• International Commerce and Information Review
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• v.10 no.4
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• pp.457-491
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• 2008

As stage equipment export markets along with special lighting service lack the attraction for already globally established businesses, such markets can be viewed as an advantageous opportunity for SMEs as in general. In reality, global businesses tend to focus on large construction projects and this indicates relatively less substantial markets such as stage equipment and special lighting service export are more suitable for SME businesses. However, possible problems may be recognized as following; doubtful capabilities by such businesses to join in the vast and competitive global market and pursue manufacturing and service based export. This point is also supported by the fact that such in general SME businesses have substantially less experience in exporting products and services abroad. Realizing the distinctive features of the Korean economy, it is unarguable that every sector and area of global market must be regarded and monitored closely. Hence, it can be argued that there is an imminent need for establishment of supportive institution to assist export process of combination of stage equipments and special lighting service. This study emphasizes the need to improve export process of stage equipments, special lighting services as well as other related products and services which have been focused in domestic market only until now. Further, it also analyzed the potential prospect of such direction reconciling current crisis our manufacturing industry is facing. Even though it maybe regarded as one of the niche market for export of Korea in the short term view, stage equipment and special lighting service industry may rapidly grow as the global cultural industries have grown along with the increase of national income earnings overall. Due to such advantageous features, it can be expected that such industries will show strong growth in the near future. After analyzing the fact that Korea's plants (eg. powerplants) export sector is at its boom, there is a need to transform stage equipment and special lighting service export market into a primary market from a secondary(niche) market for SMEs. This study is viewed from the Korean economic and export sector aspect in the aim of seeking a solution to conquest our realistic limit in our export sector by developing a suitable export model. There have been cases of very few attempts to expand abroad by SMEs who have failed miserably due to their failure to adapt to foreign culture, practice and languages as well as substantial lack in experience in export marketing. Despite this, neglecting our manufacturing industry as it is which is showing its limit and problems is out of option therefore, it is imminent that we come up with an effective measure to address this problem and service export can be suggested as one of them. This study reveals manufacturing-service export model of stage equipment and special lighting service and its related areas is recognized as a field with a very strong future and furthermore, it is expected to bring synergy effects in manufacturing and services sector as well. Further, the operation strategy contains combination, composition and fusion(convergence) of manufacturing and service sectors which could derive various of export products which displays greater success probability or this export model. The outcome of this research is expected to become a useful source for enterprises related to such industry which are seeking a possible global expansion. Furthermore, it is also expected to become a catalyst which fastens the process of global expansion and not only that, we are firmly assured that this study will become an opportunity to improve our current policies and institutions related to this area's export market.

• Radiation Oncology Journal
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• v.19 no.1
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• pp.66-73
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• 2001

Purpose : For the research of Boron Neutron Capture Therapy (BNCT), fast neutrons generated from the MC-50 cyclotron with maximum energy of 34.4 MeV in Korea Cancer Center Hospital were moderated by 70 cm paraffin and then the dose characteristics were investigated. Using these results, we hope to establish the protocol about dose measurement of epi-thermal neutron, to make a basis of dose characteristic of epi-thermal neutron emitted from nuclear reactor, and to find feasibility about accelerator-based BNCT. Method and Materials : For measuring the absorbed dose and dose distribution of fast neutron beams, we used Unidos 10005 (PTW, Germany) electrometer and IC-17 (Far West, USA), IC-18, ElC-1 ion chambers manufactured by A-150 plastic and used IC-l7M ion chamber manufactured by magnesium for gamma dose. There chambers were flushed with tissue equivalent gas and argon gas and then the flow rate was S co per minute. Using Monte Carlo N-Particle (MCNP) code, transport program in mixed field with neutron, photon, electron, two dimensional dose and energy fluence distribution was calculated and there results were compared with measured results. Results : The absorbed dose of fast neutron beams was $6.47\times10^{-3}$ cGy per 1 MU at the 4 cm depth of the water phantom, which is assumed to be effective depth for BNCT. The magnitude of gamma contamination intermingled with fast neutron beams was $65.2{\pm}0.9\%$ at the same depth. In the dose distribution according to the depth of water, the neutron dose decreased linearly and the gamma dose decreased exponentially as the depth was deepened. The factor expressed energy level, $D_{20}/D_{10}$, of the total dose was 0.718. Conclusion : Through the direct measurement using the two ion chambers, which is made different wall materials, and computer calculation of isodose distribution using MCNP simulation method, we have found the dose characteristics of low fluence fast neutron beams. If the power supply and the target material, which generate high voltage and current, will be developed and gamma contamination was reduced by lead or bismuth, we think, it may be possible to accelerator-based BNCT.

