• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.123-139
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• 2019

The job classification system of major job sites differs from site to site and is different from the job classification system of the 'SQF(Sectoral Qualifications Framework)' proposed by the SW field. Therefore, a new job classification system is needed for SW companies, SW job seekers, and job sites to understand. The purpose of this study is to establish a standard job classification system that reflects market demand by analyzing SQF based on job offer information of major job sites and the NCS(National Competency Standards). For this purpose, the association analysis between occupations of major job sites is conducted and the association rule between SQF and occupation is conducted to derive the association rule between occupations. Using this association rule, we proposed an intelligent job classification system based on data mapping the job classification system of major job sites and SQF and job classification system. First, major job sites are selected to obtain information on the job classification system of the SW market. Then We identify ways to collect job information from each site and collect data through open API. Focusing on the relationship between the data, filtering only the job information posted on each job site at the same time, other job information is deleted. Next, we will map the job classification system between job sites using the association rules derived from the association analysis. We will complete the mapping between these market segments, discuss with the experts, further map the SQF, and finally propose a new job classification system. As a result, more than 30,000 job listings were collected in XML format using open API in 'WORKNET,' 'JOBKOREA,' and 'saramin', which are the main job sites in Korea. After filtering out about 900 job postings simultaneously posted on multiple job sites, 800 association rules were derived by applying the Apriori algorithm, which is a frequent pattern mining. Based on 800 related rules, the job classification system of WORKNET, JOBKOREA, and saramin and the SQF job classification system were mapped and classified into 1st and 4th stages. In the new job taxonomy, the first primary class, IT consulting, computer system, network, and security related job system, consisted of three secondary classifications, five tertiary classifications, and five fourth classifications. The second primary classification, the database and the job system related to system operation, consisted of three secondary classifications, three tertiary classifications, and four fourth classifications. The third primary category, Web Planning, Web Programming, Web Design, and Game, was composed of four secondary classifications, nine tertiary classifications, and two fourth classifications. The last primary classification, job systems related to ICT management, computer and communication engineering technology, consisted of three secondary classifications and six tertiary classifications. In particular, the new job classification system has a relatively flexible stage of classification, unlike other existing classification systems. WORKNET divides jobs into third categories, JOBKOREA divides jobs into second categories, and the subdivided jobs into keywords. saramin divided the job into the second classification, and the subdivided the job into keyword form. The newly proposed standard job classification system accepts some keyword-based jobs, and treats some product names as jobs. In the classification system, not only are jobs suspended in the second classification, but there are also jobs that are subdivided into the fourth classification. This reflected the idea that not all jobs could be broken down into the same steps. We also proposed a combination of rules and experts' opinions from market data collected and conducted associative analysis. Therefore, the newly proposed job classification system can be regarded as a data-based intelligent job classification system that reflects the market demand, unlike the existing job classification system. This study is meaningful in that it suggests a new job classification system that reflects market demand by attempting mapping between occupations based on data through the association analysis between occupations rather than intuition of some experts. However, this study has a limitation in that it cannot fully reflect the market demand that changes over time because the data collection point is temporary. As market demands change over time, including seasonal factors and major corporate public recruitment timings, continuous data monitoring and repeated experiments are needed to achieve more accurate matching. The results of this study can be used to suggest the direction of improvement of SQF in the SW industry in the future, and it is expected to be transferred to other industries with the experience of success in the SW industry.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.1-25
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• 2020

