• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.1
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• pp.28-36
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• 2023

Solar radiation that is measured at relatively small number of weather stations is one of key inputs to crop models for estimation of crop productivity. Solar radiation products derived from GK-2A and Himawari 8 satellite data have become available, which would allow for preparation of input data to crop models, especially for assessment of crop productivity under an agrivoltaic system where crop and power can be produced at the same time. The objective of this study was to compare the degree of agreement between the solar radiation products obtained from those satellite data. The sub hourly products for solar radiation were collected to prepare their daily summary for the period from May to October in 2020 during which both satellite products for solar radiation were available. Root mean square error (RMSE) and its normalized error (NRMSE) were determined for daily sum of solar radiation. The cumulative values of solar radiation for the study period were also compared to represent the impact of the errors for those products on crop growth simulations. It was found that the data product from the Himawari 8 satellite tended to have smaller values of RMSE and NRMSE than that from the GK-2A satellite. The Himawari 8 satellite product had smaller errors at a large number of weather stations when the cumulative solar radiation was compared with the measurements. This suggests that the use of Himawari 8 satellite products would cause less uncertainty than that of GK2-A products for estimation of crop yield. This merits further studies to apply the Himawari 8 satellites to estimation of solar power generation as well as crop yield under an agrivoltaic system.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.2
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• pp.1-11
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• 2023

This study intended to develop a technique for quantitatively and 3-dimensionally predicting the potential failure zone and impulse that may occur when trees are fall down. The main outcomes of this study are as follows. First, this study established the potential failure zone and impulse calculation formula in order to quantitatively calculate the risks generated when trees are fallen down. When estimating the potential failure zone, the calculation was performed by magnifying the height of trees by 1.5 times, reflecting the likelihood of trees falling down and slipping. With regard to the slope of a tree, the range of 360° centered on the root collar was set in the case of trees that grow upright and the range of 180° from the inclined direction was set in the case of trees that grow inclined. The angular momentum was calculated by reflecting the rotational motion from the root collar when the trees fell down, and the impulse was calculated by converting it into the linear momentum. Second, the program to calculate a potential failure zone and impulse was developed using Rhino3D and Grasshopper. This study created the 3-dimensional models of the shapes for topography, buildings, and trees using the Rhino3D, thereby connecting them to Grasshopper to construct the spatial information. The algorithm was programmed using the calculation formula in the stage of risk calculation. This calculation considered the information on the trees' growth such as the height, inclination, and weight of trees and the surrounding environment including adjacent trees, damage targets, and analysis ranges. In the stage of risk inquiry, the calculation results were visualized into a three-dimensional model by summarizing them. For instance, the risk degrees were classified into various colors to efficiently determine the dangerous trees and dangerous areas.

• Knowledge Management Research
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• v.23 no.4
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• pp.315-338
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• 2022

In 1986, Korea established legal systems to support small and medium-sized start-ups, which becomes the main pillars of national development. The legal systems have stimulated start-up ecosystems to have more than 1 million new start-up companies founded every year during the past 30 years. To analyze the trend of Korea's start-up ecosystem, in this study, we collected 1.18 million news articles from 1991 to 2020. Then, we extracted news articles that have the keywords "start-up", "venture", and "start-up". We employed network analysis and topic modeling to analyze collected news articles. Our analysis can contribute to analyzing the government policy direction shown in the history of start-up support policy. Specifically, our analysis identifies the dynamic characteristics of government influenced by external environmental factors (e.g., society, economy, and culture). The results of our analysis suggest that the start-up ecosystems in Korea have changed and developed mainly by the government policies for corporation governance, industrial development planning, deregulation, and economic prosperity plan. Our frequency keyword analysis contributes to understanding entrepreneurial productivity attributed to activities among the networked components in industrial ecosystems. Our analyses and results provide practitioners and researchers with practical and academic implications that can help to establish dedicated support policies through forecast tasks of the economic environment surrounding the start-ups. Korean entrepreneurial productivity has been empowered by growing numbers of large companies in the mobile phone industry. The spectrum of large companies incorporates content startups, platform providers, online shopping malls, and youth-oriented start-ups. In addition, economic situational factors contribute to the growth of Korean entrepreneurial productivity the economic, which are related to the global expansions of the mobile industry, and government efforts to foster start-ups. Our research is methodologically implicative. We employ natural language processes for 30 years of media articles, which enables more rigorous analysis compared to the existing studies which only observe changes in government and policy based on a qualitative manner.

