Retrospect and prospect of political geography and general-synoptic part of human geography in Korea (한국 정치지리학과 인문지리학 일반 50년의 회고)
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- Journal of the Korean Geographical Society
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- v.31 no.2
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- pp.295-308
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- 1996
1. Retrospect of Political Geographic Studies since Liberation, 1945 : 1) Period from 1945 to mid 1960s : There was not political geography as a science in Korea at the time of liberation from Japan 1945. At that time were not pure political geographers in Korea. In 1947, Moon-Hwa Pyo, economics professor, published a book titled Outline of Korean Geopolitics. This book was a first one in the field of political geography and available at that time in the logical descriptions. Bok-Hyon Choi was a first political geographer who in 1959 wrote a book titled Political geography for the collegians of Seoul National University. Professor Choi introduced American-style political geography through the book above mentioned. In 1963, Kie-Joo Hyong published an article titled "Korean Unification: Possibility from the Geopolitical Viewpoint" which was a first article published by Korean young scholar who studied geography in this country. 2) Period from late 1960s to late 1980s : Both Yoon Cha and Duck-Soon Im published frequently several articles of political geography or geopolitics respectively in 1968-1969. And they issued geopolitical disputes on Korean geopolitical structure and an application of rimland theory to Korean peninsula in 1969 through a magazine named Joung-Kyong Younku (the political and economic researches). The disputes played an important role of showing political geography (or geopolitics) to political sciences especially international political Science. Active researches still continued in 1970s. In that atmosphere the first Korean book of political geography written by a post-liberation scholar (Duck-Soon Im) titled Principles of Political Geography was published in 1973. This book was influenced much by American political geography after Second World War. In 1980s, the researches continued more actively. Especially administrative districts, capital cities, and sub-capital cities were frequently studied during this period. 3) Period from late 1980s to Present: Recent Studies : 1985 was a year of much production of articles of political geography. The first Ph.D thesis of political geography published in the same year in our country. And since 1985 produced many M.A. articles. Several categories of esearches of political geography was made in the period from late 1980s to present. Capital cities, Korean unification, administrative districts, urban politics, elections, sub-capital cities, and defense walls were important research categories. Reviewing the researches from 1945 to present. I found eight categories of political geography in Korea: capital cities, administrative districts, geopolitical structure of Korean peninsula, division and unification of Korea, sub-capital cities, defense walls, elections, and urban politics. Each category includes several scholars respectiveiy. 2. Study Tasks and Prospects in Korean Political Geography: In relation to Korean circumstances there are three study-tasks. The first task of Korean people is unification of two Koreas. Political geographers of Korea must al survey titled Survey Methods of Human Geography for collegians. This book was first one on survey part in Korea. The book however, is insufficient in comprehensiveness in aspects too. I think that the important tasks of general-synoptic human geography in Korea are \circled1 publication of comprehensive books of human geography in the aspects and methodologies for collegians and \circled2 acceptance of academic world of human geography in Korea of variety in methodologies of human geography for future progress. progress.
