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

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2006.11a
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• pp.597-601
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• 2006

There are considerable amount of man power and time spent for analysis and selection of various materials due to the inadequate application system and rapid searching process of material related information in each stage of building production process. Also, due to the insufficiency in recycling system of important information created for each process, they are hoarded at each task stage and project completion. As a result, because of the repetition of the similar/identical tasks on each process, it is the major reason for impeding the efficient employment of manpower of the company and decreasing competition of the company. Moreover, in selecting finish material in the project field, there are many difficulties due to the lack of technical information such as product characteristics and field applications. The construction quality also affects the profit and loss of the product which calls for a need to develop continued information management system that the finish material related examples could be shared in real time. The objective of this study is to propose a building finish material information which the real time research and application is possible to raise the productivity. TO do this, the current material information task status analysis and questionnaire research should be conducted to understand the demand of system development and reflect the result onto the system for easy access and application. Therefore, the building finish material information system for enhancement of productivity of construction task proposed in this study is expected to be utilized in enhancement of construction quality, maximization of company profit, and strengthening of company competition.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2004.03a
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• pp.599-605
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• 2004

기존의 구축된 GIS 컴포넌트 혹은 개발 중이거나 향후개발을 목표로 설계단계에 있는 컴포넌트들의 최종 목표는 재사용성과 상호운용성의 가능성 여부이다. 하지만 컴포넌트 개발에 있어 시스템 개발환경의 다양성으로 인하여 그 재활용성은 생각만큼 쉬운 작업이 아니며, 특히 공간정보를 다루고 있는 GIS(Geographic Information System)분야에서의 GIS 컴포넌트 재활용은 전 세계의 산재한 각 데이터형의 포맷, 개발 환경, 운영환경을 고려하여 볼 때 시급한 일임에도 불구하고 그에 대한 노력이 상당히 미진한 실 정 이 다. 본 논문에서는 GIS 애플리케이션을 보다 효율적이고 유용하게 개발하기 위하여 GIS 컴포넌트의 개발과 관리에 이르는 전 과정을 관리 감독할 수 있는 COGIS(Component Oriented Geographic Information System)을 제안하고, COGIS 프로세스의 가이드라인이며 GIS 컴포넌트의 기능적인 면을 정의하기 위한 GCA(GIS based Component Architecture) 아키텍처를 제안하였다. 아울러 GIS 컴포넌트의 메타데이터를 분류 및 정의하여 GIS 컴포넌트의 비 기능적면을 제시하고 이를 이용하여 웹 기반 GIS 컴포넌트 등록/검색 에이전트 시스템을 개발하였으며 기존 GIS 컴포넌트 재사용 및 확장, 신규 컴포넌트의 등록, 검색이 가능하도록 한다. 사례연구로 웹 상에서 산불 발생 위험지수 표출을 위한 GIS 공간 분포도 작성이 쉽게 이루어지도록 2FDRV.avx와 2FDRC.exe 컴포넌트를 개발하였으며, COGIS 프로세스의 컴포넌트 관리방법을 통하여 여러 관련 컴포넌트를 조합함으로써 웹 기반 산불위험지수예보시스템을 구축하였다.입력 근거의 확보’, ‘갱신주체별 역할의 정의 및 유지관리 기준의 설정’, ‘분야별업무 특성을 고려한 관련 기준의 마련 및 타 시스템과 연계되는 항목을 고려한 절차 정의’ 등에 대한 다양한 접근을 시도하였다. 본 연구에서 제시하는 유지관리 모델을 기반으로 각 지자체별로 적절한 컨설팅이 진행되고 이에 따라 담당자의 실천이 이루어진다면 지자체 GIS의 투자대비 효과에 대한 기대는 이상이 아닌 현실로 다가오게 될 것이다.가오게 될 것이다. 동일하게 25%의 소유권을 가지고 있다. ？스굴 시추사업은 2008년까지 수행될 계획이며, 시추작업은 2005년까지 완료될 계획이다. 연구 진행과 관련하여, 공동연구의 명분을 높이고 분석의 효율성을 높이기 위해서 시료채취 및 기초자료 획득은 4개국의 연구원이 모여 공동으로 수행한 후의 결과물을 서로 공유하고, 자세한 전문분야 연구는 각 국의 대표기관이 독립적으로 수행하는 방식을 택하였다 ？스굴에 대한 제1차 시추작업은 2004년 3월 말에 실시하였다. 시추작업 결과, 약 80m의 시추 코아가 성공적으로 회수되어 현재 러시아 이르쿠츠크 지구화학연구소에 보관중이다. 이 시추코아는 2004년 8월 중순경에 4개국 연구팀원들에 의해 공동으로 기재된 후에 분할될 계획이다. 분할된 시료는 국내로 운반되어 다양한 전문분야별 연구에 이용될 것이다. 한편, 제2차 시추작업은 2004년 12월에서 2005년 2월 사이에 실시될 계획이다. 수백만년에 이르는 장기간에 걸쳐 지구환경변화 기록이 보존되어 있는 ？스굴호에 대한 시추사업은 후기 신생대 동안 유라시아 대륙 중부에서 일어난 지구환경 및 기후변화를 이해함과 동시에 이러한 변화가 육상생태계 및 지표지질환경에 미친 영향을 이해하는데 크게 기여할 것이다.