• Radiation Oncology Journal
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• v.16 no.2
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• pp.147-157
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• 1998

Purpose : The aim of this retrospective study is to assess the necessity of s1aging laparotomy in the management of supradiaphragmatic CS I-II Hodgkin's disease. Prognostic factors and the usefulness of prognostic factor groups were also analyzed. Materials and Methods : From 1985 to 1995, fifty one Patients who were diagnosed as supradiaphragmatic CS I-II Hodgkin's disease at Yonsei Cancer Center in Seoul, Korea were enrolled in this study Age range was 4 to 67 with median age of 30. The number of patients with each CS IA, II A, and IIB were 16, 25, and 10, respectively. Radiotherapy(RT) was delivered using 4 or 6 MV photon beam to a total dose of 19.5 to 55.6Gy (median dose : 45Gy) with a 1.5 to 1.BGy per fraction. Chemotherapy(CT) was given in 2-12 cycles(median : 6 cycles). Thirty one Patients were treated with RT alone, 4 patients with CT alone and 16 patients with combined chemoradiotherapy. RT volumes varied from involved fields(3), subtotal nodal fields(18) or mantle fields(26). Results : Five-year disease-free survival rate(DFS) was $78.0\%$ and overall survival rate(05) was $87.6\%$. Fifty Patients achieved a complete remission after initial treatment and 8 patients were relapsed. Salvage therapy was given to 7 patients, 1 with RT alone, 4 with CT alone, 2 with RT+CT. Only two patients were successfully salvaged. Feminine gender and large media-stinal adenopathy were significant adverse prognostic factors in the univariate analysis for DFS. The significant adverse prognostic factors of OS were B symptom and clinical stage. When patients were analyzed according to European Organization for Research and Treatment of Cancer(EORTC) prognostic factor groups, the DFS in Patients with very favorable, favorable and unfavorable group was 100, 100 and $55.8\%$(p<0.05), and the 05 in each patients' group was 100, 100 and $75.1\%$(p<0.05), respectively. In very favorable and favorable groups, the DFS and 05 were all $100\%$ by RT alone, but in unfavorable group, RT with CT had a lesser relapse rate than RT alone. The subtotal nodal irradiation had better OFS than mantle RT in patients treated with RT. Conclusion : In present study, the DFS and OS in patients who did not undergo s1aging laparotomy were similar with the results in the literatures of which patients were surgically staged. Therefore, we may suggest that staging laparotomy would not influence the outcome of treatments. In univariate analysis, gender, large mediastinal adenopathy. B symptoms and clinical stage were significant prognostic factors for the survival rate. We confirm the usefulness of EORTC prognostic factor groups which may be a good.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.38 no.1
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• pp.115-131
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• 2020

