• MISULJARYO - National Museum of Korea Art Journal
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• v.101
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• pp.12-46
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• 2022

Completed in 1467, the Thirteen-story Stone Pagoda of Wongaksa Temple is the last Buddhist pagoda erected at the center of the capital (present-day Seoul) of the Joseon Dynasty. It was commissioned by King Sejo, the final Korean king to favor Buddhism. In this paper, I aim to examine King Sejo's intentions behind celebrating the tenth anniversary of his enthronement with the construction of the thirteen-story stone pagoda in the central area of the capital and the enshrinement of sarira from Shakyamuni Buddha and the Newly Translated Sutra of Perfect Enlightenment (圓覺經). This paper provides a summary of this examination and suggests future research directions. The second chapter of the paper discusses the scriptural background for thirteen-story stone pagodas from multiple perspectives. I was the first to specify the Latter Part of the Nirvana Sutra (大般涅槃經後分) as the most direct and fundamental scripture for the erection of a thirteen-story stone pagoda. I also found that this sutra was translated in Central Java in the latter half of the seventh century and was then circulated in East Asia. Moreover, I focused on the so-called Kanishka-style stupa as the origin of thirteen-story stone pagodas and provided an overview of thirteen-story stone pagodas built around East Asia, including in Korea. In addition, by consulting Buddhist references, I prove that the thirteen stories symbolize the stages of the practice of asceticism towards enlightenment. In this regard, the number thirteen can be viewed as a special and sacred number to Buddhist devotees. The third chapter explores the Buddhist background of King Sejo's establishment of the Thirteen-story Stone Pagoda of Wongaksa Temple. I studied both the Dictionary of Sanskrit-Chinese Translation of Buddhist Terms (翻譯名義集) (which King Sejo personally purchased in China and published for the first time in Korea) and the Sutra of Perfect Enlightenment. King Sejo involved himself in the first translation of the Sutra of Perfect Enlightenment into Korean. The Dictionary of Sanskrit-Chinese Translation of Buddhist Terms was published in the fourteenth century as a type of Buddhist glossary. King Sejo is presumed to have been introduced to the Latter Part of the Nirvana Sutra, the fundamental scripture regarding thirteen-story pagodas, through the Dictionary of Sanskrit-Chinese Translation of Buddhist Terms, when he was set to erect a pagoda at Wongaksa Temple. King Sejo also enshrined the Newly Translated Sutra of Perfect Enlightenment inside the Wongaksa pagoda as a scripture representing the entire Tripitaka. This enshrined sutra appears to be the vernacular version for which King Sejo participated in the first Korean translation. Furthermore, I assert that the original text of the vernacular version is the Abridged Commentary on the Sutra of Perfect Enlightenment (圓覺經略疏) by Zongmi (宗密, 780-841), different from what has been previously believed. The final chapter of the paper elucidates the political semantics of the establishment of the Wongaksa pagoda by comparing and examining stone pagodas erected at neungsa (陵寺) or jinjeonsawon (眞殿寺院), which were types of temples built to protect the tombs of royal family members near their tombs during the early Joseon period. These stone pagodas include the Thirteen-story Pagoda of Gyeongcheonsa Temple, the Stone Pagoda of Gaegyeongsa Temple, the Stone Pagoda of Yeongyeongsa Temple, and the Multi-story Stone Pagoda of Silleuksa Temple. The comparative analysis of these stone pagodas reveals that King Sejo established the Thirteen-story Stone Pagoda at Wongaksa Temple as a political emblem to legitimize his succession to the throne. In this paper, I attempt to better understand the scriptural and political semantics of the Wongaksa pagoda as a thirteen-story pagoda. By providing a Korean case study, this attempt will contribute to the understanding of Buddhist pagoda culture that reached its peak during the late Goryeo and early Joseon periods. It also contributes to the research on thirteen-story pagodas in East Asia that originated with Kanishka stupa and were based on the Latter Part of the Nirvana Sutra.

• The Korean Journal of Applied Statistics
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• v.27 no.7
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• pp.1207-1217
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• 2014

2011 Korean Economic Census is the first economic census in Korea, which contains text data on menus served by Korean-food restaurants as well as structured data on characteristics of restaurants including area, opening year and total sales. In this paper, we applied text mining to the text data and investigated statistical and technical issues and characteristics of Korean text mining. Pork belly roast was the most popular menu across provinces and/or restaurant types in year 2010, and the number of restaurants per 10000 people was especially high in Kangwon-do and Daejeon metropolitan city. Beef tartare and fried pork cutlet are popular menus in start-up restaurants while whole chicken soup and maeuntang (spicy fish stew) are in long-lived restaurants. These results can be used as a guideline for menu development to restaurant owners, and for government policy-making process that lead small restaurants to choose proper menus for successful business.