In this paper, we suggest an application system architecture which provides accurate, fast and efficient automatic gasometer reading function. The system captures gasometer image using mobile device camera, transmits the image to a cloud server on top of private LTE network, and analyzes the image to extract character information of device ID and gas usage amount by selective optical character recognition based on deep learning technology. In general, there are many types of character in an image and optical character recognition technology extracts all character information in an image. But some applications need to ignore non-of-interest types of character and only have to focus on some specific types of characters. For an example of the application, automatic gasometer reading system only need to extract device ID and gas usage amount character information from gasometer images to send bill to users. Non-of-interest character strings, such as device type, manufacturer, manufacturing date, specification and etc., are not valuable information to the application. Thus, the application have to analyze point of interest region and specific types of characters to extract valuable information only. We adopted CNN (Convolutional Neural Network) based object detection and CRNN (Convolutional Recurrent Neural Network) technology for selective optical character recognition which only analyze point of interest region for selective character information extraction. We build up 3 neural networks for the application system. The first is a convolutional neural network which detects point of interest region of gas usage amount and device ID information character strings, the second is another convolutional neural network which transforms spatial information of point of interest region to spatial sequential feature vectors, and the third is bi-directional long short term memory network which converts spatial sequential information to character strings using time-series analysis mapping from feature vectors to character strings. In this research, point of interest character strings are device ID and gas usage amount. Device ID consists of 12 arabic character strings and gas usage amount consists of 4 ~ 5 arabic character strings. All system components are implemented in Amazon Web Service Cloud with Intel Zeon E5-2686 v4 CPU and NVidia TESLA V100 GPU. The system architecture adopts master-lave processing structure for efficient and fast parallel processing coping with about 700,000 requests per day. Mobile device captures gasometer image and transmits to master process in AWS cloud. Master process runs on Intel Zeon CPU and pushes reading request from mobile device to an input queue with FIFO (First In First Out) structure. Slave process consists of 3 types of deep neural networks which conduct character recognition process and runs on NVidia GPU module. Slave process is always polling the input queue to get recognition request. If there are some requests from master process in the input queue, slave process converts the image in the input queue to device ID character string, gas usage amount character string and position information of the strings, returns the information to output queue, and switch to idle mode to poll the input queue. Master process gets final information form the output queue and delivers the information to the mobile device. We used total 27,120 gasometer images for training, validation and testing of 3 types of deep neural network. 22,985 images were used for training and validation, 4,135 images were used for testing. We randomly splitted 22,985 images with 8:2 ratio for training and validation respectively for each training epoch. 4,135 test image were categorized into 5 types (Normal, noise, reflex, scale and slant). Normal data is clean image data, noise means image with noise signal, relfex means image with light reflection in gasometer region, scale means images with small object size due to long-distance capturing and slant means images which is not horizontally flat. Final character string recognition accuracies for device ID and gas usage amount of normal data are 0.960 and 0.864 respectively.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.30 no.1
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• pp.14-21
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• 2012

The object of the study, Yousang-Dae(流觴臺) and engraved Go broad text on the flat rock in Gangneung-si Yungok-myun Yoodung-ri Baemgol, reveals that the place was for appreciating arts like Yusang Goksu and Taoist hermit's games. three times of detail reconnaissance survey brought about the results as follows. There is a the text, Manwolsan(滿月山) Baegundongcheon(白雲洞天), engraved on the rock in Baegunsa(白雲寺) that had been built by Doun at the first year of King Hungang(in 875) of the United Shilla, became in ruins in the middle of Joseon, and then was rebuilt in 1954. The text is an invaluable evidence indicating that the tradition of Taoist hermit and Sunbee(classical scholars) culture has been generated in Baemgol Valley. According to the 2nd vol. of Donghoseungram(東湖勝覽), the chronicle of Gangneung published by Choi Baeksoon in 1934, there is a record saying that 'Baegunsa