• Korea Science and Art Forum
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• v.20
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• pp.455-464
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• 2015

As the recognition toward the Korean design education development to nurture creative talents for the future society has been expanded recently, various supports and promoting strategies are being suggested. This study suggests the orientalism-based new design education platform in design education field to nurture creative talents. To have the competitiveness of creative talent nurturing, the system and education programs to rear creative talents are required. The purpose of this study is to suggest the new platform for the change of direction in design education and search for the methods in detail. The research process can be described as following: First, this study stated about the research background and its boundary. Based on the literature review and the condition of the crisis of Korean design education (Korean Industrial Statistic Investigation), it described the current condition and the characteristics. Second, this study stated about the education which will be disappeared in the information society, the change of direction in design education, and the new platform. In the current study, the change toward the strategies that give priority to the growth strategies on the knowledge-based industry was stated. Third, this study stated about that the future design education should be centered on the orientalism-based creativity in the trend changing to the six conditions for the future talents and the beliefs and values toward Asia, and what methods should be sought to achieve this trend. It suggested focusing on the aim for the direction for College education and its program curriculums as the solutions in detail. Fourth, based on the contents stated earlier in this study, it stated synthetically the direction of practice through the network of the design cluster and derived the implications. In conclusion, based on the recent orientalism-based mind, this study suggested the ways to find the identity of Korean design education itself and have the competitiveness in design education programs. The ways to secure them is to come from the integrated system innovation of the network. By actively applying the design clusters, colleges and universities, designers, studios, government policy organizations, design institutes, corporates, media, and fairs, this study suggests the sustainable education system and the practical methods.

• Journal of the Korean Society of International Agriculture
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• v.31 no.3
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• pp.249-254
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• 2019

'Japonica 6' is a japonica rice variety developed from a cross between 'MS11', the beginning variety adaptable to tropical region, and 'IR86743-28-1-4', an elite line of high yield and good plant type by a Korea(RDA)-IRRI cooperative breeding program at IRRI in 2017. The growth duration of 'Japonica 6' is 121 days from sowing to harvest. It is 10 days later than that of the check variety 'MS11'. The culm length of 'Japonica 6' is 70 cm, and 1,000-brown rice grain weight is 26.7 g. It has a shorter culm and a larger grain. size than that of MS11. 'Japonica 6' is moderately resistant to blast disease but susceptible to bacterial blight, tungro virus and plant hoppers. The milled rice recovery rate of 'Japonica 6' is improved than that of 'MS11'. The head rice rate of 'Japonica 6' is significantly higher than that of 'MS11'. Yield of 'Japonica 6' is averagely 3.59 MT/ha of milled rice in 5 areas of the Philippines. The 'Japonica 6' was registered in Philippines and would be adaptable to the diverse regions of tropical Asia (Registration No in Philippines. BPI-NSIC-2017-Rc 484SR).

• Journal of Korea Entertainment Industry Association
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• v.13 no.2
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• pp.27-36
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• 2019

