• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.39-54
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• 2013

Recent explosive increase of electronic commerce provides many advantageous purchase opportunities to customers. In this situation, customers who do not have enough knowledge about their purchases, may accept product recommendations. Product recommender systems automatically reflect user's preference and provide recommendation list to the users. Thus, product recommender system in online shopping store has been known as one of the most popular tools for one-to-one marketing. However, recommender systems which do not properly reflect user's preference cause user's disappointment and waste of time. In this study, we propose a novel recommender system which uses data mining and multi-model ensemble techniques to enhance the recommendation performance through reflecting the precise user's preference. The research data is collected from the real-world online shopping store, which deals products from famous art galleries and museums in Korea. The data initially contain 5759 transaction data, but finally remain 3167 transaction data after deletion of null data. In this study, we transform the categorical variables into dummy variables and exclude outlier data. The proposed model consists of two steps. The first step predicts customers who have high likelihood to purchase products in the online shopping store. In this step, we first use logistic regression, decision trees, and artificial neural networks to predict customers who have high likelihood to purchase products in each product group. We perform above data mining techniques using SAS E-Miner software. In this study, we partition datasets into two sets as modeling and validation sets for the logistic regression and decision trees. We also partition datasets into three sets as training, test, and validation sets for the artificial neural network model. The validation dataset is equal for the all experiments. Then we composite the results of each predictor using the multi-model ensemble techniques such as bagging and bumping. Bagging is the abbreviation of "Bootstrap Aggregation" and it composite outputs from several machine learning techniques for raising the performance and stability of prediction or classification. This technique is special form of the averaging method. Bumping is the abbreviation of "Bootstrap Umbrella of Model Parameter," and it only considers the model which has the lowest error value. The results show that bumping outperforms bagging and the other predictors except for "Poster" product group. For the "Poster" product group, artificial neural network model performs better than the other models. In the second step, we use the market basket analysis to extract association rules for co-purchased products. We can extract thirty one association rules according to values of Lift, Support, and Confidence measure. We set the minimum transaction frequency to support associations as 5%, maximum number of items in an association as 4, and minimum confidence for rule generation as 10%. This study also excludes the extracted association rules below 1 of lift value. We finally get fifteen association rules by excluding duplicate rules. Among the fifteen association rules, eleven rules contain association between products in "Office Supplies" product group, one rules include the association between "Office Supplies" and "Fashion" product groups, and other three rules contain association between "Office Supplies" and "Home Decoration" product groups. Finally, the proposed product recommender systems provides list of recommendations to the proper customers. We test the usability of the proposed system by using prototype and real-world transaction and profile data. For this end, we construct the prototype system by using the ASP, Java Script and Microsoft Access. In addition, we survey about user satisfaction for the recommended product list from the proposed system and the randomly selected product lists. The participants for the survey are 173 persons who use MSN Messenger, Daum Caf$\acute{e}$, and P2P services. We evaluate the user satisfaction using five-scale Likert measure. This study also performs "Paired Sample T-test" for the results of the survey. The results show that the proposed model outperforms the random selection model with 1% statistical significance level. It means that the users satisfied the recommended product list significantly. The results also show that the proposed system may be useful in real-world online shopping store.

• The Korean Society of Law and Medicine
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• v.16 no.2
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• pp.263-291
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• 2015

In May, 2015, a 68 years old man, who has been Middle East Saudi Arabia and the United Arab Emirates, had high fever, muscle aches, cough and shortness of breath. he went two local hospital near his house and the S Medical Center emergency center. He was diagnosed MERS(Middle East respiratory syndrome) and the diseases had put South Korea the fear of epidemics for three months. Especially, this disease has firstly reported in Middle East Asia in September 2012 and spreaded to twenty-six countries. In 21, July, 2015, European Center for disease prevention and control reported 533 people were died and in South Korea, 186 people were infected, 36 people were died and 16,693 people were isolated from MERS. South Korea government were faced into epidemic control and blamed from public. Especially, hospital acquired infection, disease control chain, opening of information, ventilation, lack of isolation bed, the problem of function of local health center, the issue of reparation for hospital and insurance cover rate, the classification of disease, the role of Korea Centers for disease control and prevention, the culture of visiting hospital to see sick people, the issue of hospital multiple room and other related social support policy. it is time to study and discuss to solve these problems. South Korea citizens felt fear and fright from MERS. What is wore, they thought the dieses were out of their government control. It was unusual case for word except Middle East Asia. numerous tourists canceled visiting korea. South korea economic were severly damaged especially, tourism industry. South korea government should admit that they had failed initial action against MERS and take full reasonability from any damages. The government have to open information to public in terms of epidemic diseases and try to prevent any other epidemic diseases and try to work with local governments.