in Namjeonhyeon is the classroom where famous teachers like Yulgok Lee Yi or Seongje Choi Ok were teaching' that verifies the historic property of the place. In addition, the management of Nujeong(樓亭) and Dongcheon can be traced through Baegunjeong(白雲亭) constructed by Kim Yoonkyung(金潤卿) in Muo year, the 9th year of Cheoljong(1858) according to Donghoseungram and the completed version of Jeungboyimyoungji(增補臨瀛誌). Also, Baegundongdongcheon(白雲亭洞天), the text engraved on the standing stone across the stream from Yousang-Dae stone, was created 3 years after the Baegunjeong construction in the 12th year of Cheoljong(1861), which refers a symbolic sign closely related with Yousang-Dae. Based on this premise and circumstance, with careful studying the remains of 'Yusang-dae' Goksuro, we discovered that the Sebun-seok(細分石) controling the amount and the speed of moving water and the remains of furrows of Keumbae-soek(擒盃石) and Yubae-gong(留盃孔) containing water stream with cups through the mountain stream and rocks around Yusang-Dae. In addition, as 21 people's names engraved under the statement of 'Oh-Seong(午星)' were discovered on the bottom of the rock, this clearly confirms that the place was one of the main cultural footholds of tasting the arts which have characteristics of Yu-Sang-Gok-Su-Yeon(流觴曲水宴) until the middle of the 20th century. It implies that the arts tasting culture of Sunbees had been inherited centering on Yusang-dae in this particular place until the middle of the 20th century. It is necessary to be studied in depth because the place is a historic and unique cultural place where 'Confucianism, Buddhism, and Zen'were combined together. Based on the result of the study, the identification of 23 people as well as the writer of Yusang-Dae text should be carefully studied in depth in terms of the characteristics of the place through gathering data about appreciation of arts like Yusanggoksu. Likewise, we should make efforts to discover the chess board engraved on the rock described on the documents, thus we should consider to establish plans to recover the original shape of the place, for example, breaking the cement pavement of the road, additional excavation, changing the existing route, and so fourth.

• Asia pacific journal of information systems
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• v.20 no.1
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• pp.141-170
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• 2010

User created content (UCC) is created and shared by common users on line. From the user's perspective, the increase of UCCs has led to an expansion of alternative means of communications, while from the business perspective UCCs have formed an environment in which an abundant amount of new contents can be produced. Despite outward quantitative growth, however, many aspects of UCCs do not meet the expectations of general users in terms of quality, and this can be observed through pirated contents and user-copied contents. The purpose of this research is to investigate effective methods for fostering production of creative user-generated content. This study proposes two core elements, namely, reward and motivation, which are believed to enhance content creativity as well as the mediating factor and users' committement, which will be effective for bridging the increasing motivation and content creativity. Based on this perspective, this research takes an in-depth look at issues related to constructing the dimensions of reward and motivation in UCC services for creative content product, which are identified in three phases. First, three dimensions of rewards have been proposed: task dimension, social dimension, and organizational dimention. The task dimension rewards are related to the inherent characteristics of a task such as writing blog articles and pasting photos. Four concrete ways of providing task-related rewards in UCC environments are suggested in this study, which include skill variety, task significance, task identity, and autonomy. The social dimensioni rewards are related to the connected relationships among users. The organizational dimension consists of monetary payoff and recognition from others. Second, the two types of motivations are suggested to be affected by the diverse rewards schemes: intrinsic motivation and extrinsic motivation. Intrinsic motivation occurs when people create new UCC contents for its' own sake, whereas extrinsic motivation occurs when people create new contents for other purposes such as fame and money. Third, commitments are suggested to work as important mediating variables between motivation and content creativity. We believe commitments are especially important in online environments because they have been found to exert stronger impacts on the Internet users than other relevant factors do. Two types of commitments are suggested in this study: emotional commitment and continuity commitment. Finally, content creativity is proposed as the final dependent variable in this study. We provide a systematic method to measure the creativity of UCC content based on the prior studies in creativity measurement. The method includes