• Asia pacific journal of information systems
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• v.24 no.2
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• pp.233-253
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• 2014

Can the stock market really be predicted? Stock market prediction has attracted much attention from many fields including business, economics, statistics, and mathematics. Early research on stock market prediction was based on random walk theory (RWT) and the efficient market hypothesis (EMH). According to the EMH, stock market are largely driven by new information rather than present and past prices. Since it is unpredictable, stock market will follow a random walk. Even though these theories, Schumaker [2010] asserted that people keep trying to predict the stock market by using artificial intelligence, statistical estimates, and mathematical models. Mathematical approaches include Percolation Methods, Log-Periodic Oscillations and Wavelet Transforms to model future prices. Examples of artificial intelligence approaches that deals with optimization and machine learning are Genetic Algorithms, Support Vector Machines (SVM) and Neural Networks. Statistical approaches typically predicts the future by using past stock market data. Recently, financial engineers have started to predict the stock prices movement pattern by using the SNS data. SNS is the place where peoples opinions and ideas are freely flow and affect others' beliefs on certain things. Through word-of-mouth in SNS, people share product usage experiences, subjective feelings, and commonly accompanying sentiment or mood with others. An increasing number of empirical analyses of sentiment and mood are based on textual collections of public user generated data on the web. The Opinion mining is one domain of the data mining fields extracting public opinions exposed in SNS by utilizing data mining. There have been many studies on the issues of opinion mining from Web sources such as product reviews, forum posts and blogs. In relation to this literatures, we are trying to understand the effects of SNS exposures of firms on stock prices in Korea. Similarly to Bollen et al. [2011], we empirically analyze the impact of SNS exposures on stock return rates. We use Social Metrics by Daum Soft, an SNS big data analysis company in Korea. Social Metrics provides trends and public opinions in Twitter and blogs by using natural language process and analysis tools. It collects the sentences circulated in the Twitter in real time, and breaks down these sentences into the word units and then extracts keywords. In this study, we classify firms' exposures in SNS into two groups: positive and negative. To test the correlation and causation relationship between SNS exposures and stock price returns, we first collect 252 firms' stock prices and KRX100 index in the Korea Stock Exchange (KRX) from May 25, 2012 to September 1, 2012. We also gather the public attitudes (positive, negative) about these firms from Social Metrics over the same period of time. We conduct regression analysis between stock prices and the number of SNS exposures. Having checked the correlation between the two variables, we perform Granger causality test to see the causation direction between the two variables. The research result is that the number of total SNS exposures is positively related with stock market returns. The number of positive mentions of has also positive relationship with stock market returns. Contrarily, the number of negative mentions has negative relationship with stock market returns, but this relationship is statistically not significant. This means that the impact of positive mentions is statistically bigger than the impact of negative mentions. We also investigate whether the impacts are moderated by industry type and firm's size. We find that the SNS exposures impacts are bigger for IT firms than for non-IT firms, and bigger for small sized firms than for large sized firms. The results of Granger causality test shows change of stock price return is caused by SNS exposures, while the causation of the other way round is not significant. Therefore the correlation relationship between SNS exposures and stock prices has uni-direction causality. The more a firm is exposed in SNS, the more is the stock price likely to increase, while stock price changes may not cause more SNS mentions.

• Journal of Environmental Policy
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• v.6 no.1
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• pp.1-40
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• 2007

The research in this paper, for the effective implementation of CBD PoW PA(Program of Work on Protected Areas of Convention on Biological Diversity) that was adopted by CBD COP7(Conference of the Parties) in 2004, shows the objectives and activities of 9 each subject in PoW PA regarding domestic status and cases of national park management. Before anything else, according to the result of the review on the status of protected areas in Korea, there are 1,119 protected areas which are classified into 14 types and the total area is about $15,621km^2$. After a thorough review on 9 each subject about the implementation of CBD PoW PA, we found out that some parts such as management planning, prevention and alleviation of threats, and establishment of PAs system, are improved while financial support, improved social benefit, and MEE(Management Effectiveness Evaluation} fields are need to be improved. Especially regarding time-bound, ecological gap analysis on national level and MEE are need to be improved immediately. This paper could help us to understand the current status of PAs management system in Korea and to prepare national reports of CBD and implementation report of PoW PA. Based on research and results of this paper, we need to find the fields that have gaps in order to meet the requirements of the CBD PoW PA and the implementation tools that are suitable for managing Korea's protected areas. To effectively implement the various activities which require a systematic approach on the national level, the establishment of the networks among relevant organizations for protected areas are vital. To effectively reach the ultimate goal of CBD PoW PA, reducing the rate of biodiversity loss, it is essential that lots of plans established by authorities must be carried out in a constant manner to achieve goals of CBD PoW PA.

