• Journal of Intelligence and Information Systems
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• v.18 no.2
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• pp.143-156
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• 2012

People easily believe that news and stock index are closely related. They think that securing news before anyone else can help them forecast the stock prices and enjoy great profit, or perhaps capture the investment opportunity. However, it is no easy feat to determine to what extent the two are related, come up with the investment decision based on news, or find out such investment information is valid. If the significance of news and its impact on the stock market are analyzed, it will be possible to extract the information that can assist the investment decisions. The reality however is that the world is inundated with a massive wave of news in real time. And news is not patterned text. This study suggests the stock-index invest model based on "News Big Data" opinion mining that systematically collects, categorizes and analyzes the news and creates investment information. To verify the validity of the model, the relationship between the result of news opinion mining and stock-index was empirically analyzed by using statistics. Steps in the mining that converts news into information for investment decision making, are as follows. First, it is indexing information of news after getting a supply of news from news provider that collects news on real-time basis. Not only contents of news but also various information such as media, time, and news type and so on are collected and classified, and then are reworked as variable from which investment decision making can be inferred. Next step is to derive word that can judge polarity by separating text of news contents into morpheme, and to tag positive/negative polarity of each word by comparing this with sentimental dictionary. Third, positive/negative polarity of news is judged by using indexed classification information and scoring rule, and then final investment decision making information is derived according to daily scoring criteria. For this study, KOSPI index and its fluctuation range has been collected for 63 days that stock market was open during 3 months from July 2011 to September in Korea Exchange, and news data was collected by parsing 766 articles of economic news media M company on web page among article carried on stock information>news>main news of portal site Naver.com. In change of the price index of stocks during 3 months, it rose on 33 days and fell on 30 days, and news contents included 197 news articles before opening of stock market, 385 news articles during the session, 184 news articles after closing of market. Results of mining of collected news contents and of comparison with stock price showed that positive/negative opinion of news contents had significant relation with stock price, and change of the price index of stocks could be better explained in case of applying news opinion by deriving in positive/negative ratio instead of judging between simplified positive and negative opinion. And in order to check whether news had an effect on fluctuation of stock price, or at least went ahead of fluctuation of stock price, in the results that change of stock price was compared only with news happening before opening of stock market, it was verified to be statistically significant as well. In addition, because news contained various type and information such as social, economic, and overseas news, and corporate earnings, the present condition of type of industry, market outlook, the present condition of market and so on, it was expected that influence on stock market or significance of the relation would be different according to the type of news, and therefore each type of news was compared with fluctuation of stock price, and the results showed that market condition, outlook, and overseas news was the most useful to explain fluctuation of news. On the contrary, news about individual company was not statistically significant, but opinion mining value showed tendency opposite to stock price, and the reason can be thought to be the appearance of promotional and planned news for preventing stock price from falling. Finally, multiple regression analysis and logistic regression analysis was carried out in order to derive function of investment decision making on the basis of relation between positive/negative opinion of news and stock price, and the results showed that regression equation using variable of market conditions, outlook, and overseas news before opening of stock market was statistically significant, and classification accuracy of logistic regression accuracy results was shown to be 70.0% in rise of stock price, 78.8% in fall of stock price, and 74.6% on average. This study first analyzed relation between news and stock price through analyzing and quantifying sensitivity of atypical news contents by using opinion mining among big data analysis techniques, and furthermore, proposed and verified smart investment decision making model that could systematically carry out opinion mining and derive and support investment information. This shows that news can be used as variable to predict the price index of stocks for investment, and it is expected the model can be used as real investment support system if it is implemented as system and verified in the future.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.4
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• pp.158-168
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• 2019

