• Journal of Intelligence and Information Systems
• /
• v.21 no.2
• /
• pp.191-204
• /
• 2015

According to the '2013 Performance Assessment Report on the Financial Program' from the National Assembly Budget Office, the unfilled recruitment ratio of Software(SW) Developers in South Korea was 25% in the 2012 fiscal year. Moreover, the unfilled recruitment ratio of highly-qualified SW developers reaches almost 80%. This phenomenon is intensified in small and medium enterprises consisting of less than 300 employees. Young job-seekers in South Korea are increasingly avoiding becoming a SW developer and even the current SW developers want to change careers, which hinders the national development of IT industries. The Korean government has recently realized the problem and implemented policies to foster young SW developers. Due to this effort, it has become easier to find young SW developers at the beginning-level. However, it is still hard to recruit highly-qualified SW developers for many IT companies. This is because in order to become a SW developing expert, having a long term experiences are important. Thus, improving job continuity intentions of current SW developers is more important than fostering new SW developers. Therefore, this study surveyed the job continuity intentions of SW developers and analyzed the factors associated with them. As a method, we carried out a survey from September 2014 to October 2014, which was targeted on 130 SW developers who were working in IT industries in South Korea. We gathered the demographic information and characteristics of the respondents, work environments of a SW industry, and social positions for SW developers. Afterward, a regression analysis and a decision tree method were performed to analyze the data. These two methods are widely used data mining techniques, which have explanation ability and are mutually complementary. We first performed a linear regression method to find the important factors assaociated with a job continuity intension of SW developers. The result showed that an 'expected age' to work as a SW developer were the most significant factor associated with the job continuity intention. We supposed that the major cause of this phenomenon is the structural problem of IT industries in South Korea, which requires SW developers to change the work field from developing area to management as they are promoted. Also, a 'motivation' to become a SW developer and a 'personality (introverted tendency)' of a SW developer are highly importantly factors associated with the job continuity intention. Next, the decision tree method was performed to extract the characteristics of highly motivated developers and the low motivated ones. We used well-known C4.5 algorithm for decision tree analysis. The results showed that 'motivation', 'personality', and 'expected age' were also important factors influencing the job continuity intentions, which was similar to the results of the regression analysis. In addition to that, the 'ability to learn' new technology was a crucial factor for the decision rules of job continuity. In other words, a person with high ability to learn new technology tends to work as a SW developer for a longer period of time. The decision rule also showed that a 'social position' of SW developers and a 'prospect' of SW industry were minor factors influencing job continuity intensions. On the other hand, 'type of an employment (regular position/ non-regular position)' and 'type of company (ordering company/ service providing company)' did not affect the job continuity intension in both methods. In this research, we demonstrated the job continuity intentions of SW developers, who were actually working at IT companies in South Korea, and we analyzed the factors associated with them. These results can be used for human resource management in many IT companies when recruiting or fostering highly-qualified SW experts. It can also help to build SW developer fostering policy and to solve the problem of unfilled recruitment of SW Developers in South Korea.

• Journal of Periodontal and Implant Science
• /
• v.24 no.3
• /
• pp.581-596
• /
• 1994

