• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.149-169
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• 2018

Korea is currently accumulating a large amount of data in public institutions based on the public data open policy and the "Government 3.0". Especially, a lot of data is accumulated in the tourism field. However, the academic discussions utilizing the tourism data are still limited. Moreover, the openness of the data of restaurants, hotels, and online tourism information, and how to use SNS Big Data in tourism are still limited. Therefore, utilization through tourism big data analysis is still low. In this paper, we tried to analyze influencing factors on foreign tourists' satisfaction in Korea through numerical data using data mining technique and R programming technique. In this study, we tried to find ways to revitalize the tourism industry by analyzing about 36,000 big data of the "Survey on the actual situation of foreign tourists from 2013 to 2015" surveyed by the Korea Culture & Tourism Research Institute. To do this, we analyzed the factors that have high influence on the 'Satisfaction', 'Revisit intention', and 'Recommendation' variables of foreign tourists. Furthermore, we analyzed the practical influences of the variables that are mentioned above. As a procedure of this study, we first integrated survey data of foreign tourists conducted by Korea Culture & Tourism Research Institute, which is stored in the tourist information system from 2013 to 2015, and eliminate unnecessary variables that are inconsistent with the research purpose among the integrated data. Some variables were modified to improve the accuracy of the analysis. And we analyzed the factors affecting the dependent variables by using data-mining methods: decision tree(C5.0, CART, CHAID, QUEST), artificial neural network, and logistic regression analysis of SPSS IBM Modeler 16.0. The seven variables that have the greatest effect on each dependent variable were derived. As a result of data analysis, it was found that seven major variables influencing 'overall satisfaction' were sightseeing spot attraction, food satisfaction, accommodation satisfaction, traffic satisfaction, guide service satisfaction, number of visiting places, and country. Variables that had a great influence appeared food satisfaction and sightseeing spot attraction. The seven variables that had the greatest influence on 'revisit intention' were the country, travel motivation, activity, food satisfaction, best activity, guide service satisfaction and sightseeing spot attraction. The most influential variables were food satisfaction and travel motivation for Korean style. Lastly, the seven variables that have the greatest influence on the 'recommendation intention' were the country, sightseeing spot attraction, number of visiting places, food satisfaction, activity, tour guide service satisfaction and cost. And then the variables that had the greatest influence were the country, sightseeing spot attraction, and food satisfaction. In addition, in order to grasp the influence of each independent variables more deeply, we used R programming to identify the influence of independent variables. As a result, it was found that the food satisfaction and sightseeing spot attraction were higher than other variables in overall satisfaction and had a greater effect than other influential variables. Revisit intention had a higher ${\beta}$ value in the travel motive as the purpose of Korean Wave than other variables. It will be necessary to have a policy that will lead to a substantial revisit of tourists by enhancing tourist attractions for the purpose of Korean Wave. Lastly, the recommendation had the same result of satisfaction as the sightseeing spot attraction and food satisfaction have higher ${\beta}$ value than other variables. From this analysis, we found that 'food satisfaction' and 'sightseeing spot attraction' variables were the common factors to influence three dependent variables that are mentioned above('Overall satisfaction', 'Revisit intention' and 'Recommendation'), and that those factors affected the satisfaction of travel in Korea significantly. The purpose of this study is to examine how to activate foreign tourists in Korea through big data analysis. It is expected to be used as basic data for analyzing tourism data and establishing effective tourism policy. It is expected to be used as a material to establish an activation plan that can contribute to tourism development in Korea in the future.

• Journal of Intelligence and Information Systems
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• v.21 no.4
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• pp.37-51
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• 2015

