• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.241-254
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• 2011

Financial time-series forecasting is one of the most important issues because it is essential for the risk management of financial institutions. Therefore, researchers have tried to forecast financial time-series using various data mining techniques such as regression, artificial neural networks, decision trees, k-nearest neighbor etc. Recently, support vector machines (SVMs) are popularly applied to this research area because they have advantages that they don't require huge training data and have low possibility of overfitting. However, a user must determine several design factors by heuristics in order to use SVM. For example, the selection of appropriate kernel function and its parameters and proper feature subset selection are major design factors of SVM. Other than these factors, the proper selection of instance subset may also improve the forecasting performance of SVM by eliminating irrelevant and distorting training instances. Nonetheless, there have been few studies that have applied instance selection to SVM, especially in the domain of stock market prediction. Instance selection tries to choose proper instance subsets from original training data. It may be considered as a method of knowledge refinement and it maintains the instance-base. This study proposes the novel instance selection algorithm for SVMs. The proposed technique in this study uses genetic algorithm (GA) to optimize instance selection process with parameter optimization simultaneously. We call the model as ISVM (SVM with Instance selection) in this study. Experiments on stock market data are implemented using ISVM. In this study, the GA searches for optimal or near-optimal values of kernel parameters and relevant instances for SVMs. This study needs two sets of parameters in chromosomes in GA setting : The codes for kernel parameters and for instance selection. For the controlling parameters of the GA search, the population size is set at 50 organisms and the value of the crossover rate is set at 0.7 while the mutation rate is 0.1. As the stopping condition, 50 generations are permitted. The application data used in this study consists of technical indicators and the direction of change in the daily Korea stock price index (KOSPI). The total number of samples is 2218 trading days. We separate the whole data into three subsets as training, test, hold-out data set. The number of data in each subset is 1056, 581, 581 respectively. This study compares ISVM to several comparative models including logistic regression (logit), backpropagation neural networks (ANN), nearest neighbor (1-NN), conventional SVM (SVM) and SVM with the optimized parameters (PSVM). In especial, PSVM uses optimized kernel parameters by the genetic algorithm. The experimental results show that ISVM outperforms 1-NN by 15.32%, ANN by 6.89%, Logit and SVM by 5.34%, and PSVM by 4.82% for the holdout data. For ISVM, only 556 data from 1056 original training data are used to produce the result. In addition, the two-sample test for proportions is used to examine whether ISVM significantly outperforms other comparative models. The results indicate that ISVM outperforms ANN and 1-NN at the 1% statistical significance level. In addition, ISVM performs better than Logit, SVM and PSVM at the 5% statistical significance level.

• Proceedings of the KSPS conference
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• 2000.07a
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• pp.235-240
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• 2000

