• Journal of the Daesoon Academy of Sciences
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• v.47
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• pp.241-279
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• 2023

The Scripture of Myriad Laws was first published in 1986 and then reprinted in 1994 and 1995. It gained widespread recognition as a mysterious text or a Buddhist document containing enigmatic content that deemed difficult to comprehend. Through the analysis of the content of The Scripture of Myriad Laws, it was revealed that the book was published by the Dragon Flower Order, a Jeungsanist religion founded by Seo Baek-Il (徐白一). Therefore, the various texts included in The Scripture of Myriad Laws can be classified as 'Songs of Jeungsanism' (Jeungsan-gyo Gasa 甑山敎歌辭). The contents included in The Scripture of Myriad Laws often mention terms unique to the Jeungsanist orders, such as 'the Reordering Works of Heaven and Earth' (天地公事), 'presiding over cures' (醫統), 'Degree Number' (度數), 'the West God' (西神), 'the nobility of heaven' (天尊), 'the nobility of earth' (地尊), 'the nobility of humanity' (人尊), 'ruling the world for 50 years' (治天下五十年), and 'the era of Resolving Grievances (解冤時代).' It also discusses the birthplace and birth date of Kang Jeungsan, his family name, and the duration of his existence. The contents directly quote the words spoken by Jeungsan and incorporate them into songs. They also mention unique Jeungsan terms such as 'Five Immortals Playing Baduk' (五仙圍碁), 'open-weight wresting match,' 'birth, growth, harvest, and storage' (生長斂藏), 'the god who listens to words' (言聽神), 'pillar of foundation' (基礎棟樑),' 'Ocean Seal' (海印), and 'the higher gods' (上計神). It is also notable that some verses of Chinese poetry that Jeungsan taught his disciples are directly quoted in this scripture. Furthermore, the scripture shows traces of Buddhist salvational beliefs; particularly those that emphasize faith in Maitreya Bodhisattva (彌勒信仰). However, The Scripture of Myriad Laws differs from traditional Buddhist beliefs in that it anticipates and emphasizes the birth of a specific individual endowed with the power and abilities of Maitreya Buddha. While emphasizing Maitreya Buddha (彌勒世尊) and the Dragon Flower Gathering (龍華會上), the scripture also specifically mentions Geumsan-sa Temple (金山寺) located on Mount Moak (母岳山) in North Jeolla Province, and these details are sung about in a special manner. This positive portrayal serves to affirm the belief of followers that Jeungsan, centered around Geumsan-sa Temple, was an incarnation of Maitreya Buddha. Moreover, The Scripture of Myriad Laws subtly asserts that Seo Baek-il, the leader of the Dragon Flower Order, who is mentioned in the scripture, is the absolute savior who has come to this world in place of Jeungsan. In support of this teaching, his birth date, birthplace, years of imprisonment, release date, and honorific name (號) are all recorded in precise detail.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.101-124
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• 2018

