• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.4
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• pp.1123-1146
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• 2023

In South Korea, there have been many studies on efficient building-energy management using renewable energy facilities in single zero-energy houses or buildings. However, such management was limited due to spatial and economic problems. To realize a smart zero-energy city, studying efficient energy integration for the entire city, not just for a single house or building, is necessary. Therefore, this study was conducted in the eco-friendly energy town of Chungbuk Innovation City. Chungbuk successfully realized energy independence by converging new and renewable energy facilities for the first time in South Korea. This study analyzes energy data collected from public buildings in that town every minute for a year. We propose a smart city building-energy management model based on the results that combine various renewable energy sources with grid power. Supervised learning can determine when it is best to sell surplus electricity, or unsupervised learning can be used if there is a particular pattern or rule for energy use. However, it is more appropriate to use reinforcement learning to maximize rewards in an environment with numerous variables that change every moment. Therefore, we propose a power distribution algorithm based on reinforcement learning that considers the sales of Energy Storage System power from surplus renewable energy. Finally, we confirm through economic analysis that a 10% saving is possible from this efficiency.

• The Journal of the Korea Contents Association
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• v.19 no.5
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• pp.48-63
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• 2019

We tried new analysis including social network analysis(SNA) on the transaction network centered on electronic companies using more than 50 thousand company transaction data obtained from Korean enterprise data (KED) for the year of 2015. We found 97 clusters having more than 10 firms and remarkable 13 clusters having more than 90% sales of the electronic industry in Korea. Clusters are the groups of companies having most of their transactions in the clusters they belong to. We found 5 clusters have 83% of sales in the electronic industry. Most of clusters have main single firms having most of the sales in each clusters except a few clusters. However, we found a few firms to have high rear production linkage effect and found the firms with high linkage effect specially for the small and medium size enterprise (SME). The companies with high production linkage (specially on SMEs) should be managed in terms of (SME) growth policy. The last firm group consisting of the small clusters with less than 10 firms has high employment coefficients. The clusters or company having high production linkage effect on this last firm group should be noted in the terms of employment policy. We also note that there exist the firms with the high value of betweenness coefficients meaning high potential of technology development. They should be managed carefully in terms of technology development policy.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.4
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• pp.173-178
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• 2023

As Korean literature spreads around the world, its position in the overseas publishing market has become important. As demand in the overseas publishing market continues to grow, it is essential to predict future book sales and analyze the characteristics of books that have been highly favored by overseas readers in the past. In this study, we proposed ensemble learning based prediction model and analyzed characteristics of the cumulative sales of more than 5,000 copies classified as good sellers published overseas over the past 5 years. We applied the five ensemble learning models, i.e., XGBoost, Gradient Boosting, Adaboost, LightGBM, and Random Forest, and compared them with other machine learning algorithms, i.e., Support Vector Machine, Logistic Regression, and Deep Learning. Our experimental results showed that the ensemble algorithm outperforms other approaches in troubleshooting imbalanced data. In particular, the LightGBM model obtained an AUC value of 99.86% which is the best prediction performance. Among the features used for prediction, the most important feature is the author's number of overseas publications, and the second important feature is publication in countries with the largest publication market size. The number of evaluation participants is also an important feature. In addition, text mining was performed on the four book reviews that sold the most among good-selling books. Many reviews were interested in stories, characters, and writers and it seems that support for translation is needed as many of the keywords of "translation" appear in low-rated reviews.

• Spatial Information Research
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• v.21 no.6
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• pp.69-80
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• 2013

Our country has made every efforts to develop Real Estate Transaction culture with emphasis on Licensed Realtors by introducing Real Estate Transaction Law in 1983. Also, MOLIT(Ministry of Land, Infrastructure and Transport) designated several organizations including KAR(Korea Association of Realtors) as Real Estate Transaction Information Network Licensees for data credibility enhancement and transaction transparency. Nevertheless, the level of law abiding spirit and transaction culture are still similar to those of the old 'Bokdeokbang' era. The under-developed transaction behaviors prevent the social capital of people's credibility on Licensed Realtors from advancing, and results in the outcomes of unnecessary social cost. That is, very low credibility on the data on Sales Items in the market and the fear of speculative real estate price uprise and market distortions are continuing on. In this context, the purpose of this study is to propose the model of GIS-based Modernized Real Estate Transaction System and its execution policies to support credible Real Estate Information to the general public for efficient transactions in the market. Accordingly, the study aims at contributing to the modernization of Real Estate Transactions, fostering competitiveness of Realtors in the Real Estate Market.