• (The) Research of the performance art and culture
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• no.20
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• pp.251-307
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• 2010

Manbojeonseo, a kind of an encyclopedia published several times in Ming Ch'ing dynasty, includes useful information for scholars and common people on daily lives. In 1720, Manbojeonseo was first introduced to Joseon(朝鮮) dynasty by the diplomatic corps visiting Ch'ing dynasty, and widely circulated in the society as an useful information magazine or an individual collection of reference book. Since Manbojeonseo includes the systematically-organized contents of Geumdoron(琴道論, a theory of a heptachord), it could provide a useful reference when the Geumdoron was inserted as the contents of old scores. For an instance, Obultan(五不彈), Tangeumsuji(彈琴須知), and Taeeumgibeop(太音紀法) recorded in Hangeumsinbo(韓琴新譜, 1724) clearly acknowledge Manbojeonseo as their common source. In this paper, the order and the contents of Geumdorons from four different Manbojeonseo are compared. At first, the comparative analysis of Manbojeonseo (1610) edited by Seo Giryong(徐企龍) and Manbojeonseo(1612) edited by Yu Jamyeong(劉子明) are carried out focusing on the contents of the Geumdoron, where both Manbojeonseos contain considerable amount of Geumdoron sections. The tables of the contents in both Manbojeonseos are composed of upper and lower levels classified into 4 large divisions for each. While the contents of the upper level is presumably older and focused more on the theory of the cardinal virtues, the contents of the lower one is relatively new and centered more on the skills for the real play of a heptachord(琴), the lyrics and the musical scores composed of Gamjabo(減字譜). Therefore, it could be said that the upper level is metaphysical while the lower level is physical. One of the differences between those two Manbojeonseos lies in the order and the terminology found in the large divisions. In the case of Manbojeonseo(1612), some terms in the large division represent and theoretically group the detailed descriptions in the small divisions such as 5 demands or 7 taboos in the play of the heptachord. In addition, a few lower divisions were newly added or revised in order to enhance the completeness of Geumhangmun(琴學門, study of a heptachord), and the detailed classification was revised and polished to improve the reasonableness. In Manbojeonseo(1614) composed by the same editor as Manbojeonseo(1610), the contents of the Geumdoron become much briefer than those of Manbojeonseo(1610) and Manbojeonseo(1612). In the case of Manbojeonseo(1739), a new type of the Geumdoron is included called Oeumjeongjobo(五音正操譜) while carrying a similarly brief section of the Geumdoron. Finally, the Geumdorons in Manbojeonseo and several old scores are comparatively analyzed. While the Geumbo(琴譜) owned by Gugagwon(國樂院) and Hangeumsinbo contains relatively old Geumdoron, Yuyeji(遊藝志) and Bangsanhanssigeumbo(芳山韓氏琴譜) adopt practical and relatively new Geumdorons different from the former old scores and similar to Manbojeonseo(1739) considering the order and the contents. In particular, the contents of the Geumdoron in Geumheonakbo(琴軒樂譜) is notably unique containing much of the upper and the lower levels of Manbojeonseo(1612), therefore thought to have actively adopted the contents of new Geumdorons.

• Journal of the Korean Institute of Landscape Architecture
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• v.47 no.2
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• pp.59-75
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• 2019