This in vitro study was undertaken to obtain optimal tetracycline concentration that aids proliferation and spreading of human periodontal ligament cells, for clinical application in root surfaces of periodontally diseased teeth. Periodontal ligament cells used in this study were obtained from explants of periodontal ligament of 1st premolar teeth which were extracted for the purpose of orthodontic treatment. The cells were cultured in Dulbecco's Modified Eagle Medium(DMEM) supplemented with 100 U/ml penicillin, $100\;{\mu}g/ml$ streptomycin and 10% FBS at $37^{\circ}C$, 100% humidity, 5% $CO_2-95%$ air. Cells were used between the third to 4th passage. After root planing of periodontally extracted teeth, the root slabs were cut with carborundum disk. In the cell proliferation experiment, experimental groups were root planing only group, immersed groups in 25, 50, 75, 100, 150mg/ml aqueous solution of Tetracycline HCl followed by a vigorous rinse in PBS. Human PDL cells at concentration of $1{\times}10^5\;cells/ml$ were seeded in each culture well which contained root slabs and incubated for 6 hours. Then, all of the root slabs were moved into new 24 culture well and incubated 24, 48 and 72 hours. The cell counting was done by inverted phase contrast microscope after trypsinization. The following results were obtained. The cell number was increased in order root planing only group, 25, 150, 50, 75, 100mg/ml of Tetracycline HCl treated group in 24, 48 and 72 hours. The maximal cell number was obtained when the root slabs were immersed in solution with 100mg/ml of Tetracycline HCl. There were statistically significant between the root planing only group and 75, 100 mg/ml of Tetracycline HCl treated group in 24 hours, between the root planing only group and 100mg/ml of Tetracycline HCl treated group in 48 hours, between the root planing only group and 50, 75, 100mg/ml of Tetracycline HCl treated group, between 25 and 100mg/ml of Tetracycline HCl treated group in 72 hours(p<0.05). In the cell spreading experiment, after 30 minutes of incubated, in the root planing only group, the cells were generally round in shape. The cell surface was mostly covered with blebs. The cells started to attach to root surface by cytoplasmic extension in 50, 100mg/ml of Tetracycline HCl treated groups, more numerous cells attached to root surface than root planing only group. Many orifices of dentinal tubule were exposed, cells showed radially spreaded cytoplasm and unspreaded central region of the cell was covered with blebs. After 6 hours of incubation, in the root planing only group, cells showed radially spreaded cytoplasm and were attached flat appearance. In 50, 100mg/ml of Tetracycline HCl treated groups, cellular margin was concaved and cytoplasm showed elongated appearance with polarity. After 24 hours of incubation, in the root planing group, cells showed characteristic polarity. In 50, 100mg/ml of Tetracycline HCl treated groups, cells showed more elongated and spindle - like appearance.

• The Korean Journal of Food And Nutrition
• /
• v.29 no.6
• /
• pp.835-848
• /
• 2016

The purpose of this study was to find efficient and customized tools for delivering the benefit of health functional foods (HFFs). Delivery tools which could influence the impact of advertising were images, explanations of ingredients, diagrams of health benefit, patents, and comments from authority. Six advertisements were developed using these tools: "A": relevant image + explanation of ingredients + scientific diagram of efficacy; "B": relevant image + explanation of ingredients; "C": relevant image; "D": irrelevant image; "E": irrelevant image + explanation of ingredient + patent; "F": irrelevant image + explanation of ingredient + comments from authority. To analyze the consumer perceptions on HFFs and advertisement effects, 300 respondents were requested to answer a questionnaire comprising of the following questions: 5 questions of attitudes (necessity of HFFs, trust in HFFs, gathering information, watching advertisements and trust in advertisement claims) and 6 questions on the 6 developed advertisements (attention, understanding, sufficiency of information, sympathy, trust, and purchase). Scoring was done as per the 5 Likert scale. There was a higher proportion of females and the elderly, as compared to males and youngsters. The overall consumer attitudes were positive. Explanation of ingredients, scientific diagram of health benefit, patents and expert comments were helpful factors in increasing the advertisement evaluation by consumer, but the images were not. Advertisement evaluation of consumer did not differ with gender and age. However, differences were observed between some of the consumer attitudes (necessity of HFFs, trust in HFFs, gathering information and trust in advertisements claim) and advertisement evaluations (attention, understanding, sympathy and purchase). Our results indicate that for consumers utilizing the HFFs, advertisements with concrete tools such as diagrams, patent, and expert comments are more helpful. However, for consumers who do not have interest in HFFs, the scientific information was irrelevant. We believe that to maximize the effect of health information in advertisements, consumers should be segmented, and customized tools for each segment needs to be developed.