Korea Hydrographic and Oceanographic Agency(KHOA) carried out a research project named 'Marine Fisheries Infrastructure Construction and Technology Training for the Philippines' as part of the 1st Official Development Assistance(ODA) from 2015 to 2018. It is preparing for the 2nd ODA project which will begin in 2020. Besides, recently, the Philippines is paying attention to marine territory management and response capability due to problems such as the sea-level rise and coastal erosion caused by climate change. Therefore, before 2nd ODA to the Philippines, this study analyzed the vertical ocean model on the vertical datum in Korea and suggests the direction of development of the vertical ocean modeling system for the vertical datum in the Philippines using the observed data from the permanent tide station which was built by the Philippines ODA research project over the last four years. Moreover, as a pilot study, the Sulu Sea in the Philippines was selected and analyzed by harmonic analysis method. At each tide station, constants for correction had been computed. And the grid-based tidal model was constructed based on this study. As a result of the study, similar tidal characteristic were observed when the prediction and the measured tide were compared by applying the constants for correction between two station in the sea area with similar tidal level. These results could be used as basic data for the 2nd ODA to the Philippines, and contributed to construct and maintain a close cooperation and friendship between Korea and the Philippines.

• Journal of Venture Innovation
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• v.5 no.4
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• pp.135-156
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• 2022

This study attempted to identify the factors affecting entrepreneurial intention and to confirm the moderating effect of social support that plays a positive role in increasing entrepreneurial intention. The subjects of the study were 419 ordinary people, and data were obtained online and analyzed. The analysis method of this study was based on the SPSS statistical program Ver. 24, and a hierarchical regression analysis method was conducted to analyze the moderating effect. The results of hypothesis verification analysis in this study are as follows. First, innovativeness, risk-taking, self-fulfillment, economic motivation, immersion in a drama, drama role model, and indirect experience, all had a significant positive(+) effect on entrepreneurial intention. Second, among the factors affecting entrepreneurial intention, self-fulfillment was found to have the greatest influence. Third, it was confirmed that the moderating effect of social support between various variables and entrepreneurial intention had a significant effect on innovativeness, self-fulfillment, drama role model, and indirect experience, and entrepreneurial intention. The academic value of this study is to confirm the effect of drama characteristic variables on entrepreneurial intention. In addition, it was possible to confirm the moderating effect of social support, which is the total of individual external support. The implication of this study is that the desire for achievement had the greatest influence on entrepreneurial intention. Therefore, it is necessary to develop a desire to achieve in start-up support policies and start-up education. In addition, in light of the ripple effect of TV dramas, drama role model and indirect experience increase entrepreneurial intention, so it was possible to predict its influence on changes in perception of start-ups and entrepreneurs.

• Journal of Internet Computing and Services
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• v.22 no.6
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• pp.25-32
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• 2021

In line with future changes in the marine environment, Aids to Navigation has been used in various fields and their use is increasing. The term "Aids to Navigation" means an aid to navigation prescribed by Ordinance of the Ministry of Oceans and Fisheries which shows navigating ships the position and direction of the ships, position of obstacles, etc. through lights, shapes, colors, sound, radio waves, etc. Also now the use of Aids to Navigation is transforming into a means of identifying and recording the marine weather environment by mounting various sensors and cameras. However, Aids to Navigation are mainly lost due to collisions with ships, and in particular, safety accidents occur because of poor observation visibility due to sea fog. The inflow of sea fog poses risks to ports and sea transportation, and it is not easy to predict sea fog because of the large difference in the possibility of occurrence depending on time and region. In addition, it is difficult to manage individually due to the features of Aids to Navigation distributed throughout the sea. To solve this problem, this paper aims to identify the marine weather environment by estimating sea fog level approximately with images taken by cameras mounted on Aids to Navigation and to resolve safety accidents caused by weather. Instead of optical and temperature sensors that are difficult to install and expensive to measure sea fog level, sea fog level is measured through the use of general images of cameras mounted on Aids to Navigation. Furthermore, as a prior study for real-time sea fog level estimation in various seas, the sea fog level criteria are presented using the Haze Model and Dark Channel Prior. A specific threshold value is set in the image through Dark Channel Prior(DCP), and based on this, the number of pixels without sea fog is found in the entire image to estimate the sea fog level. Experimental results demonstrate the possibility of estimating the sea fog level using synthetic haze image dataset and real haze image dataset.