In the age of global communication, more human exchange is extended at the grass-roots level. In the old days, language policy and language planning was based on one nation-state with one language. But high waves of globalizaiton have allowed extended human flow of exchange beyond one's national border on a daily basis. Under such circumstances, homogeneity in Japan may not allow Japanese to speak and communicate only in Japanese and only with Japanese people. In Japan, an advisory report was made to the Ministry of Education in June 1996 about what education should be like in the 21st century. In this report, an introduction of English at public elementary schools was for the first time made. A basic policy of English instruction at the elementary school level was revealed. With this concept, English instruction is not required at the elementary school level but each school has their own choice of introducing English as their curriculum starting April 2002. As Baker, Colin (1996) indicates the age of three as being the threshold diving a child becoming bilingual naturally or by formal instruction. Threre is a movement towards making second language acquisition more naturalistic in an educational setting, developing communicative competence in a more or less formal way. From the lesson of the Canadian immersion success, Genesee (1987) stresses the importance of early language instruction. It is clear that from a psycho-linguistic perspective, most children acquire basic communication skills in their first language apparently effortlessly and without systematic and formal instruction during the first six or seven years of life. This innate capacity diminishes with age, thereby making language learning increasingly difficult. The author, being a returnee, experienced considerable difficulty acquiring L2, and especially achieving native-like competence. There will be many hurdles to conquer until Japanese students are able to reach at least a communicative level in English. It has been mentioned that English is not taught to clear the college entrance examination, but to communicate. However, Japanese college entrance examination still makes students focus more on the grammar-translation method. This is expected to shift to a more communication stressed approach. Japan does not have to aim at becoming an official bilingual country, but at least communicative English should be taught at every level in school Mito College is a small two-year co-ed college in Japan. Students at Mito College are basically notgood at English. It has only one department for business and economics, and English is required for all freshmen. It is necessary for me to make my classes enjoyable and attractive so that students can at least get motivated to learn English. My major target is communicative English so that students may be prepared to use English in various business settings. As an experiment to introduce more communicative English, the author has made the following syllabus design. This program aims at training students speak and enjoy English. 90-minute class (only 190-minute session per week is most common in Japanese colleges) is divided into two: The first half is to train students orally using Graded Direct Method. The latter half uses different materials each time so that students can learn and enjoy English culture and language simultaneously. There are no quizes or examinations in my one-academic year program. However, all students are required to make an original English poem by the end of the spring semester. 2-6 students work together in a group on one poem. Students coming to Mito College, Japan have one of the lowest English levels in all of Japan. However, an attached example of one poem made by a group shows that students can improve their creativity as long as they are kept encouraged. At the end of the fall semester, all students are then required individually to make a 3-minute original English speech. An example of that speech contest will be presented at the Convention in Seoul.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.177-192
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• 2016

Machine learning is a field of artificial intelligence. It refers to an area of computer science related to providing machines the ability to perform their own data analysis, decision making and forecasting. For example, one of the representative machine learning models is artificial neural network, which is a statistical learning algorithm inspired by the neural network structure of biology. In addition, there are other machine learning models such as decision tree model, naive bayes model and SVM(support vector machine) model. Among the machine learning models, we use SVM model in this study because it is mainly used for classification and regression analysis that fits well to our study. The core principle of SVM is to find a reasonable hyperplane that distinguishes different group in the data space. Given information about the data in any two groups, the SVM model judges to which group the new data belongs based on the hyperplane obtained from the given data set. Thus, the more the amount of meaningful data, the better the machine learning ability. In recent years, many financial experts have focused on machine learning, seeing the possibility of combining with machine learning and the financial field where vast amounts of financial data exist. Machine learning techniques have been proved to be powerful in describing the non-stationary and chaotic stock price dynamics. A lot of researches have been successfully conducted on forecasting of stock prices using machine learning algorithms. Recently, financial companies have begun to provide Robo-Advisor service, a compound word of Robot and Advisor, which can perform various financial tasks through advanced algorithms using rapidly changing huge amount of data. Robo-Adviser's main task is to advise the investors about the investor's personal investment propensity and to provide the service to manage the portfolio automatically. In this study, we propose a method of forecasting the Korean volatility index, VKOSPI, using the SVM model, which is one of the machine learning methods, and applying it to real option trading to increase the trading performance. VKOSPI is a measure of the future volatility of the KOSPI 200 index based on KOSPI 200 index option prices. VKOSPI is similar to the VIX index, which is based on S&P 500 option price in the United States. The Korea Exchange(KRX) calculates and announce the real-time VKOSPI index. VKOSPI is the same as the usual volatility and affects the option prices. The direction of VKOSPI and option prices show positive relation regardless of the option type (call and put options with various striking prices). If the volatility increases, all of the call and put option premium increases because the probability of the option's exercise possibility increases. The investor can know the rising value of the option price with respect to the volatility rising value in real time through Vega, a Black-Scholes's measurement index of an option's sensitivity to changes in the volatility. Therefore, accurate forecasting of VKOSPI movements is one of the important factors that can generate profit in option trading. In this study, we verified through real option data that the accurate forecast of VKOSPI is able to make a big profit in real option trading. To the best of our knowledge, there have been no studies on the idea of predicting the direction of VKOSPI based on machine learning and introducing the idea of applying it to actual option trading. In this study predicted daily VKOSPI changes through SVM model and then made intraday option strangle position, which gives profit as option prices reduce, only when VKOSPI is expected to decline during daytime. We analyzed the results and tested whether it is applicable to real option trading based on SVM's prediction. The results showed the prediction accuracy of VKOSPI was 57.83% on average, and the number of position entry times was 43.2 times, which is less than half of the benchmark (100 times). A small number of trading is an indicator of trading efficiency. In addition, the experiment proved that the trading performance was significantly higher than the benchmark.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.143-159
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• 2015