Due to the development of internet technology and the rapid increase of internet data, various studies are actively conducted on how to use and analyze internet data for various purposes. In particular, in recent years, a number of studies have been performed on the applications of text mining techniques in order to overcome the limitations of the current application of structured data. Especially, there are various studies on sentimental analysis to score opinions based on the distribution of polarity such as positivity or negativity of vocabularies or sentences of the texts in documents. As a part of such studies, this study tries to predict ups and downs of stock prices of companies by performing sentimental analysis on news contexts of the particular companies in the Internet. A variety of news on companies is produced online by different economic agents, and it is diffused quickly and accessed easily in the Internet. So, based on inefficient market hypothesis, we can expect that news information of an individual company can be used to predict the fluctuations of stock prices of the company if we apply proper data analysis techniques. However, as the areas of corporate management activity are different, an analysis considering characteristics of each company is required in the analysis of text data based on machine-learning. In addition, since the news including positive or negative information on certain companies have various impacts on other companies or industry fields, an analysis for the prediction of the stock price of each company is necessary. Therefore, this study attempted to predict changes in the stock prices of the individual companies that applied a sentimental analysis of the online news data. Accordingly, this study chose top company in KOSPI 200 as the subjects of the analysis, and collected and analyzed online news data by each company produced for two years on a representative domestic search portal service, Naver. In addition, considering the differences in the meanings of vocabularies for each of the certain economic subjects, it aims to improve performance by building up a lexicon for each individual company and applying that to an analysis. As a result of the analysis, the accuracy of the prediction by each company are different, and the prediction accurate rate turned out to be 56% on average. Comparing the accuracy of the prediction of stock prices on industry sectors, 'energy/chemical', 'consumer goods for living' and 'consumer discretionary' showed a relatively higher accuracy of the prediction of stock prices than other industries, while it was found that the sectors such as 'information technology' and 'shipbuilding/transportation' industry had lower accuracy of prediction. The number of the representative companies in each industry collected was five each, so it is somewhat difficult to generalize, but it could be confirmed that there was a difference in the accuracy of the prediction of stock prices depending on industry sectors. In addition, at the individual company level, the companies such as 'Kangwon Land', 'KT & G' and 'SK Innovation' showed a relatively higher prediction accuracy as compared to other companies, while it showed that the companies such as 'Young Poong', 'LG', 'Samsung Life Insurance', and 'Doosan' had a low prediction accuracy of less than 50%. In this paper, we performed an analysis of the share price performance relative to the prediction of individual companies through the vocabulary of pre-built company to take advantage of the online news information. In this paper, we aim to improve performance of the stock prices prediction, applying online news information, through the stock price prediction of individual companies. Based on this, in the future, it will be possible to find ways to increase the stock price prediction accuracy by complementing the problem of unnecessary words that are added to the sentiment dictionary.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.155-175
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• 2017

As social data become into the spotlight, mainstream web search engines provide data indicate how many people searched specific keyword: Web Search Traffic data. Web search traffic information is collection of each crowd that search for specific keyword. In a various area, web search traffic can be used as one of useful variables that represent the attention of common users on specific interests. A lot of studies uses web search traffic data to nowcast or forecast social phenomenon such as epidemic prediction, consumer pattern analysis, product life cycle, financial invest modeling and so on. Also web search traffic data have begun to be applied to predict tourist inbound. Proper demand prediction is needed because tourism is high value-added industry as increasing employment and foreign exchange. Among those tourists, especially Chinese tourists: Youke is continuously growing nowadays, Youke has been largest tourist inbound of Korea tourism for many years and tourism profits per one Youke as well. It is important that research into proper demand prediction approaches of Youke in both public and private sector. Accurate tourism demands prediction is important to efficient decision making in a limited resource. This study suggests improved model that reflects latest issue of society by presented the attention from group of individual. Trip abroad is generally high-involvement activity so that potential tourists likely deep into searching for information about their own trip. Web search traffic data presents tourists' attention in the process of preparation their journey instantaneous and dynamic way. So that this study attempted select key words that potential Chinese tourists likely searched out internet. Baidu-Chinese biggest web search engine that share over 80%- provides users with accessing to web search traffic data. Qualitative interview with potential tourists helps us to understand the information search behavior before a trip and identify the keywords for this study. Selected key words of web search traffic are categorized by how much directly related to "Korean Tourism" in a three levels. Classifying categories helps to find out which keyword can explain Youke inbound demands from close one to far one as distance of category. Web search traffic data of each key words gathered by web crawler developed to crawling web search data onto Baidu Index. Using automatically gathered variable data, linear model is designed by multiple regression analysis for suitable for operational application of decision and policy making because of easiness to explanation about variables' effective relationship. After regression linear models have composed, comparing with model composed traditional variables and model additional input web search traffic data variables to traditional model has conducted by significance and R squared. after comparing performance of models, final model is composed. Final regression model has improved explanation and advantage of real-time immediacy and convenience than traditional model. Furthermore, this study demonstrates system intuitively visualized to general use -Youke Mining solution has several functions of tourist decision making including embed final regression model. Youke Mining solution has algorithm based on data science and well-designed simple interface. In the end this research suggests three significant meanings on theoretical, practical and political aspects. Theoretically, Youke Mining system and the model in this research are the first step on the Youke inbound prediction using interactive and instant variable: web search traffic information represents tourists' attention while prepare their trip. Baidu web search traffic data has more than 80% of web search engine market. Practically, Baidu data could represent attention of the potential tourists who prepare their own tour as real-time. Finally, in political way, designed Chinese tourist demands prediction model based on web search traffic can be used to tourism decision making for efficient managing of resource and optimizing opportunity for successful policy.

