• The Journal of Korean Philosophical History
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• no.29
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• pp.89-123
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• 2010

As above, as theoretical basis of critiques against School of Mohism, the researcher summarized the positions of the elder Confucian scholars including Meng Zi. In the body of text, taking it as promises, the researcher examined the critiques against Mo Tzu and School of Mohism as well focusing on the aspects and development of the theory of rejecting heterodoxy which had been introduced and strongly argued from the end of Goryeo kingdom to the late Joseon period. The summary of the body of this text is as follows: In the old literatures prior to Goryeo Kingdom, the researcher couldn't find any cases that either the School of Mohism or Mo Tzu including the Hundred Schools of Thought had been rejected explicitly. Having reached the end of Goryeo and the beginning of Joseon period, Meng Zi's viewpoints on the theory of rejecting heterodoxy had begun to emerge and come into play with the progress of accepting Neo-Confucianism, and, these critiques against Yang Zhu and Mo Tzu being given, the scholar-literati circle had started rejecting Buddhism and Lao Tzu. Basically the contents of the critiques against the School of Mohism in the early period of Joseon were in succession to Meng Zi's theory of rejecting heterodoxy and the views and thoughts of the elder Confucian scholars including Han Yu rather than any specific critiques against Mo Tzu' ideology itself. Until entering the middle of Joseon period, the critiques against the School of Mohism had been used as a tool to promote Confucianism in an affirmative manner, while arguing strongly against the viewpoint of Han Yu in the first place. Particularly, not only the original text of the Mo Tzu's writings were directly quoted, although it was partial, but also the contents of the critiques against the School of Mohism had been developed and stretched to the extent of their entire ideological system. Having approached to the late period of Joseon, the critiques against the School of Mohism had begun to be linked to those critiques against the study of state examination or of sentence patterns including Catholic Church, furthermore the critics raised their harsh tones against the irregularities of the society at large like the issue of corruptions of the government officials of those days instead, although they still had firmly stood on the ground of the theory of rejecting heterodoxy. Those scholars that belonged to the School of Practical Learning, in particular, said in justification of the School of Mohism arguing that the major ideologies of Mo Zi had usefulness in the real world, also they even evaluated that Meng Zi ' critiques against the School of Mohism were immoderate. To sum up, characteristics of scholars in the Joseon period to understand and critique the School of Mohism are that ideologies of Mo Tzu were mostly used as a tool for the sake of critiques against heresies in other sectors of society based mainly on Meng Zi's theory of rejecting heterodoxy, rather than opposing views against the ideologies or philosophies of the School of Mohism itself. Meanwhile, however, on the plus side, the critics praised Mo Tzu's individual efforts in order to put his ideology of peace into practice apart from the ideological system of the School of Mohism. Also, having reached the late period of Joseon, the researcher was able to have discovered the fact that the writings of Mo Tzu had been used as historical materials in order to ascertain historical truths of Confucian Scriptures, rather not having it regarded as an ideology text.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.21-44
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• 2018