Predicting IT trends has been a long and important subject for information systems research. IT trend prediction makes it possible to acknowledge emerging eras of innovation and allocate budgets to prepare against rapidly changing technological trends. Towards the end of each year, various domestic and global organizations predict and announce IT trends for the following year. For example, Gartner Predicts 10 top IT trend during the next year, and these predictions affect IT and industry leaders and organization's basic assumptions about technology and the future of IT, but the accuracy of these reports are difficult to verify. Social media data can be useful tool to verify the accuracy. As social media services have gained in popularity, it is used in a variety of ways, from posting about personal daily life to keeping up to date with news and trends. In the recent years, rates of social media activity in Korea have reached unprecedented levels. Hundreds of millions of users now participate in online social networks and communicate with colleague and friends their opinions and thoughts. In particular, Twitter is currently the major micro blog service, it has an important function named 'tweets' which is to report their current thoughts and actions, comments on news and engage in discussions. For an analysis on IT trends, we chose Tweet data because not only it produces massive unstructured textual data in real time but also it serves as an influential channel for opinion leading on technology. Previous studies found that the tweet data provides useful information and detects the trend of society effectively, these studies also identifies that Twitter can track the issue faster than the other media, newspapers. Therefore, this study investigates how frequently the predicted IT trends for the following year announced by public organizations are mentioned on social network services like Twitter. IT trend predictions for 2013, announced near the end of 2012 from two domestic organizations, the National IT Industry Promotion Agency (NIPA) and the National Information Society Agency (NIA), were used as a basis for this research. The present study analyzes the Twitter data generated from Seoul (Korea) compared with the predictions of the two organizations to analyze the differences. Thus, Twitter data analysis requires various natural language processing techniques, including the removal of stop words, and noun extraction for processing various unrefined forms of unstructured data. To overcome these challenges, we used SAS IRS (Information Retrieval Studio) developed by SAS to capture the trend in real-time processing big stream datasets of Twitter. The system offers a framework for crawling, normalizing, analyzing, indexing and searching tweet data. As a result, we have crawled the entire Twitter sphere in Seoul area and obtained 21,589 tweets in 2013 to review how frequently the IT trend topics announced by the two organizations were mentioned by the people in Seoul. The results shows that most IT trend predicted by NIPA and NIA were all frequently mentioned in Twitter except some topics such as 'new types of security threat', 'green IT', 'next generation semiconductor' since these topics non generalized compound words so they can be mentioned in Twitter with other words. To answer whether the IT trend tweets from Korea is related to the following year's IT trends in real world, we compared Twitter's trending topics with those in Nara Market, Korea's online e-Procurement system which is a nationwide web-based procurement system, dealing with whole procurement process of all public organizations in Korea. The correlation analysis show that Tweet frequencies on IT trending topics predicted by NIPA and NIA are significantly correlated with frequencies on IT topics mentioned in project announcements by Nara market in 2012 and 2013. The main contribution of our research can be found in the following aspects: i) the IT topic predictions announced by NIPA and NIA can provide an effective guideline to IT professionals and researchers in Korea who are looking for verified IT topic trends in the following topic, ii) researchers can use Twitter to get some useful ideas to detect and predict dynamic trends of technological and social issues.