Recently, most of the technologies have been developed in various forms through the advancement of single technology or interaction with other technologies. Particularly, these technologies have the characteristic of the convergence caused by the interaction between two or more techniques. In addition, efforts in responding to technological changes by advance are continuously increasing through forecasting promising convergence technologies that will emerge in the near future. According to this phenomenon, many researchers are attempting to perform various analyses about forecasting promising convergence technologies. A convergence technology has characteristics of various technologies according to the principle of generation. Therefore, forecasting promising convergence technologies is much more difficult than forecasting general technologies with high growth potential. Nevertheless, some achievements have been confirmed in an attempt to forecasting promising technologies using big data analysis and social network analysis. Studies of convergence technology through data analysis are actively conducted with the theme of discovering new convergence technologies and analyzing their trends. According that, information about new convergence technologies is being provided more abundantly than in the past. However, existing methods in analyzing convergence technology have some limitations. Firstly, most studies deal with convergence technology analyze data through predefined technology classifications. The technologies appearing recently tend to have characteristics of convergence and thus consist of technologies from various fields. In other words, the new convergence technologies may not belong to the defined classification. Therefore, the existing method does not properly reflect the dynamic change of the convergence phenomenon. Secondly, in order to forecast the promising convergence technologies, most of the existing analysis method use the general purpose indicators in process. This method does not fully utilize the specificity of convergence phenomenon. The new convergence technology is highly dependent on the existing technology, which is the origin of that technology. Based on that, it can grow into the independent field or disappear rapidly, according to the change of the dependent technology. In the existing analysis, the potential growth of convergence technology is judged through the traditional indicators designed from the general purpose. However, these indicators do not reflect the principle of convergence. In other words, these indicators do not reflect the characteristics of convergence technology, which brings the meaning of new technologies emerge through two or more mature technologies and grown technologies affect the creation of another technology. Thirdly, previous studies do not provide objective methods for evaluating the accuracy of models in forecasting promising convergence technologies. In the studies of convergence technology, the subject of forecasting promising technologies was relatively insufficient due to the complexity of the field. Therefore, it is difficult to find a method to evaluate the accuracy of the model that forecasting promising convergence technologies. In order to activate the field of forecasting promising convergence technology, it is important to establish a method for objectively verifying and evaluating the accuracy of the model proposed by each study. To overcome these limitations, we propose a new method for analysis of convergence technologies. First of all, through topic modeling, we derive a new technology classification in terms of text content. It reflects the dynamic change of the actual technology market, not the existing fixed classification standard. In addition, we identify the influence relationships between technologies through the topic correspondence weights of each document, and structuralize them into a network. In addition, we devise a centrality indicator (PGC, potential growth centrality) to forecast the future growth of technology by utilizing the centrality information of each technology. It reflects the convergence characteristics of each technology, according to technology maturity and interdependence between technologies. Along with this, we propose a method to evaluate the accuracy of forecasting model by measuring the growth rate of promising technology. It is based on the variation of potential growth centrality by period. In this paper, we conduct experiments with 13,477 patent documents dealing with technical contents to evaluate the performance and practical applicability of the proposed method. As a result, it is confirmed that the forecast model based on a centrality indicator of the proposed method has a maximum forecast accuracy of about 2.88 times higher than the accuracy of the forecast model based on the currently used network indicators.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.21-41
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• 2019

Thanks to the rapid development of information technologies, the data available on Internet have grown rapidly. In this era of big data, many studies have attempted to offer insights and express the effects of data analysis. In the tourism and hospitality industry, many firms and studies in the era of big data have paid attention to online reviews on social media because of their large influence over customers. As tourism is an information-intensive industry, the effect of these information networks on social media platforms is more remarkable compared to any other types of media. However, there are some limitations to the improvements in service quality that can be made based on opinions on social media platforms. Users on social media platforms represent their opinions as text, images, and so on. Raw data sets from these reviews are unstructured. Moreover, these data sets are too big to extract new information and hidden knowledge by human competences. To use them for business intelligence and analytics applications, proper big data techniques like Natural Language Processing and data mining techniques are needed. This study suggests an analytical approach to directly yield insights from these reviews to improve the service quality of hotels. Our proposed approach consists of topic mining to extract topics contained in the reviews and the decision tree modeling to explain the relationship between topics and ratings. Topic mining refers to a method for finding a group of words from a collection of documents that represents a document. Among several topic mining methods, we adopted the Latent Dirichlet Allocation algorithm, which is considered as the most universal algorithm. However, LDA is not enough to find insights that can improve service quality because it cannot find the relationship between topics and ratings. To overcome this limitation, we also use the Classification and Regression Tree method, which is a kind of decision tree technique. Through the CART method, we can find what topics are related to positive or negative ratings of a hotel and visualize the results. Therefore, this study aims to investigate the representation of an analytical approach for the improvement of hotel service quality from unstructured review data sets. Through experiments for four hotels in Hong Kong, we can find the strengths and weaknesses of services for each hotel and suggest improvements to aid in customer satisfaction. Especially from positive reviews, we find what these hotels should maintain for service quality. For example, compared with the other hotels, a hotel has a good location and room condition which are extracted from positive reviews for it. In contrast, we also find what they should modify in their services from negative reviews. For example, a hotel should improve room condition related to soundproof. These results mean that our approach is useful in finding some insights for the service quality of hotels. That is, from the enormous size of review data, our approach can provide practical suggestions for hotel managers to improve their service quality. In the past, studies for improving service quality relied on surveys or interviews of customers. However, these methods are often costly and time consuming and the results may be biased by biased sampling or untrustworthy answers. The proposed approach directly obtains honest feedback from customers' online reviews and draws some insights through a type of big data analysis. So it will be a more useful tool to overcome the limitations of surveys or interviews. Moreover, our approach easily obtains the service quality information of other hotels or services in the tourism industry because it needs only open online reviews and ratings as input data. Furthermore, the performance of our approach will be better if other structured and unstructured data sources are added.

