• Journal of Preventive Medicine and Public Health
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• v.4 no.1
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• pp.65-76
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• 1971

In view of ever rising water pollution problems of river in the vicinity of large urban communities, the author has made an investigation on the pollution of water sampled from Han River (Seoul area) and Nakdong River (Daegu city area) during the period from July to December, 1970. The water samples were taken twice a month during the study period of 6 months from 7 points (locations) along the main stream of Han River at Seoul city and 5 points of Nakdong River at Daegu city. The samples ware measured and analyzed in accordance with the recognized methods in the 'Standard Methods for Examination of Water and waste' by American Public Health Association. The obtained results are as follows : I. Han River. 1. Average turbidity was 5.1 units ranging from 1 to 10 units and the turbidity of down stream was higher than that of the upper stream. 2. pH value showed slight alkalinity (mean;7.2) except Yunchang-Dong (6.9). 3. The mean value of Dissolved Oxygen contents (D.O) was 7.2 ppm. (range of 3.4-10.5ppm.). D.O. of the upper stream (8.2 ppm. at Walker Hill boating place, 8.0 ppm. at the Gwangzang Bridge and Ddookdo) was higher than that of he downstream (5.6ppm. at Yumchang-Dong, 6.4 ppm. at the 2nd Han River Bridge), and D.O. in the winter season was higher than that in the summer season, respectively. 4 The mean value of the Biochemical Oxygen Demand (B.O.D.) was 28.3 ppm. (range of 6.2-64.8 ppm.). The mean value of B.O.D. was 48.7 ppm. at Yumchang-Dong, 42.3 ppm. at the 2nd Han River Bridge, 34.0 ppm. at the 1st nan River Bridge, 28.5 ppm. at the 3rd Han River Bridge, 19.2 ppm. at Dookdo, 13.2 ppm. at the Gwangzang Bridge, and 10.2 ppm. at the Walker Hill boating place in order of value. B.O.D. in July and August (35.6 and 34.5 ppm.) were the highest and that in November and December (18.6 and 21.2 ppm.) were the lowest. 5. Suspended Solids (SS) were from 15.0 to 667.0 ppm. with the mean of 222.1 ppm. 'Suspended Solids' of the water samples at Yumchang-Dong and the 2nd Han River Bridge were found to be 378.1 ppm. and 283.9 ppm. respectively which were higher than at the Gwangzang Bridge (134.1 ppm.) and at Walker Hill boating place (79.3ppm.). 6. Coliform colonies counting of the water samples ranged from $0-2,500{\times}10/100ml$. with the mean value of $205.6{\times}10/100ml$. The most contaminated water sample by coliform were from the point of the 2nd Han River Bridge with $640.8{\times}10/100ml$ while the lowest ones were from Walker Hill boating place with $17.2{\times}10/100ml$. There was also a seasonal variation in coliform contamination that is the higher in summer and the lower in winter. II. Nakdong River 1. The mean value of turbidity was 2.3 units with range of 0 to 9.0 units. The highest point was at Geumho River (7.2 units). and the lowest point was at Gangzung and Moonsan (0.45 and 0.41 units). 2. The mean value of pH was 7.5 (range of 7.1-8.5) and highest point was Geumho River with 8.5. 3. The mean value of D.O. was 8.1 ppm. (range of 3.4-11.2 ppm.). D.O. of the upper stream showed higher value than that of the down stream, and the winter season than the summer season. 4. B.O.D. ranged from 2.6 to 57.0 ppm. (mean; 20.4ppm.). The water sample at Geumho River showed the highest value (41.5 ppm.) while at Moonsan and Gangzung showed the lowest (4.6 and 4.7 ppm.). 5. The mean value of suspended solids was 48.7 ppm. (range of 4.0-182.0 ppm.). The highest month was July (63.7ppm.) and August (62.1 ppm.) and the lowest month was October (37.0 ppm.) and December (24.4 ppm.). 6. The mean value of the coliform colonies was $22.7{\times}10/100ml$. (range of $0-243{\times}10/100ml$.). The highest number of the colonies was found in the sample water at the Whawon recreation area ($50.5{\times}10/100ml$.) followed by the Geumho River ($33.9{\times}10/100ml$.), the Goryung Bridge ($28.3{\times}10/100ml$.), Gangzung($0.7{\times}10/100ml$), and Moonsan ($0.6{\times}10/100ml$.).