Today, the Korean wave headed by K-pop is newly named as 'New Korean Wave' in that it has been extended to United States, Europe and Russia. K-POP, the main player of the new Korean wave, has been successful in SNS marketing channels. Furthermore, the content of K-pop has attracted the attention of the global audience. The media and public attention on the Korean Wave is meaningful because it is not merely a cultural export. It also makes Korean people feel national pride, seeing the mental influence of its culture on other regions. Moreover, the development of the cultural industry in our society, which is different from industrial or material development, is a proof that Korean society is at the center of globalization. Until the 20th century, Korean culture had been rather receptive than dominant. In other words, it was focused more on acceptance of other cultures than active creation or outflow of its own. Now, however, K-POP is not anymore copying Western culture. It is creating its own unique characters, which makes K-pop very competitive. Korean culture has been formed for a long time in Korea's unique historical background. Korean popular culture also has to establish a solid foothold in world markets through its distinctive and traditional feature. The positive consumer response to Korean pop culture will create the added value of Korean contents and their derivatives, which will heighten Korea's national image also. In other words, if traditional art and K-POP are converged and equipped with our own unique and highly artistic culture, they will take the lead in the global cultural art market. In this study, we will recognize the possibility, growth and development of K-pop culture and analyze the cases of combining K-pop and Korean traditional art. First, we have to blend traditional art and other various genres to create diverse contents, and we have to actively utilize media channels. Second, we must improve people's awareness of the copyrights of traditional art. Also, we have to mitigate the copyrights of creative dance to expand the disclosure of contents which can be utilized. Third, we have to learn about traditional arts from younger age. Fourth, we will expand traditional arts to the whole of Korean cultural policies, which can enhance the nation's cultural value and create economic benefits. These four are expected to be effective ways to preserve the identity of traditional art and at the same time, globalize Korean culture.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.42 no.3
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• pp.13-26
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• 2024

This study examines the historical and cultural landscape of Qingguo Lane (靑果巷) in Changzhou, Jiangsu Province, China, focusing on the relationship between the changes in the landscape and the local residents from the Ming Dynasty to the present. By analyzing ancient maps, literature, and field photographs, the research reveals that the residents played a crucial role in the transformation of the Qingguo Lane landscape. The findings can be summarized as follows: Firstly, the naming of Qingguo Lane. 1) The name "Qingguo Lane" first appeared in the Changzhoufu and was mistakenly understood as a place for selling fruits. In reality, it was a residential area, and the name originated from descriptions of the plant landscape in poetry. 2) Qingguo Lane served as a residential area for the upper-class, including the prominent Bi-Ling Tang and Dong families, from the Ming Dynasty through the Qing Dynasty. Secondly, changes in administrative divisions and road development. 1) During the Ming Dynasty, Qingguo Lane spanned three administrative regions: Zhongwushang, Xiwushang, and Dongwushang, later narrowing to Xiwushang and Dongwushang during the Qing Dynasty. 2) The main road of Qingguo Lane with nine alleys running north to south, forming the historical and cultural preservation area of Qingguo Lane. Over time, the number of roads increased, and the area transitioned into a residential and commercial space, shaping the modern Qingguo Lane. Thirdly, the formation of the cultural landscape of the upper-class in Qingguo Lane. 1) The development of Qingguo Lane was influenced by population movements and growth during the peaceful period following the Yuan Dynasty massacres. The importance of the natural landscape attracted literati to settle there, and Qingguo Lane became a new residential area for the Changzhou upper-class as commerce and culture flourished. 2) From the late Ming Dynasty, Qingguo Lane gained social and cultural prominence through the garden culture of the upper-class. 3) The concentration of upper-class residents attracted many scholars and merchants, leading to the construction of numerous gardens. The literati of the Ming and Qing Dynasties helped shape the unique cultural landscape of Qingguo Lane, and in modern times, it has developed into a protected historical and cultural area with diverse functions as a multifunctional complex.