• Economic and Environmental Geology
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• v.52 no.6
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• pp.637-645
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• 2019

Due to the transformation to the intelligent information society, the rapid change of our life and environment is expected. The Ministry of Science and ICT (MSIT) and the National Research Council of Science and Technology (NST) introduced a five-year government supported research institution's planning and evaluation based on the mid-to long-term perspective. This study collects international benchmarking information including industry, academia, and research fields by collecting mid- and long-term strategy reports from public research institutes, surveys by experts from abroad universities and research institutes, and analyzing overseas market information reports. The British Geological Survey (BGS), the U.S. Geological Survey (USGS) and the japanese geological survey related institutes (AIST-GSJ) plans for three-dimensional national geological information, predictions of geological environmental disasters, and development of important metals and material in the low carbon economic transformation and in the era of the Fourth Industrial Revolution. The mid- and long-term program emphasizes basic and public research on geological information through abroad experts survey such as the IPGP-CNRS etc. The market analysis of the mining automation and digital map sectors has been able to derive the fields in which the role of public research institutes by the market is expected such as data collection on land and in the air, mobile or three-dimensional information production, smooth/fast/real-time maps, custom map design, mapping support to various platforms, geological environmental risk assessment and disaster management information and maps.

• Journal of Korean Society of Transportation
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• v.19 no.4
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• pp.7-18
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• 2001

This study represents a first attempt in Korea to develop the simultaneous freight supply-demand model which considers the relationship between freight supply and demand. As the existing study was limited in one area, or the supply and the demand was separated and assumed not to affect each other, this study take it into consideration the fact that the demand affects supply and simultaneously vice versa. This approach allows us to diagnose a policy carried on and helps us to make a resonable alternative for the effectiveness of freight transportation system. To find a relationship between them, we use a method of econometrics. a structural equation theory and two stage least-squares(2SLS) estimation technique, to get rid of bias which involves two successive applications of OLS. Based on the domestic freight data, this study consider as explanatory variables a number of population(P), industry(IN), the amount of production of the mining and manufacturing industries(MMI), the rate of the effectiveness of freight capacity(LE) and the distance of an empty carriage operation(VC). This study describes well the simultaneous process of freight supply-demand system in that the increase of VC from the decrease of VC raises the cargo capacity and cargo capacity also augments VC. By the way. it is analyzed that the increment of VC due to the increase of the cargo capacity is larger than the reduction of VC owing to the increase of the quantify of goods. Therefore an alternative policy is needed in a short and long run point of view. That is to say, to promote the effectiveness of the freight transportation system, a short term supply control and a long run logistic infrastructure are urgent based on the restoration of market economy by successive deregulation. So we are able to conclude that gradual deregulation is more desirable to build effective freight market.

• Journal of Soil and Groundwater Environment
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• v.10 no.5
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• pp.1-10
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• 2005

Policies of the United States, the United Kingdom, the Netherlands, Germany and Denmark were compared and analyzed on risk assessment of contaminated sites. These countries were chosen from a feasible preliminary analysis of 18 countries of the European Union and the U. S. All the countries selected met two major criteria : I) implementation of risk assessment to determine the soil contamination and remediation targets of contaminated sites, ii) use of soil guidance values and risk assessment as complementary measures to determine soil contamination. Suggested policy improvements to Korea regarding these issues include i) legislation of a rational risk assessment methodology of contaminated sites, and ii) enactment of collaboration of risk assessment with the soil guidance values. To establish effective risk assessment legislation, additional in-depth research on social, economic and long-term effects of the proposed risk assessment methodologies, as well as the mutual consent of all parties including academia, industry, and administration will be necessary. Linking risk assessment with soil guidance values would be applicable to a site contaminated where the contaminant concentration exceeds a certain soil guidance value. In parallel, application of risk assessment to a site where a contaminant concentration is naturally different such as mining sites would be plausible. The policy suggestions above are not yet conclusive due to a lack of policy implementation, and simulation. Thus, additional research on developing risk assessment methodology is needed. Nevertheless, initiation of the suggested policy would increase the efficacy of Korean policy regarding the survey and remediation of contaminated sites.