expert evaluation of blog pages posted by the Internet users. In order to test the theoretical model of our study, 133 active blog users were recruited to participate in a group discussion as well as a survey. They were asked to fill out a questionnaire on their commitment, motivation and rewards of creating UCC contents. At the same time, their creativity was measured by independent experts using Torrance Tests of Creative Thinking. Finally, two independent users visited the study participants' blog pages and evaluated their content creativity using the Creative Products Semantic Scale. All the data were compiled and analyzed through structural equation modeling. We first conducted a confirmatory factor analysis to validate the measurement model of our research. It was found that measures used in our study satisfied the requirement of reliability, convergent validity as well as discriminant validity. Given the fact that our measurement model is valid and reliable, we proceeded to conduct a structural model analysis. The results indicated that all the variables in our model had higher than necessary explanatory powers in terms of R-square values. The study results identified several important reward shemes. First of all, skill variety, task importance, task identity, and automony were all found to have significant influences on the intrinsic motivation of creating UCC contents. Also, the relationship with other users was found to have strong influences upon both intrinsic and extrinsic motivation. Finally, the opportunity to get recognition for their UCC work was found to have a significant impact on the extrinsic motivation of UCC users. However, different from our expectation, monetary compensation was found not to have a significant impact on the extrinsic motivation. It was also found that commitment was an important mediating factor in UCC environment between motivation and content creativity. A more fully mediating model was found to have the highest explanation power compared to no-mediation or partially mediated models. This paper ends with implications of the study results. First, from the theoretical perspective this study proposes and empirically validates the commitment as an important mediating factor between motivation and content creativity. This result reflects the characteristics of online environment in which the UCC creation activities occur voluntarily. Second, from the practical perspective this study proposes several concrete reward factors that are germane to the UCC environment, and their effectiveness to the content creativity is estimated. In addition to the quantitive results of relative importance of the reward factrs, this study also proposes concrete ways to provide the rewards in the UCC environment based on the FGI data that are collected after our participants finish asnwering survey questions. Finally, from the methodological perspective, this study suggests and implements a way to measure the UCC content creativity independently from the content generators' creativity, which can be used later by future research on UCC creativity. In sum, this study proposes and validates important reward features and their relations to the motivation, commitment, and the content creativity in UCC environment, which is believed to be one of the most important factors for the success of UCC and Web 2.0. As such, this study can provide significant theoretical as well as practical bases for fostering creativity in UCC contents.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.37 no.2
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• pp.74-88
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• 2019

This study developed the Assessment Indicator evaluating eco-cultural value of temple forest in Korea and applied the developed Assessment Indicator to Songgwang-sa(also known as Seungbo-sachal), one of the Three Jewels Temple. Literature reviews and the draft of Assessment Indicator were drawn from brainstorming(including 2 forest therapy experts, 1 Buddhist monk expert, 1 landscape architect, 1 forest expert, and 6 researchers). After that, the Assessment Indicator drawn from the group of experts(the 1st in-depth interview: 32 people, the 2nd in-depth interview: 30 people) was verified and revised. The final Assessment Indicator, which was composed of 4 parts and 20 items, was developed. The results are as follows. The eco-cultural Assessment Indicator of temple forest was composed of 4 parts, which were Historical Cultural value, Ecological value, Recreatory Visitational value, and Educational Useful value, and 20 items and each item had 5 points. Historical Cultural value had 5 items and its total points were 25. Ecological value had 5 items and had total 25 points. Recreatory Visitational value had 6 items, 30 total points. Educational Useful value had 4 items, 20 total points. The total points of the eco-cultural Assessment Indicator were 100 points. As a result of applying the developed Assessment Indicator to the target place, Songgwang-sa in Mt. Jogye, Historical Cultural value of temple forest was calculated as 23 points(out of 25). Ecological value was 21 point(out of 