• The Journal of the Korea Contents Association
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• v.19 no.2
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• pp.259-268
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• 2019

Dengue virus is a typical mosquito-borne virus, and the half of the world's population is exposed to infection. Dengue virus causes relatively mild symptoms such as dengue fever. However, when not treated properly, it is known to cause severe symptoms such as dengue hemorrhagic fever and dengue shock syndrome with a mortality rate of over 20%. Development of dengue virus detection technology is very important because it is reported that early diagnosis of dengue fever can lower the mortality rate to less than 1%. In this study, patent search related to dengue virus detection technology was conducted in Korea, USA, Europe, Japan, and China. The quantitative analysis of 69 validated patents from the searched patents was conducted by country, year, and patent holder. In addition, in-depth analysis was carried out by classifying into three categories: molecular diagnostics, immuno-diagnostics, and cell culture-based diagnostics from all validated patents. From these results, we analyzed the patent trend related to dengue virus detection and dengue fever diagnosis technology and discussed the features and limitations of molecular diagnostics and immuno-diagnostics at present level. Furthermore, we discussed the direction of technology development and future prospects to overcome limitations.

• Journal of The Korean Association For Science Education
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• v.20 no.1
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• pp.112-136
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• 2000

In this study, literatures concerning the scientifically gifted/talented were identified through exploration of ERIC(Education Research Information Center) and then categorized. Existing educational programs for the scientifically gifted/talented were analyzed to aid in development and progress of education program of the scientifically gifted/talented. The followings are the results of this study 1. Exploration of ERIC from 1981 to 1997 showed 150 documents related to the scientifically gifted/talented and of those found there were 63 scientifically gifted/talented education program documents which accounts for 42.0%. 2. 42.0% of documents related to the scientifically gifted/talented and 65.1% of education program for the scientifically gifted/talented were in the publication type of journal articles. 3. 60.0% of documents related to the scientifically gifted/talented and 68.3% of education program for the scientifically gifted/talented were in the type of paper of reports. 4. 71.4% of education programs for the gifted/talented was centered around scientifically gifted/talented students in middle or high school. 5. 52.4% of education programs for the scientifically gifted/talented was being carried out as an supplementary enrichment education program such as summer programs or short term projects. Education programs for the scientifically gifted/talented carried out as a regular class accounted for 38.1%. 6. Systems like Mentorship System and Internship System is being well carried out due to good interrelationships between universities and institutions. There were many programs encouraging majors and careers in science related fields. 7. Individualized education, which is effective in teaching the scientifically gifted/talented whose abilities, interests, and attitudes differ, is being well carried out.

• Journal of Korea Multimedia Society
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• v.4 no.1
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• pp.13-28
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• 2001

In a VOD(Vide-On-Demand) system, video data are generally stored in magnetic disk array. In order to provide real-time requirement for data retrieval, video streams must be delivered continuously to the clients such that the delivery of continuous media can be guaranteed in a timely fashion. Compared to the increased performance of processors and networks, the performance of magnetic disk systems have improved only modestly. In order to improve the performance of storage system, disk array system is proposed and used. The array system improves I/O performance by placing disks in parallel and retrieving data concurrently. In this paper, two approaches are considered in order to access the video data in a VOD system, which are CTL(Constant Time Length) and CDL(Constant Data Length) access policies. Disk scheduling policies are also classified into the two categories and compared in terms of the maximum allowable video streams with different degrees of disk array synchronization, under the mixed environments in which both data access policy and disk scheduling policy are considered. Among the compared scheduling policies, LOOK was shown to have the best performance. In terms of degree of disk synchronization, more gain was achieved with large degree of synchronization. In comparisons of performance of CTL and CDL, CTL was proved to have a little superior performance in terms of number of maximum allowable streams.

• Journal of Internet Computing and Services
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• v.22 no.5
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• pp.47-55
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• 2021

Analysis of research trends in specific subject areas is performed by examining related topics and subject changes by using topic modeling techniques through keyword extraction for most of the literature information (paper, patents, etc.). Unlike existing research methods, this paper extracts topics related to the research topic using the LDA topic modeling technique for the project information of national R&D projects provided by the National Science and Technology Knowledge Information Service (NTIS) in the field of artificial intelligence. By analyzing these topics, this study aims to analyze research topics and investment directions for national R&D projects. NTIS provides a vast amount of national R&D information, from information on tasks carried out through national R&D projects to research results (thesis, patents, etc.) generated through research. In this paper, the search results were confirmed by performing artificial intelligence keywords and related classification searches in NTIS integrated search, and basic data was constructed by downloading the latest three-year project information. Using the LDA topic modeling library provided by Python, related topics and keywords were extracted and analyzed for basic data (research goals, research content, expected effects, keywords, etc.) to derive insights on the direction of research investment.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.85-97
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• 2010