• Journal of the HCI Society of Korea
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• v.10 no.1
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• pp.5-17
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• 2015

Nowadays various public data have been serviced to the public. Through the opening of public data, the transparency and effectiveness of public policy developed by governments are increased and users can lead to the growth of industry related to public data. Since end-users of using public data are citizens, it is very important for everyone to figure out the meaning of public data using proper visualization techniques. In this work, to indicate the significance of widespread public data, we consider UN voting record as public data in which many people may be interested. In general, it has high utilization value by diplomatic and educational purposes, and is available in public. If we use proper data mining and visualization algorithms, we can get an insight regarding the voting patterns of UN members. To visualize, it is necessary to measure the voting similarity values among UN members and then a social graph is created by the similarity values. Next, using a graph layout algorithm, the social graph is rendered on the screen. If we use the existing method for visualizing the social graph, it is hard to understand the meaning of the social graph because the graph is usually dense. To improve the weak point of the existing social graph visualization, we propose Friend-Matching, Friend-Rival Matching, and Bubble Heap algorithms in this paper. We also validate that our proposed algorithms can improve the quality of visualizing social graphs displayed by the existing method. Finally, our prototype system has been released in http://datalab.kunsan.ac.kr/politiz/un/. Please, see if it is useful in the aspect of public data utilization.

• Resources Recycling
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• v.20 no.3
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• pp.12-27
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• 2011

DOWA group has been working on metal recycling applying the smelting and refining process of KOSAKA Smelter. DOWA has developed it's metal recycling technologies through the treatment of black ore(complex sulfide ores) that contain many kinds of non-ferrous metals. In addition to these special technologies, DOWA has strengthened its hydrometallurgical process of precious metals and ability to deal with low-grade materials such as used electrical appliances or vehicles. On the other hand, JX Nippon Mining & Metals Corporation(JX-NMMC) carries out its metal recycling and industrial waste treatment businesses employing advanced separation, extraction and refining technologies developed through its extensive experience in the smelting of non-ferrous metals. JX-NMMC collects approximately 100,000t/y of copper and precious metal scraps from waste sources such as electronic parts, mobile phones, catalytic converters, print circuit boards and gold plated parts. These items are recycled through the smelting and refining operations of Saganoseki smelter and Hitachi Metal-recycling complex(HMC). In this like, metal recycling industries combined with environmental business service in Japan have been developed through excellent technologies for mineral processing and non-ferrous smelting. Also, both group, Dowa and JX-NMMC, were contributed to establish Japan's recycling-oriented society as the typical leading company of non-ferrous smelting. Now. it is an important issue to set up the collection system for e-waste.

• The Korean Journal of Air & Space Law and Policy
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• v.25 no.2
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• pp.201-230
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• 2010

With starting the industry of automobiles, railroads and mining, the legal principle of "erlaubtes Risiko" that began as a means of maintaining the revitalized world for the cause of social utility has interpreted as a system of negligence theory in the precedent while it has gained academic recognition. Yet in aircraft operation, which is one area of high technology, CAT which can be the cause of some accidents or events or thunderstorm with turbulence is an abnormal meteorological phenomenon with frequent change that cannot be monitored perfectly just as some patient with unstable condition and that cannot be ascertained about not only the possibility of its happening but also the degree of how big the accident is. Yet the use of jet current which has the possibility of CAT can be an act of high social utility where we not only drastically cut down on time fuel also guarantee the arrival and departure on schedule when landing in airports that have thunderstorm which does not appear as fatal risk. Although we could take some measures where we can predict and avoid the potential risk, easing the regular duty of care is necessary by applying the legal principles of permitted risk concerning the incidents and accidents caused by operating in areas with the risk of turbulence or CAT with the low probability by the reason of social utility.

• Journal of Navigation and Port Research
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• v.40 no.6
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• pp.401-412
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• 2016

The sustainable operation and development of ports is a key industry for Korea's national economy. It is increasingly more important to resolve conflicts with local communities due to port environmental problems such as air pollution, water pollution, noise and ecosystem destruction while securing port competitiveness through infrastructure expansion. In case of the Busan New Port development project in Korea, construction has been temporally suspended due to conflict with local fishermen over marine sand mining for construction. A primary reason for this is the absence and limitation of qualitative port environmental impact assessment methodologies in Korea. This includes the current investigation of fisheries damaged by ports. Therefore, the main purpose of this study is to propose economic valuation methods for assessing environmental impacts that are essential for efficient port environmental management and for sustainable port operation and development in Korea. To do this, this study examines the overall port environmental problems and their effects (damages) through the analysis of environmental policies and case studies of domestic and overseas ports. Then economic valuation methods are suggested for total economic values (TEV) of damaged environmental goods and services. Among the proposed methods, Habitat Equivalency Analysis (HEA), as a more scientific data based method, was applied to estimate marine ecosystem service damages from the designation of Busan New Port Anchorages. Finally, based on the study results, more efficient port environmental management will be achieved through the institutional adoption of the proposed economic impact assessment methods for port environmental damages.