Through literature research and field investigation, this paper attempts to study the distribution, morphology and the typification of the visual and perceptual stone inscription in Wuyi-Gugok of China. The results are as follows: First, there are 350 stone inscriptions in total from the 1^st Gok to 9^th Gok in Wuyi-Gugok. Second, according to the analysis of the stone inscription distribution, 74(21.2%) stone inscriptions in the 5^th Gok, 67(19.2%) in the 6^th Gok, 65(18.6%) in the 1^st Gok, 60(17.2%) in the 2^nd Gok and 53(15.2%) in the 4^th Gok are confirmed. The above five Goks contain 319(91.1%) stone inscriptions, so they have rich cultural landscape. Third, according to the survey, the number of the stone inscriptions existed in the Sugwangseok of the 1^st Gok are 41(22.6%), in the Homagan of Cheonyubong of the 6^th Gok are 29(8.3%), in the Jesiam of the 4^th Gok are 23(6.6%), in the Nyeongam of the 2^nd Gok are 22(6.3%), in the Hyangseongam of the 6^th Gok are 21(6%), in the Unwa of the 5^th Gok are 19(5.4%), in the Bokhoam of the 5^th Gok are 18(5.1%), in the Eunbyeongbong of the 5^th Gok are 17(4.9%), in the Daejangbong of the 4^th Gok are 14(4%), in the Daewangbong of the 1^st Gok and the Geumgokam of the 4^th Gok are 12(3.4%). Thus, a total of 228 (65.1%) stone inscriptions are concentrated in these 11 sites, which represent the popularity and cultural value of these rocks. Fourth, the stone inscription of Wuyi-Gugok, praising the landform and topographical geological landscape of Mount Wuyi, mainly describe the scenic name of each Gok related to Zhu Xi's Gugok culture, appreciate Zhu Xi's tracks and the stone inscription in the sacred land of Neo-Confucianism culture, and also record the Confucian edification of mencius thoughts, Muigun(武夷君) and the myths and legends related to the site names of Wuyi mountain, which can remind people of the worldview of the celestial paradise where the gods live and the fairyland of the land of peach blossoms. In addition, it indicates that the historical and cultural landscape, which is full of colorful history and myths and legends, including allusions related to Confucian, buddhist and Taoist celebrities and the ancestor ancient things related to traditional culture of China is very diverse. Fifth, the results of the classification, based on the content of the stone inscription in Wuyi-Gugok, are classified as the scenery name inscription, the praise scene inscription, the recording travel inscription, the recording event inscription, the philosophy inscription, the expressing emotion inscription, the religion inscription, the inscription for auspiciousness, the slogan and expressing ambition inscription and the official document notice inscription, among which there are 102(29.1%) praise scene inscriptions, 93(26.6%) scenery name inscriptions and 61(17.4%) recording travel inscriptions. The stone inscriptions of Wuyi-Gugok have the characteristics of the special emphasis on scenery names, landscape praise and commemorative tours. Sixth, the analysis of the intertext between the 「Figure of Wuyi-Gugok」 and Wuyi-Gugok rock letters, in the study found that the method of propagation between media was mostly the method of propagation of quotations and maintained intermedia through extension, repetition, extension, and compression.

• Journal of Radiation Protection and Research
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• v.39 no.2
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• pp.118-126
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• 2014

A survey was conducted on perceptions, knowledge, and attitudes of elementary, middle, and high school students, who will lead public opinion in the future, regarding irradiated food, nuclear power generation, and medical radiation. These topics urgently require general social acceptability among various fields in which radiation is used. Educational methods to enhance social acceptability were partially discovered. First, it is necessary to implement different strategies when designing courses for female and male students. Male students have higher levels of objective knowledge (p<0.039) of irradiated food, necessity (p<0.001) and objective knowledge (p<0.001) of nuclear power generation, approval of building a nuclear power plant in the nation (p<0.001), necessity (p<0.001) and objective knowledge (p<0.001) of medical radiation, and attitudes regarding using medical radiation (p<0.007, p<0.001). Second, the educational effect of explanations to help increase national understanding of the necessity and safety of nuclear power generation will increase if information on the necessity and safety of medical radiation is provided as well. Both male and female students perceived that medical radiation is the most necessary (p<0.001), medical radiation is the safest (p<0.001), and nuclear power generation is the least safe (p<0.013). Moreover, the correlation between medical radiation and nuclear power generation was the highest. Third, there is a need for different lectures between classes, since the patterns of perception vary according to the field of radiation use among elementary, middle, and high school students. Elementary school students had high interest in education on nuclear power generation (p<0.005), perceived that irradiated food is safe (p<0.001), and had the most positive attitude toward consuming irradiated food (p<0.001). Middle school students had high interest in education on nuclear power generation (p<0.018), perceived that nuclear power generation (p<0.001) and medical radiation (p<0.002) are safe, and had the most positive attitude toward using radiation for treatment (p<0.001). High school students had the highest level of objective knowledge on nuclear power generation (p<0.001) and medical radiation (p<0.001), and perceived that medical radiation is the most necessary (p<0.017); however, they perceived that nuclear power generation is the least safe (p<0.001). Attitudes toward irradiated food intake (p<0.001) and approving construction of a nuclear power plant in their neighborhood (p<0.001) were both low. Fourth, it is necessary to provide educational programs to change perceptions and improve attitudes rather than providing education focused on objective knowledge. There was no correlation between objective knowledge and necessity of irradiated food, objective knowledge and safety and interest in education on nuclear power generation, and objective knowledge and interest in education and information acquirement regarding medical radiation. In particular, high school students had the highest level of objective knowledge and yet had the least positive attitudes toward approving construction of nuclear power plants in their neighborhood and intake of irradiated food. Therefore, to increase the social acceptability of using nuclear energy and radiation in Korea, it is desirable to provide strategic educational programs to improve perceptions, knowledge, and attitudes regarding the necessity and safety of their use.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.79-96
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• 2012