• The Korean Society of Law and Medicine
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• v.24 no.2
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• pp.35-77
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• 2023

As the amendment to the Personal Information Protection Act, which newly established the basis for the right to request transmission of personal information, was promulgated through the plenary session of the National Assembly, MyData, which was previously applied only to the financial sector, could spread to all fields. The right to request transmission of personal information is the right of the information subject to be guaranteed for the realization of MyData. However, since the right to request transmission of personal information stipulated in the Personal Information Protection Act is designed to be applied to all fields, not a special field such as the medical field, it has many shortcomings to act as a core basis for implementing MyData in Medicine. Based on this awareness of the problem, this paper compares and analyzes major legal trends related to the right to portability of personal health information at home and abroad, and examines the limitations of Korea's Personal Information Protection Act and Medical Act in realizing Medical MyData. Under the Personal Information Protection Act, the right to request transmission of personal information is insufficient to apply to the medical field, such as the scope of information to be transmitted, the transmission method, and the scope of the person obligated to perform the transmission, etc.. Regulations on the right to access medical information and transmission of medical records under the Medical Act also have limitations in implementing the full function of Medical My Data in that the target information and the leading institution are very limited. In order to overcome these limitations, this paper prepared a separate and independent special law to regulate matters related to the use and protection of personal health information as a measure to improve the legal system that can effectively guarantee the right to portability of personal health information, taking into account the specificity of the medical field. It was proposed to specifically regulate the contents of the movement and transmission system of personal health information.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.33-56
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• 2017

As Internet usage is becoming more common worldwide and smartphone become necessity in daily life, technologies and applications related to mobile Internet are developing rapidly. The results of the Internet usage patterns of consumers around the world imply that there are many potential new business opportunities for mobile Internet technologies and applications. The location-based service (LBS) is a service based on the location information of the mobile device. LBS has recently gotten much attention among many mobile applications and various LBSs are rapidly developing in numerous categories. However, even with the development of LBS related technologies and services, there is still a lack of empirical research on the intention to use LBS. The application of previous researches is limited because they focused on the effect of one particular factor and had not shown the direct relationship on the intention to use LBS. Therefore, this study presents a research model of factors that affect the intention to use and actual use of LBS whose market is expected to grow rapidly, and tested it by conducting a questionnaire survey of 330 users. The results of data analysis showed that service customization, service quality, and personal innovativeness have a positive effect on the intention to use LBS and the intention to use LBS has a positive effect on the actual use of LBS. These results implies that LBS providers can enhance the user's intention to use LBS by offering service customization through the provision of various LBSs based on users' needs, improving information service qualities such as accuracy, timeliness, sensitivity, and reliability, and encouraging personal innovativeness. However, privacy concerns in the context of LBS are not significantly affected by service customization and personal innovativeness and privacy concerns do not significantly affect the intention to use LBS. In fact, the information related to users' location collected by LBS is less sensitive when compared with the information that is used to perform financial transactions. Therefore, such outcomes on privacy concern are revealed. In addition, the advantages of using LBS are more important than the sensitivity of privacy protection to the users who use LBS than to the users who use information systems such as electronic commerce that involves financial transactions. Therefore, LBS are recommended to be treated differently from other information systems. This study is significant in the theoretical point of contribution that it proposed factors affecting the intention to use LBS in a multi-faceted perspective, proved the proposed research model empirically, brought new insights on LBS, and broadens understanding of the intention to use and actual use of LBS. Also, the empirical results of the customization of LBS affecting the user's intention to use the LBS suggest that the provision of customized LBS services based on the usage data analysis through utilizing technologies such as artificial intelligence can enhance the user's intention to use. In a practical point of view, the results of this study are expected to help LBS providers to develop a competitive strategy for responding to LBS users effectively and lead to the LBS market grows. We expect that there will be differences in using LBSs depending on some factors such as types of LBS, whether it is free of charge or not, privacy policies related to LBS, the levels of reliability related application and technology, the frequency of use, etc. Therefore, if we can make comparative studies with those factors, it will contribute to the development of the research areas of LBS. We hope this study can inspire many researchers and initiate many great researches in LBS fields.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.39-55
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• 2019