• Information Systems Review
• /
• v.16 no.3
• /
• pp.161-177
• /
• 2014

Corporate credit rating assessment consists of complicated processes in which various factors describing a company are taken into consideration. Such assessment is known to be very expensive since domain experts should be employed to assess the ratings. As a result, the data-driven corporate credit rating prediction using statistical and artificial intelligence (AI) techniques has received considerable attention from researchers and practitioners. In particular, statistical methods such as multiple discriminant analysis (MDA) and multinomial logistic regression analysis (MLOGIT), and AI methods including case-based reasoning (CBR), artificial neural network (ANN), and multiclass support vector machine (MSVM) have been applied to corporate credit rating.2) Among them, MSVM has recently become popular because of its robustness and high prediction accuracy. In this study, we propose a novel optimized MSVM model, and appy it to corporate credit rating prediction in order to enhance the accuracy. Our model, named 'GAMSVM (Genetic Algorithm-optimized Multiclass Support Vector Machine),' is designed to simultaneously optimize the kernel parameters and the feature subset selection. Prior studies like Lorena and de Carvalho (2008), and Chatterjee (2013) show that proper kernel parameters may improve the performance of MSVMs. Also, the results from the studies such as Shieh and Yang (2008) and Chatterjee (2013) imply that appropriate feature selection may lead to higher prediction accuracy. Based on these prior studies, we propose to apply GAMSVM to corporate credit rating prediction. As a tool for optimizing the kernel parameters and the feature subset selection, we suggest genetic algorithm (GA). GA is known as an efficient and effective search method that attempts to simulate the biological evolution phenomenon. By applying genetic operations such as selection, crossover, and mutation, it is designed to gradually improve the search results. Especially, mutation operator prevents GA from falling into the local optima, thus we can find the globally optimal or near-optimal solution using it. GA has popularly been applied to search optimal parameters or feature subset selections of AI techniques including MSVM. With these reasons, we also adopt GA as an optimization tool. To empirically validate the usefulness of GAMSVM, we applied it to a real-world case of credit rating in Korea. Our application is in bond rating, which is the most frequently studied area of credit rating for specific debt issues or other financial obligations. The experimental dataset was collected from a large credit rating company in South Korea. It contained 39 financial ratios of 1,295 companies in the manufacturing industry, and their credit ratings. Using various statistical methods including the one-way ANOVA and the stepwise MDA, we selected 14 financial ratios as the candidate independent variables. The dependent variable, i.e. credit rating, was labeled as four classes: 1(A1); 2(A2); 3(A3); 4(B and C). 80 percent of total data for each class was used for training, and remaining 20 percent was used for validation. And, to overcome small sample size, we applied five-fold cross validation to our dataset. In order to examine the competitiveness of the proposed model, we also experimented several comparative models including MDA, MLOGIT, CBR, ANN and MSVM. In case of MSVM, we adopted One-Against-One (OAO) and DAGSVM (Directed Acyclic Graph SVM) approaches because they are known to be the most accurate approaches among various MSVM approaches. GAMSVM was implemented using LIBSVM-an open-source software, and Evolver 5.5-a commercial software enables GA. Other comparative models were experimented using various statistical and AI packages such as SPSS for Windows, Neuroshell, and Microsoft Excel VBA (Visual Basic for Applications). Experimental results showed that the proposed model-GAMSVM-outperformed all the competitive models. In addition, the model was found to use less independent variables, but to show higher accuracy. In our experiments, five variables such as X7 (total debt), X9 (sales per employee), X13 (years after founded), X15 (accumulated earning to total asset), and X39 (the index related to the cash flows from operating activity) were found to be the most important factors in predicting the corporate credit ratings. However, the values of the finally selected kernel parameters were found to be almost same among the data subsets. To examine whether the predictive performance of GAMSVM was significantly greater than those of other models, we used the McNemar test. As a result, we found that GAMSVM was better than MDA, MLOGIT, CBR, and ANN at the 1% significance level, and better than OAO and DAGSVM at the 5% significance level.

• Journal of the Korean Society of Food Science and Nutrition
• /
• v.35 no.6
• /
• pp.698-707
• /
• 2006

Precise and correct assessment of nutrient intake using appropriate dietary intake method is necessary to improve the nutritional status of the target people group. It is more likely so in elderly people since their dietary habits and inadequate nutrient intakes are of special concern even worse in rural areas. Two popular methods of gathering dietary intake are 24-hour recall and food frequency method (or food frequency questionnaire). In the present study, we conducted both 24-hour recall and food frequency method on 120 rural elderly people $(aged\;65{\sim}74\;years)$, 62 male and 58 female. The dietary intakes were analyzed and the correlation of the dietary intake between 24-hour recall and food frequency method to determine the reliability between two methods. Also each nutrient intake was compared to recommended dietary allowance (RDA) or nutrient reference value (NRV) as appropriate. Even correlation did not show significance between the two methods except for dietary fiber intake (0.65 at p<0.01) and energy-yielding nutrients which mostly showed similar results with nutrient intake level. These support the possible reliability between 24-hours record and food frequency method that is also shown on the cases of most mineral and vitamin intakes. Thus, the food frequency method used in this study for the assessment of nutrient intakes of the elderly people would be reliable for the assessment of the nutrient intake along with the 24-hour recall. Also, the present study results suggested that rural female elderly people would be under optimal nutriture status due to the lower food intake measured by 24-hour recall. The optimal food frequency method would be considered to be developed for the precise nutrient assessment.