In recent years, the rapid development of internet technology and the popularization of smart devices have resulted in massive amounts of text data. Those text data were produced and distributed through various media platforms such as World Wide Web, Internet news feeds, microblog, and social media. However, this enormous amount of easily obtained information is lack of organization. Therefore, this problem has raised the interest of many researchers in order to manage this huge amount of information. Further, this problem also required professionals that are capable of classifying relevant information and hence text classification is introduced. Text classification is a challenging task in modern data analysis, which it needs to assign a text document into one or more predefined categories or classes. In text classification field, there are different kinds of techniques available such as K-Nearest Neighbor, Naïve Bayes Algorithm, Support Vector Machine, Decision Tree, and Artificial Neural Network. However, while dealing with huge amount of text data, model performance and accuracy becomes a challenge. According to the type of words used in the corpus and type of features created for classification, the performance of a text classification model can be varied. Most of the attempts are been made based on proposing a new algorithm or modifying an existing algorithm. This kind of research can be said already reached their certain limitations for further improvements. In this study, aside from proposing a new algorithm or modifying the algorithm, we focus on searching a way to modify the use of data. It is widely known that classifier performance is influenced by the quality of training data upon which this classifier is built. The real world datasets in most of the time contain noise, or in other words noisy data, these can actually affect the decision made by the classifiers built from these data. In this study, we consider that the data from different domains, which is heterogeneous data might have the characteristics of noise which can be utilized in the classification process. In order to build the classifier, machine learning algorithm is performed based on the assumption that the characteristics of training data and target data are the same or very similar to each other. However, in the case of unstructured data such as text, the features are determined according to the vocabularies included in the document. If the viewpoints of the learning data and target data are different, the features may be appearing different between these two data. In this study, we attempt to improve the classification accuracy by strengthening the robustness of the document classifier through artificially injecting the noise into the process of constructing the document classifier. With data coming from various kind of sources, these data are likely formatted differently. These cause difficulties for traditional machine learning algorithms because they are not developed to recognize different type of data representation at one time and to put them together in same generalization. Therefore, in order to utilize heterogeneous data in the learning process of document classifier, we apply semi-supervised learning in our study. However, unlabeled data might have the possibility to degrade the performance of the document classifier. Therefore, we further proposed a method called Rule Selection-Based Ensemble Semi-Supervised Learning Algorithm (RSESLA) to select only the documents that contributing to the accuracy improvement of the classifier. RSESLA creates multiple views by manipulating the features using different types of classification models and different types of heterogeneous data. The most confident classification rules will be selected and applied for the final decision making. In this paper, three different types of real-world data sources were used, which are news, twitter and blogs.

• Journal of the Korean Institute of Landscape Architecture
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• v.45 no.6
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• pp.76-89
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• 2017

Tourism is being used as a tool to regenerate declining spaces. Therefore, the government is carrying out various projects to create tourist attractions to revitalize the traditional marketplace, which is declining nationwide. Because of these government-led projects, traditional marketplaces have been transformed into tourist attractions, and some markets have received enough positive feedback that they have been successfully revitalized economically. However, as marketplaces have become tourist destinations, negative views about government support projects are also increasing. This also leads to conflicts due to differences in perception and interests of stakeholders. This paper examines the process of the marketplace becoming a tourist destination focused on the Tongin Market, in Seoul which has been regenerated as a tourist attraction through a government support project. The purpose of this study is, first, to examine the background of tourist markets becoming tourist attractions and the issues surrounding them. The second was to explore in depth the types of conflict perceptions of visitors, residents and tourists, and the perception of their responses. As a research method, the process of the revitalization of traditional markets through news and existing literature, issues and the difference of perceptions about tourist-centric traditional marketplaces were examined. In addition, the Q methodology was used, which is a qualitative research methodology that can measure the difference of viewpoints and perceptions of specific events in order to analyze the difference of perception among visitors in traditional marketplaces. The results of the study show that there are three main perspectives of difference among visitors' perceptions about government support projects in traditional marketplaces and the marketplace becoming a tourist attraction. The 'policy dependent perspective' emphasizes the necessity of government regulations, a 'critical perspective' criticizes the government's traditional marketplace support policy, and the 'neutral perspective' acknowledges the need for government-led projects and accentuating the internal competitiveness of the marketplace. The study provided the environment for academic discussion about traditional marketplaces, which are becoming tourist attractions nationwide. In addition, this paper can contribute to providing implications for future government projects by analyzing the perception of marketplace visitors.

• Journal of the Korean Institute of Landscape Architecture
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• v.49 no.2
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• pp.128-140
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• 2021