• Journal of the Korean Society for Library and Information Science
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• v.49 no.1
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• pp.45-67
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• 2015

The purpose of this study is to analyse the semantic relations of terms in STNet, a structured terminology dictionary based on author keywords of humanities, social sciences, and art and sport in the Korea Citation Index (KCI) and to describe the procedure for optimizing the relation types and specifying the name of relationships. The results indicate that four logical criteria, such as creating new names for relationships or limitation of typing the relationship by the appearance frequency of same type, consideration of direction of relationship, reflection to accept the existing name of relationships, are required for the optimization of the typing and naming the relationships. We applied these criteria to the relationships in the class "real person" of STNet and the result shows that 1,135 out of 1,743 uncertain relationships such as RT, RT_X or RT_Y are specified and clarified. This rate of optimization with ca. 65% represents the usefulness of the criteria applicable to the cases of database construction and retrieval.

• Journal of the Korea Society of Computer and Information
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• v.17 no.10
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• pp.25-33
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• 2012

In this paper, we propose a rule-based model to correct errors in a speech recognition result in the mobile device environment. The proposed model considers the mobile device environment with limited resources such as processing time and memory, as follows. In order to minimize the error correction processing time, the proposed model removes some processing steps such as morphological analysis and the composition and decomposition of syllable. Also, the proposed model utilizes the longest match rule selection method to generate one error correction candidate per point, assumed that an error occurs. For the purpose of deploying memory resource, the proposed model uses neither the Eojeol dictionary nor the morphological analyzer, and stores a combined rule list without any classification. Considering the modification and maintenance of the proposed model, the error correction rules are automatically extracted from a training corpus. Experimental results show that the proposed model improves 5.27% on the precision and 5.60% on the recall based on Eojoel unit for the speech recognition result.

• Journal of KIISE
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• v.42 no.4
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• pp.512-521
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• 2015

Internet users purchase goods on the Internet and express their positive or negative emotions of the goods in product reviews. Analysis of the product reviews become critical data to both potential consumers and to the decision making of enterprises. Therefore, the importance of opinion mining techniques which derive opinions by analyzing meaningful data from large numbers of Internet reviews. Existing studies were mostly based on comments written in English, yet analysis in Korean has not actively been done. Unlike English, Korean has characteristics of complex adjectives and suffixes. Existing studies did not consider the characteristics of the Internet language. This study proposes an emotional classification method which increases the accuracy of emotional classification by analyzing the characteristics of the Internet language connoting feelings. We can classify positive and negative comments about products automatically using the Internet emoticon. Also we can check the validity of the proposed algorithm through the result of high precision, recall and coverage for the evaluation of this method.

• Proceedings of the Korea Information Processing Society Conference
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• 2003.11b
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• pp.853-856
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• 2003

바이오 텍스트 마이닝을 위한 정보 추출의 첫 단계는 생물학적 문헌으로부터의 유전자, 단백질, 세포조직 등과 같은 생물학적 개체명의 인식이다. 생물학적 개체명의 명명법상 특징이 매우 다양하고 저자의 개성에 의해 쉽게 좌우되어 단순히 규칙이나 학습 방법 만으로는 쉽게 개체명들을 인식할 수 없다. 또한, 생물학 관련 문헌에 나오는 가능한 모든 개체명과 이들의 모든 변형을 수록하는 것은 현실적으로 불가능하므로 이를 해결하기 위해 이미 알려진 개체명에 대해서 기본적으로 사전을 탐색하고 알려지지 않은 용어들을 규칙과 통계 기반 방법을 통하여 인식하는 것이 효과적이다. 그러나 만족할 만한 수준의 양질의 사전을 구축하는 것은 쉽지 않을 뿐만 아니라 많은 비용이 소요되며, 어느 순간 만족할 만한 성능을 낼 수 있는 사전을 구축했다. 할지라도 유지 관리 하는 것이 결코 쉬운 일이 아니며 마찬가지로 많은 비용을 필요로 하게 된다. 따라서, 잘 구축된 자원으로부터 필요한 정보를 추출하여 적절한 사전을 자동으로 구축하여 활용하는 방법을 사용할 경우, 사전 구축 및 관리에 드는 많은 비용을 줄이면서도 상당히 효과적인 성능을 얻을 수 있을 것이다. 본 연구에서는 바이오 텍스트 마이닝 엔진을 위한 생물학적 개체명 사전을 자동으로 구축하고 이를 쉽게 관리하도록 하는 도구를 개발하였다.