25), Recreatory Visitational value, 22 points(out of 30), and Educational Useful value, 16 points(out of 20). The total points were 82(out of 100). Consequently, this study is meaningful based on the following 5 aspects. Firstly, this study challenged the development of the eco-cultural Assessment Indicator of temple forest for the first time. It is significant because the developed Assessment Indicator can be a useful resource for the eco-cultural value of temple forest. Secondly, the result showed that Educational Useful value and Recreatory Visitational value of forest temple were very low. Therefore, the supports for leisure, tour, education, and use of temple forest are needed from Korea Forest Service, Ministry of Environment, Cultural Heritage Administration and other government agencies since they acknowledge the temple forest as the best customers in Korea. Thirdly, the excellence or for eco-cultural value of temple forest needs to be extended in a national level. It is possible to make a Korean National Bran(e.g., the Therapy at the Temple) by blending temple stay, which is only in temples, and therapy, and is also possible to be a global tour industry. Fourthly, this study suggested legal definition about the necessary of legal definition for temple forest because there is no legal definition on temple forest in the current situation. When the definition of temple forest is legally arranaged, it would be a foundation for conserving eco-cultural value of temple forest, for organizing exclusively responsible departments in governmental institutions, and further for registering temple forest as World Natural Heritage. Lastly, the developed eco-cultural Assessment Indicators of temple forest from this study would be applied to "the 7 Sansa, Buddhist Mountain Monasteries in Korea(Sansa)" and the characteristics of each 7 temple are drawn. This study would be a basic data for temples' management and use with the eco-cultural Assessment Indicator of temple forest.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.4
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• pp.50-63
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• 2018

The rapid urbanization had led to a distortion of natural hydrological cycle system. The change in hydrological cycle structure is causing streamflow depletion, changing the existing use tendency of water resources. To manage such phenomena, a streamflow depletion impact assessment technology to forecast depletion is required. For performing such technology, it is indispensable to build GIS-based spatial data as fundamental data, but there is a shortage of related research. Therefore, this study was conducted to use the use of GIS-based time series spatial data for streamflow depletion assessment. For this study, GIS data over decades of changes on a national scale were constructed, targeting 6 streamflow depletion impact factors (weather, soil depth, forest density, road network, groundwater usage and landuse) and the data were used as the basic data for the operation of continuous hydrologic model. Focusing on these impact factors, the causes for streamflow depletion were analyzed depending on time series. Then, using distributed continuous hydrologic model based DrySAT, annual runoff of each streamflow depletion impact factor was measured and depletion assessment was conducted. As a result, the default value of annual runoff was measured at 977.9mm under the given weather condition without considering other factors. When considering the decrease in soil depth, the increase in forest density, road development, and groundwater usage, along with the change in land use and development, and annual runoff were measured at 1,003.5mm, 942.1mm, 961.9mm, 915.5mm, and 1003.7mm, respectively. The results showed that the major causes of the streaflow depletion were lowered soil depth to decrease the infiltration volume and surface runoff thereby decreasing streamflow; the increased forest density to decrease surface runoff; the increased road network to decrease the sub-surface flow; the increased groundwater use from undiscriminated development to decrease the baseflow; increased impervious areas to increase surface runoff. Also, each standard watershed depending on the grade of depletion was indicated, based on the definition of streamflow depletion and the range of grade. Considering the weather, the decrease in soil depth, the increase in forest density, road development, and groundwater usage, and the change in land use and development, the grade of depletion were 2.1, 2.2, 2.5, 2.3, 2.8, 2.2, respectively. Among the five streamflow depletion impact factors except rainfall condition, the change in groundwater usage showed the biggest influence on depletion, followed by the change in forest density, road construction, land use, and soil depth. In conclusion, it is anticipated that a national streamflow depletion assessment system to be develop in the future would provide customized depletion management and prevention plans based on the system assessment results regarding future data changes of the six streamflow depletion impact factors and the prospect of depletion progress.