• The Journal of the Korea Contents Association
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• v.19 no.7
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• pp.360-375
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• 2019

This paper tries to study the ecosystem after constructing the network of the continuing transactions associated with distribution industry with the data of more than 50 thousands firms provided by the Korean enterprise data (KED) for 2015. After applying the clustering method, one of social network analysis tools, we find the firms in the network grouped into 732 clusters occupying about 80% of whole distribution industry sales in KED data. The firms in a cluster have most of their transactions with other firms in the cluster. But the clusters have smaller firm numbers in the cluster and sales portion of the biggest firms in the industry than the case of the manufacturing industry. The Input-output analysis for the biggest distribution firms show that the small and medium size enterprise(SME)s have very high sale dependency on a main firm in some clusters. This fact implies more efficient fair transaction policies within the clusters. And small number of big distribution firms have very high rear production linkage effects on SMEs or on the 10th or 31th group with high portion of SME employment. They should be considered important in the SME growth and employment policies.

• The Journal of Society for e-Business Studies
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• v.26 no.4
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• pp.81-93
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• 2021

Through processors, wholesale markets, intermediate sellers, and retailers, agricultural products have been distributed in a multi-level customary manner for a long time as they are easy to deteriorate and no not have a standardized system of size and quality. However, with the advancement of Internet networks and logistic services during the 2000s that facilitated the development of offline markets, and the rise of the non-contact purchase preference in direct response to COVID-19, previous offline consumers flowed into the online market to purchase agricultural goods. In other words, the volume of online agricultural transactions exploded since the pandemic. Against this social backdrop, this study focused on the difference in distribution costs as a result of converting from conventional offline distribution channels to online channels, and analyzed the reduced distribution costs through a case study of garlic sales on the online platform "H" shopping mall. The analysis found that considerable economic effects occurred, some of the effects being an approximate 39% decrease in distribution cost when comparing direct online transactions of the online shopping mall with other more traditional means, a reduced distribution cost rate of approximately 28%p, and increased profit for farmers.

• Asia pacific journal of information systems
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• v.18 no.2
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• pp.95-114
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• 2008

Recent interests in data mining result from the expansion of the amount of business data and the growing business needs for extracting valuable knowledge from the data and then utilizing it for decision making process. In particular, recent advances in association rule mining techniques enable us to acquire knowledge concerning sales patterns among individual items from the voluminous transactional data. Certainly, one of the major purposes of association rule mining is to utilize acquired knowledge in providing marketing strategies such as cross-selling, sales promotion, and shelf-space allocation. In spite of the potential applicability of association rule mining, unfortunately, it is not often the case that the marketing mix acquired from data mining leads to the realized profit. The main difficulty of mining-based profit realization can be found in the fact that tremendous numbers of patterns are discovered by the association rule mining. Due to the many patterns, data mining experts should perform additional mining of the results of initial mining in order to extract only actionable and profitable knowledge, which exhausts much time and costs. In the literature, a number of interestingness measures have been devised for estimating discovered patterns. Most of the measures can be directly calculated from what is known as a contingency table, which summarizes the sales frequencies of exclusive items or itemsets. A contingency table can provide brief insights into the relationship between two or more itemsets of concern. However, it is important to note that some useful information concerning sales transactions may be lost when a contingency table is constructed. For instance, information regarding the size of each market basket(i.e., the number of items in each transaction) cannot be described in a contingency table. It is natural that a larger basket has a tendency to consist of more sales patterns. Therefore, if two itemsets are sold together in a very large basket, it can be expected that the basket contains two or more patterns and that the two itemsets belong to mutually different patterns. Therefore, we should classify frequent itemset into two categories, inter-pattern co-occurrence and intra-pattern co-occurrence, and investigate the effect of the market basket size on the two categories. This notion implies that any interestingness measures for association rules should consider not only the total frequency of target itemsets but also the size of each basket. There have been many attempts on analyzing various interestingness measures in the literature. Most of them have conducted qualitative comparison among various measures. The studies proposed desirable properties of interestingness measures and then surveyed how many properties are obeyed by each measure. However, relatively few attentions have been made on evaluating how well the patterns discovered by each measure are regarded to be valuable in the real world. In this paper, attempts are made to propose two notions regarding association rule measures. First, a quantitative criterion for estimating accuracy of association rule measures is presented. According to this criterion, a measure can be considered to be accurate if it assigns high scores to meaningful patterns that actually exist and low scores to arbitrary patterns that co-occur by coincidence. Next, complementary measures are presented to improve the accuracy of traditional association rule measures. By adopting the factor of market basket size, the devised measures attempt to discriminate the co-occurrence of itemsets in a small basket from another co-occurrence in a large basket. Intensive computer simulations under various workloads were performed in order to analyze the accuracy of various interestingness measures including traditional measures and the proposed measures.