• Journal of Bio-Environment Control
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• v.32 no.4
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• pp.416-422
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• 2023

This study was aimed to determine the changes in CO₂ concentration according to the temperatures of daytime and nighttime in the CO₂ supplemental greenhouse, and to compare calculated supplementary CO₂ concentration during winter and spring cultivation seasons. CO₂ concentrations in experimental greenhouses were analyzed by selecting representative days with different average temperatures due to differences in integrated solar radiation at the growth stage of leaf area index (LAI) 2.0 during the winter season of 2022 and 2023 years. The CO₂ concentration was 459, 299, 275, and 239 µmol·mol^-1, respectively at 1, 2, 3, and 4 p.m. after the CO₂ supplementary time (10:00-13:00) under the higher temperature (HT, > 18℃ daytime temp. avg. 31.7, 26.8, 23.8, and 22.4℃, respectively), while it was 500, 368, 366, 364 µmol·mol^-1, respectively under the lower temperature (LT, < 18℃ daytime temp. avg. 22.0, 18.9, 15.0, and 13.7℃, respectively), indicating the CO₂ reduction was significantly higher in the HT than that of LT. During the nighttime, the concentration of CO₂ gradually increased from 6 p.m. (346 µmol·mol^-1) to 3 a.m. (454 µmol·mol^-1) in the HT with a rate of 11 µmol·mol^-1 per hour (240 tomatoes, leaf area 330m²), while the increase was very lesser under the LT. During the spring season, the CO₂ concentration measured just before the start of CO₂ fertilization (7:30 a.m.) in the CO₂ enrichment greenhouse was 3-4 times higher in the HT (>15℃ nighttime temperature avg.) than that of LT (< 15℃ nighttime temperature avg.), and the calculated amount of CO₂ fertilization on the day was also lower in HT. All the integrated results indicate that CO₂ concentrations during the nighttime varies depending on the temperature, and the increased CO₂ is a major source of CO₂ for photosynthesis after sunrise, and it is necessary to develop a model formula for CO₂ supplement considering the nighttime CO₂ concentration.

• Korean small business review
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• v.31 no.4
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• pp.67-93
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• 2009