• Korean Journal of Heritage: History & Science
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• v.42 no.2
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• pp.62-85
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• 2009

The Nam-Hae Sin-sa, the South Sea shrine in Yeong-Am, Korea was a national institution for public peace and bliss, was excavated in 2000, and the shrine and the 3-way-gate were reconstructed in 2001. Hae Sin-sa, the Sea shrine is a place for religious service separated into the Nam-Hae Sin-sa, the Dong-Hae Myo, and the Seo-Hae Dan. The Dong-Hae Myo was reconstructed, but restored shrine and 3-way-gate of the Nam-Hae Sin-sa is not perfect in comparison with excavation plan in 2000, therefore new reconstruction was researched through the related literature, the analysis of historical maps and excavation results, the interview with the concerned people and the case study. This research defines the analysis of the Plan of the Nam-Hae Sin-sa Reconstruction as follows. 1. The Nam-Hae Sin-sa was the institution for religious service operated by national direct management, represents the shrine for public peace and bliss on the Mountain, the Sea, and the River. Especially the Nam-Hae Sin-sa had an important position on the pivot of international trade with China and Japan, and had a role of main shrine with another one in the Mt. Ji-ri San. 2. The name of the Sea shrine was called as Nam-Hae Sin-sa(the South Sea shrine), Dong-Hae Myo(the East Sea shrine), Seo-Hae Dan(the West Sea shrine). But the name of the South Sea shrine had changed in the early period of Chosun as Nam-Hae Sin-sa to the later Chosun as Nam-Hae Dang through the research of related literature and historical map. Such as the Seo-Hae Dan, it was constructed for the Dan, the flat raised-floor without buildings, and changed to the type of Sa-Dang with addition of buildings. 3. The historical map of Hae Sin-sa informs the types of the roof, the Mat-bae roof was used in the Dong-Hae Myo, but the Pal-jak roof was showed in the Seo-Hae Dan and the Nam-Hae Sin-sa. 4. According to the analysis of Yong-Ch'uck the unit length, Nam-Hae Sin-sa was reconstructed in the period of Koryo on large scale, but it was restored in the Chosun on middle scale. And the Unit of Yong Ch'uck was changed into Yeong-jo Ch'uck in the period of Chosun. 5. As the results, The Plan of the Nam-Hae Sin-sa Reconstruction designed the new shrine into the 3 Kan front and the 2 Kan side with 3:2 scale. An-ch'o-gong with Yong-du and Yong Mi the ornaments represents head and tail of dragon, the Un-gong and the ornament of Pa-ryun-dae-gong in the building, and the Ch'ung-ryang of the Yong-du show the image of the institution for religious service for the god of the sea who look like dragon. The inner gate building and the main entrance were designed as same plan and scale as Hyang-gyo, the Korean Traditional School and Shrine of Confucianism, on the basis of results of excavation. Raise the 3-tall gate of the main entrance with harmony of the scale and the shape, because the side of gate building has the Mat-bae roof. 6. This research shows that Plan of the Nam-Hae Sin-sa Reconstruction is composed into shrine space and reservation space from the main entrance to inner gate and shrine like Jung-ak Dan in the Mt. Gye-ryong San, and it also informs the well in the west side of Sin-sa is an important factor of the plan of shrine architecture.

• Korean Journal of Heritage: History & Science
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• v.53 no.4
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• pp.32-59
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• 2020

South Korea's area-based heritage preservation system originates from the "Preservation of Traditional Buildings Act" enacted in 1984. However, this system was abolished in 1996. As there was a need for protection of ancient cities in the 1960s, Japan enacted the Historic City Preservation Act in 1966, and 'Preservation Areas for Historic Landscapes' and 'Special Preservation Districts for Historic Landscapes' were introduced. For the preservation of area-based heritage sites, the 'Important Preservation Districts for Groups of Traditional Buildings' system introduced as part of the revision of the Cultural Heritage Protection Act in 1975 was the beginning. Then, in the early-2000s, discussions on the preservation of area-based heritage sites began in earnest, and the 'Important Cultural Landscape' system was introduced for protection of the space and context between heritage sites. Also, '33 Groups of Modernization Industry Heritage Sites' were designated in 2007, covering various material and immaterial resources related to the modernization of Japan, and '100 Beautiful Historic Landscapes of Japan' were selected for protection of local landscapes with historic value in the same year. In 2015, the "Japanese Heritage" system was established for the integrated preservation and management of tangible and intangible heritage aspects located in specific areas; in 2016, the "Japanese Agricultural Heritage" system was established for the succession and fostering of the disappearing agriculture and fishery industries; and in 2017, "the 20th Century Heritage," was established, representing evidence of modern and contemporary Japanese technologies in the 20th century. As a result, presently (in September 2020), 30 'Historic Landscape Preservation Areas', 60 'Historic Landscape Special Districts,' 120 'Important Preservation Districts for Groups of Traditional Buildings," 65 'Important