This study applied the theory of Landscape Ecology to representative resources of Jeju Olle-gil, which is a representative subject of walking tourism, to identify ecological characteristics and to establish a technique for landscape ecological analysis of Olle-gil resources. Jeju Olle Trail type based on the biotope type, major land use, vegetation status around Olle Trail and roads were divided into 12 types. Based on the type of ecological tourism resource classification, the Jeju Olle-gil walking tourism resource classification was divided into seven types of natural resources and seven types of humanities resources, and each resource was characterized by Geotope, Biotope, and Anthropopope, just like the landscape ecology system. Geotope resources are strong in landscape characteristics such as coast and beach, rocks, bedrocks, waterfalls, geology and Jusangjeolli Cliff, Oreum and craters, water resources, and landscape viewpoints. The Biotope resources showed strong ecological characteristics due to large tree and protected tree, Gotjawal, forest road and vegetation communities, biological habitat, vegetation landscape view point. Antropotope include Culture of Jeju Haenyeo and traditional culture, potting and lighthouses, experience facilities, temples and churches, military and beacon facilities, other historical and cultural facilities, and cultural landscape views. Jeju Olle Trail The representative resources for each type of Jeju Olle Trail are coastal, Oreum, Gotjawal, field and Stonewall Fencing farming land, Jeju Village and Stone wall of Jeju. In order to learn about the components and various functions of the resources representing the Olle Trail's ecological culture, the landscape ecological technique was interpreted. Looking at the ecological and cultural characteristics of coastal, the coast includes black basalt rocks, coastal vegetation, coastal grasslands, coastal rock vegetation, winter migratory birds and Jeju haenyeo. Oreum is a unique volcanic topography, which includes circular and oval mountain bodies, oreum vegetation, crater wetlands, the origin and legend of the name of Oreum, the legend of the name of Oreum, the culture of grazing horses, the use of military purposes, the object of folk belief, and the view from the summit. Gotjawal features rocky bumps, unique microclimate formation, Gotjawal vegetation, geographical names, the culture of charcoal being baked in the past, and bizarre shapes of trees and vines. Field walls include the structure and shape of field walls, field cultivation crops, field wall habitats, Jeju agricultural culture, and field walls. The village includes a stone wall and roof structure built from basalt, a pavilion at the entrance of the village, a yard and garden inside the house, a view of the lives of local people, and an alleyway view. These resources have slowly changed with the long lives of humans, and are now unique to Jeju Island. By providing contents specialized for each type of Olle Trail, tourists who walk on Olle will be able to experience the Olle Trail in depth as they learn the story of the resources, and will be able to increase the sustainable use and satisfaction of Jeju Olle Trail users.

• Journal of the Korean Institute of Landscape Architecture
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• v.49 no.3
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• pp.1-10
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• 2021

This study aimed to evaluate preferences of Bukhansan dulegil using sentiment analysis, a natural language processing technique, to derive preferred and non-preferred factors. Therefore, we collected blog articles written in 2019 and produced sentimental scores by the derivation of positive and negative words in the texts for 21 dulegil courses. Then, content analysis was conducted to determine which factors led visitors to prefer or dislike each course. In blogs written about Bukhansan dulegil, positive words appeared in approximately 73% of the content, and the percentage of positive documents was significantly higher than that of negative documents for each course. Through this, it can be seen that visitors generally had positive sentiments toward Bukhansan dulegil. Nevertheless, according to the sentiment score analysis, all 21 dulegil courses belonged to both the preferred and non-preferred courses. Among courses, visitors preferred less difficult courses, in which they could walk without a burden, and in which various landscape elements (visual, auditory, olfactory, etc.) were harmonious yet distinct. Furthermore, they preferred courses with various landscapes and landscape sequences. Additionally, visitors appreciated the presence of viewpoints, such as observation decks, as a significant factor and preferred courses with excellent accessibility and information provisions, such as information boards. Conversely, the dissatisfaction with the dulegil courses was due to noise caused by adjacent roads, excessive urban areas, and the inequality or difficulty of the course which was primarily attributed to insufficient information on the landscape or section of the course. The results of this study can serve not only serve as a guide in national parks but also in the management of nearby forest green areas to formulate a plan to repair and improve dulegil. Further, the sentiment analysis used in this study is meaningful in that it can continuously monitor actual users' responses towards natural areas. However, since it was evaluated based on a predefined sentiment dictionary, continuous updates are needed. Additionally, since there is a tendency to share positive content rather than negative views due to the nature of social media, it is necessary to compare and review the results of analysis, such as with on-site surveys.