• Journal of the Korean Geographical Society
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• v.28 no.2
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• pp.77-98
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• 1993

The intent of this study is to analyze the characteristics of distribution, patter, and deposits of the exposed debris slope landform by aerial photography interpretation, measure-ment on the topographical maps and field surveys in the southern part Taebaek mountains. It also aims to research the arrangement types of mountain slope and the landform development of debris slopes in this area. In conclusion, main observations can be summed up as follows. 1. The distribution characteristics 1)From the viewpoint of bedrocks, the distribution density of talus is high in case of the bedrock with high density of joints, sheeting structures and hard rocks, but that of the block stream is high in case of intrusive rocks with the talus line. 2)From the viewpoint of bedrocks, the distribution density of talus is high in case of the bedrock with high density of joints, sheeting structures and hard rocks, but that of the block stream is high in case of inrtusive rocks with the talus line. 2) From the viewpoint of distribution altitude, talus is mainly distributed in the 301~500 meters part above the sea level, while the block stream is distributed in the 101~300 meters part. 3) From the viewpoint of slope oriention, the distribution density of talus on the slope facing the south(S, SE, SW) is a little higher than that of talus on the slope facing the north(N, NE, NW). 2. The Pattern Characteristics 1) The tongue-shaped type among the four types is the most in number. 2) The average length of talus slope is 99 meters, especially that of talus composed of hornfels or granodiorite is longer. Foth the former is easy to make free face; the latter is easdy to produce round stones. The average length of block stream slope is 145 meters, the longest of all is one km(granodiorite). 3) The gradient of talus slope is 20~45${^\circ}$, most of them 26-30${^\croc}$; but talus composed of intrusive rocks is gentle. 4) The slope pattern of talus shows concave slope, which means readjustment of constituent debris. Some of the block stream slope patterns show concave slope at the upper slope and the lower slope, but convex slope at the middle slope; others have uneven slope. 3. The deposit characteristics 1) The average length of constituent debris is 48~172 centimeters in diameter, the sorting of debris is not bad without matrix. That of block stream is longer than that of talus; this difference of debris average diameter is funda-mentally caused by joint space of bedrocks. 2) The shape of constituent debris in talus is mainly angular, but that of the debris composed of intrusive rocks is sub-angular. The shape of constituent debris in block stream is mainly sub-roundl. 3) IN case dof talus, debris diameter is generally increasing with downward slope, but some of them are disordered and the debris diameter of the sides are larger than that of the middle part on a landform surface. In block stream, debris diameter variation is perpendicularly disordered, and the debris diameter of the middle part is generally larger than that of the sides on a landform surface. 4)The long axis orientation of debris is a not bad at the lower part of the slope in talus (only 2 of 6 talus). In block stream(2 of 3), one is good in sorting; another is not bad. The researcher thinks that the latter was caused by the collapse of constituent debris. 5) Most debris were weathered and some are secondly weathered in situ, but talus composed of fresh debris is developing. 4. The landform development of debris slopes and the arrangement types of the mountain slope 1) The formation and development period of talus is divided into two periods. The first period is formation period of talus9the last glacial period), the second period is adjustment period(postglacial age). And that of block stream is divided into three periods: the first period is production period of blocks(tertiary, interglacial period), the second formation period of block stream(the last glacial period), and the third adjustment period of block stream(postglacialage). 2) The arrangement types of mountain slope are divided into six types in this research area, which are as follows. Type I; high level convex slope-free face-talus-block stream-alluvial surface Type II: high level convex slope-free face-talus-alluvial surface Type III: free face-talus-block stream-all-uvial surface Type IV: free face-talus-alluval surface Type V: talus-alluval surface Type VI: block stream-alluvial surface Particularly, type IV id\s basic type of all; others are modified ones.

• Journal of the Korean Society for Library and Information Science
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• v.17
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• pp.11-47
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• 1989