The purpose of this paper is to explore the relations between financial constraints and dividend smoothing of innovative small and medium sized enterprises(SMEs) listed on Korea Securities Market and Kosdaq Market of Korea Exchange. The innovative SMEs is defined as the firms with high level of R&D intensity which is measured by (R&D investment/total sales) ratio, according to Chauvin and Hirschey (1993). The R&D investment plays an important role as the innovative driver that can increase the future growth opportunity and profitability of the firms. Therefore, the R&D investment have large, positive, and consistent influences on the market value of the firm. In this point of view, we expect that the innovative SMEs can adjust dividend payment faster than the noninnovative SMEs, on the ground of their future growth opportunity and profitability. And also, we expect that the financial unconstrained firms can adjust dividend payment faster than the financial constrained firms, on the ground of their financing ability of investment funds through the market accessibility. Aivazian et al.(2006) exert that the financial unconstrained firms with the high accessibility to capital market can adjust dividend payment faster than the financial constrained firms. We collect the sample firms among the total SMEs listed on Korea Securities Market and Kosdaq Market of Korea Exchange during the periods from January 1999 to December 2007 from the KIS Value Library database. The total number of firm-year observations of the total sample firms throughout the entire period is 5,544, the number of firm-year observations of the dividend firms is 2,919, and the number of firm-year observations of the non-dividend firms is 2,625. About 53%(or 2,919) of these total 5,544 observations involve firms that make a dividend payment. The dividend firms are divided into two groups according to the R&D intensity, such as the innovative SMEs with larger than median of R&D intensity and the noninnovative SMEs with smaller than median of R&D intensity. The number of firm-year observations of the innovative SMEs is 1,506, and the number of firm-year observations of the noninnovative SMEs is 1,413. Furthermore, the innovative SMEs are divided into two groups according to level of financial constraints, such as the financial unconstrained firms and the financial constrained firms. The number of firm-year observations of the former is 894, and the number of firm-year observations of the latter is 612. Although all available firm-year observations of the dividend firms are collected, deletions are made in the case of financial industries such as banks, securities company, insurance company, and other financial services company, because their capital structure and business style are widely different from the general manufacturing firms. The stock repurchase was involved in dividend payment because Grullon and Michaely (2002) examined the substitution hypothesis between dividends and stock repurchases. However, our data structure is an unbalanced panel data since there is no requirement that the firm-year observations data are all available for each firms during the entire periods from January 1999 to December 2007 from the KIS Value Library database. We firstly estimate the classic Lintner(1956) dividend adjustment model, where the decision to smooth dividend or to adopt a residual dividend policy depends on financial constraints measured by market accessibility. Lintner model indicates that firms maintain stable and long run target payout ratio, and that firms adjust partially the gap between current payout rato and target payout ratio each year. In the Lintner model, dependent variable is the current dividend per share(DPS_t), and independent variables are the past dividend per share(DPS_t-1) and the current earnings per share(EPS_t). We hypothesized that firms adjust partially the gap between the current dividend per share(DPS_t) and the target payout ratio(Ω) each year, when the past dividend per share(DPS_t-1) deviate from the target payout ratio(Ω). We secondly estimate the expansion model that extend the Lintner model by including the determinants suggested by the major theories of dividend, namely, residual dividend theory, dividend signaling theory, agency theory, catering theory, and transactions cost theory. In the expansion model, dependent variable is the current dividend per share(DPS_t), explanatory variables are the past dividend per share(DPS_t-1) and the current earnings per share(EPS_t), and control variables are the current capital expenditure ratio(CEA_t), the current leverage ratio(LEV_t), the current operating return on assets(ROA_t), the current business risk(RISK_t), the current trading volume turnover ratio(TURN_t), and the current dividend premium(DPREM_t). In these control variables, CEA_t, LEV_t, and ROA_t are the determinants suggested by the residual dividend theory and the agency theory, ROA_t and RISK_t are the determinants suggested by the dividend signaling theory, TURN_t is the determinant suggested by the transactions cost theory, and DPREM_t is the determinant suggested by the catering theory. Furthermore, we thirdly estimate the Lintner model and the expansion model by using the panel data of the financial unconstrained firms and the financial constrained firms, that are divided into two groups according to level of financial constraints. We expect that the financial unconstrained firms can adjust dividend payment faster than the financial constrained firms, because the former can finance more easily the investment funds through the market accessibility than the latter. We analyzed descriptive statistics such as mean, standard deviation, and median to delete the outliers from the panel data, conducted one way analysis of variance to check up the industry-specfic effects, and conducted difference test of firms characteristic variables between innovative SMEs and noninnovative SMEs as well as difference test of firms characteristic variables between financial unconstrained firms and financial constrained firms. We also conducted the correlation analysis and the variance inflation factors analysis to detect any multicollinearity among the independent variables. Both of the correlation coefficients and the variance inflation factors are roughly low to the extent that may be ignored the multicollinearity among the independent variables. Furthermore, we estimate both of the Lintner model and the expansion model using the panel regression analysis. We firstly test the time-specific effects and the firm-specific effects may be involved in our panel data through the Lagrange multiplier test that was proposed by Breusch and Pagan(1980), and secondly conduct Hausman test to prove that fixed effect model is fitter with our panel data than the random effect model. The main results of this study can be summarized as follows. The determinants suggested by the major theories of dividend, namely, residual dividend theory, dividend signaling theory, agency theory, catering theory, and transactions cost theory explain significantly the dividend policy of the innovative SMEs. Lintner model indicates that firms maintain stable and long run target payout ratio, and that firms adjust partially the gap between the current payout ratio and the target payout ratio each year. In the core variables of Lintner model, the past dividend per share has more effects to dividend smoothing than the current earnings per share. These results suggest that the innovative SMEs maintain stable and long run dividend policy which sustains the past dividend per share level without corporate special reasons. The main results show that dividend adjustment speed of the innovative SMEs is faster than that of the noninnovative SMEs. This means that the innovative SMEs with high level of R&D intensity can adjust dividend payment faster than the noninnovative SMEs, on the ground of their future growth opportunity and profitability. The other main results show that dividend adjustment speed of the financial unconstrained SMEs is faster than that of the financial constrained SMEs. This means that the financial unconstrained firms with high accessibility to capital market can adjust dividend payment faster than the financial constrained firms, on the ground of their financing ability of investment funds through the market accessibility. Futhermore, the other additional results show that dividend adjustment speed of the innovative SMEs classified by the Small and Medium Business Administration is faster than that of the unclassified SMEs. They are linked with various financial policies and services such as credit guaranteed service, policy fund for SMEs, venture investment fund, insurance program, and so on. In conclusion, the past dividend per share and the current earnings per share suggested by the Lintner model explain mainly dividend adjustment speed of the innovative SMEs, and also the financial constraints explain partially. Therefore, if managers can properly understand of the relations between financial constraints and dividend smoothing of innovative SMEs, they can maintain stable and long run dividend policy of the innovative SMEs through dividend smoothing. These are encouraging results for Korea government, that is, the Small and Medium Business Administration as it has implemented many policies to commit to the innovative SMEs. This paper may have a few limitations because it may be only early study about the relations between financial constraints and dividend smoothing of the innovative SMEs. Specifically, this paper may not adequately capture all of the subtle features of the innovative SMEs and the financial unconstrained SMEs. Therefore, we think that it is necessary to expand sample firms and control variables, and use more elaborate analysis methods in the future studies.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.1-21
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• 2020

