• Knowledge Management Research
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• v.22 no.3
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• pp.273-293
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• 2021

Due to the COVID-19 pandemic, the size of the e-commerce has been increased rapidly. This pandemic, which made contact-less communication culture in everyday life made the e-commerce market to be opened even to the consumers who would hesitate to purchase and pay by electronic device without any personal contacts and seeing or touching the real products. Consumers who have experienced the easy access and convenience of the online purchase would continue to take those advantages even after the pandemic. During this time of transformation, however, the size of information source for the consumers has become even shrunk into a flat screen and limited to visual only. To provide differentiated and competitive information on products, companies are adopting AR/VR and steaming technologies but the reviews from the honest users need to be recognized as important in that it is regarded as strong as the well refined product information provided by marketing professionals of the company and companies may obtain useful insight for product development, marketing and sales strategies. Then from the consumer's point of view, if the ratings of reviews are widely diverged how consumers would process the review information before purchase? Are non-converged ratings always unreliable and worthless? In this study, we analyzed how consumer's regulatory focus moderate the attitude to process the diverged information. This experiment was designed as a 2x2 factorial study to see how the variance of product review ratings (high vs. low) for cosmetics affects product attitudes by the consumers' regulatory focus (prevention focus vs. improvement focus). As a result of the study, it was found that prevention-focused consumers showed high product attitude when the review variance was low, whereas promotion-focused consumers showed high product attitude when the review variance was high. With such a study, this thesis can explain that even if a product with exactly the same average rating, the converged or diverged review can be interpreted differently by customer's regulatory focus. This paper has a theoretical contribution to elucidate the mechanism of consumer's information process when the information is not converged. In practice, as reviews and sales records of each product are accumulated, as an one of applied knowledge management types with big data, companies may develop and provide even reinforced customer experience by providing personalized and optimized products and review information.

• Journal of Environmental Impact Assessment
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• v.28 no.2
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• pp.152-168
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• 2019

The element arsenic, which is abundant in the Earth's crust, is used for various industrial purposes including materials for disease treatment and household goods. Various human activities, such as the disposal of soil waste, metal mining and smelting, and combustion of fossil fuels, have caused the pollution of the environment with arsenic. Recently, guidelines for arsenic in rice have been adopted by the Korean ministry of food and drug safety to prevent health risks based on rice consumption. Because of the exposure to arsenic and its accumulation in the human body through various channels, such as air inhalation, skin contact, ingestion of drinking water, and food consumption, integrated multimedia risk assessment is required to adopt appropriate risk management policies. Therefore, integrated human health risk assessment was carried out in this study using integrated exposure assessment based on multimedia (e.g., air, water, and soil) and multi-route (e.g., oral, inhalation, and dermal) scenarios. The results show that oral uptake via drinking water is the most common pathway of arsenic into the human body, accounting for 57%-96% of the total arsenic exposure. Among various age groups, the highest exposures to arsenic were observed in infants because the body weight of infants is low and the surface areas of infant bodies are large. Based on the results of the exposure assessment, the cancer and non-cancer risks were calculated. The cancer risk for CTE and RME is in the range of 2.3E-05 to 6.7E-05 and thus is negligible because it does not exceed the cancer probability of 1.0E-04 for all age groups. On the other hand, the cancer risk for RME varies from 6.4E-05 to 1.8E-04 and from 1.3E-04 to 1.8E-04 for infants and preschool children, exceeding the excess cancer risk of 1.0E-04. The non-cancer risks range from 5.4E-02 to 1.9E-01 and from 1.5E-01 to 6.8E-01, respectively. They do not exceed the hazard index 1 for all scenarios and all ages.

• Korean Journal of Heritage: History & Science
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• v.42 no.3
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• pp.106-130
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• 2009