• Korean Journal of Heritage: History & Science
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• v.46 no.3
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• pp.134-149
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• 2013

The Sudang-ri Site in Geumsan is considered the historic site where Baekje dominated the inland traffic route to Gaya through Geumsan and Jinan in the 5th Century. This study identified the production techniques of iron by conducting an analysis of metallographical microstructure of the artifacts such as an iron sword and an iron sickle that were excavated in Sudang-ri Site, Geumsan, one of the regions ruled by Baekje, and tried to figure out the characteristics and the technical systems of Baekje's ironmaking around the 5th Century by comparing them with other iron artifacts produced around the same time. The analysis showed that various production techniques were applied to the artifacts excavated in Sudang-ri Site, Geumsan. Depending on the production techniques, they can be divided largely into three methods: the simple shape-forging method, the steel manufacture method after forging, and the steel manufacture & heat-treatment method after forging. The iron sickle from the stone chamber tomb No. 1, which was produced only through forging, is mostly composed of soft ferrite at both edges of the blade and at the rear making the use of the weapon impractical. From this fact, it is presumed that they were produced as burial objects or ceremonial accessories for the person buried. The iron axe from the outer stone coffin tomb No. 1 and the iron swords and sickle from the outer stone coffin tomb No. 12, which were produced through the steel manufacture method after forging such as carburizing, did not go through the heat treatment such as quenching, but applied different production processes to each part. Therefore, it is deemed that they were produced as daily tools for cultivation rather than burial objects or ceremonial accessories. The production techniques following the forging process - carburizing and heat treatment - can be found on the iron swords from the outer stone coffin tomb No. 5 and the outer stone coffin tomb No. 12. The sturdy structure of the blade part and the durable structure of the rear processed with heat are deemed to have been produced as weaponry and used by the person buried. Based on the analysis of the iron artifacts excavated from Sudang-ri Site in Geumsan, the characteristics of iron production techniques were investigated by comparing them with the artifacts from Yongwon-ri Site in Cheonan, Bongseon-ri Site in Seocheon, and Bujang-ri Site in Seosan that were made around the same time as the cluster of Baekje tombs examined by the metallographical microstructure analysis of this study. For the iron artifacts analyzed here, the changes in the techniques were investigated using the iron swords common in all of the tombs. In the case of the iron swords, it was identified the heat treatment technique called tempering was applied from the 4th Century.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.47-64
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• 2021

The global spread of COVID-19 around the world has not only affected many parts of our daily life but also has a huge impact on many areas, including the economy and society. As the number of confirmed cases and deaths increases, medical staff and the public are said to be experiencing psychological problems such as anxiety, depression, and stress. The collective tragedy that accompanies the epidemic raises fear and anxiety, which is known to cause enormous disruptions to the behavior and psychological well-being of many. Long-term negative emotions can reduce people's immunity and destroy their physical balance, so it is essential to understand the psychological state of COVID-19. This study suggests a method of monitoring medial news reflecting current days which requires striving not only for physical but also for psychological quarantine in the prolonged COVID-19 situation. Moreover, it is presented how an easier method of analyzing social media networks applies to those cases. The aim of this study is to assist health policymakers in fast and complex decision-making processes. News plays a major role in setting the policy agenda. Among various major media, news headlines are considered important in the field of communication science as a summary of the core content that the media wants to convey to the audiences who read it. News data used in this study was easily collected using "Bigkinds" that is created by integrating big data technology. With the collected news data, keywords were classified through text mining, and the relationship between words was visualized through semantic network analysis between keywords. Using the KrKwic program, a Korean semantic network analysis tool, text mining was performed and the frequency of words was calculated to easily identify keywords. The frequency of words appearing in keywords of articles related to COVID-19 emotions was checked and visualized in word cloud 'China', 'anxiety', 'situation', 'mind', 'social', and 'health' appeared high in relation to the emotions of COVID-19. In addition, UCINET, a specialized social network analysis program, was used to analyze connection centrality and cluster analysis, and a method of visualizing a graph using Net Draw was performed. As a result of analyzing the connection centrality between each data, it was found that the most central keywords in the keyword-centric network were 'psychology', 'COVID-19', 'blue', and 'anxiety'. The network of frequency of co-occurrence among the keywords appearing in the headlines of the news was visualized as a graph. The thickness of the line on the graph is proportional to the frequency of co-occurrence, and if the frequency of two words appearing at the same time is high, it is indicated by a thick line. It can be seen that the 'COVID-blue' pair is displayed in the boldest, and the 'COVID-emotion' and 'COVID-anxiety' pairs are displayed with a relatively thick line. 'Blue' related to COVID-19 is a word that means depression, and it was confirmed that COVID-19 and depression are keywords that should be of interest now. The research methodology used in this study has the convenience of being able to quickly measure social phenomena and changes while reducing costs. In this study, by analyzing news headlines, we were able to identify people's feelings and perceptions on issues related to COVID-19 depression, and identify the main agendas to be analyzed by deriving important keywords. By presenting and visualizing the subject and important keywords related to the COVID-19 emotion at a time, medical policy managers will be able to be provided a variety of perspectives when identifying and researching the regarding phenomenon. It is expected that it can help to use it as basic data for support, treatment and service development for psychological quarantine issues related to COVID-19.

