• Journal of Oral Medicine and Pain
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• v.31 no.3
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• pp.199-210
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• 2006

The epidemiological researches on the inpatients hospitalized at the oral medicine ward have been continuously carried out since 1970, and most researches have been performed by centering around the oral medicine wards of college hospitals. Numerous specialists have been produced after the establishment of oral medicine, and they have been active in various fields. As dental clinics have gotten bigger, the function of oral medicine in the secondary clinics is being brought out. As admissive channel, case features, case composition and otherwise have not been researched for a long time, the related researches should be carried out from now on. Hereupon, this study was carried out by targeting the 100 inpatients hospitalized at the oral medicine ward of Sun Hospital located in Daejeon Korea, through questionnaire. As the result, the following results were derived. 1. The ages of the inpatients in Sun Hospital were $29.21{\pm}11.31$ on the average; 71 females' mean average was $29.63{\pm}11.29$ and 29 males' mean average was $28.17{\pm}11.48$. In regard of school career, the patients who finished high-school course or higher accounted for 78%; the patients' school career seemed to be relatively high. The patients who complained of temporomandibular pain accounted for the highest proportion with 65%. In motivation to visit this hospital, internet surfing was 11%, mass media was 10%, acquaintance's introduction was 38%. The patients, who were hospitalized at another hospital due to the same symptom, accounted for 56%. The dental clinics, which made the patients visit this hospital, accounted for 20%. The patients, who were previously aware that the present symptom should be treated by oral medicine, accounted for 38%. The patients, who were not aware of the fact in advance, were 62%. The respondents of 51% answered that they were aware of the fact one month or below before hospitalization. 2. The patients, who complained of craniocervical ache, accounted for 58%; the patients, whose ache aches affect dailylife, were 22%. Continuous ache was 14% and intermittent ache was 68%, and dull pain was 23%. 3. Life variations were compared with each other by using SRRS (Social Readjustment Rating Scale). In consequence, the variation within 3 years indicated a significant difference in the both groups but the variation within 6 months did not indicate any differences. 4. In regard of the questionnaire on the incidents happened for a week, the ache-group was compared with the group free from the ache. As the result, the number of strain arisen for a week, the decrease of favorite works and sudden fear indicated a significant difference. Pleasant feeling and the decrease of interests in looks did not indicate a significant difference, but came close to the significance. 5. In the questionnaire on impatience, the ache-group indicated higher value but there was not a significant difference. 6. In the questionnaire on the symptoms caused by stress, the two groups indicated significant differences in the item of 'the teethridge itches and feels a tooth rising' and 'the occiput or the nape is stiff.' In the item 'the inside of the cheek or the teethridge are widely peeled off, accompanied with ache and hemorrhage', 'the face has acne or pimple' and 'headache frequently attacks', a significant difference was not observed but the two groups came close to the significance.

• Korean Journal of Agricultural Science
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• v.19 no.1
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• pp.51-64
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• 1992

This experiment was carried out to elucidate the effects of the thyroid function on lactation in female rats. One hundred and five female rats, whose body weight was approximately 250g with normal parturition, were divided into 3.5 THY, 35 PTU, and 35 CON. The $30{\mu}g$ L-thyroxine per rat was administered subcutaneously for the THY group with 3-days intervals arid 0.03% propylthiouracil solution was drunk for the PTU group. After the treatments body weight, thyroid weights and prolactin levels in serum, and histological changes in thyroid and mammary gland were investigated for 3 weeks with 3-days interval. The results obtained were as follows 1. The body weights of PTU group were lower than those of CON arid THY groups. The changes in body weights were significant between 3 and 6 days and between 15 and 18 days. 2. Differences in thyroid weight among the groups were significant after 9 days, The thyroid weights of PTU group were much higher than those of CON and THY group. 3. The follicular epithelia of PTU group after 6 days showed cuboidal phenomena which were accompanied by hypertrophy and hyperplasia, and this phenomena continued until post weaning period. Those of THY group after 9 days showed a squamous degeneration together with pyknosis. 4. The prolactin concentrations of THY group were higher than the other groups after 12 days. and those of CON group were higher than the others after 18 days. However, those of PTU group were lower all through the period. 5. The secretary epithelial cells of THY and CON groups became cuboidal after 12 days, but after 15 days the differentiation of mammary tissue was progressing in THY group faster than CON group. The degeneration of mammary tissue were observed in PTU group as time lapses, so after 15 days the exfoliation of secretory epithelium and atrophy of alveolus were recognized. 6. The body weights of offspring for all experimental groups were increasing as time lapses, but the values for PTU group were markedly lower than the others.