As the pace of competition dramatically accelerates and the complexity of change grows, a variety of research have been conducted to improve firms' short-term performance and to enhance firms' long-term survival. In particular, researchers and practitioners have paid their attention to identify promising technologies that lead competitive advantage to a firm. Discovery of promising technology depends on how a firm evaluates the value of technologies, thus many evaluating methods have been proposed. Experts' opinion based approaches have been widely accepted to predict the value of technologies. Whereas this approach provides in-depth analysis and ensures validity of analysis results, it is usually cost-and time-ineffective and is limited to qualitative evaluation. Considerable studies attempt to forecast the value of technology by using patent information to overcome the limitation of experts' opinion based approach. Patent based technology evaluation has served as a valuable assessment approach of the technological forecasting because it contains a full and practical description of technology with uniform structure. Furthermore, it provides information that is not divulged in any other sources. Although patent information based approach has contributed to our understanding of prediction of promising technologies, it has some limitations because prediction has been made based on the past patent information, and the interpretations of patent analyses are not consistent. In order to fill this gap, this study proposes a technology forecasting methodology by integrating patent information approach and artificial intelligence method. The methodology consists of three modules : evaluation of technologies promising, implementation of technologies value prediction model, and recommendation of promising technologies. In the first module, technologies promising is evaluated from three different and complementary dimensions; impact, fusion, and diffusion perspectives. The impact of technologies refers to their influence on future technologies development and improvement, and is also clearly associated with their monetary value. The fusion of technologies denotes the extent to which a technology fuses different technologies, and represents the breadth of search underlying the technology. The fusion of technologies can be calculated based on technology or patent, thus this study measures two types of fusion index; fusion index per technology and fusion index per patent. Finally, the diffusion of technologies denotes their degree of applicability across scientific and technological fields. In the same vein, diffusion index per technology and diffusion index per patent are considered respectively. In the second module, technologies value prediction model is implemented using artificial intelligence method. This studies use the values of five indexes (i.e., impact index, fusion index per technology, fusion index per patent, diffusion index per technology and diffusion index per patent) at different time (e.g., t-n, t-n-1, t-n-2, ${\cdots}$) as input variables. The out variables are values of five indexes at time t, which is used for learning. The learning method adopted in this study is backpropagation algorithm. In the third module, this study recommends final promising technologies based on analytic hierarchy process. AHP provides relative importance of each index, leading to final promising index for technology. Applicability of the proposed methodology is tested by using U.S. patents in international patent class G06F (i.e., electronic digital data processing) from 2000 to 2008. The results show that mean absolute error value for prediction produced by the proposed methodology is lower than the value produced by multiple regression analysis in cases of fusion indexes. However, mean absolute error value of the proposed methodology is slightly higher than the value of multiple regression analysis. These unexpected results may be explained, in part, by small number of patents. Since this study only uses patent data in class G06F, number of sample patent data is relatively small, leading to incomplete learning to satisfy complex artificial intelligence structure. In addition, fusion index per technology and impact index are found to be important criteria to predict promising technology. This study attempts to extend the existing knowledge by proposing a new methodology for prediction technology value by integrating patent information analysis and artificial intelligence network. It helps managers who want to technology develop planning and policy maker who want to implement technology policy by providing quantitative prediction methodology. In addition, this study could help other researchers by proving a deeper understanding of the complex technological forecasting field.