• Journal of Korean Society of Forest Science
• /
• v.29 no.1
• /
• pp.1-19
• /
• 1976

This study has been made to make an observation regarding present status of the coal mine props which is desperately needed for coal production, despite of great shortage of the timber resources in this country, and investigate the effects of diffusion process on the decay resistances of the mine props as applied preservatives of Malenit and chromated zinc chloride. The results are as follows. 1. Present status of the coal mine props Total demand of coal mine props in the year of 1975 was approximately 456 thousand cubic meters. The main species used for mine props are conifer (mainly Pinus densiflora) and hardwood (mainly Quercus). Portions between them are half and half. With non fixed specification, wide varieties of timber in size and form are used. And volume of wood used per ton-of coal production shows also wide range from 0.017 cubic meter to 0.03 cubic meter. 2. Decay resistance test a) The oven dry weight decreased between untreated specimen and treated specimen has not shown any significantly, although it has shown some differences in average values between them. It may be caused by the shorter length of the test. b) The strength of compression test between untreated specimen and treated specimen has also shown the same results as shown in case of weight decrease. Reasons assumed are the same. c) The amounts of the extractives in one percent of sodium hydroxide (NaOH) between untreated and treated specimen have shown the large value in case of untreated specimen than that of treated. 3. The economical benifit between untreated and treated wood when applied in field has seen better in long term base in case of treated wood, although the primary cost of treated wood add a little bit more cost than that of the untreated wood.

• Radiation Oncology Journal
• /
• v.23 no.1
• /
• pp.22-31
• /
• 2005

Purpose : To conduct a nationwide survey on the principals in radiotherapy for rectal cancer, and produce a database of Korean Patterns of Care Study. Materials and Methods : We developed web-based Patterns of Care Study system and a national survey was conducted using random sampling based on power allocation methods. Eligible patients were who had postoperative radiotherapy for rectal cancer without gross residual tumor after surgical resection and without previous history of other cancer and radiotherapy to pelvis. Data of patients were Inputted to the web based PCS system by each investigators in 19 institutions. Results : Informations on 309 patients with rectal cancer who received radiotherapy between 1998 and 1999 were collected. Male to female ratio was 59 : 41, and the most common location of tumor was lower rectum ($46\%$). Preoperative CEA was checked in $79\%$ of cases and its value was higher than 6 ng/ml in $32\%$. Pathologic stage were I in $1.5\%$, II in $32\%$, III in $53\%$, and IV in $1.6\%$. Low anterior resection was the most common type of surgery and complete resection was peformed in $95\%$ of cases. Distal resection margin was less than 2 cm in $30\%$, and number of lymph node dissected was less than 12 in $31\%$. Chemotherapy was peformed in $91\%$ and most common regimen was 5-FU and leucovorine ($59\%$). The most common type of field arrangement used for the initial pelvic field was the four field box (Posterior-Right-Left) technique ($65.0\%$), and there was no AP-PA parallel opposing field used. Patient position was prone in $81.2\%$, and the boost field was used in $61.8\%$. To displace bowel outward, pressure modulating devices or bladder filling was used in $40.1\%$. Radiation dose was prescribed to isocenter in $45.3\%$ and to isodose line in 123 cases ($39.8\%$). Percent delivered dose over $90\%$ was achieved in $92.9\%$. Conclusion : We could find the Patterns of Care for the radiotherapy in Korean rectal cancer patients was similar to that of US national survey. The type of surgery and the regimen of chemotherapy were variable according to institutions and the variations of radiation dose and field arrangement were within acceptable range.

