• Journal of Korean Philosophical Society
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• v.129
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• pp.315-339
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• 2014

Diese Abhandlung untersucht Jacobis ${\ddot{U}}ber$ die Lehre Spinoza und den von diesem veranlassten Spinoza-Streit. Damit sie $enth{\ddot{u}}llt$ zuerst Jacobischen Zusammenhang zwischen transzent und immanent und folgt auf seine Wirkungsgeschichte in der Moderne. Ich rekonstruiere den Streit zwischen Jacobi und Lessing und danach interpretiere dessen Rezeption durch Hegel und Schleiermacher. Lessing stellt anstatt der traditionellen Begriffe der Gottheit ἑν ${\kappa}{\alpha}{\iota}$ ${\pi}{\alpha}{\nu}$ auf. $Demgegen{\ddot{u}}ber$ behauptet Jacobi Salto mortale um ihn ${\ddot{u}}berschreiten$ zu $k{\ddot{o}}nnen$, indem er Lessing als Pantheist und Atheist bestimmt. Salto mortale bei Jacobi ist der Sprung zu dem ${\ddot{U}}bernat{\ddot{u}}rlichen$ und dem Glaube. Der Streit zwischen Jacobi und Lessing ist der zwischen dem Naturalismus und ${\ddot{U}}bernaturalismus$ und $dar{\ddot{u}}berhinaus$ der zwischen dem Athismus und Theismus. $W{\ddot{a}}hrend$ die Natur der Inbegriff der Bedingten ist, ist Gott der absolute Anfang der Natur $au{\ss}erhalb$ des Naturzusammenhangs. $W{\ddot{a}}hrend$ Spinoza Gott im $nat{\ddot{u}}rlichen$ Zusammenhang begreift, $fa{\ss}t$ Jacobi den im ${\ddot{u}}bernat{\ddot{u}}rlichen$ auf. Deus sive natura bei Spinoza $ver{\ddot{a}}ndert$ sich Gott im Menschen bei Jacobi. Gott im Menschen ist nichts anders als das Prinzip des Lebens und das aller Vernuft. In diesem Zusammenhang $fa{\ss}t$ Hegel Gott als Geist denn Subjekt des Lebens auf und $h{\ddot{a}}lt$ das Wesen des Geistes $f{\ddot{u}}r$ die sich selbst vermittelnde Bewegung. Dies zeigt sich als die Spinoza ${\ddot{u}}berbietende$ Immanenzphilosophie. $Demgegen{\ddot{u}}ber$ behauptet Schleiermacher die Einheit des Endlichen und Unendlichen in der $religi{\ddot{o}}sen$ Anschuung. Die Verbindung von Mensch und Gott ist die im Endlichen immanent bleibende Anschauung der $g{\ddot{o}}ttlichen$ Eigenschaft. Dies zeigt das transzendente im immanenten.

• Sim-seong Yeon-gu
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• v.33 no.1
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• pp.1-60
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• 2018

The paper was inspired by Jung's words in the Red Book "just as Christ tormented the flesh through the spirit, the God of this time will torment the spirit through the flesh." I propose that the new form of torment in this era could be eroticism as a way of the individuation process because it seems to be one of a very few ways left to modern men to grasp the sense of permanence, the essence of the divine, without religion because of its peculiar nature of transcendence. I suppose that it is not only a man who is tortured but also god is in torment since the divine needs a man as a womb for his incarnation. Therefore I suggest that man and god are fated to seduce each other to be redeemed by each other. I imagine that Eros with numinous sexuality seduces a man who has potentials for the god's incarnation and who would be willing to give in to the god's demand. This god needs a man who desires his essence of perpetuity, the eternal water of life, in ecstasy. Thus the purpose of the divine's seduction is to make a man awake from unconsciousness to pursue god himself, namely the individuation process. I call such divine seduction "eroticism of god" There seem to be a certain type of people who are destined to live eroticism as a way of individuation process. Through investigations, a melancholic tendency appears to be suitable for this type of individuation. Melancholia is deeply related to the poignant awareness of impermanence as the existential condition, which is a precondition for seeking permanence through eroticism. Melancholia essentially causes deep longing for eternity that bears fulfillment, which exists in eroticism, so melancholic agony seems inevitable for eroticism as the path for individuation in that, without knowing about deficiency, we never seek what is lacking in us. It can also be viewed that while a lover is driven to seduce lost love, what actually waits to become seduced for redemption is the god of love itself behind the human beloved. Man and god are fated to seduce each other for redemption. I suppose that the initiation to Eros implies how to seduce Eros. In a woman's psyche, psychological virginity is one of the essential qualities that her ego needs to attain. To the male it is vital to live his sensuality thoroughly and to experience his own and his lover's emotions to their limit. It cannot be an easy task because it demands us to give up our egotism entirely. Through eroticism, unconsciousness seduces us to make us live life as a whole. The god of love brings powerful sexuality as a means of "spiritual crisis" to redeem our lukewarm soul. Only a few can withstand the experience since it requires a strong will to bear the brunt of the sword despite the keen awareness that it may leave us bleeding in pain.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.95-118
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• 2017