This study intends to examine the background and the procedure of the carving of the tablets of the second edition of Dae-Jang-Mock­Lock(재조대장목록). the time and the route of the moving of the tablets. into Haein-sa, and the contents and the system of it. This study is mainly based on the second edition of Dae-Jang-Mock-Lock. But the other closely related materials such as restored first. edition of the Dae- Jang-Mock-Lock, Koryo Sin-Jo-Dae-Jang-Byeol-Lock (고려신조대장교정별록). Kae-Won-Seok-Kyo-Lock (개원석교록). Sok-Kae­Won-Seok-Kyo-Lock (속개원석교록). Jeong-Won-Sin-Jeong-Seok-Kyo­Lock(정원신정석교록), Sok-Jeong-Won-Seok-Kyo-Lock(속정원석교록), Dea-Jung-Sang-Bu-Beob-Bo-Lock(대중상부법보록), and Kyeong-Woo-Sin-Su-Beob-Bo-Lock(경우신수법보록), are also analysed and closely examined. The results of this study can be summarized as follows: 1. The second edition of Tripitaka Koreana(고려대장경) was carved for the purpose of defending the country from Mongolia with the power of Buddhism, after the tablets of the first edition in Buin-sa(부이사) was destroyed by fire. 2. In 1236. Dae-Jang-Do-Gam(대장도감) was established, and the preparation for the recarving of the tablets such as comparison between the content, of the first edition of Tripitalk Koreana, Gal-Bo-Chik-Pan-Dae­Jang-Kyeong and Kitan Dae- Jang-Kyeong, transcription of the original copy and the preparation of the wood, etc. was started. 3. In 1237 after the announcement of Dae-Jang-Gyeong-Gak-Pan-Gun­Sin-Gi-Go-Mun(대장경핵판군신석고문), the carving was started on a full scale. And seven years later (1243), Bun-Sa-Dae-Jang-Do-Gam(분사대장도감) was established in the area of the South to expand and hasten the work. And a large number of the tablets were carved in there. 4. It took 16 years to carve the main text and the supplements of the second edition of Tripitaka Koreana, the main text being carved from 1237 to 1248 and the supplement from 1244 to 1251. 5. It can be supposed that the tablets of the second edition of Tripitaka Koreana, stored in Seon-Won-Sa(선원사), Kang-Wha(강화), for about 140 years, was moved to Ji-Cheon-Sa(지천사), Yong-San(용산), and to Hae-In-Sa(해인사) again, through the west and the south sea and Jang-Gyeong-Po(장경포), Go-Ryeong(고령), in the autumn of the same year. 6. The second edition of Tripitaka Koreana was carved mainly based on the first edition, comparing with Gae-Bo-Chik-Pan-Dae-Jang-Kyeong(개보판대장경) and Kitan Dae-Jang-Kyeong(계단대장경). And the second edition of Dae-Jang-Mock-Lock also compiled mainly based on the first edition with the reference to Kae-Won-Seok-Kyo-Lock and Sok-Jeong-Won-Seok-Kyo-Lock. 7. Comparing with the first edition of Dae-Jang-Mock-Lock, in the second edition 7 items of 9 volumes of Kitan text such as Weol-Deung­Sam-Mae-Gyeong-Ron(월증삼매경론) are added and 3 items of 60 volumes such as Dae-Jong-Ji-Hyeon-Mun-Ron(대종지현문논) are substituted into others from Cheon chest(천함) to Kaeng chest(경함), and 92 items of 601 volumes such as Beob-Won-Ju-Rim-Jeon(법원주임전) are added after Kaeng chest. And 4 items of 50 volumes such as Yuk-Ja-Sin-Ju-Wang-Kyeong(육자신주왕경) are ommitted in the second edition. 8. Comparing with Kae-Won-Seok-Kyo-Lock, Cheon chest to Young chest (영함) of the second edition is compiled according to Ib-Jang-Lock(입장록) of Kae-Won-Seok-Kyo-Lock. But 15 items of 43 vol­umes such as Bul-Seol-Ban-Ju-Sam-Mae-Kyeong(불설반주삼매경) are ;added and 7 items of 35 volumes such as Dae-Bang-Deung-Dae-Jib-Il­Jang-Kyeong(대방등대집일장경) are ommitted. 9. Comparing with Sok-Jeong-Won-Seok-Kyo-Lock, 3 items of the 47 volumes (or 49 volumes) are ommitted and 4 items of 96 volumes are ;added in Caek chest(책함) to Mil chest(밀함) of the second edition. But the items are arranged in the same order. 10. Comparing with Dae- Jung-Sang-Bo-Beob-Bo-Lock, the arrangement of the second edition is entirely different from it. But 170 items of 329 volumes are also included in Doo chest(두함) to Kyeong chest(경함) of the second edition, and 53 items of 125 volumes in Jun chest(존함) to Jeong chest(정함). And 10 items of 108 volumes in the last part of Dae-Jung-Sang-Bo-Beob-Bo-Lock are ommitted and 3 items of 131 volumes such as Beob-Won-Ju-Rim-Jeon(법원주임전) are added in the second edition. 11. Comparing with Kyeong-Woo-Sin-Su-Beob-Bo-Lock, all of the items (21 items of 161 volumes) are included in the second edition without ;any classificatory system. And 22 items of 172 volumes in the Seong­Hyeon-Jib-Jeon(성현집전) part such as Myo-Gak-Bi-Cheon(묘각비전) are ommitted. 12. The last part of the second edition, Joo chest(주함) to Dong chest (동함), includes 14 items of 237 volumes. But these items cannot be found in any other former Buddhist catalog. So it might be supposed as the Kitan texts. 13. Besides including almost all items in Kae-Won-Seok-Kyo-Lock and all items in Sok-Jeong-Won-Seok-Kyo-Lock, Dae-Jung-Sang-Bo­Beob-Bo-Lock, and Kyeong-Woo-Sin-Su-Beob-Bo-Lock, the second edition of Dae-Jang-Mock-Lock includes more items, at least 20 items of about 300 volumes of Kitan Tripitaka and 15 items of 43 volumes of traditional Korean Tripitake that cannot be found any others. Therefore, Tripitaka Koreana can be said as a comprehensive Tripitaka covering all items of Tripitakas translated in Chinese character.