Cultural Landscapes,' 66 'Groups of Modernization Industry Heritage Sites,' 264 "100 Beautiful Historic Landscapes of Japan,' 104 'Japanese Heritage Sites,' and 15 'Japanese Agricultural Heritage Sites' have been designated. According to this perception of situations, the research process for this study with its basic purpose of extracting the general characteristics of Japan's area-based heritage preservation system, has sequentially spread since 1976 as follows. First, this study investigates Japan's area-based heritage site preservation system and sets the scope of research through discussions of literature and preceding studies. Second, this study investigates the process of the spread of the area-based heritage site preservation system and analyzes the relationship between the systems according to their development, in order to draw upon their characteristics. Third, to concretize content related to relationships and characteristics, this study involves in-depth analysis of three representative examples and sums them up to identify the characteristics of Japan's area-based heritage system. A noticeable characteristic of Japan's area-based heritage site preservation system drawn from this is that new heritage sites are born each year. Consequently, an overlapping phenomenon takes place between heritage sites, and such phenomena occur alongside revitalization of related industries, traditional industry, and cultural tourism and the improvement of localities as well as the preservation of area-based heritage. These characteristics can be applied as suggestions for the revitalization of the 'modern historical and cultural space' system implemented by South Korea.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.83-102
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• 2021

The government recently announced various policies for developing big-data and artificial intelligence fields to provide a great opportunity to the public with respect to disclosure of high-quality data within public institutions. KSURE(Korea Trade Insurance Corporation) is a major public institution for financial policy in Korea, and thus the company is strongly committed to backing export companies with various systems. Nevertheless, there are still fewer cases of realized business model based on big-data analyses. In this situation, this paper aims to develop a new business model which can be applied to an ex-ante prediction for the likelihood of the insurance accident of credit guarantee. We utilize internal data from KSURE which supports export companies in Korea and apply machine learning models. Then, we conduct performance comparison among the predictive models including Logistic Regression, Random Forest, XGBoost, LightGBM, and DNN(Deep Neural Network). For decades, many researchers have tried to find better models which can help to predict bankruptcy since the ex-ante prediction is crucial for corporate managers, investors, creditors, and other stakeholders. The development of the prediction for financial distress or bankruptcy was originated from Smith(1930), Fitzpatrick(1932), or Merwin(1942). One of the most famous models is the Altman's Z-score model(Altman, 1968) which was based on the multiple discriminant analysis. This model is widely used in both research and practice by this time. The author suggests the score model that utilizes five key financial ratios to predict the probability of bankruptcy in the next two years. Ohlson(1980) introduces logit model to complement some limitations of previous models. Furthermore, Elmer and Borowski(1988) develop and examine a rule-based, automated system which conducts the financial analysis of savings and loans. Since the 1980s, researchers in Korea have started to examine analyses on the prediction of financial distress or bankruptcy. Kim(1987) analyzes financial ratios and develops the prediction model. Also, Han et al.(1995, 1996, 1997, 2003, 2005, 2006) construct the prediction model using various techniques including artificial neural network. Yang(1996) introduces multiple discriminant analysis and logit model. Besides, Kim and Kim(2001) utilize artificial neural network techniques for ex-ante prediction of insolvent enterprises. After that, many scholars have been trying to predict financial distress or bankruptcy more precisely based on diverse models such as Random Forest or SVM. One major distinction of our research from the previous research is that we focus on examining the predicted probability of default for each sample case, not only on investigating the classification accuracy of each model for the entire sample. Most predictive models in this paper show that the level of the accuracy of classification is about 70% based on the entire sample. To be specific, LightGBM model shows the highest accuracy of 71.1% and Logit model indicates the lowest accuracy of 69%. However, we confirm that there are open to multiple interpretations. In the context of the business, we have to put more emphasis on efforts to minimize type 2 error which causes more harmful operating losses for the guaranty company. Thus, we also compare the classification accuracy by splitting predicted probability of the default into ten equal intervals. When we examine the classification accuracy for each interval, Logit model has the highest accuracy of 100% for 0~10% of the predicted probability of the default, however, Logit model has a relatively lower accuracy of 61.5% for 90~100% of the predicted probability of the default. On the other hand, Random Forest, XGBoost, LightGBM, and