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

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

• The Journal of Korean Obstetrics and Gynecology
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• v.30 no.4
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• pp.18-44
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• 2017

Purpose: The object of this study was to observe the anti-climacterium activity of Gagamguibiondam-tang (GGOT) on ovariectomized (OVX) rats, a well-documented rodent models resembles with women postmenopausal climacterium symptoms, as including cardiovascular diseases, obesity, hyperlipidemia, osteoporosis, organ steatosis and mental disorders. Methods: In this study, anti-climacteric effects were evaluated separated into three categories; 1) anti-obese, 2) anti-uterine atrophy and 3) anti-osteoporotic effects. Five groups were used (8 rats in each group); sham control, OVX control, GGOT 500, 250 and 125 mg/kg administered groups. Twenty-eight days after bilateral OVX surgery, GGOT were orally administered, once a day for 84 days, and then the changes on the body weight and gain during experimental periods, serum estradiol levels, abdominal fat pad and uterus weights with histopathology of abdominal fat pads (total thickness and mean adipocyte diameters) and uterus (total, epithelial and mucosal thickness, percentages of uterine gland regions) for anti-obese and estrogenic effects. In addition, femur, tibia and fourth or fifth lumbar vertebrae (L4 or L5) wet, dry and ash weights, mineral density (BMD), bone strength (failure load), serum osteocalcin and bone specific alkaline phosphatase (bALP) contents, histological and histomorphometrical analyses - bone mass and structure with bone resorption, were monitored for anti-osteoporosis activity. Results: As a result of OVX, noticeable increases of body weight and gains, food and water consumption, weights of abdominal fat pad deposited in dorsal abdominal cavity, serum osteocalcin levels were demonstrated in this experiment with decrease of uterus, femur, tibia and L5 weights, serum bALP and estradiol levels. In addition, marked hypertrophic changes of adipocytes located in deposited abdominal fat pads, uterine disused atrophic changes, decreases of bone mass and structures of femur, tibia and L4 were also observed in OVX control rats with dramatic increases of bone resorption markers, the Ocn and OS/BS at histopathological and histomorphometrical analysis in this study as compared with sham-operated control rats, suggesting the estrogen-deficient climacterium symptoms - obese and osteoporosis were induced by OVX, respectively. However, these estrogen-deficient climacterium symptoms induced by bilateral OVX in rats were significantly inhibited by 84 days of continuous oral treatment of GGOT 500, 250 and 125 mg/kg, respectively. Especially, GGOT 500, 250 and 125 mg/kg showed clear dose-dependent inhibitory activities on the OVX-induced climacterium signs. Conclusion: The results suggest that oral administration of GGOT 500, 250 and 125 mg/kg has clear dose-dependent favorable anti-climacterium effects - estrogenic, anti-obese and anti-osteoporotic activities in OVX rats in this experiment.

• The Korean Journal of Archival Studies
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• no.26
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• pp.103-149
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• 2010