• Journal of Intelligence and Information Systems
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• v.20 no.3
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• pp.109-131
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• 2014

As the demand of nuclear power plant equipment is continuously growing worldwide, the importance of handling nuclear strategic materials is also increasing. While the number of cases submitted for the exports of nuclear-power commodity and technology is dramatically increasing, preadjudication (or prescreening to be simple) of strategic materials has been done so far by experts of a long-time experience and extensive field knowledge. However, there is severe shortage of experts in this domain, not to mention that it takes a long time to develop an expert. Because human experts must manually evaluate all the documents submitted for export permission, the current practice of nuclear material export is neither time-efficient nor cost-effective. Toward alleviating the problem of relying on costly human experts only, our research proposes a new system designed to help field experts make their decisions more effectively and efficiently. The proposed system is built upon case-based reasoning, which in essence extracts key features from the existing cases, compares the features with the features of a new case, and derives a solution for the new case by referencing similar cases and their solutions. Our research proposes a framework of case-based reasoning system, designs a case-based reasoning system for the control of nuclear material exports, and evaluates the performance of alternative keyword extraction methods (full automatic, full manual, and semi-automatic). A keyword extraction method is an essential component of the case-based reasoning system as it is used to extract key features of the cases. The full automatic method was conducted using TF-IDF, which is a widely used de facto standard method for representative keyword extraction in text mining. TF (Term Frequency) is based on the frequency count of the term within a document, showing how important the term is within a document while IDF (Inverted Document Frequency) is based on the infrequency of the term within a document set, showing how uniquely the term represents the document. The results show that the semi-automatic approach, which is based on the collaboration of machine and human, is the most effective solution regardless of whether the human is a field expert or a student who majors in nuclear engineering. Moreover, we propose a new approach of computing nuclear document similarity along with a new framework of document analysis. The proposed algorithm of nuclear document similarity considers both document-to-document similarity (${\alpha}$) and document-to-nuclear system similarity (${\beta}$), in order to derive the final score (${\gamma}$) for the decision of whether the presented case is of strategic material or not. The final score (${\gamma}$) represents a document similarity between the past cases and the new case. The score is induced by not only exploiting conventional TF-IDF, but utilizing a nuclear system similarity score, which takes the context of nuclear system domain into account. Finally, the system retrieves top-3 documents stored in the case base that are considered as the most similar cases with regard to the new case, and provides them with the degree of credibility. With this final score and the credibility score, it becomes easier for a user to see which documents in the case base are more worthy of looking up so that the user can make a proper decision with relatively lower cost. The evaluation of the system has been conducted by developing a prototype and testing with field data. The system workflows and outcomes have been verified by the field experts. This research is expected to contribute the growth of knowledge service industry by proposing a new system that can effectively reduce the burden of relying on costly human experts for the export control of nuclear materials and that can be considered as a meaningful example of knowledge service application.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.25-44
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• 2013