This study was carried out to explore the 4th Industrial Revolution technology from the perspective of the landscape industry to provide the basic data necessary to increase the virtuous circle value. The 4th Industrial Revolution, the characteristics of the landscape industry and urban regeneration were considered and the methodology was established and studied including the technical classification system suitable for systematic research, which was selected as a framework. First, the 4th Industrial Revolution technology based on digital data was selected, which could be utilized to increase the value of the virtuous circle for the landscape industry. From 'Element Technology Level', and 'Core Technology' such as the Internet of Things, Cloud Computing, Big Data, Artificial Intelligence, Robot, 'Peripheral Technology', Virtual or Augmented Reality, Drones, 3D 4D Printing, and 3D Scanning were highlighted as the 4th Industrial Revolution technology. It has been shown that it is possible to increase the value of the virtuous circle when applied at the 'Trend Level', in particular to the landscape industry. The 'System Level' was analyzed as a general-purpose technology, and based on the platform, the level of element technology(computers, and smart devices) was systematically interconnected, and illuminated with the 4th Industrial Revolution technology based on digital data. The application of the 'Trend Level' specific to the landscape industry has been shown to be an effective technology for increasing the virtuous circle values. It is possible to realize all synergistic effects and implementation of the proposed method at the trend level applying the element technology level. Smart gardens, smart parks, etc. have been analyzed to the level they should pursue. It was judged that Smart City, Smart Home, Smart Farm, and Precision Agriculture, Smart Tourism, and Smart Health Care could be highly linked through the collaboration among technologies in adjacent areas at the Trend Level. Additionally, various utilization measures of related technology applied at the Trend Level were highlighted in the process of urban regeneration, public service space creation, maintenance, and public service. In other words, with the realization of ubiquitous computing, Hyper-Connectivity, Hyper-Reality, Hyper-Intelligence, and Hyper-Convergence were proposed, reflecting the basic characteristics of digital technology in the landscape industry can be achieved. It was analyzed that the landscaping industry was effectively accommodating and coordinating with the needs of new characters, education and consulting, as well as existing tasks, even when participating in urban regeneration projects. In particular, it has been shown that the overall landscapig area is effective in increasing the virtuous circle value when it systems the related technology at the trend level by linking maintenance with strategic bridgehead. This is because the industrial structure is effective in distributing data and information produced from various channels. Subsequent research, such as demonstrating the fusion of the 4th Industrial Revolution technology based on the use of digital data in creation, maintenance, and service of actual landscape space is necessary.

• Journal of Food Hygiene and Safety
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• v.33 no.6
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• pp.417-426
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• 2018

Food preservatives are very important food additives for the biological and chemical safety of processed foods. The purposes of this study were to investigate Korean consumer's perception and information needs on food preservatives, to develop an educational booklet as a risk communication material on food preservatives, and to assess the educational effect of the developed booklet. To understand perception on food preservatives, a self-administered questionnaire survey was conducted by 381 parents having elementary school students at Seoul and Geoynggi area in Korea. Based on the survey results, brain storming of the authors along with consultation from the professionals, we developed a risk communication booklet about food preservatives. It was exposed to 35 parents of elementary school children, and their evaluation was collected by using a questionnaire and analyzed statistically. Respondents considered food safety (44.8%) as the most important factor while purchasing processed foods. They still perceived food additives as the most hazardous one (41.5%), and among those, food preservatives were the most concerned (45.9%). Total 67.7% of the respondents considered the consumption of food preservatives as hazardous or very hazardous. However, 90.6% of respondents did not have any educational experience about food additives and food preservatives. Based on their information needs, a science-based booklet consisting of the definition, classification, safety, intake, and management of food preservatives was developed. When the booklet titled as 'Food preservatives, Just Know Them!' was exposed to the parents via elementary school teacher, their negative perceptions on food additives and food preservatives were changed positively by increasing the understanding level on preservatives from 18.9% to 90.9% and obtaining 72.7% positive answers on their safety. Therefore, it could be used as an effective risk communication material on food preservatives.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.239-251
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• 2019