Recently banks and large financial institutions have introduced lots of Robo-Advisor products. Robo-Advisor is a Robot to produce the optimal asset allocation portfolio for investors by using the financial engineering algorithms without any human intervention. Since the first introduction in Wall Street in 2008, the market size has grown to 60 billion dollars and is expected to expand to 2,000 billion dollars by 2020. Since Robo-Advisor algorithms suggest asset allocation output to investors, mathematical or statistical asset allocation strategies are applied. Mean variance optimization model developed by Markowitz is the typical asset allocation model. The model is a simple but quite intuitive portfolio strategy. For example, assets are allocated in order to minimize the risk on the portfolio while maximizing the expected return on the portfolio using optimization techniques. Despite its theoretical background, both academics and practitioners find that the standard mean variance optimization portfolio is very sensitive to the expected returns calculated by past price data. Corner solutions are often found to be allocated only to a few assets. The Black-Litterman Optimization model overcomes these problems by choosing a neutral Capital Asset Pricing Model equilibrium point. Implied equilibrium returns of each asset are derived from equilibrium market portfolio through reverse optimization. The Black-Litterman model uses a Bayesian approach to combine the subjective views on the price forecast of one or more assets with implied equilibrium returns, resulting a new estimates of risk and expected returns. These new estimates can produce optimal portfolio by the well-known Markowitz mean-variance optimization algorithm. If the investor does not have any views on his asset classes, the Black-Litterman optimization model produce the same portfolio as the market portfolio. What if the subjective views are incorrect? A survey on reports of stocks performance recommended by securities analysts show very poor results. Therefore the incorrect views combined with implied equilibrium returns may produce very poor portfolio output to the Black-Litterman model users. This paper suggests an objective investor views model based on Support Vector Machines(SVM), which have showed good performance results in stock price forecasting. SVM is a discriminative classifier defined by a separating hyper plane. The linear, radial basis and polynomial kernel functions are used to learn the hyper planes. Input variables for the SVM are returns, standard deviations, Stochastics %K and price parity degree for each asset class. SVM output returns expected stock price movements and their probabilities, which are used as input variables in the intelligent views model. The stock price movements are categorized by three phases; down, neutral and up. The expected stock returns make P matrix and their probability results are used in Q matrix. Implied equilibrium returns vector is combined with the intelligent views matrix, resulting the Black-Litterman optimal portfolio. For comparisons, Markowitz mean-variance optimization model and risk parity model are used. The value weighted market portfolio and equal weighted market portfolio are used as benchmark indexes. We collect the 8 KOSPI 200 sector indexes from January 2008 to December 2018 including 132 monthly index values. Training period is from 2008 to 2015 and testing period is from 2016 to 2018. Our suggested intelligent view model combined with implied equilibrium returns produced the optimal Black-Litterman portfolio. The out of sample period portfolio showed better performance compared with the well-known Markowitz mean-variance optimization portfolio, risk parity portfolio and market portfolio. The total return from 3 year-period Black-Litterman portfolio records 6.4%, which is the highest value. The maximum draw down is -20.8%, which is also the lowest value. Sharpe Ratio shows the highest value, 0.17. It measures the return to risk ratio. Overall, our suggested view model shows the possibility of replacing subjective analysts's views with objective view model for practitioners to apply the Robo-Advisor asset allocation algorithms in the real trading fields.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.25-38
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• 2019