Accessing movie contents has become easier and increased with the advent of smart TV, IPTV and web services that are able to be used to search and watch movies. In this situation, there are increasing search for preference movie contents of users. However, since the amount of provided movie contents is too large, the user needs more effort and time for searching the movie contents. Hence, there are a lot of researches for recommendations of personalized item through analysis and clustering of the user preferences and user profiles. In this study, we propose recommendation system which uses ontology based knowledge base. Our ontology can represent not only relations between metadata of movies but also relations between metadata and profile of user. The relation of each metadata can show similarity between movies. In order to build, the knowledge base our ontology model is considered two aspects which are the movie metadata model and the user model. On the part of build the movie metadata model based on ontology, we decide main metadata that are genre, actor/actress, keywords and synopsis. Those affect that users choose the interested movie. And there are demographic information of user and relation between user and movie metadata in user model. In our model, movie ontology model consists of seven concepts (Movie, Genre, Keywords, Synopsis Keywords, Character, and Person), eight attributes (title, rating, limit, description, character name, character description, person job, person name) and ten relations between concepts. For our knowledge base, we input individual data of 14,374 movies for each concept in contents ontology model. This movie metadata knowledge base is used to search the movie that is related to interesting metadata of user. And it can search the similar movie through relations between concepts. We also propose the architecture for movie recommendation. The proposed architecture consists of four components. The first component search candidate movies based the demographic information of the user. In this component, we decide the group of users according to demographic information to recommend the movie for each group and define the rule to decide the group of users. We generate the query that be used to search the candidate movie for recommendation in this component. The second component search candidate movies based user preference. When users choose the movie, users consider metadata such as genre, actor/actress, synopsis, keywords. Users input their preference and then in this component, system search the movie based on users preferences. The proposed system can search the similar movie through relation between concepts, unlike existing movie recommendation systems. Each metadata of recommended candidate movies have weight that will be used for deciding recommendation order. The third component the merges results of first component and second component. In this step, we calculate the weight of movies using the weight value of metadata for each movie. Then we sort movies order by the weight value. The fourth component analyzes result of third component, and then it decides level of the contribution of metadata. And we apply contribution weight to metadata. Finally, we use the result of this step as recommendation for users. We test the usability of the proposed scheme by using web application. We implement that web application for experimental process by using JSP, Java Script and prot$\acute{e}$g$\acute{e}$ API. In our experiment, we collect results of 20 men and woman, ranging in age from 20 to 29. And we use 7,418 movies with rating that is not fewer than 7.0. In order to experiment, we provide Top-5, Top-10 and Top-20 recommended movies to user, and then users choose interested movies. The result of experiment is that average number of to choose interested movie are 2.1 in Top-5, 3.35 in Top-10, 6.35 in Top-20. It is better than results that are yielded by for each metadata.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.113-125
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• 2013

Every company wants to know customer's requirement and makes an effort to meet them. Cause that, communication between customer and company became core competition of business and that important is increasing continuously. There are several strategies to find customer's needs, but VOC (Voice of customer) is one of most powerful communication tools and VOC gathering by several channels as telephone, post, e-mail, website and so on is so meaningful. So, almost company is gathering VOC and operating VOC system. VOC is important not only to business organization but also public organization such as government, education institute, and medical center that should drive up public service quality and customer satisfaction. Accordingly, they make a VOC gathering and analyzing System and then use for making a new product and service, and upgrade. In recent years, innovations in internet and ICT have made diverse channels such as SNS, mobile, website and call-center to collect VOC data. Although a lot of VOC data is collected through diverse channel, the proper utilization is still difficult. It is because the VOC data is made of very emotional contents by voice or text of informal style and the volume of the VOC data are so big. These unstructured big data make a difficult to store and analyze for use by human. So that, the organization need to automatic collecting, storing, classifying and analyzing system for unstructured big VOC data. This study propose an intelligent VOC analyzing system based on opinion mining to classify the unstructured VOC data automatically and determine the polarity as well as the type of VOC. And then, the basis of the VOC opinion analyzing system, called domain-oriented sentiment dictionary is created and corresponding stages are presented in detail. The experiment is conducted with 4,300 VOC data collected from a medical website to measure the effectiveness of the proposed system and utilized them to develop the sensitive data dictionary by determining the special sentiment vocabulary and their polarity value in a medical domain. Through the experiment, it comes out that positive terms such as "칭찬, 친절함, 감사, 무사히, 잘해, 감동, 미소" have high positive opinion value, and negative terms such as "퉁명, 뭡니까, 말하더군요, 무시하는" have strong negative opinion. These terms are in general use and the experiment result seems to be a high probability of opinion polarity. Furthermore, the accuracy of proposed VOC classification model has been compared and the highest classification accuracy of 77.8% is conformed at threshold with -0.50 of opinion classification of VOC. Through the proposed intelligent VOC analyzing system, the real time opinion classification and response priority of VOC can be predicted. Ultimately the positive effectiveness is expected to catch the customer complains at early stage and deal with it quickly with the lower number of staff to operate the VOC system. It can be made available human resource and time of customer service part. Above all, this study is new try to automatic analyzing the unstructured VOC data using opinion mining, and shows that the system could be used as variable to classify the positive or negative polarity of VOC opinion. It is expected to suggest practical framework of the VOC analysis to diverse use and the model can be used as real VOC analyzing system if it is implemented as system. Despite experiment results and expectation, this study has several limits. First of all, the sample data is only collected from a hospital web-site. It means that the sentimental dictionary made by sample data can be lean too much towards on that hospital and web-site. Therefore, next research has to take several channels such as call-center and SNS, and other domain like government, financial company, and education institute.