Statistical methods such as moving averages, Kalman filtering, exponential smoothing, regression analysis, and ARIMA (autoregressive integrated moving average) have been used for stock market predictions. However, these statistical methods have not produced superior performances. In recent years, machine learning techniques have been widely used in stock market predictions, including artificial neural network, SVM, and genetic algorithm. In particular, a case-based reasoning method, known as k-nearest neighbor is also widely used for stock price prediction. Case based reasoning retrieves several similar cases from previous cases when a new problem occurs, and combines the class labels of similar cases to create a classification for the new problem. However, case based reasoning has some problems. First, case based reasoning has a tendency to search for a fixed number of neighbors in the observation space and always selects the same number of neighbors rather than the best similar neighbors for the target case. So, case based reasoning may have to take into account more cases even when there are fewer cases applicable depending on the subject. Second, case based reasoning may select neighbors that are far away from the target case. Thus, case based reasoning does not guarantee an optimal pseudo-neighborhood for various target cases, and the predictability can be degraded due to a deviation from the desired similar neighbor. This paper examines how the size of learning data affects stock price predictability through k-nearest neighbor and compares the predictability of k-nearest neighbor with the random walk model according to the size of the learning data and the number of neighbors. In this study, Samsung electronics stock prices were predicted by dividing the learning dataset into two types. For the prediction of next day's closing price, we used four variables: opening value, daily high, daily low, and daily close. In the first experiment, data from January 1, 2000 to December 31, 2017 were used for the learning process. In the second experiment, data from January 1, 2015 to December 31, 2017 were used for the learning process. The test data is from January 1, 2018 to August 31, 2018 for both experiments. We compared the performance of k-NN with the random walk model using the two learning dataset. The mean absolute percentage error (MAPE) was 1.3497 for the random walk model and 1.3570 for the k-NN for the first experiment when the learning data was small. However, the mean absolute percentage error (MAPE) for the random walk model was 1.3497 and the k-NN was 1.2928 for the second experiment when the learning data was large. These results show that the prediction power when more learning data are used is higher than when less learning data are used. Also, this paper shows that k-NN generally produces a better predictive power than random walk model for larger learning datasets and does not when the learning dataset is relatively small. Future studies need to consider macroeconomic variables related to stock price forecasting including opening price, low price, high price, and closing price. Also, to produce better results, it is recommended that the k-nearest neighbor needs to find nearest neighbors using the second step filtering method considering fundamental economic variables as well as a sufficient amount of learning data.

• The Korean Journal of Archival Studies
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• no.28
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• pp.35-81
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• 2011

Manhwa is a mass media (to expose all faces of an era such as politics, society, cultures, etc with the methodology of irony, parody, etc). Since the Manhwa records is primary culture infrastructure, it can create the high value-added industry by connecting with fancy, character, game, movie, drama, theme park, advertising business. However, due to lack of active and systematic aquisition system, as precious Manhwa manuscript is being lost every year and the contents hard to preserve such as Manhwa content in the form of electronic records are increasing, the countermeasure of Manhwa contents management is needed desperately. In this study, based on these perceptions, the need of Manhwa records management is examined, and the characteristics and the components of Manhwa records were analyzed. And at the same time, the functions of record management process reflecting the characteristics of Manhwa records were extracted by analyzing various cases of overseas Cartoon Archives. And then, the framework of record-keeping regime was segmented into each of acquisition management service areas and the general Manhwa records archiving strategy, which manages the Manhwa contents records, was established and suggested. The acquired Manhwa content records will secure the context among records and warrant the preservation of records and provide diverse access points by reflecting multi classification and multi-level descriptive element. The Manhwa records completed the intellectual arrangement will be preserved after the conservation in an environment equipped with preservation facilities or preserved using digital format in case of electronic records or when there is potential risk of damaging the records. Since the purpose of the Manhwa records is to use them, the information may be provided to diverse classes of users through the exhibition, the distribution, and the development of archival information content. Since the term of "Manhwa records" is unfamiliar yet and almost no study has been conducted in the perspective of records management, it will be the limit of this study only presenting acquisition strategy, management and service strategy of Manhwa contents and suggesting simple examples. However, if Manhwa records management strategy are possibly introduced practically to Manhwa manuscript repositories through archival approach, it will allow systematic acquisition, preservation, arrangement of Manhwa records and will contribute greatly to form a foundation for future Korean culture contents management.

• Journal of Korean Society of Forest Science
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• v.100 no.3
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• pp.522-534
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• 2011

