• Journal of the Korea Society of Computer and Information
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• v.25 no.2
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• pp.67-74
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• 2020

In this paper, we proposes to develop an online academic vocabulary dictionary as a way of educating academic vocabulary for content-oriented Korean language education. Various academic languages exist in the content-based Korean language teaching materials they encounter when studying at university. You cannot understand or produce academic text without knowing the academic vocabulary. Therefore, one of the tasks of Korean language education has become to improve educational efficiency by preparing a method for academic vocabulary education that is most suitable for them in consideration of their own. Prior to the development of the online academic vocabulary dictionary, the institute conducted a basic study on how the content should be contained in the online dictionary. Online academic vocabulary dictionaries allow students to naturally link their limited education into and out of the classroom, thereby overcoming the limitations of vocabulary education at the educational scene and maximizing their educational effectiveness.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.9 no.1
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• pp.75-81
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• 2016

The main characters play leading roles in novels. In the previous studies, they recognize the main characters in a novel mainly based on dictionaries that built beforehand. In English, names begin with upper cases and are used with some words. In this paper, we propose a recognition method for main characters name in Korean novels by using predicates, rules and weights. We first recognize candidates for the characters name by predicates and propose some rules to exclude candidates that cannot be characters. We assign importances for candidates, considering weights that given by the number of candidates appeared in a sentence. Finally, if the importance of the character is more than a threshold, we decide that the character is one of main characters. The results from the experiments for 300 novels show that an average accuracy is 85.97%. The main characters name may be used to grasp relationships among characters, character's action and tendency.

• The KIPS Transactions:PartB
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• v.13B no.2 s.105
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• pp.171-178
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• 2006

Most approaches for extracting hypernyms of a noun from its definitions in an MRD rely on lexical patterns compiled by human experts. Not only these approaches require high cost for compiling lexical patterns but also it is very difficult for human experts to compile a set of lexical patterns with a broad-coverage because in natural languages there are various expressions which represent same concept. To alleviate these problems, this paper proposes a new method for extracting hypernyms of a noun from its definitions in an MRD. In proposed approach, we use only syntactic (part-of-speech) patterns instead of lexical patterns in identifying hypernyms to reduce the number of patterns with keeping their coverage broad. Our experiment has shown that the classification accuracy of the proposed method is 92.37% which is significantly much better than that of previous approaches.

• 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.

• Journal of the Korean Data Analysis Society
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• v.20 no.6
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• pp.2917-2932
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• 2018

Many researches are accomplished as a result of the efforts of developing the production predicting model to solve the supply imbalance of onions which are vegetables very closely related to Korean food. But considering the possibility of storing onions, it is very difficult to solve the supply imbalance of onions only with predicting the production. So, this paper's purpose is trying to build a sentiment dictionary to predict the price of onions by using the internet articles which include the informations about the production of onions and various factors of the price, and these articles are very easy to access on our daily lives. Articles about onions are from 2012 to 2016, using TF-IDF for comparing with four kinds of TF-IDFs through the documents classification of wholesale prices of onions. As a result of classifying the positive/negative words for price by k-means clustering, DBSCAN (density based spatial cluster application with noise) clustering, GMM (Gaussian mixture model) clustering which are partitional clustering, GMM clustering is composed with three meaningful dictionaries. To compare the reasonability of these built dictionary, applying classified articles about the rise and drop of the price on logistic regression, and it shows 85.7% accuracy.

• Journal of Korean Medical classics
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• v.34 no.1
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• pp.67-87
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• 2021

Objectives :The purpose of this paper is to evaluate the significance of the 『Joseonbogeonsa』 by examining North Korea's perspective in its documentation of the history of medicine, and to further understand North Korea's perception of Korean Traditional Medicine. Methods : The focus of examination was on the perspective of historical description as shown in the first chapter of the 『Joseonbogeonsa』. Its unique features were made clear through comparison with historical texts of medicine of South Korea such as the 『History of Medicine in Korea』, and the 『History of Korean Medicine』. In order to grasp the current of historical research in North Korea, various Traditional Medicine related dictionaries and academic journals of North Korea along with the 『Joseontongsa』 were examined. Results & Conclusions : The historical views of the 『Joseonbogeonsa』 could be categorized as nation-focused, materialistic, and nationalistic. These are core elements that make up North Korea's self-reliance ideology, which influenced the interpretation of medical facts. While the text is valuable in that it introduced new historical material along with its interpretation, and argued for a more independent development of Traditional Medicine, its limitation of interpreting historical material from a conclusive, pre-determined standpoint cannot be overlooked. The North Korean 'Goryeo Medicine' is defined by its historical nature rather than academic characteristics, and its significance is determined by its clinical efficacy rather than theoretical value.

• Nuclear Engineering and Technology
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• v.54 no.3
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• pp.1037-1048
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• 2022

A radioactive isotope identification algorithm is a prerequisite for a low-resolution scintillation detector applied to an unmanned radiation monitoring system. In this paper, a sparse representation with dictionary learning approach is proposed and applied to plastic gamma-ray spectra. Label-consistent K-SVD was used to learn a discriminative dictionary for the spectra corresponding to a mixture of four isotopes (¹³³Ba, ²²Na, ¹³⁷Cs, and ⁶⁰Co). A Monte Carlo simulation was employed to produce the simulated data as learning samples. Experimental measurement was conducted to obtain practical spectra. After determining the hyper parameters, two dictionaries tailored to the learning samples were tested by varying with the source position and the measurement time. They achieved average accuracies of 97.6% and 98.0% for all testing spectra. The average accuracy of each dictionary was above 96% for spectra measured over 2 s. They also showed acceptable performance when the spectra were artificially shifted. Thus, the proposed method could be useful for identifying radioisotopes in gamma-ray spectra from a plastic scintillation detector even when a dictionary is adapted to only simulated data. Furthermore, owing to the outstanding properties of sparse representation, the proposed approach can easily be built into an insitu monitoring system.