• Journal of Korea Spatial Information System Society
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• v.5 no.1 s.9
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• pp.49-63
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• 2003

Recently, two international standard organizations, ISO and OGC, have done the work of standardization for GIS. Current standardization work for providing interoperability among GIS DB focuses on the design of open interfaces. But, this work has not considered procedures and methods for designing GIS DB. Eventually, GIS DB has its own model. When we share the data by open interface among heterogeneous GIS DB, differences between models result in the loss of information. Our aim in this paper is to revise the design guidelines for geographic information databases in order to make consistent spatial data models, logical structures, and semantic structure of populated geographical databases. In details, we propose standard guidelines which convert ISO abstract schema into relation model, object-relation model, object-centered model, and geometry-centered model. Furthermore, we provide sample models for applying these guidelines in commercial GIS S/Ws. Building GIS DB based on design guidelines proposed in the paper has the following advantages: the interoperability among databases, the standardization of schema definitions, and the catalogue of GIS databases through.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.111-126
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• 2017

Recommender systems based on association rule mining significantly contribute to seller's sales by reducing consumers' time to search for products that they want. Recommendations based on the frequency of transactions such as orders can effectively screen out the products that are statistically marketable among multiple products. A product with a high possibility of sales, however, can be omitted from the recommendation if it records insufficient number of transactions at the beginning of the sale. Products missing from the associated recommendations may lose the chance of exposure to consumers, which leads to a decline in the number of transactions. In turn, diminished transactions may create a vicious circle of lost opportunity to be recommended. Thus, initial sales are likely to remain stagnant for a certain period of time. Products that are susceptible to fashion or seasonality, such as clothing, may be greatly affected. This study was aimed at expanding association rules to include into the list of recommendations those products whose initial trading frequency of transactions is low despite the possibility of high sales. The particular purpose is to predict the strength of the direct connection of two unconnected items through the properties of the paths located between them. An association between two items revealed in transactions can be interpreted as the interaction between them, which can be expressed as a link in a social network whose nodes are items. The first step calculates the centralities of the nodes in the middle of the paths that indirectly connect the two nodes without direct connection. The next step identifies the number of the paths and the shortest among them. These extracts are used as independent variables in the regression analysis to predict future connection strength between the nodes. The strength of the connection between the two nodes of the model, which is defined by the number of nodes between the two nodes, is measured after a certain period of time. The regression analysis results confirm that the number of paths between the two products, the distance of the shortest path, and the number of neighboring items connected to the products are significantly related to their potential strength. This study used actual order transaction data collected for three months from February to April in 2016 from an online commerce company. To reduce the complexity of analytics as the scale of the network grows, the analysis was performed only on miscellaneous goods. Two consecutively purchased items were chosen from each customer's transactions to obtain a pair of antecedent and consequent, which secures a link needed for constituting a social network. The direction of the link was determined in the order in which the goods were purchased. Except for the last ten days of the data collection period, the social network of associated items was built for the extraction of independent variables. The model predicts the number of links to be connected in the next ten days from the explanatory variables. Of the 5,711 previously unconnected links, 611 were newly connected for the last ten days. Through experiments, the proposed model demonstrated excellent predictions. Of the 571 links that the proposed model predicts, 269 were confirmed to have been connected. This is 4.4 times more than the average of 61, which can be found without any prediction model. This study is expected to be useful regarding industries whose new products launch quickly with short life cycles, since their exposure time is critical. Also, it can be used to detect diseases that are rarely found in the early stages of medical treatment because of the low incidence of outbreaks. Since the complexity of the social networking analysis is sensitive to the number of nodes and links that make up the network, this study was conducted in a particular category of miscellaneous goods. Future research should consider that this condition may limit the opportunity to detect unexpected associations between products belonging to different categories of classification.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.11 no.2
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• pp.35-48
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• 2016