• Journal of Intelligence and Information Systems
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• v.26 no.3
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• pp.149-169
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• 2020

"The Urban Renewal New Deal project", one of the government's major national projects, is about developing underdeveloped areas by investing 50 trillion won in 100 locations on the first year and 500 over the next four years. This project is drawing keen attention from the media and local governments. However, the project model which fails to reflect the original characteristics of the area as it divides project area into five categories: "Our Neighborhood Restoration, Housing Maintenance Support Type, General Neighborhood Type, Central Urban Type, and Economic Base Type," According to keywords for successful urban regeneration in Korea, "resident participation," "regional specialization," "ministerial cooperation" and "public-private cooperation", when local governments propose urban regeneration projects to the government, they can see that it is most important to accurately understand the characteristics of the city and push ahead with the projects in a way that suits the characteristics of the city with the help of local residents and private companies. In addition, considering the gentrification problem, which is one of the side effects of urban regeneration projects, it is important to select and implement urban regeneration types suitable for the characteristics of the area. In order to supplement the limitations of the 'Urban Regeneration New Deal Project' methodology, this study aims to propose a system that recommends urban regeneration types suitable for urban regeneration sites by utilizing various machine learning algorithms, referring to the urban regeneration types of the '2025 Seoul Metropolitan Government Urban Regeneration Strategy Plan' promoted based on regional characteristics. There are four types of urban regeneration in Seoul: "Low-use Low-Level Development, Abandonment, Deteriorated Housing, and Specialization of Historical and Cultural Resources" (Shon and Park, 2017). In order to identify regional characteristics, approximately 100,000 text data were collected for 22 regions where the project was carried out for a total of four types of urban regeneration. Using the collected data, we drew key keywords for each region according to the type of urban regeneration and conducted topic modeling to explore whether there were differences between types. As a result, it was confirmed that a number of topics related to real estate and economy appeared in old residential areas, and in the case of declining and underdeveloped areas, topics reflecting the characteristics of areas where industrial activities were active in the past appeared. In the case of the historical and cultural resource area, since it is an area that contains traces of the past, many keywords related to the government appeared. Therefore, it was possible to confirm political topics and cultural topics resulting from various events. Finally, in the case of low-use and under-developed areas, many topics on real estate and accessibility are emerging, so accessibility is good. It mainly had the characteristics of a region where development is planned or is likely to be developed. Furthermore, a model was implemented that proposes urban regeneration types tailored to regional characteristics for regions other than Seoul. Machine learning technology was used to implement the model, and training data and test data were randomly extracted at an 8:2 ratio and used. In order to compare the performance between various models, the input variables are set in two ways: Count Vector and TF-IDF Vector, and as Classifier, there are 5 types of SVM (Support Vector Machine), Decision Tree, Random Forest, Logistic Regression, and Gradient Boosting. By applying it, performance comparison for a total of 10 models was conducted. The model with the highest performance was the Gradient Boosting method using TF-IDF Vector input data, and the accuracy was 97%. Therefore, the recommendation system proposed in this study is expected to recommend urban regeneration types based on the regional characteristics of new business sites in the process of carrying out urban regeneration projects."