• Journal of Korea Technology Innovation Society
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• v.19 no.2
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• pp.254-279
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• 2016

Recently, with the conversion towards knowledge-based economy era, the importance of the evaluation for patent valuation has been growing rapidly because technology transactions are increasing with the purpose of practically utilizing R&D outcomes such as technology commercialization and technology transfer. Nevertheless, there is a lack of research on determinants of patent valuation by analyzing technology transactions due to the difficulty of collecting data in practice. Hence, to suggest quantitative determinants for the patent valuation which could be applied to scoring methods, 15 patent valuation models domestically and overseas are analysed in order to assure the objectiveness for subjective results from qualitative methods such as expert surveys, comparison assessment, etc. Through this analysis, the important 6 common determinants are drawn and patent information is matched which can be used as proxy variables of individual determinant factors by advanced researches. In addition, to validate whether the model proposed has a statistically meaningful effect, total 517 technology transactions are collected from both public and private technology transaction offices and analysed by multiple regression analysis, which led to significant patent determinant factors in deciding its value. As a result, it is herein presented that patent connectivity(number of literature cited) and commercialization stage in market influence significantly on patent valuation. The meaning of this study is in that it suggests the significant quantitative determinants of patent valuation based on the technology transactions data in practice, and if research results by industry are systematically verified through seamless collection of transaction data and their monitoring, we would propose the customized patent valuation model by industry which is applicable for both strategic planning of patent registration and achievement assessment of research projects (with representative patents).

• Journal of Information Technology Applications and Management
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• v.19 no.2
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• pp.79-96
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• 2012

Thanks to the growth of information technology (IT), e-commerce transactions are rapidly developing. Consumers searched and purchased for products and services through e-commerce transactions and felt excitement and satisfaction through shopping behaviors in online shopping malls. The enlargement of company's marketing efforts and consumer tastes of the uncontrolled consumption for goods and services increased the impulsive purchase in online shopping malls. In diffusing consumers' e-impulse buying, consumers increased in expenditures according to unnecessary purchasing behavior in online shopping malls. However, enterprises increased sales and benefits due to consumers' impulse buying in online shopping malls. Accordingly, in research areas of enterprises and consumers levels, the studies of e-impulse buying will provide significant values for marketers of companies. In this study, we analyzed the relationships among intention to use, trust, and value in online shopping malls. And we also analyzed the moderating effect of e-impulse buying with utilitarian and hedonic value to establish trust in online shopping malls. The result of this study showed that hedonic and utilitarian value should have a positive impact trust and trust should have a positive impact intention to use in the online shopping malls. The e-impulsive buying showed a moderating effect on the relationship between hedonic value and trust in online shopping malls. The e-impulsive buying didn't show, however, a moderating effect on the between utilitarian value and trust in online shopping malls. The results of this study will provide valuable implications for implementing e-commerce strategies.

• Journal of Arbitration Studies
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• v.26 no.1
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• pp.89-105
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• 2016

2008 began with the American financial crisis which gave way to the liquidity crisis (Fannie Mae and Freddie Mac) situation in which 'the withdrawal of investment initiated from the insufficiency of the U.S. subprime mortgage loan companies', 'the large size loss situation of the financial company (Bear Stearns) due to the American structured bond insufficiency' and the second half opening part national debt mortgage company. Within the American financial crisis was propagated the crisis of international derivatives. Due to this, the withdrawal of foreign investment progressed in the interior of a country with the considerable. By the end of 2007, the exchange rate fluctuation was absorbed in the domestic financial circle on the belief the potentiality of the domestic financial market had been growing drastically through the expansion of the foreign currency debt according to this and it came to the defence but while the exchange rate jumped up to the dollar shortage according to the international crisis, the small and medium companies making the banks and exchange rate-related derivatives contract were going bankrupt due to the derivatives loss. The small and medium factories establish the bank exchange rate-related derivatives has nose (KIKO), pivot (PIVOT), and snowball (Snowball) etc. at that time and the damage which it is the KIKO grasped at 6 end of the months in 2008 caused by reaches to 1 thousand billion 4 thousand hundred million dollars. Small and medium companies in which the dollar which it has to denounce among small and medium companies bearing the KIKO contract in fact with the Knock-In generation city bank exceeds the amount of sales were known to be 68 enterprises among 480 enterprises. This paper departs in this awareness of a problem and tries to look into the risk factor of the derivatives, including nose and study the essential ring risk management plan of small and medium manufacturer.