Internet communities are a typical space for knowledge creation and use on the Internet as people discuss their common interests within the internet communities. When we define 'Knowledge Communities' as internet communities that are related to knowledge creation and use, they are categorized into 4 different types such as 'Search Engine,' 'Open Communities,' 'Specialty Communities,' and 'Activity Communities.' Each type of knowledge community does not remain the same, for example. Rather, it changes with time and is also affected by the external business environment. Therefore, it is critical to develop processes for practical use of such changeable knowledge communities. Yet there is little research regarding a strategic framework for knowledge communities as a source of knowledge creation and use. The purposes of this study are (1) to find factors that can affect knowledge creation and use for each type of knowledge community and (2) to develop a strategic framework for practical use of the knowledge communities. Based on previous research, we found 7 factors that have considerable impacts on knowledge creation and use. They were 'Fitness,' 'Reliability,' 'Systemicity,' 'Richness,' 'Similarity,' 'Feedback,' and 'Understanding.' We created 30 different questions from each type of knowledge community. The questions included common sense, IT, business and hobbies, and were uniformly selected from various knowledge communities. Instead of using survey, we used these questions to ask users of the 4 representative web sites such as Google from Search Engine, NAVER Knowledge iN from Open Communities, SLRClub from Specialty Communities, and Wikipedia from Activity Communities. These 4 representative web sites were selected based on popularity (i.e., the 4 most popular sites in Korea). They were also among the 4 most frequently mentioned sitesin previous research. The answers of the 30 knowledge questions were collected and evaluated by the 11 IT experts who have been working for IT companies more than 3 years. When evaluating, the 11 experts used the above 7 knowledge factors as criteria. Using a stepwise linear regression for the evaluation of the 7 knowledge factors, we found that each factors affects differently knowledge creation and use for each type of knowledge community. The results of the stepwise linear regression analysis showed the relationship between 'Understanding' and other knowledge factors. The relationship was different regarding the type of knowledge community. The results indicated that 'Understanding' was significantly related to 'Reliability' at 'Search Engine type', to 'Fitness' at 'Open Community type', to 'Reliability' and 'Similarity' at 'Specialty Community type', and to 'Richness' and 'Similarity' at 'Activity Community type'. A strategic framework was created from the results of this study and such framework can be useful for knowledge communities that are not stable with time. For the success of knowledge community, the results of this study suggest that it is essential to ensure there are factors that can influence knowledge communities. It is also vital to reinforce each factor has its unique influence on related knowledge community. Thus, these changeable knowledge communities should be transformed into an adequate type with proper business strategies and objectives. They also should be progressed into a type that covers varioustypes of knowledge communities. For example, DCInside started from a small specialty community focusing on digital camera hardware and camerawork and then was transformed to an open community focusing on social issues through well-known photo galleries. NAVER started from a typical search engine and now covers an open community and a special community through additional web services such as NAVER knowledge iN, NAVER Cafe, and NAVER Blog. NAVER is currently competing withan activity community such as Wikipedia through the NAVER encyclopedia that provides similar services with NAVER encyclopedia's users as Wikipedia does. Finally, the results of this study provide meaningfully practical guidance for practitioners in that which type of knowledge community is most appropriate to the fluctuated business environment as knowledge community itself evolves with time.

• Journal of KIISE:Databases
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• v.37 no.3
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• pp.127-136
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• 2010

With rapid growth of information and computer communication technologies, the numbers of digital documents including multimedia data have been recently exploded. In particular, news video database and news video mining have became the subject of extensive research, to develop effective and efficient tools for manipulation and analysis of news videos, because of their information richness. However, many research focus on browsing, retrieval and summarization of news videos. Up to date, it is a relatively early state to discover and to analyse the plentiful latent semantic knowledge from news videos. In this paper, we propose the news video mining system based on multi-modal approach and text mining, which uses the visual-textual information of news video clips and their scripts. The proposed system systematically constructs a taxonomy of news video stories in automatic manner with hierarchical clustering algorithm which is one of text mining methods. Then, it multilaterally analyzes the topics of news video stories by means of time-cluster trend graph, weighted cluster growth index, and network analysis. To clarify the validity of our approach, we analyzed the news videos on "The Second Summit of South and North Korea in 2007".

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.4
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• pp.466-472
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• 2021

This paper aims to guide experts who manage dementia by exploring the various non-drug interventions and analyzing the effective intervention methods applicable according to the functional level of the elderly with dementia. Fourteen studies were analyzed in this study. Meta-analysis was performed using the means, standard deviations, and the number of samples. Subsequent meta-analysis showed that the Holnis program had the largest effect size in cognitive function, the bakery activity program in memory, and the composite intermediation program with ADL was the largest. In addition, client-centric cognitive stimulation interventions showed the most significant effect sizes, while in depression and BPSD, rhythmic movement activities had the most significant effect size. Elderly with dementia exhibit various symptoms depending on their characteristics and the progress of the disease. Therefore, more efficient arbitration could be provided if the effects of each intervention can be applied differently.