DNN indicate more desirable results since they indicate a higher level of accuracy for both 0~10% and 90~100% of the predicted probability of the default but have a lower level of accuracy around 50% of the predicted probability of the default. When it comes to the distribution of samples for each predicted probability of the default, both LightGBM and XGBoost models have a relatively large number of samples for both 0~10% and 90~100% of the predicted probability of the default. Although Random Forest model has an advantage with regard to the perspective of classification accuracy with small number of cases, LightGBM or XGBoost could become a more desirable model since they classify large number of cases into the two extreme intervals of the predicted probability of the default, even allowing for their relatively low classification accuracy. Considering the importance of type 2 error and total prediction accuracy, XGBoost and DNN show superior performance. Next, Random Forest and LightGBM show good results, but logistic regression shows the worst performance. However, each predictive model has a comparative advantage in terms of various evaluation standards. For instance, Random Forest model shows almost 100% accuracy for samples which are expected to have a high level of the probability of default. Collectively, we can construct more comprehensive ensemble models which contain multiple classification machine learning models and conduct majority voting for maximizing its overall performance.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.45-68
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• 2022

The central and local governments of the Republic of Korea provided information necessary for disaster response through wireless emergency alerts (WEAs) in order to overcome the pandemic situation in which COVID-19 rapidly spreads. Among all channels for delivering disaster information, wireless emergency alert is the most efficient, and since it adopts the CBS(Cell Broadcast Service) method that broadcasts directly to the mobile phone, it has the advantage of being able to easily access disaster information through the mobile phone without the effort of searching. In this study, the characteristics of wireless emergency alerts sent to Seoul during the past year and one month (January 2020 to January 2021) were derived through various text mining methodologies, and various types of information contained in wireless emergency alerts were analyzed. In addition, it was confirmed through the population mobility by age in the districts of Seoul that what kind of influence it had on the movement behavior of people. After going through the process of classifying key words and information included in each character, text analysis was performed so that individual sent characters can be used as an analysis unit by applying a document cluster analysis technique based on the included words. The number of WEAs sent to the Seoul has grown dramatically since the spread of Covid-19. In January 2020, only 10 WEAs were sent to the Seoul, but the number of the WEAs increased 5 times in March, and 7.7 times over the previous months. Since the basic, regional local government were authorized to send wireless emergency alerts independently, the sending behavior of related to wireless emergency alerts are different for each local government. Although most of the basic local governments increased the transmission of WEAs as the number of confirmed cases of Covid-19 increases, the trend of the increase in WEAs according to the increase in the number of confirmed cases of Covid-19 was different by region. By using structured econometric model, the effect of disaster information included in wireless emergency alerts on population mobility was measured by dividing it into baseline effect and accumulating effect. Six types of disaster information, including date, order, online URL, symptom, location, normative guidance, were identified in WEAs and analyzed through econometric modelling. It was confirmed that the types of information that significantly change population mobility by age are different. Population mobility of people in their 60s and 70s decreased when wireless emergency alerts included information related to date and order. As date and order information is appeared in WEAs when they intend to give information about Covid-19 confirmed cases, these results show that the population mobility of higher ages decreased as they reacted to the messages reporting of confirmed cases of Covid-19. Online information (URL) decreased the population mobility of in their 20s, and information related to symptoms reduced the population mobility of people in their 30s. On the other hand, it was confirmed that normative words that including the meaning of encouraging compliance with quarantine policies did not cause significant changes in the population mobility of all ages. This means that only meaningful information which is useful for disaster response should be included in the wireless emergency alerts. Repeated sending of wireless emergency alerts reduces the magnitude of the impact of disaster information on population mobility. It proves indirectly that under the prolonged pandemic, people started to feel tired of getting repetitive WEAs with similar content and started to react less. In order to effectively use WEAs for quarantine and overcoming disaster situations, it is necessary to reduce the fatigue of the people who receive WEA by sending them only in necessary situations, and to raise awareness of WEAs.