The aim of this paper is analysis of structure and development pattern about wooden coffin and chamber tombs in Gyeongju from the 2nd century B.C. to the 3rd century A.D. for researching to socio-political tendency and growth process of Sarokuk. Tombs buried with iron objects were built in Youngnam(嶺南) from the 2nd century B.C. with spread wooden coffin with stone mound(積石木棺墓). Also medium or small sized wooden coffin tombs buried with bronze mirror of western Han(前漢) and soft stoneware(瓦質土器) were appeared the 2nd century B.C. in Gyeongju, because of establishment of Han's commanderies(漢郡縣) in the Korean Peninsula and refuge from Daedong river(大同江) to Jinhan(辰韓). Separate tombs(獨立墓) with lots of bronze object ware assumed high ranked tombs of parsonage(司祭王) or local chief(地域首長). From the 2nd century A.D. the size of wooden coffin tombs became enlarged and funerary objects ware abundant, for example Sarari 130th tomb(舍羅里 130號). The burying pattern of this tomb is similar to wooden chamber tombs in Lelang(樂浪), which had prestige goods like lacquer ware and bronze mirror in wood box(木匣) beside coffin. Appearance of these wooden chamber tombs that were different from original wooden coffin tombs imply interaction between Lelang and these area with iron. Sarari community that held right of trade and distribution to outside through the geographical advantage grew up centered position in Gyeongju politically, socially, and culturally. Chamber in tomb as a new structural notion that can secure funerary objects became firmly was established from the 2nd century A.D. in Gyeongju and large sized wooden chamber tombs were generally built early of the 3rd century A.D. This tendency was reflected in stratification of community and growth as center of local state. After late of the 3rd century A.D. Gyeongju type wooden chamber tomb(慶州式木槨墓) which had subordinate outer coffin(副槨) was appeared and then subordinate outer coffin was as bigger as main chamber(主槨) the 4th century A.D., because of centralization and stratification in society and unification of various communities among the Gyeongju area.

• The Journal of Bigdata
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• v.3 no.2
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• pp.87-99
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• 2018

This study analyze the factors affecting the number of bidders in public contracts by collecting contract data such as purchase of goods, service and facility construction through KONEPS among various forms of public contracts. The reason why the number of bidders is important in public contracts is that it can be a minimum criterion for judging whether to enter into a rational contract through fair competition and is closely related to the budget reduction of the ordering organization or the profitability of the bidders. The purpose of this study is to analyze the factors that determine the participation of bidders in public contracts and to present the problems and policy implications of bidders' participation in public contracts. This research distinguishes the existing sampling based research by analyzing and analyzing many contracts such as purchasing, service and facility construction of 4.35 million items in which 50,000 public institutions have been placed as national markets and 300,000 individual companies and corporations participated. As a research model, the number of announcement days, budget amount, contract method and winning bid is used as independent variables and the number of bidders is used as a dependent variable. Big data and multidimensional analysis techniques are used for survey analysis. The conclusions are as follows: First, the larger the budget amount of public works projects, the smaller the number of participants. Second, in the contract method, restricted competition has more participants than general competition. Third, the duration of bidding notice did not significantly affect the number of bidders. Fourth, in the winning bid method, the qualification examination bidding system has more bidders than the lowest bidding system.

• (The)Study of the Eastern Classic
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• no.73
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• pp.153-184
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• 2018

The aim of this thesis was to examine the circumstances that led up to successful coin use across the entire nation in 1678 (the $4^{th}$ year of King Sukjong's reign), during the Joseon Dynasty. To this end, this thesis analysed the Sa-Mouk(事目, Provisions) that contained the institutional protocol for coin circulation, implemented by King Hyojong and the statesman Kim Youk(金堉) who had practical experience in these matters over the ten years of King Hyojong's reign(1649-1659). To regulate the problematic wide circulation of coarse cotton cloth as currency in the market of 1650 (the $1^{st}$ year of King Hyojong's reign), prohibition measures were implemented. Besides the superficial justification given for these measures(i.e., that the market price was disturbed by the use of coarse cotton cloth), there was another purpose to prohibiting the circulation of cotton cloth as money, following the standard ruled by the government: the state aimed to ensure momentum for the upcoming coin circulation policy, by strengthening its control of the current economy. In 1651 (the $2^{nd}$ year of King Hyojong's reign), the government fully cracked down on the use of coarse cotton cloth as currency, and simultaneously implemented its coin circulation policy in the Pyeongan(平安) region. The pretext for this policy was to raise finances to support people who were starving as a result of poor harvests and famine. People who received coins from government officials could purchase food in the market, and the coin circulation policy was judged to be successful. Subsequently, to extend coin circulation further throughout the region, the Sa-Mouk for Seoul was established. The Sa-Mouk included stipulations regarding the use of coin in transactions and for government expenditure; it aimed thereby to enhance the national policy's market credit. The hasty implementation of the policy for the expansion of coin circulation caused some problems that required its modification. In 1652 (the $3^{rd}$ year of King Hyojong's reign), coin circulation was increased to encompass the Gyeonggi(京畿) region, and some of the tax that had been paid in rice was now paid in coin. However, coins were in short supply, since there was insufficient copper, the main material used in coin production, and the policy faced a significant limitation. Therefore, in 1655(the $6^{th}$ year of King Hyojong's reign), a new Sa-Mouk for coin circulation was established. This Sa-Mouk included specifications regarding the determination of coin values based on rice and silver, and mandated the wide spread installation of stores for exchanging spot goods for coins throughout the region in which coins were circulating. This policy's objective was to secure stability for the national economy by further regulating coin circulation. The sustained implementation of the coin circulation policy for ten years by King Hyojong and the statesman Kim Youk offered the government an opportunity to accumulate experience in coin circulation in the market, and also to learn from institutional trial and error. This may have been one of the contributing factors to the nation-wide coin circulation that was established in 1678. The objective of the policy implemented during King Hyojong's reign was not to meet the market's requirements, but rather to ensure the preservation of the national economy, and this misjudgement constituted the policy's key limitation. At this time, the government urgently needed to secure finances to cope with the war against China's Qing Dynasty.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.67-86
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• 2020