• Korean journal of food and cookery science
• /
• v.21 no.3 s.87
• /
• pp.290-300
• /
• 2005

Increased sanitation management of foodservice establishments is required because most of the reported foodborne-disease outbreaks were in the foodservice industry. The purpose of this study was to determine the important control points for good sanitation. In this study, we inspected twenty foodservice establishments in Seoul, Kyunggi, Kyungnam with a self-developed monitoring tool. These foodservice establishments included secondary schools, universities, and industries. Six of them had appointed as the HACCP-certified establishments from the Korea Food and Drug Administration. The inspection was conducted from June to August in 2002. The inspection tool consisted of nine dimensions and sixty-five items. The dimensions were 'personal sanitation', 'supply of raw food', 'food storage', 'handling of raw food and ready-to-eat', 'cleaning and sterilization', 'waste control', 'pest control', and 'control of establishment and equipment' The highest possible score of this inspection tool is 105 points. Statistical data analysis was completed using the SPSS Package(11.0) for descriptive analysis Kruskal-Wallis. The score for the secondary schools (83.6 points) was higher than for the others and number of in compliance item was 50.9 on average. Therefore, we concluded that the secondary schools' sanitation condition was good. The foodservice establishments acquired HACCP certification was 89.7 points, which was significantly higher than that of establishments not applying foodservices in total score. Instituting the HACCP system in a foodservice is very effective for sanitation management. Many out of the compliance observations were found in the dimensions of 'waste control', 'control of establishment and equipment', and 'supply of raw food' 'Clean condition of refrigerator' item was $65\%$ out of the compliance that was the highest percent in this study. 'Notify and observance of heating/reheating temperature' was $45\%$ out of compliance. Items which were over $30\%$ out of compliance were 'sterilization of knifes and chopping boards in cooking', 'education of workers', 'maintain refrigerator temperature blow $5^{\circ}C$', and 'countermeasure of infection workers' In the results, most of the foodservice establishments were poorly managed in temperature control and cross-contamination. The important control points revealed in this study were preventing contamination, cooking temperature compliance, management of raw food and refrigerator. Therefore foodservice establishments should pay attention to education and training about important control points. The systematic sanitation management monitoring tool developed in this study can be effectively applied for conducting self-inspection and improving the sanitary conditions of their own foodservice operations.

• Journal of the Korean Society of Food Science and Nutrition
• /
• v.12 no.2
• /
• pp.122-136
• /
• 1983

The effect of dietary casein, calcium, magnesium and some vegetable oils such as seasme, perilla and soybean oil on the serum cholesterol level in the rabbit were studied for a period of 5 weeks using isocalories and isonitrogenous as basal diets. The experimental rabbits fed the following basal diets containing crude protein 68.47%, carbohydrates 13.35%. fats 16.18% and vegetable oil 10%. casein 10%, calcium and magnesium according to experimental plan making. In order to calculate the feeding efficiency, protein efficiency and calorie efficiency during period, the body weight gains were measured at the same time using same balance, respectively. The results are summarized as follows. Body weight gains per week of the group fed perilla oil, calcium and basal diet were the higher than any other groups. And body weights gains per week of the group fed basal diet, vegetable oil were the lower than any other groups. In the case of efficiency of reed, protein and calorie, the efficiency ratios of the group fed perilla oil were the higher than any other groups. Especially, perilla oil and calcium diet effect on body weight gain in rabbit. In the case of serum protein, the total proteins in serum were almost same value for all the groups. Serum albumin of group fed basal diet. vegetable oil and casein were the higher than any other groups. The ${\alpha}$-globulin of the groups, fed basal diet and calcium was the lower than any other grosps. The ${\beta}$-globulins of the groups fed basad diet, perilla oil and casein were the highest value. In serum lipoprotein, lipalbumin was almost same value for the groups fed vegetable oil, but fed vegetable oil and calcium diet was the lowest value. The ${\beta}$-lipoprotein in high cholesterol level group was increased some degree, the group fed perilla oil added was lower. The ratio of ${\beta}$-lipoprotein per lipalbumin was from 0.11 to 0.26. The ratio of lipalbumin per total lipoprotein was high in calcium and soybean oil added diet. In serum triglyceride, the level of triglyceride of groups fed seasme oil or perilla oil was the higher than any othe groups, but in the group fed casein and calcium or magnesium, the level of triglyceride level was decreased. Calcium and magnesium effect on triglyceridge level lowering action. In serum total cholesterol, the group does fed vegetable oil with basal diet and casein added more, total cholesterol level increased as much as triglyceride level increased. But the group does fed perilla oil and magnesium shows total cholesterol level decreased remarkably. In the group fed basal diet with calium, the amount of serum calcium was increased, but of serum magnesium was decreased. In the case of blood glucose, the group fed basal diet and vegetable oil was decreased. According to the regression and correlation coefficient in blood components in rabbit, there are positive correlation $${\gamma}{\sim_=}1$$ between serum cholesterol and triglyceride, ${\beta}$-lipoprotein, ${\alpha}$-globulin, calcium and magnesium according to diet composition. From the above results, the serum cholesterol level lowering factors in rabbit, was the amount of triglyceride and ${\beta}$-lipoprotein which was decreased in perilla oil fed. It assumes that serum cholesterol and triglyceride level lowering factors are not only unsaturation degree of fatty acid but the amount of calcium and magnesium and the ratio calcium per magnesium 2:1 in the diet.