The organization for managing records and archives did not emerge together with the founding of the Chinese Communist Party. Such management became active with the establishment of the Department of Documents (文書科) and its affiliated offices overseeing reading and safekeeping of official papers, after the formation of the Central Secretariat(中央秘書處) in 1926. Improving the work of the Secretariat's organization became the focus of critical discussions in the early 1930s. The main criticism was that the Secretariat had failed to be cognizant of its political role and degenerated into a mere "functional organization." The solution to this was the "politicization of the Secretariat's work." Moreover, influenced by the "Rectification Movement" in the 1940s, the party emphasized the responsibility of the Resources Department (材料科) that extended beyond managing documents to collecting, organizing and providing various kinds of important information data. In the mean time, maintaining security with regard to composing documents continued to be emphasized through such methods as using different names for figures and organizations or employing special inks for document production. In addition, communications between the central political organs and regional offices were emphasized through regular reports on work activities and situations of the local areas. The General Secretary not only composed the drafts of the major official documents but also handled the reading and examination of all documents, and thus played a central role in record processing. The records, called archives after undergoing document processing, were placed in safekeeping. This function was handled by the "Document Safekeeping Office(文件保管處)" of the Central Secretariat's Department of Documents. Although the Document Safekeeping Office, also called the "Central Repository(中央文庫)", could no longer accept, beginning in the early 1930s, additional archive transfers, the Resources Department continued to strengthen throughout the 1940s its role of safekeeping and providing documents and publication materials. In particular, collections of materials for research and study were carried out, and with the recovery of regions which had been under the Japanese rule, massive amounts of archive and document materials were collected. After being stipulated by rules in 1931, the archive classification and cataloguing methods became actively systematized, especially in the 1940s. Basically, "subject" classification methods and fundamental cataloguing techniques were adopted. The principle of assuming "importance" and "confidentiality" as the criteria of management emerged from a relatively early period, but the concept or process of evaluation that differentiated preservation and discarding of documents was not clear. While implementing a system of secure management and restricted access for confidential information, the critical view on providing use of archive materials was very strong, as can be seen in the slogan, "the unification of preservation and use." Even during the revolutionary movement and wars, the Chinese Communist Party continued their efforts to strengthen management and preservation of records & archives. The results were not always desirable nor were there any reasons for such experiences to lead to stable development. The historical conditions in which the Chinese Communist Party found itself probably made it inevitable. The most pronounced characteristics of this process can be found in the fact that they not only pursued efficiency of records & archives management at the functional level but, while strengthening their self-awareness of the political significance impacting the Chinese Communist Party's revolution movement, they also paid attention to the value possessed by archive materials as actual evidence for revolutionary policy research and as historical evidence of the Chinese Communist Party.
Selecting high-quality information that meets the interests and needs of users among the overflowing contents is becoming more important as the generation continues. In the flood of information, efforts to reflect the intention of the user in the search result better are being tried, rather than recognizing the information request as a simple string. Also, large IT companies such as Google and Microsoft focus on developing knowledge-based technologies including search engines which provide users with satisfaction and convenience. Especially, the finance is one of the fields expected to have the usefulness and potential of text data analysis because it's constantly generating new information, and the earlier the information is, the more valuable it is. Automatic knowledge extraction can be effective in areas where information flow is vast, such as financial sector, and new information continues to emerge. However, there are several practical difficulties faced by automatic knowledge extraction. First, there are difficulties in making corpus from different fields with same algorithm, and it is difficult to extract good quality triple. Second, it becomes more difficult to produce labeled text data by people if the extent and scope of knowledge increases and patterns are constantly updated. Third, performance evaluation is difficult due to the characteristics of unsupervised learning. Finally, problem definition for automatic knowledge extraction is not easy because of ambiguous conceptual characteristics of knowledge. So, in order to overcome limits described above and improve the semantic performance of stock-related information searching, this study attempts to extract the knowledge entity by using neural tensor network and evaluate the performance of them. Different from other references, the purpose of this study is to extract knowledge entity which is related to individual stock items. Various but relatively simple data processing methods are applied in the presented model to solve the problems of previous researches and to enhance the effectiveness of the model. From these processes, this study has the following three significances. First, A practical and simple automatic knowledge extraction method that can be applied. Second, the possibility of performance evaluation is presented through simple problem definition. Finally, the expressiveness of the knowledge increased by generating input data on a sentence basis without complex morphological analysis. The results of the empirical analysis and objective performance evaluation method are also presented. The empirical study to confirm the usefulness of the presented model, experts' reports about individual 30 stocks which are top 30 items based on frequency of publication from May 30, 2017 to May 21, 2018 are used. the total number of reports are 5,600, and 3,074 reports, which accounts about 55% of the total, is designated as a training set, and other 45% of reports are designated as a testing set. Before constructing the model, all reports of a training set are classified by stocks, and their entities are extracted using named entity recognition tool which is the KKMA. for each stocks, top 100 entities based on appearance frequency are selected, and become vectorized using one-hot encoding. After that, by using neural tensor network, the same number of score functions as stocks are trained. Thus, if a new entity from a testing set appears, we can try to calculate the score by putting it into every single score function, and the stock of the function with the highest score is predicted as the related item with the entity. To evaluate presented models, we confirm prediction power and determining whether the score functions are well constructed by calculating hit ratio for all reports of testing set. As a result of the empirical study, the presented model shows 69.3% hit accuracy for testing set which consists of 2,526 reports. this hit ratio is meaningfully high despite of some constraints for conducting research. Looking at the prediction performance of the model for each stocks, only 3 stocks, which are LG ELECTRONICS, KiaMtr, and Mando, show extremely low performance than average. this result maybe due to the interference effect with other similar items and generation of new knowledge. In this paper, we propose a methodology to find out key entities or their combinations which are necessary to search related information in accordance with the user's investment intention. Graph data is generated by using only the named entity recognition tool and applied to the neural tensor network without learning corpus or word vectors for the field. From the empirical test, we confirm the effectiveness of the presented model as described above. However, there also exist some limits and things to complement. Representatively, the phenomenon that the model performance is especially bad for only some stocks shows the need for further researches. Finally, through the empirical study, we confirmed that the learning method presented in this study can be used for the purpose of matching the new text information semantically with the related stocks.