Documentation strategy has been experimented in various subject areas and local regions since late 1980's when it was proposed as archival appraisal and selection methods by archival communities in the United States. Though it was criticized to be too ideal, it needs to shed new light on the potentialities of the strategy for documenting local regions in digital environment. The purpose of this study is to analyse the implementation issues of documentation strategy and to suggest the directions for documenting local regions of Korea through the application of the strategy. The documentation strategy which was developed more than twenty years ago in mostly western countries gives us some implications for documenting local regions even in current digital environments. They are as follows; Firstly, documentation strategy can enhance the value of archivists as well as archives in local regions because archivist should be active shaper of history rather than passive receiver of archives according to the strategy. It can also be a solution for overcoming poor conditions of local archives management in Korea. Secondly, the strategy can encourage cooperation between collecting institutions including museums, libraries, archives, cultural centers, history institutions, etc. in each local region. In the networked environment the cooperation can be achieved more effectively than in traditional environment where the heavy workload of cooperative institutions is needed. Thirdly, the strategy can facilitate solidarity of various groups in local region. According to the analysis of the strategy projects, it is essential to collect their knowledge, passion, and enthusiasm of related groups to effectively implement the strategy. It can also provide a methodology for minor groups of society to document their memories. This study suggests the directions of documenting local regions in consideration of current archival infrastructure of Korean as follows; Firstly, very selective and intensive documentation should be pursued rather than comprehensive one for documenting local regions. Though it is a very political problem to decide what subject has priority for documentation, interests of local community members as well as professional groups should be considered in the decision-making process seriously. Secondly, it is effective to plan integrated representation of local history in the distributed custody of local archives. It would be desirable to implement archival gateway for integrated search and representation of local archives regardless of the location of archives. Thirdly, it is necessary to try digital documentation using Web 2.0 technologies. Documentation strategy as the methodology of selecting and acquiring archives can not avoid subjectivity and prejudices of appraiser completely. To mitigate the problems, open documentation system should be prepared for reflecting different interests of different groups. Fourth, it is desirable to apply a conspectus model used in cooperative collection management of libraries to document local regions digitally. Conspectus can show existing documentation strength and future documentation intensity for each participating institution. Using this, documentation level of each subject area can be set up cooperatively and effectively in the local regions.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.161-177
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• 2019

In this paper, we study the performance improvement of the answer extraction in Question-Answering system by using sentence dependency parsing result. The Question-Answering (QA) system consists of query analysis, which is a method of analyzing the user's query, and answer extraction, which is a method to extract appropriate answers in the document. And various studies have been conducted on two methods. In order to improve the performance of answer extraction, it is necessary to accurately reflect the grammatical information of sentences. In Korean, because word order structure is free and omission of sentence components is frequent, dependency parsing is a good way to analyze Korean syntax. Therefore, in this study, we improved the performance of the answer extraction by adding the features generated by dependency parsing analysis to the inputs of the answer extraction model (Bidirectional LSTM-CRF). The process of generating the dependency graph embedding consists of the steps of generating the dependency graph from the dependency parsing result and learning the embedding of the graph. In this study, we compared the performance of the answer extraction model when inputting basic word features generated without the dependency parsing and the performance of the model when inputting the addition of the Eojeol tag feature and dependency graph embedding feature. Since dependency parsing is performed on a basic unit of an Eojeol, which is a component of sentences separated by a space, the tag information of the Eojeol can be obtained as a result of the dependency parsing. The Eojeol tag feature means the tag information of the Eojeol. The process of generating the dependency graph embedding consists of the steps of generating the dependency graph from the dependency parsing result and learning the embedding of the graph. From the dependency parsing result, a graph is generated from the Eojeol to the node, the dependency between the Eojeol to the edge, and the Eojeol tag to the node label. In this process, an undirected graph is generated or a directed graph is generated according to whether or not the dependency relation direction is considered. To obtain the embedding of the graph, we used Graph2Vec, which is a method of finding the embedding of the graph by the subgraphs constituting a graph. We can specify the maximum path length between nodes in the process of finding subgraphs of a graph. If the maximum path length between nodes is 1, graph embedding is generated only by direct dependency between Eojeol, and graph embedding is generated including indirect dependencies as the maximum path length between nodes becomes larger. In the experiment, the maximum path length between nodes is adjusted differently from 1 to 3 depending on whether direction of dependency is considered or not, and the performance of answer extraction is measured. Experimental results show that both Eojeol tag feature and dependency graph embedding feature improve the performance of answer extraction. In particular, considering the direction of the dependency relation and extracting the dependency graph generated with the maximum path length of 1 in the subgraph extraction process in Graph2Vec as the input of the model, the highest answer extraction performance was shown. As a result of these experiments, we concluded that it is better to take into account the direction of dependence and to consider only the direct connection rather than the indirect dependence between the words. The significance of this study is as follows. First, we improved the performance of answer extraction by adding features using dependency parsing results, taking into account the characteristics of Korean, which is free of word order structure and omission of sentence components. Second, we generated feature of dependency parsing result by learning - based graph embedding method without defining the pattern of dependency between Eojeol. Future research directions are as follows. In this study, the features generated as a result of the dependency parsing are applied only to the answer extraction model in order to grasp the meaning. However, in the future, if the performance is confirmed by applying the features to various natural language processing models such as sentiment analysis or name entity recognition, the validity of the features can be verified more accurately.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.197-218
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• 2019