• Korean Journal of Heritage: History & Science
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• v.54 no.1
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• pp.70-99
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• 2021

Yeong-am's 'Jeongwon (貞元)' stone monument, designated as the Jeollanam-do Cultural Heritage, is considered to be the oldest of the epigraphs in Jeollanam-do. Immediately after the discovery, the possibility of it being a Maehyangbi of Memorial Inscriptions was mentioned and attracted attention. However, there is an absolute age of the 'Jeongwon (貞元) of 2 years' (786), so despite it is a relatively early epigraph (金石文), there are not many papers on the theme related to this stone monument. I believe that this stone monument is a Maehyangbi (埋香碑). While reviewing and comparing the results of the existing research, I decoded the text from the 42nd character of the 4th line. As a result of the review, that was conducted, it was confirmed that this stone monument is truly a Maehyangbi (埋香碑). In particular, it was recorded in the literature of the late Joseon Dongguk-myungsanggi (東國名山記) that the letters of the Maehyangbi (埋香碑) are not recognizable. However, it is clearly stated that this stone monument is a Maehyangbi (埋香碑). Although there is no common expression for 'bury (埋)' or 'incense burial (埋香)' in the traditional Maehyangbi (埋香碑), which were popular in the late Goryeo and early Joseon Periods, it can be seen that it is a Maehyangbi (埋香碑) from the words "hide (呑藏)" and "10 bundles of fragrant incense (合香十束)" that are engraved on the stone monument with the name 'Jeongwon.' In other words, it is thought that it meant 'hide (呑藏)' instead of 'bury (埋)'. Circumstantial evidence for the monument of Jingamseonsa (眞鑑禪師), built in 888, contains the an epigraph from the Unified Silla Era. There is a phrase on it that says 'Plant incense on the shore (海岸植香)' on the monument of Jingamseonsa (眞鑑禪師), and it conveys its meaning without using the character 'bury (埋)'. As a result of the absence of the character 'bury (埋)' on the stone monument with the name 'Jeongwon', it is not considered as a Maehyangbi (埋香碑). However, there is evidence that the stone monument with the name 'Jeongwon (貞元)' is in fact a Maehyangbi (埋香碑) and it is also in the Geumpyoseok (禁標石; Forbidden Stone) around Gukjangsaeng (國長生) and at the entrance of Dogapsa Temple (道甲寺). The letters written on the gold sign suggest the possibility that the charcoal used to burn incense (香炭) at the royal tombs of King Jeongjo (正祖) was produced around at Dogapsa Temple (道甲寺) in Wolchulsan (月出山). Since the charcoal used to burn incense (香炭) is naturally related to incense (香), it has been shown that the area around Wolchulsan, where Dogapsa Temple is located, has a long history related to incense (香). The letters visible on the stone monument, the record of Dongguk-myungsanggi (東國名山記) in the late Joseon Dynasty, and the letters on the Geompyoseok (禁標石; Forbidden Stone), all show that the stone monument with the name 'Jeongwon (貞元)' is a Maehyangbi (埋香碑). Considering the fact that the earliest Maehyangbi (埋香碑) in existence is the Maehyangbi (埋香碑) in Yeongam (靈巖) Ippam-ri (笠巖里), which has two dates from 1371 at the end of Goryeo and 1410 at the beginning of Joseon, the stone monument with the name 'Jeongwon' which was set up in 786, would be the oldest Maehyangbi (埋香碑) that we know of. In addition, there is a historical significance in that the Maehyangbi (埋香碑) is proven in the record of Dongguk-myungsanggi (東國名山記), a document from the late Joseon period.