• Journal of Intelligence and Information Systems
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• v.19 no.4
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• pp.21-37
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• 2013

Recently, as the advent of the knowledge-based society, there are more people getting interested in the intellectual property. Especially, the ICT companies leading the high-tech industry are working hard to strive for systematic management of intellectual property. As we know, the patent information represents the intellectual capital of the company. Also now the quantitative analysis on the continuously accumulated patent information becomes possible. The analysis at various levels becomes also possible by utilizing the patent information, ranging from the patent level to the enterprise level, industrial level and country level. Through the patent information, we can identify the technology status and analyze the impact of the performance. We are also able to find out the flow of the knowledge through the network analysis. By that, we can not only identify the changes in technology, but also predict the direction of the future research. In the field using the network analysis there are two important analyses which utilize the patent citation information; citation indicator analysis utilizing the frequency of the citation and network analysis based on the citation relationships. Furthermore, this study analyzes whether there are any impacts between the size of the company and patent citation relationships. 74 S&P 500 registered companies that provide IT and communication services are selected for this study. In order to determine the relationship of patent citation between the companies, the patent citation in 2009 and 2010 is collected and sociomatrices which show the patent citation relationship between the companies are created. In addition, the companies' total assets are collected as an index of company size. The distance between companies is defined as the absolute value of the difference between the total assets. And simple differences are considered to be described as the hierarchy of the company. The QAP Correlation analysis and MR-QAP analysis is carried out by using the distance and hierarchy between companies, and also the sociomatrices that shows the patent citation in 2009 and 2010. Through the result of QAP Correlation analysis, the patent citation relationship between companies in the 2009's company's patent citation network and the 2010's company's patent citation network shows the highest correlation. In addition, positive correlation is shown in the patent citation relationships between companies and the distance between companies. This is because the patent citation relationship is increased when there is a difference of size between companies. Not only that, negative correlation is found through the analysis using the patent citation relationship between companies and the hierarchy between companies. Relatively it is indicated that there is a high evaluation about the patent of the higher tier companies influenced toward the lower tier companies. MR-QAP analysis is carried out as follow. The sociomatrix that is generated by using the year 2010 patent citation relationship is used as the dependent variable. Additionally the 2009's company's patent citation network and the distance and hierarchy networks between the companies are used as the independent variables. This study performed MR-QAP analysis to find the main factors influencing the patent citation relationship between the companies in 2010. The analysis results show that all independent variables have positively influenced the 2010's patent citation relationship between the companies. In particular, the 2009's patent citation relationship between the companies has the most significant impact on the 2010's, which means that there is consecutiveness regarding the patent citation relationships. Through the result of QAP correlation analysis and MR-QAP analysis, the patent citation relationship between companies is affected by the size of the companies. But the most significant impact is the patent citation relationships that had been done in the past. The reason why we need to maintain the patent citation relationship between companies is it might be important in the use of strategic aspect of the companies to look into relationships to share intellectual property between each other, also seen as an important auxiliary of the partner companies to cooperate with.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.35 no.2
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• pp.91-101
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• 2009

