can be summarized as the followings. First, expectation on the efforts, social impact have positive effect on the acceptance intention and perceived risk has negative effect on the acceptance intention but expectation on the efforts and promotion condition were found to have no effect on the acceptance intention. Second, among the factors suggested, social impact was found to have more effect of causing the acceptance intention of users than expectation on the efforts and perceived risk. Third, it was found that there is a significant association between the acceptance intention and use behavior of users of easy payment service. This means that, as was reviewed in the preceding researches, the acceptance intention affects actual acceptance behavior of users either directly or indirectly. Fourth, even though innovation resistance has regulation effect on the relationship between expectation on efforts or social impact and acceptance intention, it was found to have no regulation effect on the relationship between perceived risk and acceptance intention.

• The Transactions of the Korea Information Processing Society
• /
• v.5 no.1
• /
• pp.11-23
• /
• 1998

In very large databases, the problem of searching for interesting information effectively is very important in terms of efficiency and flexibility. A multiple layered database approach based on AOG(attribute-oriented generalization) method is one of the useful approaches for knowledge discovery under various situations. In this paper, we propose a multiple layered database design methodology based on AOG method in object-oriented databases. In addition, we propose a dynamic schema evolution model and implementation strategy in order to continue providing information effectively in multiple layered databases.

• Journal of Intelligence and Information Systems
• /
• v.27 no.1
• /
• pp.103-128
• /
• 2021

Recently, investors' interest and the influence of stock-related information dissemination are being considered as significant factors that explain stock returns and volume. Besides, companies that develop, distribute, or utilize innovative new technologies such as artificial intelligence have a problem that it is difficult to accurately predict a company's future stock returns and volatility due to macro-environment and market uncertainty. Market uncertainty is recognized as an obstacle to the activation and spread of artificial intelligence technology, so research is needed to mitigate this. Hence, the purpose of this study is to propose a machine learning model that predicts the volatility of a company's stock price by using the internet search volume of artificial intelligence-related technology keywords as a measure of the interest of investors. To this end, for predicting the stock market, we using the VAR(Vector Auto Regression) and deep neural network LSTM (Long Short-Term Memory). And the stock price prediction performance using keyword search volume is compared according to the technology's social acceptance stage. In addition, we also conduct the analysis of sub-technology of artificial intelligence technology to examine the change in the search volume of detailed technology keywords according to the technology acceptance stage and the effect of interest in specific technology on the stock market forecast. To this end, in this study, the words artificial intelligence, deep learning, machine learning were selected as keywords. Next, we investigated how many keywords each week appeared in online documents for five years from January 1, 2015, to December 31, 2019. The stock price and transaction volume data of KOSDAQ listed companies were also collected and used for analysis. As a result, we found that the keyword search volume for artificial intelligence technology increased as the social acceptance of artificial intelligence technology increased. In particular, starting from AlphaGo Shock, the keyword search volume for artificial intelligence itself and detailed technologies such as machine learning and deep learning appeared to increase. Also, the keyword search volume for artificial intelligence technology increases as the social acceptance stage progresses. It showed high accuracy, and it was confirmed that the acceptance stages showing the best prediction performance were different for each keyword. As a result of stock price prediction based on keyword search volume for each social acceptance stage of artificial intelligence technologies classified in this study, the awareness stage's prediction accuracy was found to be the highest. The prediction accuracy was different according to the keywords used in the stock price prediction model for each social acceptance stage. Therefore, when constructing a stock price prediction model using technology keywords, it is necessary to consider social acceptance of the technology and sub-technology classification. The results of this study provide the following implications. First, to predict the return on investment for companies based on innovative technology, it is most important to capture the recognition stage in which public interest rapidly increases in social acceptance of the technology. Second, the change in keyword search volume and the accuracy of the prediction model varies according to the social acceptance of technology should be considered in developing a Decision Support System for investment such as the big data-based Robo-advisor recently introduced by the financial sector.

• Journal of the Korean Society for information Management
• /
• v.34 no.2
• /
• pp.47-80
• /
• 2017

The purpose of this study is to develop an adoptive model of institutional repositories (IRs) by identifying the key factors affecting adoptive intention of IRs and explaining the relations among these factors. Through a survey of 270 researchers and 12 in-depth interviews in the field of physics, mathematics, and life science in Korea, performance expectancy, perceived risks, socio-organizational influence, and individual characteristics were found to have substantial influences on the adoptive intention of IRs. Among the key factors, individual characteristics showed the greatest effect on the adoptive intention of IRs, followed by performance expectancy and other socio-organizational influences except for the perceived risks. Strategies to enhance the adoptive intention of IRs based on analyses of the results were suggested, in terms of the reformation of research assessment system at the national level, strengthening of role of the operational institution, and the need for voluntary scientists-participating service.

• Journal of Digital Convergence
• /
• v.9 no.6
• /
• pp.355-368
• /
• 2011

For an effective warfare under the condition of NCW, the sharing of data between systems must be essential. Thus, the standardization and the integration of data which is considered as the MND-EA improvement and the Megacenter is important. The purpose of this research is to investigate the factors that affected the BI(Behavioral Intention to USE) by using the TAM(Technology Acceptance Model), That is to introduce the MDM into the national defense field which is an issue in every agency sector for data sharing. Also, based on the implementation architecture of Gartner which applies depending on the business enterprise type, the preferred architecture should be selected considering the national defense environment and the characteristics, and suggest an effective MND-MDM plan by analysing the effects on the BI. The survey was done through 19th September till the 7th of October 2011, by investigating the people in charge of the development and maintenance of the national defense information systems and the SI company's national defense team people who have experienced the development of the national defense information systems.