• Radiation Oncology Journal
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• v.16 no.4
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• pp.409-423
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• 1998

Purpose : This retrospective study was tried to evaluate the clinical characteristics of patients, patterns of failure, survival rates, prognostic factors affecting survival, and treatment related toxicities when non-small cell lung cancer patients was treated by definitive radiotherapy alone or combined with chemotherapy. Materials and Methods : We evaluated the treatment results of 70 patients who were treated by definitive radiation therapy for non-small cell lung cancer at the Department of Radiation Oncology, Ewha Womans University Hospital, between March 1982 and April 1996. The number of patients of each stage was 2 in stage I, 6 in stage II, 30 in stage III-A, 29 in stage III-B, 3 in stage IV. Radiation therapy was administered by 6 MV linear accelerator and daily dose was 1.8-2.0 Gy and total radiation dose was ranged from 50.4 Gy to 72.0 Gy with median dose 59.4 Gy. Thirty four patients was treated with combined therapy with neoadjuvant or concurrent chemotherapy and radiotherapy, and most of them were administered with the multi-drug combined chemotherapy including etoposide and cisplatin. The survival rate was calculated with the Kaplan-Meier methods. Results : The overall 1-year, 2-year, and 3-year survival rates were 63$\%$, 29$\%$, and 26$\%$, respectively. The median survival time of all patients was 17 months. The disease-free survival rate for 1-year and 2-year were 23$\%$ and 16$\%$, respectively. The overall 1-year survival rates according to the stage was 100$\%$ for stage I, 80$\%$ for stage II, 61$\%$ for stage III, and 50$\%$ for stage IV. The overall 1-year 2-year, and 3-year survival rates for stage III patients only were 61$\%$, 23$\%$, and 20$\%$, respectively. The median survival time of stage III patients only was 15 months. The complete response rates by radiation therapy was 10$\%$ and partial response rate was 50$\%$. Thirty patients (43$\%$) among 70 patients assessed local control at initial 3 months follow-up duration. Twenty four (80$\%$) of these 30 Patients was possible to evaluate the pattern of failure after achievement of local control. And then, treatment failure occured in 14 patients (58$\%$): local relapse in 6 patients (43$\%$), distant metastasis in 6 patients (43$\%$) and local relapse with distant metastasis in 2 patients (14$\%$). Therefore, 10 patients (23$\%$) were controlled of disease of primary site with or without distant metastases. Twenty three patients (46$\%$) among 50 patients who were possible to follow-up had distant metastasis. The overall 1-year survival rate according to the treatment modalities was 59$\%$ in radiotherapy alone and 66$\%$ in chemoirradiation group. The overall 1-year survival rates for stage III patients only was 51$\%$ in radiotherapy alone and 68$\%$ in chemoirradiation group which was significant different. The significant prognostic factors affecting survival rate were the stage and the achievement of local control for all patients at univariate- analysis. Use of neoadjuvant or concurrent chemotherapy, use of chemotherapy and the achievement of local control for stage III patients only were also prognostic factors. The stage, pretreatment performance status, use of neoadjuvant or concurrent chemotherapy, total radiation dose and the achievement of local control were significant at multivariate analysis. The treatment-related toxicities were esophagitis, radiation pneunonitis, hematologic toxicity and dermatitis, which were spontaneously improved, but 2 patients were died with radiation pneumonitis. Conclusion : The conventional radiation therapy was not sufficient therapy for achievement of long-term survival in locally advanced non-small cell lung cancer. Therefore, aggressive treatment including the addition of appropriate chemotherapeutic drug to decrease distant metastasis and preoperative radiotherapy combined with surgery, hyperfractionation radiotherapy or 3-D conformal radiation therapy for increase local control are needed.