Recommender Systems have been huge influence users and business more and more. Recently the importance of E-commerce has been reached rapid growth greatly in world-wide COVID-19 pandemic. Recommender system is the center of E-commerce lively. Top ranked E-commerce managers mentioned that recommender systems have a major influence on customer's purchase such as about 50% of Netflix, Amazon sales from their recommender systems. Most algorithms have been focused on improving accuracy of recommender system regardless of novelty, diversity, serendipity etc. Recommender systems with only high accuracy cannot satisfy business long-term profit because of generating sales polarization. In addition, customers do not experience enjoyment of shopping from only focusing accuracy recommender system because customer's preference is changed constantly. Therefore, recommender systems with various values need to be developed for user's high satisfaction. Reranking is the most useful methodology to realize diversity of recommender system. In this paper, diversity of recommender system is represented through constructing high similarity with users who have different preference using each user's purchased item's category algorithm. It is distinguished from past research approach which is changing the algorithm of recommender system without user's diversity preference level. We tried to discover user's diversity preference level and observed the results how the effect was different according to user's diversity preference level. In addition, graph-based recommender system was used to show diversity through user's network, not collaborative filtering. In this paper, Amazon Grocery and Gourmet Food data was used because the low-involvement product, such as habitual product, foods, low-priced goods etc., had high probability to show customer's diversity. First, a bipartite graph with users and items simultaneously is constructed to make graph-based recommender system. However, each users and items unipartite graph also need to be established to show diversity of recommender system. The weight of each unipartite graph has played crucial role changing Jaccard Distance of item's category. We can observe two important results from the user's unipartite network. First, the user's diversity preference level is observed from the network and second, dissimilar users can be discovered in the user's network. Through the research process, diversity of recommender system is presented highly with small accuracy loss and optimalization for higher accuracy is possible controlling diversity ratio. This paper has three important theoretical points. First, this research expands recommender system research for user's satisfaction with various values. Second, the graph-based recommender system is developed newly. Third, the evaluation indicator of diversity is made for diversity. In addition, recommender systems are useful for corporate profit practically and this paper has contribution on business closely. Above all, business long-term profit can be improved using recommender system with diversity and the recommender system can provide right service according to user's diversity level. Lastly, the corporate selling low-involvement products have great effect based on the results.

• Journal of Intelligence and Information Systems
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• v.27 no.2
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• pp.1-15
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• 2021