Selecting high-quality information that meets the interests and needs of users among the overflowing contents is becoming more important as the generation continues. In the flood of information, efforts to reflect the intention of the user in the search result better are being tried, rather than recognizing the information request as a simple string. Also, large IT companies such as Google and Microsoft focus on developing knowledge-based technologies including search engines which provide users with satisfaction and convenience. Especially, the finance is one of the fields expected to have the usefulness and potential of text data analysis because it's constantly generating new information, and the earlier the information is, the more valuable it is. Automatic knowledge extraction can be effective in areas where information flow is vast, such as financial sector, and new information continues to emerge. However, there are several practical difficulties faced by automatic knowledge extraction. First, there are difficulties in making corpus from different fields with same algorithm, and it is difficult to extract good quality triple. Second, it becomes more difficult to produce labeled text data by people if the extent and scope of knowledge increases and patterns are constantly updated. Third, performance evaluation is difficult due to the characteristics of unsupervised learning. Finally, problem definition for automatic knowledge extraction is not easy because of ambiguous conceptual characteristics of knowledge. So, in order to overcome limits described above and improve the semantic performance of stock-related information searching, this study attempts to extract the knowledge entity by using neural tensor network and evaluate the performance of them. Different from other references, the purpose of this study is to extract knowledge entity which is related to individual stock items. Various but relatively simple data processing methods are applied in the presented model to solve the problems of previous researches and to enhance the effectiveness of the model. From these processes, this study has the following three significances. First, A practical and simple automatic knowledge extraction method that can be applied. Second, the possibility of performance evaluation is presented through simple problem definition. Finally, the expressiveness of the knowledge increased by generating input data on a sentence basis without complex morphological analysis. The results of the empirical analysis and objective performance evaluation method are also presented. The empirical study to confirm the usefulness of the presented model, experts' reports about individual 30 stocks which are top 30 items based on frequency of publication from May 30, 2017 to May 21, 2018 are used. the total number of reports are 5,600, and 3,074 reports, which accounts about 55% of the total, is designated as a training set, and other 45% of reports are designated as a testing set. Before constructing the model, all reports of a training set are classified by stocks, and their entities are extracted using named entity recognition tool which is the KKMA. for each stocks, top 100 entities based on appearance frequency are selected, and become vectorized using one-hot encoding. After that, by using neural tensor network, the same number of score functions as stocks are trained. Thus, if a new entity from a testing set appears, we can try to calculate the score by putting it into every single score function, and the stock of the function with the highest score is predicted as the related item with the entity. To evaluate presented models, we confirm prediction power and determining whether the score functions are well constructed by calculating hit ratio for all reports of testing set. As a result of the empirical study, the presented model shows 69.3% hit accuracy for testing set which consists of 2,526 reports. this hit ratio is meaningfully high despite of some constraints for conducting research. Looking at the prediction performance of the model for each stocks, only 3 stocks, which are LG ELECTRONICS, KiaMtr, and Mando, show extremely low performance than average. this result maybe due to the interference effect with other similar items and generation of new knowledge. In this paper, we propose a methodology to find out key entities or their combinations which are necessary to search related information in accordance with the user's investment intention. Graph data is generated by using only the named entity recognition tool and applied to the neural tensor network without learning corpus or word vectors for the field. From the empirical test, we confirm the effectiveness of the presented model as described above. However, there also exist some limits and things to complement. Representatively, the phenomenon that the model performance is especially bad for only some stocks shows the need for further researches. Finally, through the empirical study, we confirmed that the learning method presented in this study can be used for the purpose of matching the new text information semantically with the related stocks.

• Journal of the Korean Academic Society of Industrial Cluster
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• v.1 no.1
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• pp.67-86
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• 2007