It has been suggested that Jeungsan's prophetic poem that starts with the verse "For about seven or eight years, there will be a castle in the ancient country [七八年間古國城] ⋯" originally comes from Prophecies of Jeong Gam (鄭鑑錄). Despite Jeungsan, himself, obviously having been critical of that text, this claim has become the basic grounds for discourse suggesting that Jeungsan was not only interested in Prophecies of Jeong Gam but also considerably influenced by the text. However, the claim itself was formulated due to misunderstandings of the Chinese poems that had been included in A Compilation of Secret Prophecies Hidden in the Family-clan of Seogye (西溪家臧訣). These poems pursue a different ideological orientation than the poem from Prophecies of Jeong Gam. Ultimately, the Chinese poem in the verse 84 the chapter titled, Prophetic Elucidations in The Canonical Scripture of Daesoon Jinrihoe cannot provide a basis for the claim that Jeungsan was strongly influenced by Prophecies of Jeong Gam. This claim that Prophecies of Jeong Gam made a deep impact on Jeungsan and Daesoon Thought was based on three other texts outside of those that appear within verse 84 of Prophetic Elucidations. The first supposedly-related line is: "Heaven opens at the period of the Rat (Ja 子), Earth opens at the period of the Ox (Chuk 丑), humankind starts at the period of the Tiger (Ihn 寅)." This line comes from from Shao Kangjie's Book of Supreme World Ordering Principles (皇極經世), and the line could be quoted idiomatically as an expression in the Joseon Dynasty. Accordingly, attempts to relate Daesoon Thought to Prophecies of Jeong Gam are a distortion that arise from the assumption that Jeungsan had a significant interest in Prophecies of Jeong Gam. The second related line is "At the foot of Mount Mother (母岳山), a golden icon of Buddha has the ability to speak [母岳山下 金佛能言]." That line is nearly identical to the verse "On the summit of Mount Mother, a golden icon of Buddha has the ability to speak [母岳山頭 金佛能言]." Yet, Jeungsan changed '頭 (du, the summit)' to '下 (ha, the foot or under)' and express his own unique religious prophecy. This allusion to the prophecies of Jeong Gam is actually a criticism designed to disprove the earlier prophecy. Third, is the verse, "The form of Buddhism, creation of daoism, and propriety of Confucianism [佛之形體仙之造化儒之凡節]," which is characteristically related to Daesoon Thought. This verse can only be found in the prophetic text, Prophecies of Chochang (蕉蒼訣), and it is provided a main source when alleging that Prophecies of Jeong Gam was an influence on Daesoon Thought. However, considering the context of Prophecies of Chochang and the year of its publication (it is assumed to be compiled after 1950s), this does not hold water as Jeungsan had already passed into Heaven several decades before that time. This disqualifies the verse from being a basis for asserting Prophecies of Jeong Gam as an influence on Daesoon Thought. Contrary to the original assertion, there is a considerable amount of evidence that Prophecies of Chochang absorbed aspects of Daesoon Thought, which were simply revised in a novel way. There is no truly compelling evidence underpinning the argument that Prophecies of Jeong Gam had a unilateral impact on Daesoon Thought. There seems to be a great deal of confusion and numerous misinterpretations on this matter. Therefore, the claim that Daesoon Thought, as developed by Jeungsan, was influenced by the discourse on dynastic revolution and feng shui contained in Prophecies of Jeong Gam should be re-examined at the level of its very premise.
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 (