With the rapid development of artificial intelligence technology, various techniques have been developed to extract meaningful information from unstructured text data which constitutes a large portion of big data. Over the past decades, text mining technologies have been utilized in various industries for practical applications. In the field of business intelligence, it has been employed to discover new market and/or technology opportunities and support rational decision making of business participants. The market information such as market size, market growth rate, and market share is essential for setting companies' business strategies. There has been a continuous demand in various fields for specific product level-market information. However, the information has been generally provided at industry level or broad categories based on classification standards, making it difficult to obtain specific and proper information. In this regard, we propose a new methodology that can estimate the market sizes of product groups at more detailed levels than that of previously offered. We applied Word2Vec algorithm, a neural network based semantic word embedding model, to enable automatic market size estimation from individual companies' product information in a bottom-up manner. The overall process is as follows: First, the data related to product information is collected, refined, and restructured into suitable form for applying Word2Vec model. Next, the preprocessed data is embedded into vector space by Word2Vec and then the product groups are derived by extracting similar products names based on cosine similarity calculation. Finally, the sales data on the extracted products is summated to estimate the market size of the product groups. As an experimental data, text data of product names from Statistics Korea's microdata (345,103 cases) were mapped in multidimensional vector space by Word2Vec training. We performed parameters optimization for training and then applied vector dimension of 300 and window size of 15 as optimized parameters for further experiments. We employed index words of Korean Standard Industry Classification (KSIC) as a product name dataset to more efficiently cluster product groups. The product names which are similar to KSIC indexes were extracted based on cosine similarity. The market size of extracted products as one product category was calculated from individual companies' sales data. The market sizes of 11,654 specific product lines were automatically estimated by the proposed model. For the performance verification, the results were compared with actual market size of some items. The Pearson's correlation coefficient was 0.513. Our approach has several advantages differing from the previous studies. First, text mining and machine learning techniques were applied for the first time on market size estimation, overcoming the limitations of traditional sampling based- or multiple assumption required-methods. In addition, the level of market category can be easily and efficiently adjusted according to the purpose of information use by changing cosine similarity threshold. Furthermore, it has a high potential of practical applications since it can resolve unmet needs for detailed market size information in public and private sectors. Specifically, it can be utilized in technology evaluation and technology commercialization support program conducted by governmental institutions, as well as business strategies consulting and market analysis report publishing by private firms. The limitation of our study is that the presented model needs to be improved in terms of accuracy and reliability. The semantic-based word embedding module can be advanced by giving a proper order in the preprocessed dataset or by combining another algorithm such as Jaccard similarity with Word2Vec. Also, the methods of product group clustering can be changed to other types of unsupervised machine learning algorithm. Our group is currently working on subsequent studies and we expect that it can further improve the performance of the conceptually proposed basic model in this study.