• Korean Journal of Soil Science and Fertilizer
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• v.45 no.2
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• pp.280-286
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• 2012

Clean energy farming is the agricultural activity to improve an efficiency of agricultural energy use and to replace fossil fuels. This study was carried out to establish the clean energy farming system in the controlled cultivation of vegetable crop (cucumber) adopting the biogas production facility. In order to design the clean energy farming system, mass and energy balance was analyzed between the controlled cultivation system and the biogas production facility. Net yearly heating energy demands ($E_{YHED}$) of forcing and semi-forcing cultivation types were 48,697 and $13.536Mcal\;10^{-1}$ in the controlled cultivation of vegetable cucumber. To cover these $E_{YHED}$, the pig slurry of 511 and $142m^3\;10a^{-1}$ (biogas volume of 9,482 and $2,636Nm^3\;10a^{-1}$, respectively, as 60% methane content) were needed in forcing and semi-forcing cultivation types. The pig slurry of $511m^3\;10a^{-1}$ caused N 1,788, $P_2O_5$ $511kg\;10a^{-1}$ in the forcing cultivation type, and the pig slurry of $142m^3\;10a^{-1}$ caused N 497, $P_2O_5$ $142kg\;10a^{-1}$ in the semi-forcing cultivation type. The daily heating energy demand ($E_{i,DHED}$) by the time scale analysis showed the minimum $E_{i,DHED}$ of $7.7Mcal\;10a^{-1}\;day^{-1}$, the maximum $E_{i,DHED}$ of $515.1Mcal\;10a^{-1}\;day^{-1}$, and the mean $E_{i,DHED}$ of 310.2 in the forcing cultivation type. And the minimum $E_{i,DHED}$, the maximum $E_{i,DHED}$, and the mean $E_{i,DHED}$ were 5.3, 258.0, and $165.1Mcal\;10a^{-1}\;day^{-1}$ in the semi-forcing cultivation type, respectively. Input scale of biogas production facility designed from the mean $E_{i,DHED}$ were 3.3 and $1.7m^3\;day^{-1}$ in the forcing and the semi-forcing cultivation type. The maximum $E_{i,DHED}$ gave the input scale of 5.4 and $2.7m^3\;day^{-1}$ in the forcing and the semi-forcing cultivation type.

• Journal of the Korean Society of School Health
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• v.3 no.1
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• pp.101-118
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• 1990

This study was intended to investigate actual conditions and problems relating to a variety of substance which have been used by students. A Questionnaire survey was carried out with the subject of 2411 students in an academic boys' high school, academic girls' high school, technical boys' high school and technical girls' high school in Pusan, from the 15th day to 29th day of March, 1989. The summarized results were as follows. There was not a remarkable difference in distribution of these subjects in boys' & girls' high school. The common and good health condition of subjects accounted for 90 percent or higher. 24.4 percent of them also had smoking experience, 11.6 percent of which continues to smoking. The understanding rate of these substances name other than sedative, psychostimulants and antihypnotic accounted for 90 percent or higher. The experience rate taking these substances for one year showed that anodyne, digestive and nutritive tonic accounted for 70 percent, antihypnotic for 15.6 percent, sedative for 1.4 percent, respectively, and psychostimulants for 0.5 percent. Moreover. it was shown that drugs accounted for 1.5 percent, bond for 1.4 percent, and thinner for 0.5 percent. The rate of the daily experiencers who took anodyne, digestive, nutritive tonic, sedatives, and psychostimulants and so on was 7.7 percent, 6.2 percent, 5.2 percent, 5.9 percent, and 5.0 percent respectively. This fact implied that there was a serious problem in high school students' non - narcotic abuse. The usage rate of these substances for treatment purpose showed that anodyme accounted for 90 percent or higher, and digestive for 70-80 percent, respectively, where girl students showed higher rate than one of boy students. Additionally, there was higher the usage rate for other purposes. The usage rate of drugs was highest when these students felt melancholy and curiousity. Their obtaining place appeared that these students mainly obtained these drugs, bonds and thinners from a small shop or peddler and their friend while they usually obtained other substance from the pharmacy and medical institute. The first usage time of these substances appeared during the middle school (the age of 14-15) which was the highest rate. The smoker of all subjects used remarkly large substances as compared with one of no-smoker. Particularly, it appeared that the usage of drugs was very closely related to smoking. The large number of students did not use these substances for oesrable purposes even though they understood the name of these substances. For this reason, from primasy schools it is required to teach the students dependence and harmful effects caused by these substances abuse. Moreover, it was shown that these students firstly used these substances during the middle school (the age of 14-15)due to curiosity. As a result, it is very urgent to give the students health education suitabale for prevention of these substance abuse, when considering harmful effects of these substances. And so health education for no-smoking. Finally, considering that it is very easy to obtain these substances from a small shop and pharmacy, the regulation of these substances control should be considered and completed in the future.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.1-31
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• 2017