in the cosmetics and medical supply field as a antioxidant material. The stable nano particle emulsion of skin toner type containing VEA was prepared. To evaluate the skin permeation, experiments on VEA permeation to the skin of the ICR outbred albino mice (12 weeks, about 50 g, female) and on differences of solubility as a function of receptor formulations was performed. The analysis of nano-emulsions containing VEA 0.07 % showed that the higher ethanol contents the larger emulsions were formed, while the higher surfactant contents the size became smaller.In this study, vitamin E acetate (VEA, tocopheryl acetate), a lipid-soluble vitamin which is widely used A certain contents of ethanol in receptor phase increased VEA solubility on the nano-emulsion. When the ethanol contents were 10.0 % and 20.0 %, the VEA solubility was higher than 5.0 % and 40.0 %, respectively. The type of surfactant in receptor solution influenced to VEA solubility. The comparison between three kind surfactants whose chemical structures and HLB values are different, showed that solubility of VEA was increased as order of sorbitan sesquioleate (Arlacel 83; HLB 3.7) > POE (10) hydrogenated castor oil (HCO-10; HLB 6.5) > sorbitan monostearate (Arlacel 60; HLB 4.7). VEA solubility was also shown to be different according to the type of antioxidant. In early time, the solubility of the sample including ascorbic acid was similar to those of other samples including other types of antioxidants. However, the solubility of the sample including ascorbic acid was 2 times higher than others after 24 h. Franz diffusion cell experiment using mouse skin was performed with four nano-emulsion samples which have different VEA contents. The emulsion of 10 wt% ethanol was shown to be the most permeable at the amount of 128.8 ${\mu}g/cm^2$. When the result of 10 % ethanol content was compared with initial input of 220.057 ${\mu}g/cm^2$, the permeated amount was 58.53 % and the permeated amount at 10 % ethanol was higher 45.0 % and 15.0 % than the other results which ethanol contents were 1.0 and 20.0 wt%, respectively. Emulsion particle size used 0.5 % surfactant (HCO-60) was 26.0 nm that is one twentieth time smaller than the size of 0.007 % surfactant (HCO-60) at the same ethanol content. Transepidermal permeation of VEA was 54.848 ${\mu}g/cm^2$ which is smaller than that of particlesize 590.7 nm. Skin permeation of nano-emulsion containing VEA and difference of VEA solubility as a function of receptor phase formulation were determined from the results. Using these results, optimal conditions of transepidermal permeation with VEA were considered to be set up.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.141-156
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• 2013

Social media is a representative form of the Web 2.0 that shapes the change of a user's information behavior by allowing users to produce their own contents without any expert skills. In particular, as a new communication medium, it has a profound impact on the social change by enabling users to communicate with the masses and acquaintances their opinions and thoughts. Social media data plays a significant role in an emerging Big Data arena. A variety of research areas such as social network analysis, opinion mining, and so on, therefore, have paid attention to discover meaningful information from vast amounts of data buried in social media. Social media has recently become main foci to the field of Information Retrieval and Text Mining because not only it produces massive unstructured textual data in real-time but also it serves as an influential channel for opinion leading. But most of the previous studies have adopted broad-brush and limited approaches. These approaches have made it difficult to find and analyze new information. To overcome these limitations, we developed a real-time Twitter trend mining system to capture the trend in real-time processing big stream datasets of Twitter. The system offers the functions of term co-occurrence retrieval, visualization of Twitter users by query, similarity calculation between two users, topic modeling to keep track of changes of topical trend, and mention-based user network analysis. In addition, we conducted a case study on the 2012 Korean presidential election. We collected 1,737,969 tweets which contain candidates' name and election on Twitter in Korea (http://www.twitter.com/) for one month in 2012 (October 1 to October 31). The case study shows that the system provides useful information and detects the trend of society effectively. The system also retrieves the list of terms co-occurred by given query terms. We compare the results of term co-occurrence retrieval by giving influential candidates' name, 'Geun Hae Park', 'Jae In Moon', and 'Chul Su Ahn' as query terms. General terms which are related to presidential election such as 'Presidential Election', 'Proclamation in Support', Public opinion poll' appear frequently. Also the results show specific terms that differentiate each candidate's feature such as 'Park Jung Hee' and 'Yuk Young Su' from the query 'Guen Hae Park', 'a single candidacy agreement' and 'Time of voting extension' from the query 'Jae In Moon' and 'a single candidacy agreement' and 'down contract' from the query 'Chul Su Ahn'. Our system not only extracts 10 topics along with related terms but also shows topics' dynamic changes over time by employing the multinomial Latent Dirichlet Allocation technique. Each topic can show one of two types of patterns-Rising tendency and Falling tendencydepending on the change of the probability distribution. To determine the relationship between topic trends in Twitter and social issues in the real world, we compare topic trends with related news articles. We are able to identify that Twitter can track the issue faster than the other media, newspapers. The user network in Twitter is different from those of other social media because of distinctive characteristics of making relationships in Twitter. Twitter users can make their relationships by exchanging mentions. We visualize and analyze mention based networks of 136,754 users. We put three candidates' name as query terms-Geun Hae Park', 'Jae In Moon', and 'Chul Su Ahn'. The results show that Twitter users mention all candidates' name regardless of their political tendencies. This case study discloses that Twitter could be an effective tool to detect and predict dynamic changes of social issues, and mention-based user networks could show different aspects of user behavior as a unique network that is uniquely found in Twitter.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.69-94
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• 2017