In addition to economic growth and national income increase, China is also experiencing rapid growth in consumption of cosmetics. About 67% of the total trade volume of Chinese cosmetics is made by e-commerce and especially K-Beauty products, which are Korean cosmetics are very popular. According to previous studies, 80% of consumer goods such as cosmetics are affected by the word of mouth information, searching the product information before purchase. Mostly, consumers acquire information related to cosmetics through comments made by other consumers on SNS such as SINA Weibo and Wechat, and recently they also use information about beauty related video channels. Most of the previous online word-of-mouth researches were mainly focused on media itself such as Facebook, Twitter, and blogs. However, the informational characteristics and the expression forms are also diverse. Typical types are text, picture, and video. This study focused on these types. We analyze the unstructured data of SINA Weibo, the SNS representative platform of China, and Meipai, the video platform, and analyze the impact of K-Beauty brand sales by dividing online word-of-mouth information with quantity and direction information. We analyzed about 330,000 data from Meipai, and 110,000 data from SINA Weibo and analyzed the basic properties of cosmetics. As a result of analysis, the amount of online word-of-mouth information has a positive effect on the sales of cosmetics irrespective of the type of media. However, the online videos showed higher impacts than the pictures and texts. Therefore, it is more effective for companies to carry out advertising and promotional activities in parallel with the existing SNS as well as video related information. It is understood that it is important to generate the frequency of exposure irrespective of media type. The positiveness of the video media was significant but the positiveness of the picture and text media was not significant. Due to the nature of information types, the amount of information in video media is more than that in text-oriented media, and video-related channels are emerging all over the world. In particular, China has made a number of video platforms in recent years and has enjoyed popularity among teenagers and thirties. As a result, existing SNS users are being dispersed to video media. We also analyzed the effect of online type of information on the online cosmetics sales by dividing the product type of cosmetics into basic cosmetics and color cosmetics. As a result, basic cosmetics had a positive effect on the sales according to the number of online videos and it was affected by the negative information of the videos. In the case of basic cosmetics, effects or characteristics do not appear immediately like color cosmetics, so information such as changes after use is often transmitted over a period of time. Therefore, it is important for companies to move more quickly to issues generated from video media. Color cosmetics are largely influenced by negative oral statements and sensitive to picture and text-oriented media. Information such as picture and text has the advantage and disadvantage that the process of making it can be made easier than video. Therefore, complaints and opinions are generally expressed in SNS quickly and immediately. Finally, we analyzed how product diversity affects sales according to online word of mouth information type. As a result of the analysis, it can be confirmed that when a variety of products are introduced in a video channel, they have a positive effect on online cosmetics sales. The significance of this study in the theoretical aspect is that, as in the previous studies, online sales have basically proved that K-Beauty cosmetics are also influenced by word-of-mouth. However this study focused on media types and both media have a positive impact on sales, as in previous studies, but it has been proven that video is more informative and influencing than text, depending on media abundance. In addition, according to the existing research on information direction, it is said that the negative influence has more influence, but in the basic study, the correlation is not significant, but the effect of negation in the case of color cosmetics is large. In the case of temporal fashion products such as color cosmetics, fast oral effect is influenced. In practical terms, it is expected that it will be helpful to use advertising strategies on the sales and advertising strategy of K-Beauty cosmetics in China by distinguishing basic and color cosmetics. In addition, it can be said that it recognized the importance of a video advertising strategy such as YouTube and one-person media. The results of this study can be used as basic data for analyzing the big data in understanding the Chinese cosmetics market and establishing appropriate strategies and marketing utilization of related companies.