Individual characteristics and entrepreneurship are important factors to determine entrepreneurial intentions. Despite this, little attention has been given to external factors, which effects to venture start-up decision. This study examines the relationship between individual characteristics and entrepreneurship by moderating effect of Hofstede's cultures dimensions theory. For this, 244 copies of the questionnaire were empirically analyzed. According to the results of analysis, internal locus of control, self-efficacy were found to have positive effects on autonomy, innovativeness, pro-activeness. In addition, uncertainty avoidance of Hofstede's cultures dimensions theory were found the moderating effects on entrepreneurship and entrepreneurial intentions. Therefore, this study suggests theoretical and practical implications, as below, according to the results. Firstly, pro-activeness take a important part on venture start-up. Thus, venture start-up institution and venture managers need to develop "venture education curriculum" that fostering the pro-activeness mind of entrepreneur. Secondly, In order to anticipate entrepreneurial intentions more precisely, analyzing the interaction between environmental variables and individual variables is desirable. Lastly, in the future study of entrepreneurship, the comprehensive analysis of correlation between the factors that including three factors of entrepreneurship is need to be conducted and more effective way of readdressing the entrepreneurship is necessary.

• The Journal of the Korea Contents Association
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• v.20 no.10
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• pp.654-678
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• 2020

Job crafting has gained prominence in organizational practice as an important factor to cultivate positive performance, the purpose of this study is to present theoretical and practical implications of job crafting by examination of the effective variables that induce job crafting. We verify the correlation between shared leadership and job crafting and the mediating effect of learning goal orientation and knowledge sharing in the relationship between these two variables. Hypotheses were established on the basis of precedent research and various theories including social cognitive theory and affective events theory. The data were collected by conducting online surveys of 318 office workers who have served in various domestic organizations. The reliability and validity of the collected data were verified by SPSS 25.0 and AMOS 25.0, and the hypotheses were analyzed by SPSS process macro 3.0. The study found that shared leadership yields positive effects on the learning goal orientation, knowledge sharing and job crafting of participants respectively and that learning goal orientation and knowledge sharing have a mediating effect in the relationship between shared leadership and job crafting. The results of this study present the effectiveness of shared leadership to facilitate the job crafting and implications and future research measures for the organization to develop a system for activating shared leadership, and for strengthening learning goals orientation and knowledge sharing.

• Proceedings of the Korea Database Society Conference
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• 2001.11a
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• pp.473-505
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• 2001