Recently, increase of demand for big data analysis has been driving the vigorous development of related technologies and tools. In addition, development of IT and increased penetration rate of smart devices are producing a large amount of data. According to this phenomenon, data analysis technology is rapidly becoming popular. Also, attempts to acquire insights through data analysis have been continuously increasing. It means that the big data analysis will be more important in various industries for the foreseeable future. Big data analysis is generally performed by a small number of experts and delivered to each demander of analysis. However, increase of interest about big data analysis arouses activation of computer programming education and development of many programs for data analysis. Accordingly, the entry barriers of big data analysis are gradually lowering and data analysis technology being spread out. As the result, big data analysis is expected to be performed by demanders of analysis themselves. Along with this, interest about various unstructured data is continually increasing. Especially, a lot of attention is focused on using text data. Emergence of new platforms and techniques using the web bring about mass production of text data and active attempt to analyze text data. Furthermore, result of text analysis has been utilized in various fields. Text mining is a concept that embraces various theories and techniques for text analysis. Many text mining techniques are utilized in this field for various research purposes, topic modeling is one of the most widely used and studied. Topic modeling is a technique that extracts the major issues from a lot of documents, identifies the documents that correspond to each issue and provides identified documents as a cluster. It is evaluated as a very useful technique in that reflect the semantic elements of the document. Traditional topic modeling is based on the distribution of key terms across the entire document. Thus, it is essential to analyze the entire document at once to identify topic of each document. This condition causes a long time in analysis process when topic modeling is applied to a lot of documents. In addition, it has a scalability problem that is an exponential increase in the processing time with the increase of analysis objects. This problem is particularly noticeable when the documents are distributed across multiple systems or regions. To overcome these problems, divide and conquer approach can be applied to topic modeling. It means dividing a large number of documents into sub-units and deriving topics through repetition of topic modeling to each unit. This method can be used for topic modeling on a large number of documents with limited system resources, and can improve processing speed of topic modeling. It also can significantly reduce analysis time and cost through ability to analyze documents in each location or place without combining analysis object documents. However, despite many advantages, this method has two major problems. First, the relationship between local topics derived from each unit and global topics derived from entire document is unclear. It means that in each document, local topics can be identified, but global topics cannot be identified. Second, a method for measuring the accuracy of the proposed methodology should be established. That is to say, assuming that global topic is ideal answer, the difference in a local topic on a global topic needs to be measured. By those difficulties, the study in this method is not performed sufficiently, compare with other studies dealing with topic modeling. In this paper, we propose a topic modeling approach to solve the above two problems. First of all, we divide the entire document cluster(Global set) into sub-clusters(Local set), and generate the reduced entire document cluster(RGS, Reduced global set) that consist of delegated documents extracted from each local set. We try to solve the first problem by mapping RGS topics and local topics. Along with this, we verify the accuracy of the proposed methodology by detecting documents, whether to be discerned as the same topic at result of global and local set. Using 24,000 news articles, we conduct experiments to evaluate practical applicability of the proposed methodology. In addition, through additional experiment, we confirmed that the proposed methodology can provide similar results to the entire topic modeling. We also proposed a reasonable method for comparing the result of both methods.