The aim of this study is to draw forth the tasks for establishing the right of native biology in Korea through the case study on 'Access on genetic resources and Benefit Sharing'. For this purpose, this study decided on its research subject by selecting Hoodia, on which ABS treaty was made the most recently, through the examination of the representative ABS precedents on plant species. This study analyzed the process background of ABS on Hoodia, and compared & analyzed the ABS procedures of 'Bonn Guidelines' adopted by the 6th Conference of the Parties of the Convention on Biological Diversity in 2002 and Hoodia case. Together with the ABS major issues in common drawn as a result of this analysis, and "Nagoya Protocol" adopted by the 10th Conference of the Parties of the Convention on Biological Diversity, this study intended to shed a light on the impending tasks which Korea faces at present and its role relationship. The research results are as follows: 1. It is required that species habitats should be divided based on biological classification and its subsequent community should be established with the development of infrastructure such as a community's independent production, management and monitoring of bio-species. 2. There needs to be a designation of ABS National Focal Point for sharing of ABS-related general information, boosting of implementation of the relevant convention. 3. There needs to be the establishment of ABS convention system consequent on legislative, administrative, political procedures, and designation of the Competent National Authorities for the provision of the format of Prior Informed Consent (PIC) and Mutually Agreed Terms (MAT) and their contents assessment and confirmation. 4. There should be the establishment of integrated management system of ABS-related research and development of forest biological resources and its relevant research projects. 5. There should be information development through the distribution of responsibility and role between the ministries and offices concerned according to bio-resources, and there needs to be efforts in aiming for opening a working group of academic-industrial institutions for developing a mutually interchangeable system. 6. It's required that the efficient access between industrial circles and the people should be promoted by setting up ABS support center of biological resources in ministry and office's charge. 7. There should be a selection of a national supervisory organization for securement of the right of a local community and monitoring of ABS convention implementation, and a countermeasure system for preventing outflow of forest bioresources. Conclusively, it's judged that it will be possible to inquire into the countermeasures for the establishment of the native forest biology dominion through such research results.

• The Journal of Korean Institute of Next Generation Computing
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• v.14 no.6
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• pp.30-43
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• 2018

Many studies have been carried out to retrieve images using colors, shapes, and textures which are characteristic of images. In addition, there is also progress in research related to the disease images of the crop. In this paper, to be a help to identify the disease occurred in crops grown in the agricultural field, we propose a similarity-based crop disease search system using the diseases image of horticulture crops. The proposed system improves the similarity retrieval performance compared to existing ones through the combination descriptor without using a single descriptor and applied the weight based calculation method to provide users with highly readable similarity search results. In this paper, a total of 13 Descriptors were used in combination. We used to retrieval of disease of six crops using a combination Descriptor, and a combination Descriptor with the highest average accuracy for each crop was selected as a combination Descriptor for the crop. The retrieved result were expressed as a percentage using the calculation method based on the ratio of disease names, and calculation method based on the weight. The calculation method based on the ratio of disease name has a problem in that number of images used in the query image and similarity search was output in a first order. To solve this problem, we used a calculation method based on weight. We applied the test image of each disease name to each of the two calculation methods to measure the classification performance of the retrieval results. We compared averages of retrieval performance for two calculation method for each crop. In cases of red pepper and apple, the performance of the calculation method based on the ratio of disease names was about 11.89% on average higher than that of the calculation method based on weight, respectively. In cases of chrysanthemum, strawberry, pear, and grape, the performance of the calculation method based on the weight was about 20.34% on average higher than that of the calculation method based on the ratio of disease names, respectively. In addition, the system proposed in this paper, UI/UX was configured conveniently via the feedback of actual users. Each system screen has a title and a description of the screen at the top, and was configured to display a user to conveniently view the information on the disease. The information of the disease searched based on the calculation method proposed above displays images and disease names of similar diseases. The system's environment is implemented for use with a web browser based on a pc environment and a web browser based on a mobile device environment.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.191-206
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• 2022

Recently, it is a de-facto approach to utilize a pre-trained language model(PLM) to achieve the state-of-the-art performance for various natural language tasks(called downstream tasks) such as sentiment analysis and question answering. However, similar to any other machine learning method, PLM tends to depend on the data distribution seen during the training phase and shows worse performance on the unseen (Out-of-Distribution) domain. Due to the aforementioned reason, there have been many efforts to develop domain-specified PLM for various fields such as medical and legal industries. In this paper, we discuss the training of a finance domain-specified PLM for the Korean language and its applications. Our finance domain-specified PLM, KB-BERT, is trained on a carefully curated financial corpus that includes domain-specific documents such as financial reports. We provide extensive performance evaluation results on three natural language tasks, topic classification, sentiment analysis, and question answering. Compared to the state-of-the-art Korean PLM models such as KoELECTRA and KLUE-RoBERTa, KB-BERT shows comparable performance on general datasets based on common corpora like Wikipedia and news articles. Moreover, KB-BERT outperforms compared models on finance domain datasets that require finance-specific knowledge to solve given problems.