Modern businesses are adopting new technologies to serve their markets better as well as to improve efficiency and productivity. The advertising industry has continuously experienced disruptions from the traditional channels (radio, television and print media) to new complex ones including internet, social media and mobile-based advertising. This case study focuses on proposing intelligent advertising business model in Seoul's metro network. Seoul has one of the world's busiest metro network and transports a huge number of travelers on a daily basis. The high number of travelers coupled with a well-planned metro network creates a platform where marketers can initiate engagement and interact with both customers and potential customers. In the current advertising model, advertising is on illuminated and framed posters in the stations and in-car, non-illuminated posters, and digital screens that show scheduled arrivals and departures of metros. Some stations have digital screens that show adverts but they do not have location capability. Most of the current advertising media have one key limitation: space. For posters whether illuminated or not, one space can host only one advert at a time. Empirical literatures show that there is room for improving this advertising model and eliminate the space limitation by replacing the poster adverts with digital advertising platform. This new model will not only be digital, but will also provide intelligent advertising platform that is driven by data. The digital platform will incorporate location sensing, e-commerce, and mobile platform to create new value to all stakeholders. Travel cards used in the metro will be registered and the card scanners will have a capability to capture traveler's data when travelers tap their cards. This data once analyzed will make it possible to identify different customer groups. Advertisers and marketers will then be able to target specific customer groups, customize adverts based on the targeted consumer group, and offer a wide variety of advertising formats. Format includes video, cinemagraphs, moving pictures, and animation. Different advert formats create different emotions in the customer's mind and the goal should be to use format or combination of formats that arouse the expected emotion and lead to an engagement. Combination of different formats will be more effective and this can only work in a digital platform. Adverts will be location based, ensuring that adverts will show more frequently when the metro is near the premises of an advertiser. The advertising platform will automatically detect the next station and screens inside the metro will prioritize adverts in the station where the metro will be stopping. In the mobile platform, customers who opt to receive notifications will receive them when they approach the business premises of advertiser. The mobile platform will have indoor navigation for the underground shopping malls that will allow customers to search for facilities within the mall, products they may want to buy as well as deals going on in the underground mall. To create an end-to-end solution, the mobile solution will have a capability to allow customers purchase products through their phones, get coupons for deals, and review products and shops where they have bought a product. The indoor navigation will host intelligent mobile-based advertisement and a recommendation system. The indoor navigation will have adverts such that when a customer is searching for information, the recommendation system shows adverts that are near the place traveler is searching or in the direction that the traveler is moving. These adverts will be linked to the e-commerce platform such that if a customer clicks on an advert, it leads them to the product description page. The whole system will have multi-language as well as text-to-speech capability such that both locals and tourists have no language barrier. The implications of implementing this model are varied including support for small and medium businesses operating in the underground malls, improved customer experience, new job opportunities, additional revenue to business model operator, and flexibility in advertising. The new value created will benefit all the stakeholders.