If it is difficult for us to make decisions, we ask for advice from friends or people around us. When we decide to buy products online, we read anonymous reviews and buy them. With the advent of the Data-driven era, IT technology's development is spilling out many data from individuals to objects. Companies or individuals have accumulated, processed, and analyzed such a large amount of data that they can now make decisions or execute directly using data that used to depend on experts. Nowadays, the recommender system plays a vital role in determining the user's preferences to purchase goods and uses a recommender system to induce clicks on web services (Facebook, Amazon, Netflix, Youtube). For example, Youtube's recommender system, which is used by 1 billion people worldwide every month, includes videos that users like, "like" and videos they watched. Recommended system research is deeply linked to practical business. Therefore, many researchers are interested in building better solutions. Recommender systems use the information obtained from their users to generate recommendations because the development of the provided recommender systems requires information on items that are likely to be preferred by the user. We began to trust patterns and rules derived from data rather than empirical intuition through the recommender systems. The capacity and development of data have led machine learning to develop deep learning. However, such recommender systems are not all solutions. Proceeding with the recommender systems, there should be no scarcity in all data and a sufficient amount. Also, it requires detailed information about the individual. The recommender systems work correctly when these conditions operate. The recommender systems become a complex problem for both consumers and sellers when the interaction log is insufficient. Because the seller's perspective needs to make recommendations at a personal level to the consumer and receive appropriate recommendations with reliable data from the consumer's perspective. In this paper, to improve the accuracy problem for "appropriate recommendation" to consumers, the recommender systems are proposed in combination with context-based deep learning. This research is to combine user-based data to create hybrid Recommender Systems. The hybrid approach developed is not a collaborative type of Recommender Systems, but a collaborative extension that integrates user data with deep learning. Customer review data were used for the data set. Consumers buy products in online shopping malls and then evaluate product reviews. Rating reviews are based on reviews from buyers who have already purchased, giving users confidence before purchasing the product. However, the recommendation system mainly uses scores or ratings rather than reviews to suggest items purchased by many users. In fact, consumer reviews include product opinions and user sentiment that will be spent on evaluation. By incorporating these parts into the study, this paper aims to improve the recommendation system. This study is an algorithm used when individuals have difficulty in selecting an item. Consumer reviews and record patterns made it possible to rely on recommendations appropriately. The algorithm implements a recommendation system through collaborative filtering. This study's predictive accuracy is measured by Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE). Netflix is strategically using the referral system in its programs through competitions that reduce RMSE every year, making fair use of predictive accuracy. Research on hybrid recommender systems combining the NLP approach for personalization recommender systems, deep learning base, etc. has been increasing. Among NLP studies, sentiment analysis began to take shape in the mid-2000s as user review data increased. Sentiment analysis is a text classification task based on machine learning. The machine learning-based sentiment analysis has a disadvantage in that it is difficult to identify the review's information expression because it is challenging to consider the text's characteristics. In this study, we propose a deep learning recommender system that utilizes BERT's sentiment analysis by minimizing the disadvantages of machine learning. This study offers a deep learning recommender system that uses BERT's sentiment analysis by reducing the disadvantages of machine learning. The comparison model was performed through a recommender system based on Naive-CF(collaborative filtering), SVD(singular value decomposition)-CF, MF(matrix factorization)-CF, BPR-MF(Bayesian personalized ranking matrix factorization)-CF, LSTM, CNN-LSTM, GRU(Gated Recurrent Units). As a result of the experiment, the recommender system based on BERT was the best.

• Journal of the Daesoon Academy of Sciences
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• v.39
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• pp.137-174
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• 2021

The main theme of this paper centers on how to promote Three Major Works of Daesoon Jinrihoe, charity aid, social welfare, and education projects, during the unification period. Determining the best methods of promotion is crucial because the Three Major Works must be carried out after unification, and the works must remain based on the practice of the philosophy of Haewon-sangsaeng (the Resolution of Grievances for Mutual Beneficence). The idea of Haewon-sangsaeng is in line with the preface of the U.N. Charter and the aim of world peace. North Korean residents are suffering from starvation under their devastated economy, which is certain to face a crisis of materialistic deficiency during reunification. In this study, the peaceful unification of Germany, unification under a period of sudden changes in Yemen, and the militarized unification of Vietnam were taken as case studies to diagnose and analyze the conditions which would affect the implementation of the Three Major Works. These three styles of unification commonly required a considerable budget and other forms of support to carry out the Three Major Works. Especially if unification were to occur after a period of sudden changes, this would require solutions to issues of food, shelter, and medical support due to the loss of numerous lives and the destruction of infrastructure. On the other hand, the UNHCR model was analyzed to determine the implications of expanding mental well prepared and sufficiently qualified professionals, reorganizing standard organizations within complex situations, task direction, preparing sufficient relief goods, budgeting, securing bases in border areas with North Korea, and establishing networks for sponsorship. Based on this, eight detailed tasks in the field of system construction could be used by the operators of the Three Major Works to prepare for unification. Additionally, nine tasks for review were presented in consideration of the timing of unification and the current situation between South and North Korea. In conclusion, in the event of unification, the Three Major Works should not be neglected during the transition period. The manual "Three Major Works during the Unification Period" should include strategic points on organizational formation and mission implementation, forward base and base operation, security and logistics preparation, public relations and external cooperation, safety measures, and transportation and contact systems.