예측 기관에 따라서 B2B의 시장 규모 및 성장률에 대한 차이는 있지만 B2B 시장이 빠른 속도로 성장하고 있으며, 이 같은 추세는 계속될 것이라는 점에 대한 이견은 없는 편이다. B2B는 기업에게 비용 절감과 시간 절약, 업무 효율성 증대 등의 다양한 효과를 제공해 줄 수 있기 때문에 앞으로도 그 중요성은 더 커질 것으로 예상된다. 그러나 B2B의 중요성 및 성장세와는 별도로 아직까지 B2B에 참여하는 기업들이 큰 효과를 거두지 못하고 있는 것이 사실이다. 이에 따라 많은 학자들과 컨설팅 회사들이 B2B의 모형, 추진 전략, 성공 요인들을 다양한 각도에서 제시하고 있다. 하지만 B2B에 대한 실증적 연구가 부족하여, 기업의 실무자들이 실질적인 도움을 얻기에는 부족한 점이 있기 때문에 B2B의 성공 요인과 추진 전략에 대한 실증적 연구가 절실히 필요하다. 본 연구의 목적은 B2B 유형 중 가장 널리 활용되고 있는 MRO e-marketplace의 성공에 영향을 주는 요인들을 실증적으로 분석하는 것이다. MRO e-marketplace의 성공 요인을 환경적 특성, 제품 특성, B2B 사이트 특성 등 3 그룹으로 분류한 후, 38개 기업에서 수집된 설문지를 분석하여 MRO e-marketplace의 성공 요인을 실증적으로 분석하였다. MRO e-marketplace의 성공 요인들을 요인 분석한 결과, 기업 내부 환경 요인, 기업 외부 환경 요인, 제품 정보 요인, 제품 공급 능력 요인, 사이트 기본 기능 요인, 사이트 편의성 요인, 사이트 보안성 요인 등 총 8개 요인으로 분류되었다. 한편 MRO e-marketplace의 도입 효과를 측정한 비용 절감, 시간 절약, 업무 효율성 증대, 거래 투명성 증대 등의 4개의 문항은 하나의 요인으로 묶여, 이를 MRO e-marketplace 성공으로 정의하였다. MRO e-marketplace의 성공에 영향을 미치는 요인을 찾기 위해, 추출된 8개 요인과 MRO e-marketplace 성공 간의 상관 관계를 분석하였다. 8개 요인 중에서 기업 내부 환경 요인, 제품 공급 능력 요인, 사이트 기본 기능 요인이 MRO e-marketplace의 성공에 영향을 미치는 것으로 나타났다. 마지막으로 MRO e-marketplace 성공 요인들의 상대적 중요도를 파악하기 위해 회귀 분석을 실시하였는데, 참여 기업의 내부 환경 요인이 가장 큰 중요한 것으로 나타났고, 그 다음은 제품 공급 능력 요인과 사이트 기본 기능 요인으로 나타났다. 이 같은 실증적 결과는 MRO e-marketplace나 B2B의 성공을 위해서는 참여 기업의 내부 환경 조성이 매우 중요함을 시사해 준다. 또한 참여 기업의 제품 공급 능력 요인 역시 MRO e-marketplace의 성공에 직접적인 영향을 주기 때문에 공급기업들의 제품 공급 능력을 높이는데 노력해야 한다. 또한 MRO e-marketplace를 운영하는 기업들은 사이트의 기능을 높이는데 많은 노력을 기울여야 한다는 것을 시사하고 있다. MRO e-marketplace의 성공 요인을 실증적으로 분석한 본 연구의 결과는 MRO e-marketplace와 B2B의 추진 전략의 이론적 모형 개발에 유용하게 활용될 수 있을 것이다. 또한 본 연구의 결과는 MRO e-marketplace와 B2B의 성공을 높이기 위한 추진 전략을 수립하는데 유용하게 활용될 수 있을 것으로 기대된다.

• Journal of the Korean Data and Information Science Society
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• v.26 no.2
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• pp.355-365
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• 2015

As the global climate has dramatically changed over the past decades, there has been active research on evaluating its effects on food security, which has been recognized as one of the most important issues in the field. In this study, we analyzed the impact of the climate change on the Korean agriculture using meta-analysis methods. Especially, our research focus is on estimating the effect of CO2 concentration and two adaptations (planting-date and cultivar adjustments)on rice that accounts for a larger proportion of the Korean domestic agriculture. Unlike traditional general meta-analysis methods that use summary statistics of effects of interest, meta analysis specific to the agriculture literature was conducted by integrating the data on rice yield that were generated under various CO2 emission scenarios and general circulating models of the 6 collected individual studies. As a modeling approach, the rice yield change ratio was set as the dependent variable and the main and interaction effects of CO2 concentration and adaptation were considered as independent variables in a regression model, As a result, CO2 is estimated to have opposite effects on rice yield depending on whether any of the two adaptations is applied or not; decreasing effect without adaptation and increasing effect with adaptation. In addition, it turns out that the cultivar adjustment has a higher increasing effect on rice yield than the planting-date adjustment. The results of the study are expected to be used as basic quantitative data for establishing responsive polices to the future climate changes.