• Journal of Intelligence and Information Systems
• /
• v.25 no.1
• /
• pp.1-19
• /
• 2019

Artificial intelligence (AI) is one of the main driving forces leading the Fourth Industrial Revolution. The technologies associated with AI have already shown superior abilities that are equal to or better than people in many fields including image and speech recognition. Particularly, many efforts have been actively given to identify the current technology trends and analyze development directions of it, because AI technologies can be utilized in a wide range of fields including medical, financial, manufacturing, service, and education fields. Major platforms that can develop complex AI algorithms for learning, reasoning, and recognition have been open to the public as open source projects. As a result, technologies and services that utilize them have increased rapidly. It has been confirmed as one of the major reasons for the fast development of AI technologies. Additionally, the spread of the technology is greatly in debt to open source software, developed by major global companies, supporting natural language recognition, speech recognition, and image recognition. Therefore, this study aimed to identify the practical trend of AI technology development by analyzing OSS projects associated with AI, which have been developed by the online collaboration of many parties. This study searched and collected a list of major projects related to AI, which were generated from 2000 to July 2018 on Github. This study confirmed the development trends of major technologies in detail by applying text mining technique targeting topic information, which indicates the characteristics of the collected projects and technical fields. The results of the analysis showed that the number of software development projects by year was less than 100 projects per year until 2013. However, it increased to 229 projects in 2014 and 597 projects in 2015. Particularly, the number of open source projects related to AI increased rapidly in 2016 (2,559 OSS projects). It was confirmed that the number of projects initiated in 2017 was 14,213, which is almost four-folds of the number of total projects generated from 2009 to 2016 (3,555 projects). The number of projects initiated from Jan to Jul 2018 was 8,737. The development trend of AI-related technologies was evaluated by dividing the study period into three phases. The appearance frequency of topics indicate the technology trends of AI-related OSS projects. The results showed that the natural language processing technology has continued to be at the top in all years. It implied that OSS had been developed continuously. Until 2015, Python, C ++, and Java, programming languages, were listed as the top ten frequently appeared topics. However, after 2016, programming languages other than Python disappeared from the top ten topics. Instead of them, platforms supporting the development of AI algorithms, such as TensorFlow and Keras, are showing high appearance frequency. Additionally, reinforcement learning algorithms and convolutional neural networks, which have been used in various fields, were frequently appeared topics. The results of topic network analysis showed that the most important topics of degree centrality were similar to those of appearance frequency. The main difference was that visualization and medical imaging topics were found at the top of the list, although they were not in the top of the list from 2009 to 2012. The results indicated that OSS was developed in the medical field in order to utilize the AI technology. Moreover, although the computer vision was in the top 10 of the appearance frequency list from 2013 to 2015, they were not in the top 10 of the degree centrality. The topics at the top of the degree centrality list were similar to those at the top of the appearance frequency list. It was found that the ranks of the composite neural network and reinforcement learning were changed slightly. The trend of technology development was examined using the appearance frequency of topics and degree centrality. The results showed that machine learning revealed the highest frequency and the highest degree centrality in all years. Moreover, it is noteworthy that, although the deep learning topic showed a low frequency and a low degree centrality between 2009 and 2012, their ranks abruptly increased between 2013 and 2015. It was confirmed that in recent years both technologies had high appearance frequency and degree centrality. TensorFlow first appeared during the phase of 2013-2015, and the appearance frequency and degree centrality of it soared between 2016 and 2018 to be at the top of the lists after deep learning, python. Computer vision and reinforcement learning did not show an abrupt increase or decrease, and they had relatively low appearance frequency and degree centrality compared with the above-mentioned topics. Based on these analysis results, it is possible to identify the fields in which AI technologies are actively developed. The results of this study can be used as a baseline dataset for more empirical analysis on future technology trends that can be converged.