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

• Journal of the Daesoon Academy of Sciences
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• v.27
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• pp.135-169
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• 2016

While examining the religious ideas implied by Jeungsan's Great Works of the Reordering of Universe, we find special ideas which cannot be found in any other religions, and these ideas are presented in diverse ways. Most of all, the representative idea is that of human nobility; a distinctive idea which makes Daesoonjinrihoe different from other religions. Thus, this research focuses on the following questions: when was Human Nobility concretely realized? What kind of organic relationship does human nobility have between the divine world and the world of humanity? In light of the forthcoming Era of Human Nobility, what are some concrete images which can be drawn from the interaction between the realms of heaven and humanity wherein preordinations are plotted in heaven and then carried out by humankind? Prior to formulating my own sense of the subject matter, I consulted 43 previous discussions and dissertations and arranged them chronologically so as to examine their correlation. From these sources and my own insights, I was able to gain a sense of the starting point of the era of human nobility and its tenor. I have found the following problems in previous research on the uniqueness and distinctness of human nobility: ①The conceptual undertones of human nobility have not been adequately gleaned. ②There do not seem to be any dissertations which examine the way in which human nobility is connected with the doctrines of the creative conjunction between yin and yang, the harmonious union of divine beings and human beings, and the resolution of grievances for mutual beneficence. ③In most dissertations, not only is the starting point of the Era of Human Nobility regarded as concurrent with the start of the 50,000 years of earthly paradise in the Later World, but also the point of division between the former world and the later world is widely disputed. ④In-depth and fully realized studies dealing with the subject of human nobility are not easily found. ⑤There is little sense of progression in the research on human nobility because scholars are not sufficiently engage with one another to achieve common consensus. Therefore, in this dissertation, I have provided answers to the problems I discovered in previous research. I have developed my own tenor as follows: ①By giving priority to the Jeongyeong, I have closely investigated the period which divides the Former World and the Later World. Then, I produced a chronological timeline to demonstrate the progression: the Former World → the Era of the Resolution of Grievances → the Later World. This aids in the comprehension of human nobility. ②The Era of Human Nobility was preceeded by the opening of the Era of the Resolution of Grievances of human world which began in 1901. Human nobility is stipulated as a regulatory system for the universe set in motion by the opening the Era of Resolution of Grievances. ③While synthetically examining the aspects of transition which enable the Ear of Human Nobility to be realized, the period to be studied is stipulated as beginning from 1901 and ending at the start of the Later World. The subjects are defined as the flowing from Jeungsan, the first leader of human nobility, to the noble individuals empowered by Dao and the noble populace. In the Era of Human Nobility, studying the transition process by which human nobility is realized requires delving into the resolution of grievances. Although this method is essential to understanding Daesoon ideas, in actuality it does not hinge upon speculative exegetical theorizing but instead it was gained through eisegetical rigor.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.155-174
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• 2022

From January 2020 to October 2021, more than 500,000 academic studies related to COVID-19 (Coronavirus-2, a fatal respiratory syndrome) have been published. The rapid increase in the number of papers related to COVID-19 is putting time and technical constraints on healthcare professionals and policy makers to quickly find important research. Therefore, in this study, we propose a method of extracting useful information from text data of extensive literature using LDA and Word2vec algorithm. Papers related to keywords to be searched were extracted from papers related to COVID-19, and detailed topics were identified. The data used the CORD-19 data set on Kaggle, a free academic resource prepared by major research groups and the White House to respond to the COVID-19 pandemic, updated weekly. The research methods are divided into two main categories. First, 41,062 articles were collected through data filtering and pre-processing of the abstracts of 47,110 academic papers including full text. For this purpose, the number of publications related to COVID-19 by year was analyzed through exploratory data analysis using a Python program, and the top 10 journals under active research were identified. LDA and Word2vec algorithm were used to derive research topics related to COVID-19, and after analyzing related words, similarity was measured. Second, papers containing 'vaccine' and 'treatment' were extracted from among the topics derived from all papers, and a total of 4,555 papers related to 'vaccine' and 5,971 papers related to 'treatment' were extracted. did For each collected paper, detailed topics were analyzed using LDA and Word2vec algorithms, and a clustering method through PCA dimension reduction was applied to visualize groups of papers with similar themes using the t-SNE algorithm. A noteworthy point from the results of this study is that the topics that were not derived from the topics derived for all papers being researched in relation to COVID-19 (