• Journal of Intelligence and Information Systems
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• v.26 no.3
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• pp.171-191
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• 2020

This study focused on digital music, which is the most valuable cultural asset in the modern society and occupies a particularly important position in the flow of the Korean Wave. Digital music was collected based on the "Gaon Chart," a well-established music chart in Korea. Through this, the changes in the ranking of the music that entered the chart for 73 weeks were collected. Afterwards, patterns with similar characteristics were derived through time series cluster analysis. Then, a descriptive analysis was performed on the notable features of each pattern. The research process suggested by this study is as follows. First, in the data collection process, time series data was collected to check the ranking change of digital music. Subsequently, in the data processing stage, the collected data was matched with the rankings over time, and the music title and artist name were processed. Each analysis is then sequentially performed in two stages consisting of exploratory analysis and explanatory analysis. First, the data collection period was limited to the period before 'the music bulk buying phenomenon', a reliability issue related to music ranking in Korea. Specifically, it is 73 weeks starting from December 31, 2017 to January 06, 2018 as the first week, and from May 19, 2019 to May 25, 2019. And the analysis targets were limited to digital music released in Korea. In particular, digital music was collected based on the "Gaon Chart", a well-known music chart in Korea. Unlike private music charts that are being serviced in Korea, Gaon Charts are charts approved by government agencies and have basic reliability. Therefore, it can be considered that it has more public confidence than the ranking information provided by other services. The contents of the collected data are as follows. Data on the period and ranking, the name of the music, the name of the artist, the name of the album, the Gaon index, the production company, and the distribution company were collected for the music that entered the top 100 on the music chart within the collection period. Through data collection, 7,300 music, which were included in the top 100 on the music chart, were identified for a total of 73 weeks. On the other hand, in the case of digital music, since the cases included in the music chart for more than two weeks are frequent, the duplication of music is removed through the pre-processing process. For duplicate music, the number and location of the duplicated music were checked through the duplicate check function, and then deleted to form data for analysis. Through this, a list of 742 unique music for analysis among the 7,300-music data in advance was secured. A total of 742 songs were secured through previous data collection and pre-processing. In addition, a total of 16 patterns were derived through time series cluster analysis on the ranking change. Based on the patterns derived after that, two representative patterns were identified: 'Steady Seller' and 'One-Hit Wonder'. Furthermore, the two patterns were subdivided into five patterns in consideration of the survival period of the music and the music ranking. The important characteristics of each pattern are as follows. First, the artist's superstar effect and bandwagon effect were strong in the one-hit wonder-type pattern. Therefore, when consumers choose a digital music, they are strongly influenced by the superstar effect and the bandwagon effect. Second, through the Steady Seller pattern, we confirmed the music that have been chosen by consumers for a very long time. In addition, we checked the patterns of the most selected music through consumer needs. Contrary to popular belief, the steady seller: mid-term pattern, not the one-hit wonder pattern, received the most choices from consumers. Particularly noteworthy is that the 'Climbing the Chart' phenomenon, which is contrary to the existing pattern, was confirmed through the steady-seller pattern. This study focuses on the change in the ranking of music over time, a field that has been relatively alienated centering on digital music. In addition, a new approach to music research was attempted by subdividing the pattern of ranking change rather than predicting the success and ranking of music.

• Journal of Intelligence and Information Systems
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• v.26 no.3
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• pp.109-125
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• 2020