• Journal of Information Processing Systems
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• v.16 no.3
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• pp.612-628
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• 2020

This paper presents a new approach for detecting abnormal behaviors in complex surveillance scenes where anomalies are subtle and difficult to distinguish due to the intricate correlations among multiple objects' behaviors. Specifically, a cascaded probabilistic topic model was put forward for learning the spatial context of local behavior and the temporal context of global behavior in two different stages. In the first stage of topic modeling, unlike the existing approaches using either optical flows or complete trajectories, spatio-temporal correlations between the trajectory fragments in video clips were modeled by the latent Dirichlet allocation (LDA) topic model based on Markov random fields to obtain the spatial context of local behavior in each video clip. The local behavior topic categories were then obtained by exploiting the spectral clustering algorithm. Based on the construction of a dictionary through the process of local behavior topic clustering, the second phase of the LDA topic model learns the correlations of global behaviors and temporal context. In particular, an abnormal behavior recognition method was developed based on the learned spatio-temporal context of behaviors. The specific identification method adopts a top-down strategy and consists of two stages: anomaly recognition of video clip and anomalous behavior recognition within each video clip. Evaluation was performed using the validity of spatio-temporal context learning for local behavior topics and abnormal behavior recognition. Furthermore, the performance of the proposed approach in abnormal behavior recognition improved effectively and significantly in complex surveillance scenes.

• Journal of Digital Convergence
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• v.17 no.9
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• pp.47-54
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• 2019

This study confirms the polarity of news articles on apartment prices using Opinion Mining which has widely been used for a big data analysis. The analyses were carried out utilizing internet news articles posted on the Naver for two years: 2012 and 2018. We proposed a sentiment analysis model and modeled a topic-oriented sentiment dictionary construction methods. As a result of analyzing the proposed sentiment analysis model, it was confirmed that there was a difference according to the tendency of the media companies in selecting social issues at the time of rising apartment prices. At the same time, we were able to find more affirmative articles in the media companies which share similar sentiment with the government in charge. In this paper, we proposed a sentiment analysis model that can be used in real estate field and analyzed the polarity of unformatted data related to real estate. In order to integrate them into various fields in the future, it is necessary to build the sentiment dictionaries by themes, as well as to collect various unformatted data over extended periods.

• The Journal of the Convergence on Culture Technology
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• v.8 no.1
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• pp.371-377
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• 2022

This study examines whether there are subjects and learners to pay attention to as 'processes' that have not been dealt with in Korean vocabulary education due to prioritizing learning outcomes, educational outcomes, and objects. In addition, the purpose of this study was to examine the educational value of the neologism and to suggest data construction method for it. Proposal to create a 'single-level list' of neologisms as a preliminary work to create a dictionary as a learning material to teach new words to academic purpose learners, taking neologism as the vocabulary in the blind spot and foreign academic purpose learners as learners in the blind spot stage. did The 'single-layered list' is to divide new words by period into coined words, meanings, culture, etc. and construct them as data. Through this study, we will help systematically teach Korean vocabulary by adding vocabulary to be learned as a 'process' to the results of Korean vocabulary education so far.

• Science of Emotion and Sensibility
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• v.12 no.4
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• pp.433-442
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• 2009

People are tending to buy products through the Internet rather than purchasing them from the store. Some of the consumers give their feedback on line such as reviews, replies, comments, and blogs after they purchased the products. People are also likely to get some information through the Internet. Therefore, companies and public institutes have been facing this situation where they need to collect and analyze reviews or public opinions for them because many consumers are interested in other's opinions when they are about to make a purchase. However, most of the people's reviews on web site are too numerous, short and redundant. Under these circumstances, the emotion scanning system of text documents on the web is rising to the surface. Extracting writer's opinions or subjective ideas from text exists labeled words like GI(General Inquirer) and LKB(Lexical Knowledge base of near synonym difference) in English, however Korean language is not provided yet. In this paper, we labeled positive, negative, and neutral attribute at 4 POS(part of speech) which are noun, adjective, verb, and adverb in Korean dictionary. We extract construction patterns of emotional words and relationships among words in sentences from a large training set, and learned them. Based on this knowledge, comments and reviews regarding products are classified into two classes polarities with positive and negative using SO-PMI, which found the optimal condition from a combination of 4 POS. Lastly, in the design of the system, a flexible user interface is designed to add or edit the emotional words, the construction patterns related to emotions, and relationships among the words.