• The KIPS Transactions:PartB
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• v.11B no.2
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• pp.233-240
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• 2004

This paper presents a method to implicitly resolve ambiguities using dynamic incremental clustering in Korean-to-English and Japanese-to-English cross-language information retrieval (CLIR). The main objective of this paper shows that document clusters can effectively resolve the ambiguities tremendously increased in translated queries as well as take into account the context of all the terms in a document. In the framework we propose, a query in Korean/Japanese is first translated into English by looking up bilingual dictionaries, then documents are retrieved for the translated query terms based on the vector space retrieval model or the probabilistic retrieval model. For the top-ranked retrieved documents, query-oriented document clusters are incrementally created and the weight of each retrieved document is re-calculated by using the clusters. In the experiment based on TREC test collection, our method achieved 39.41% and 36.79% improvement for translated queries without ambiguity resolution in Korean-to-English CLIR, and 17.89% and 30.46% improvements in Japanese-to-English CLIR, on the vector space retrieval and on the probabilistic retrieval, respectively. Our method achieved 12.30% improvements for all translation queries, compared with blind feedback in Korean-to-English CLIR. These results indicate that cluster analysis help to resolve ambiguity.

• Cross-Cultural Studies
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• v.38
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• pp.145-190
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• 2015

The objective of this paper is to investigate translated individual words in J. S. Gale's "Choon Yang" in comparison with its original OkJoongHwa("獄中花") while referring to early modern bilingual dictionaries and missionaries' ethnography. Gale faced a lot of translation difficulties because the source text had a very different cultural system from the object text. OkJoongHwa was a Korean pansori novel which meant it included many Korean characteristics. However, Gale considered its Korean characteristics were deeply connected with Chinese classics. Even famous people and place names cited from the Chinese classics in OkJoongHwa represented the Korean thinking. Gale tried to faithfully translate the source text as much as possible whether the words were Chinese or Korean. In this paper, we deal with mostly various translation aspects of the Chinese-letter words in OkJoongHwa. Gale's first method to translate words made of Chinese Character is transliteration, the examples of which are the name of Chinese famous people and places, and Chinese poems. The second method is to parallel transliteration and English interpretation equivalent to the Chinese Character. The examples are the names of main characters like "Spring Fragrance or Choonyang," "Mongyong, or Dream-Dragon" and in his translation of word play in Osa (Commissioner), or Kamsa (Governor), kaiksa (a dead beggar). The third is literal translation of Chinese idiomatic phrases as Gale translated 侵魚落雁 into "She'd make the fishes to sink and the wild-geese to drop from the sky." The fourth is a little free translation of the title of public office, the various names of Korean yamen servants and the unique Korean clothing and ornaments. We expect Gale's many translation difficulties as we can see the translated long list of yamen clerks and Korean clothing and ornaments. After our investigation of his translation practices in "Choon Yang" we conclude that he tried to translate its literary language very faithfully though he could not avoid inevitable loss caused by the cultural difference involved in two languages. Gale's "Choon Yang" contributed to introducing the uniqueness of the classical Korean novel and Korean culture to the world more than any other English translation works of that time through his faithful translation.

• Korean Journal of Heritage: History & Science
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• v.56 no.2
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• pp.206-220
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• 2023

In the royal publishing process of the Joseon Dynasty, the main species of wood used for woodblock printing was recorded as Jajak-mok. Although the name Jajak-mok may suggest Jajak-namu(white birch), it is presumed to refer to a different type of wood than Jajak-namu based on its recorded habitat and usage in historical documents. The aim of this paper is to clarify that during the Joseon Dynasty, the term Jajak-mok referred to Geojesu-namu (Korean birch), while Jajak-namu was called Hwa-mok(樺木). Additionally, this paper explores how the term Jajakmok eventually became the name of white birch, Jajak-namu, used today. In the mid-18th century, Japan used the character 樺(hwa) to refer to Beot-namu(Sargent cherry). As Japanese encyclopedias entered Joseon, the term Hwa-mok began to refer to both Beot-namu and Jajak-namu, which is also called Bot-namu. Since the pronunciation of Boet-namu and Bot-namu are similar, the two trees were eventually unified under the name Boet-namu. In the 20th century, the official names of three trees were established. According to notifications issued by the Ministry of Agriculture and Commerce of the Korean Empire in 1910 and the Governor-General of Chosen in 1912, Hwa-mok(white birch) was renamed asJajak-namu. In 1968, Beot-namu(Sargent cherry) retained its original name, and Jajak-mok(Korean birch) was remained . In modern Chinese character dictionaries, the meaning of 樺(hwa) is listed as "1. Beot-namu(Sargent cherry), 2. Jajak-namu(white birch)." From this, we can infer the historical background in which the names of these three trees were mixed up.