The Ministry of National Defense is pushing for the Defense Acquisition Program to build strong defense capabilities, and it spends more than 10 trillion won annually on defense improvement. As the Defense Acquisition Program is directly related to the security of the nation as well as the lives and property of the people, it must be carried out very transparently and efficiently by experts. However, the excessive diversification of laws and regulations related to the Defense Acquisition Program has made it challenging for many working-level officials to carry out the Defense Acquisition Program smoothly. It is even known that many people realize that there are related regulations that they were unaware of until they push ahead with their work. In addition, the statutory statements related to the Defense Acquisition Program have the tendency to cause serious issues even if only a single expression is wrong within the sentence. Despite this, efforts to establish a sentence comparison system to correct this issue in real time have been minimal. Therefore, this paper tries to propose a "Comparison System between the Statement of Military Reports and Related Laws" implementation plan that uses the Siamese Network-based artificial neural network, a model in the field of natural language processing (NLP), to observe the similarity between sentences that are likely to appear in the Defense Acquisition Program related documents and those from related statutory provisions to determine and classify the risk of illegality and to make users aware of the consequences. Various artificial neural network models (Bi-LSTM, Self-Attention, D_Bi-LSTM) were studied using 3,442 pairs of "Original Sentence"(described in actual statutes) and "Edited Sentence"(edited sentences derived from "Original Sentence"). Among many Defense Acquisition Program related statutes, DEFENSE ACQUISITION PROGRAM ACT, ENFORCEMENT RULE OF THE DEFENSE ACQUISITION PROGRAM ACT, and ENFORCEMENT DECREE OF THE DEFENSE ACQUISITION PROGRAM ACT were selected. Furthermore, "Original Sentence" has the 83 provisions that actually appear in the Act. "Original Sentence" has the main 83 clauses most accessible to working-level officials in their work. "Edited Sentence" is comprised of 30 to 50 similar sentences that are likely to appear modified in the county report for each clause("Original Sentence"). During the creation of the edited sentences, the original sentences were modified using 12 certain rules, and these sentences were produced in proportion to the number of such rules, as it was the case for the original sentences. After conducting 1 : 1 sentence similarity performance evaluation experiments, it was possible to classify each "Edited Sentence" as legal or illegal with considerable accuracy. In addition, the "Edited Sentence" dataset used to train the neural network models contains a variety of actual statutory statements("Original Sentence"), which are characterized by the 12 rules. On the other hand, the models are not able to effectively classify other sentences, which appear in actual military reports, when only the "Original Sentence" and "Edited Sentence" dataset have been fed to them. The dataset is not ample enough for the model to recognize other incoming new sentences. Hence, the performance of the model was reassessed by writing an additional 120 new sentences that have better resemblance to those in the actual military report and still have association with the original sentences. Thereafter, we were able to check that the models' performances surpassed a certain level even when they were trained merely with "Original Sentence" and "Edited Sentence" data. If sufficient model learning is achieved through the improvement and expansion of the full set of learning data with the addition of the actual report appearance sentences, the models will be able to better classify other sentences coming from military reports as legal or illegal. Based on the experimental results, this study confirms the possibility and value of building "Real-Time Automated Comparison System Between Military Documents and Related Laws". The research conducted in this experiment can verify which specific clause, of several that appear in related law clause is most similar to the sentence that appears in the Defense Acquisition Program-related military reports. This helps determine whether the contents in the military report sentences are at the risk of illegality when they are compared with those in the law clauses.

• Journal of the Korean Institute of Landscape Architecture
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• v.43 no.1
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• pp.40-53
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• 2015

To train the manpower to meet the requirements of the industrial field, the introduction of the National Qualification Frameworks(hereinafter referred to as NQF) was determined in 2001 by National Competency Standards(hereinafter referred to as NCS) centrally of the Office for Government Policy Coordination. Also, for landscape architecture in the construction field, the "NCS -Landscape Architecture" pilot was developed in 2008 to be test operated for 3 years starting in 2009. Especially, as the 'realization of a competence-based society, not by educational background' was adopted as one of the major government projects in the Park Geun-Hye government(inaugurated in 2013) the NCS system was constructed on a nationwide scale as a detailed method for practicing this. However, in the case of the NCS developed by the nation, the ideal job performing abilities are specified, therefore there are weaknesses of not being able to reflect the actual operational problem differences in the student level between universities, problems of securing equipment and professors, and problems in the number of current curricula. For soft landing to practical curriculum, the process of clearly analyzing the gap between the current curriculum and the NCS must be preceded. Gap analysis is the initial stage methodology to reorganize the existing curriculum into NCS based curriculum, and based on the ability unit elements and performance standards for each NCS ability unit, the discrepancy between the existing curriculum within the department or the level of coincidence used a Likert scale of 1 to 5 to fill in and analyze. Thus, the universities wishing to operate NCS in the future measuring the level of coincidence and the gap between the current university curriculum and NCS can secure the basic tool to verify the applicability of NCS and the effectiveness of further development and operation. The advantages of reorganizing the curriculum through gap analysis are, first, that the government financial support project can be connected to provide quantitative index of the NCS adoption rate for each qualitative department, and, second, an objective standard is provided on the insufficiency or sufficiency when reorganizing to NCS based curriculum. In other words, when introducing in the subdivisions of the relevant NCS, the insufficient ability units and the ability unit elements can be extracted, and the supplementary matters for each ability unit element per existing subject can be extracted at the same time. There is an advantage providing directions for detailed class program and basic subject opening. The Ministry of Education and the Ministry of Employment and Labor must gather people from the industry to actively develop and supply the NCS standard a practical level to systematically reflect the requirements of the industrial field the educational training and qualification, and the universities wishing to apply NCS must reorganize the curriculum connecting work and qualification based on NCS. To enable this, the universities must consider the relevant industrial prospect and the relation between the faculty resources within the university and the local industry to clearly select the NCS subdivision to be applied. Afterwards, gap analysis must be used for the NCS based curriculum reorganization to establish the direction of the reorganization more objectively and rationally in order to participate in the process evaluation type qualification system efficiently.