Wonju Medical Equipment Industry, despite of its short history, poor sales and weak manpower and so on, have shown remarkable outcomes in a relatively short period. At the end of 2007, totally 79 enterprises (only 4.6% of whole enterprises in Korea) made 10% of the nationwide production and 15% of the nationwide exports with an annual average growth rate of 66.7%, contributing domestic medical equipment industry tremendously. In addition, many leading medical equipment enterprises in various fields already moved or plan to move to Wonju, accelerating Wonju Medical Equipment Cluster. Wonju Medical Equipment Industry Cluster now enters into the growth stage, getting out of the initial business setup stage. Especially, the nomination of Wonju cluster project from the government accelerates networking (e.g. the development of the universal parts, the establishment of the mutual collaboration model among enterprises, and the mutual marketing), making a rapid growth in Wonju Medical Equipment Industry. Wonju Medical Equipment Industry Cluster revealed positive outcomes despite of the weakness in investment size and infra-structure comparing with the other medical industry cluster in the advanced country, while many domestic enterprises pursued their own growth models and thus failed to promote the international competitive power. Wonju Medical Equipment Industry has been developed rapidly. However, there are many challenging problems to support enterprises: small R&D investment and thus weak technology power, difficulties in recruiting R&D engineers, and poor marketing capabilities, financial infrastructure & policies, and network architecture. In order to develop a world-competitive medical equipment industry cluster at Wonju, the complement of infrastructures, the technology innovation, the mutual marketing, and the network expansion to support enterprises are further required. Wonju' s experiences in developing medical equipment industry so far suggest that our own flexible cluster model considering the industry structure and maturity for different regions should be developed, and specific action plans from the local and central governments based on their systematic strategies for industry development should be implemented in order to build world-competitive industry clusters in Korea.

• Asian-Australasian Journal of Animal Sciences
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• v.22 no.6
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• pp.836-842
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• 2009

The objectives of this study were to evaluate potential benefits of intercropping of corn with runner bean for a smallsized farming system, based on land equivalent ratio (LER) and silage yield and quality of corn intercropped with runner bean (Phaseolus vulgaris L.), in arid conditions of Turkey under an irrigation system. This experiment was established as a split-plot design in a randomized complete block, with three replications and carried out over two (consecutive) years in 2006 and 2007. Seven different mixtures (runner bean, B and silage corn sole crop, C, 10% B+90% C, 20% B+80% C, 30% B+70% C, 40% B+60%C, and 50% B+50%C) of silage corn-runner bean were intercropped. All of the mixtures were grown under irrigation. The corn-runner bean fields were planted in the second week of May and harvested in the first week of September in both years. Green beans were harvested three times each year and green bean yields were recorded each time. After the 3rd harvest of green bean, residues of bean and corn together were randomly harvested from a 1 $m^{2}$ area by hand using a clipper when the bean started to dry and corn was at the dough stage. Green mass yields of each plot were recorded. Silages were prepared from each plot (triplicate) in 1 L mini-silos. After 60 d ensiling, subsamples were taken from this material for determination of dry matter (DM), pH, organic acids, chemical composition, and in vitro DM digestibility of silages. The LER index was also calculated to evaluate intercrop efficiencies with respect to sole crops. Average pH, acetic, propionic and butyric acid concentrations were similar but lactic acid and ammonia-N levels were significantly different (p<0.05) among different mixtures of bean intercropped with corn. Ammonia-N levels linearly increased from 0.90% to 2.218 as the percentage of bean increased in the mixtures up to a 50:50 seeding ratio. While average CP content increased linearly from 6.47 to 12.45%, and average NDF and ADF contents decreased linearly from 56.17 to 44.88 and from 34.92 to 33.51%, respectively, (p<0.05) as the percentage of bean increased in the mixtures up to a 50:50 seeding ratio, but DM and OM contents did not differ among different mixtures of bean intercropped with corn (p>0.05). In vitro OM digestibility values differed significantly among bean-corn mixture silages (p<0.05). Fresh bean, herbage DM, IVOMD, ME yields, and LER index were significantly influenced by percentage of bean in the mixtures (p<0.01). As the percentage of bean increased in the mixtures up to a 50:50 seeding ratio, yields of fresh bean (from 0 to 24,380 kg/ha) and CP (from 1,258.0 to 1,563.0 kg/ha) and LER values (from 1.0 to 1.775) linearly increased, but yields of herbage DM (from 19,670 to 12,550 kg/ha), IVOMD (from 12,790 to 8,020 kg/ha) and ME (46,230 to 29,000 Mcal/ha) yields decreased (p<0.05). In conclusion, all of the bean-corn mixtures provided a good silage and better CP concentrations. Even though forage yields decreased, the LER index linearly increased as the percentage of bean increased in the mixture up to a 50:50 seeding ratio, which indicates a greater utilization of land. Therefore, a 50:50 seeding ratio seemed to be best for optimal utilization of land in this study and to provide greater financial stability for labor-intensive, small farmers.