• Journal of Intelligence and Information Systems
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• v.27 no.4
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• pp.23-48
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• 2021

The Korean economy has achieved continuous economic growth for the past several decades thanks to the government's export strategy policy. This increase in exports is playing a leading role in driving Korea's economic growth by improving economic efficiency, creating jobs, and promoting technology development. Traditionally, the main factors affecting Korea's exports can be found from two perspectives: economic factors and industrial structural factors. First, economic factors are related to exchange rates and global economic fluctuations. The impact of the exchange rate on Korea's exports depends on the exchange rate level and exchange rate volatility. Global economic fluctuations affect global import demand, which is an absolute factor influencing Korea's exports. Second, industrial structural factors are unique characteristics that occur depending on industries or products, such as slow international division of labor, increased domestic substitution of certain imported goods by China, and changes in overseas production patterns of major export industries. Looking at the most recent studies related to global exchanges, several literatures show the importance of cultural aspects as well as economic and industrial structural factors. Therefore, this study attempted to develop a forecasting model by considering cultural factors along with economic and industrial structural factors in calculating the import volume of each country from Korea. In particular, this study approaches the influence of cultural factors on imports of Korean products from the perspective of PUSH-PULL framework. The PUSH dimension is a perspective that Korea develops and actively promotes its own brand and can be defined as the degree of interest in each country for Korean brands represented by K-POP, K-FOOD, and K-CULTURE. In addition, the PULL dimension is a perspective centered on the cultural and psychological characteristics of the people of each country. This can be defined as how much they are inclined to accept Korean Flow as each country's cultural code represented by the country's governance system, masculinity, risk avoidance, and short-term/long-term orientation. The unique feature of this study is that the proposed final prediction model can be selected based on Design Principles. The design principles we presented are as follows. 1) A model was developed to reflect interest in Korea and cultural characteristics through newly added data sources. 2) It was designed in a practical and convenient way so that the forecast value can be immediately recalled by inputting changes in economic factors, item code and country code. 3) In order to derive theoretically meaningful results, an algorithm was selected that can interpret the relationship between the input and the target variable. This study can suggest meaningful implications from the technical, economic and policy aspects, and is expected to make a meaningful contribution to the export support strategies of small and medium-sized enterprises by using the import forecasting model.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.7
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• pp.1216-1221
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• 2022

Ships tend to be larger to increase the efficiency of cargo transportation. Larger ships lead to increased travel time for ship workers, increased work intensity, and reduced work efficiency. Problems such as increased work intensity are reducing the influx of young people into labor, along with the phenomenon of avoidance of high intensity labor by the younger generation. In addition, the rapid aging of the population and decrease in the young labor force aggravate the labor shortage problem in the maritime industry. To overcome this, the maritime industry has recently introduced technologies such as an intelligent production design platform and a smart production operation management system, and a smart autonomous logistics system in one of these technologies. The smart autonomous logistics system is a technology that delivers various goods using intelligent mobile robots, and enables the robot to drive itself by using sensors such as lidar and camera. Therefore, in this paper, it was checked whether the mobile robot could autonomously drive to the stop sign by detecting the passage way of the ship deck. The autonomous driving was performed by detecting the passage way of the ship deck through the camera mounted on the mobile robot based on the data learned through Nvidia's End-to-end learning. The mobile robot was stopped by checking the stop sign using SSD MobileNetV2. The experiment was repeated five times in which the mobile robot autonomously drives to the stop sign without deviation from the ship deck passage way at a distance of about 70m. As a result of the experiment, it was confirmed that the mobile robot was driven without deviation from passage way. If the smart autonomous logistics system to which this result is applied is used in the marine industry, it is thought that the stability, reduction of labor force, and work efficiency will be improved when workers work.