Recent centrally the downtown area, the transaction between the row housing and multiplex housing is activated and platform services such as Zigbang and Dabang are growing. The row housing and multiplex housing is a blind spot for real estate information. Because there is a social problem, due to the change in market size and information asymmetry due to changes in demand. Also, the 5 or 25 districts used by the Seoul Metropolitan Government or the Korean Appraisal Board(hereafter, KAB) were established within the administrative boundaries and used in existing real estate studies. This is not a district classification for real estate researches because it is zoned urban planning. Based on the existing study, this study found that the city needs to reset the Seoul Metropolitan Government's spatial structure in estimating future housing prices. So, This study attempted to classify the area without spatial heterogeneity by the reflected the property price characteristics of row housing and Multiplex housing. In other words, There has been a problem that an inefficient side has arisen due to the simple division by the existing administrative district. Therefore, this study aims to cluster Seoul as a new area for more efficient real estate analysis. This study was applied to the hedonic model based on the real transactions price data of row housing and multiplex housing. And the K-Means Clustering algorithm was used to cluster the spatial structure of Seoul. In this study, data onto real transactions price of the Seoul Row housing and Multiplex Housing from January 2014 to December 2016, and the official land value of 2016 was used and it provided by Ministry of Land, Infrastructure and Transport(hereafter, MOLIT). Data preprocessing was followed by the following processing procedures: Removal of underground transaction, Price standardization per area, Removal of Real transaction case(above 5 and below -5). In this study, we analyzed data from 132,707 cases to 126,759 data through data preprocessing. The data analysis tool used the R program. After data preprocessing, data model was constructed. Priority, the K-means Clustering was performed. In addition, a regression analysis was conducted using Hedonic model and it was conducted a cosine similarity analysis. Based on the constructed data model, we clustered on the basis of the longitude and latitude of Seoul and conducted comparative analysis of existing area. The results of this study indicated that the goodness of fit of the model was above 75 % and the variables used for the Hedonic model were significant. In other words, 5 or 25 districts that is the area of the existing administrative area are divided into 16 districts. So, this study derived a clustering method of row housing and multiplex housing in Seoul using K-Means Clustering algorithm and hedonic model by the reflected the property price characteristics. Moreover, they presented academic and practical implications and presented the limitations of this study and the direction of future research. Academic implication has clustered by reflecting the property price characteristics in order to improve the problems of the areas used in the Seoul Metropolitan Government, KAB, and Existing Real Estate Research. Another academic implications are that apartments were the main study of existing real estate research, and has proposed a method of classifying area in Seoul using public information(i.e., real-data of MOLIT) of government 3.0. Practical implication is that it can be used as a basic data for real estate related research on row housing and multiplex housing. Another practical implications are that is expected the activation of row housing and multiplex housing research and, that is expected to increase the accuracy of the model of the actual transaction. The future research direction of this study involves conducting various analyses to overcome the limitations of the threshold and indicates the need for deeper research.

• Journal of Intelligence and Information Systems
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• v.19 no.1
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• pp.95-110
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• 2013

Recently, the amount of unstructured data being generated through a variety of social media has been increasing rapidly, resulting in the increasing need to collect, store, search for, analyze, and visualize this data. This kind of data cannot be handled appropriately by using the traditional methodologies usually used for analyzing structured data because of its vast volume and unstructured nature. In this situation, many attempts are being made to analyze unstructured data such as text files and log files through various commercial or noncommercial analytical tools. Among the various contemporary issues dealt with in the literature of unstructured text data analysis, the concepts and techniques of opinion mining have been attracting much attention from pioneer researchers and business practitioners. Opinion mining or sentiment analysis refers to a series of processes that analyze participants' opinions, sentiments, evaluations, attitudes, and emotions about selected products, services, organizations, social issues, and so on. In other words, many attempts based on various opinion mining techniques are being made to resolve complicated issues that could not have otherwise been solved by existing traditional approaches. One of the most representative attempts using the opinion mining technique may be the recent research that proposed an intelligent model for predicting the direction of the stock index. This model works mainly on the basis of opinions extracted from an overwhelming number of economic news repots. News content published on various media is obviously a traditional example of unstructured text data. Every day, a large volume of new content is created, digitalized, and subsequently distributed to us via online or offline channels. Many studies have revealed that we make better decisions on political, economic, and social issues by analyzing news and other related information. In this sense, we expect to predict the fluctuation of stock markets partly by analyzing the relationship between economic news reports and the pattern of stock prices. So far, in the literature on opinion mining, most studies including ours have utilized a sentiment dictionary to elicit sentiment polarity or sentiment value from a large number of documents. A sentiment dictionary consists of pairs of selected words and their sentiment values. Sentiment classifiers refer to the dictionary to formulate the sentiment polarity of words, sentences in a document, and the whole document. However, most traditional approaches have common limitations in that they do not consider the flexibility of sentiment polarity, that is, the sentiment polarity or sentiment value of a word is fixed and cannot be changed in a traditional sentiment dictionary. In the real world, however, the sentiment polarity of a word can vary depending on the time, situation, and purpose of the analysis. It can also be contradictory in nature. The flexibility of sentiment polarity motivated us to conduct this study. In this paper, we have stated that sentiment polarity should be assigned, not merely on the basis of the inherent meaning of a word but on the basis of its ad hoc meaning within a particular context. To implement our idea, we presented an intelligent investment decision-support model based on opinion mining that performs the scrapping and parsing of massive volumes of economic news on the web, tags sentiment words, classifies sentiment polarity of the news, and finally predicts the direction of the next day's stock index. In addition, we applied a domain-specific sentiment dictionary instead of a general purpose one to classify each piece of news as either positive or negative. For the purpose of performance evaluation, we performed intensive experiments and investigated the prediction accuracy of our model. For the experiments to predict the direction of the stock index, we gathered and analyzed 1,072 articles about stock markets published by "M" and "E" media between July 2011 and September 2011.