• 대한공업교육학회지
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• v.45 no.2
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• pp.21-45
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• 2020

The purpose of this study was to verify how the vocational education for training industrial workforce as a national human resource development (NHRD) system has undergone a transition process in relation to the national economic, industrial, and socio-cultural contexts. First, how vocational education as an industrial workforce training system has changed in accordance with Korea's economic environment, industrial development, and social changes; second, what are the main factors that influenced the role and importance of vocational education; and third, vocational education as a system for training industrial workforce and training workforce in science and engineering were analyzed differently from the perspective of the NHRD model. To this end, domestic and international academic journal papers, research reports, and thesis were investigated and classified by period, and major changes in vocational education were analyzed in relation to economic, industrial, and social issues and policies by period. As a result of the research, first, as the industry advanced, the level of vocational education increased and the scope expanded. Second, vocational education tended to shrink gradually after the manufacturing industry base, and especially secondary vocational education tended to decline after the national industry focused on light industry. Third, since the 1970s, the diversification of the NHRD and jobs has resulted in wage gaps depending on the level of education, which has increased the preference for university education and avoided secondary vocational education. In addition, a NHRD model focusing on training science and engineering workforce was proposed to compare the existing NHRD model focusing on overall vocational education, and it was revealed that the NHRD needs to be subdivided into various fields or levels to derive a model and examine changes. From the results of the study, vocational education in Korea, especially in secondary vocational education, has declined due to large impacts on socio-cultural perception due to economic growth, enthusiasm for education, and external shocks such as the financial crisis, and the long-term effort to change this perception is suggested to overcome the crisis of vocational education.

• Journal of Environmental Policy
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• v.6 no.1
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• pp.41-60
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• 2007

Attempts were made to define the elements of debates, impact of decisions of the Access to Genetic Resources and Benefit-sharing(ABS) of the Conference of the Parties(COP) to the Convention on Biological Diversity(CBD) In Korea. Providing policy suggestions to cope with ABS, a cross-cutting issue of the meetings of the COP, was also undertaken. Meetings concerning ABS deal with several key matters such as an international regime, which is a legally binding implementation tool of the Bonn Guidelines, an international certificate of genetic resources' origin/source/legal provenance, and disclosure of origin of genetic resources, compliance measures with prior informed consent of the Contracting Parties providing such resources and with mutually agreed terms on which access was granted. Developing countries, rich in biodiversity and genetic resources, use the CBD as a major tool to maximize their national profits. They demand for national sovereign rights for the genetic resources and indigenous communities providing associated traditional knowledge. At the meetings of the COP, in addition, they requested that developed countries should transfer technologies and provide a financial mechanism for resource conservation to them. On the contrary, the developed countries argue that facilitating access to genetic resources is essential for scientific research and development, and that both Intellectual Property Rights and biotechnology using genetic resources should be protected to maximize their national benefits. Decisions of the COP concerning the Bonn Guidelines and compliance measures with ABS will affect on various socioeconomic fields of Korea, a country which is short of genetic resources. Especially, the importation of genetic resources and land development which might damage genetic resources will be limited seriously. Consequently, overall expenses will increase for the securing genetic resources from the foreign countries and developing biotechnology for conservation and sustainable uses of genetic resources. To minimize the adverse impacts, we endeavor to establish our clear standpoint and to lead the international trends, which are favorable for us. In order to achieve these objectives, government needs i) to proceed researches to lead the international ABS debates actively and to prepare the expected decisions of the future meetings of the COP, ii) to establish a national implementation plan to cope with the ABS and its related decisions, iii) to examine and improve the efficiencies of the national implementation plan with a proper monitoring system, and iv) cope with the other international meetings including the meetings of Trade Related Intellectual Properly Rights and International Treaty on Plant Genetic Resources for Food and Agriculture actively.