• The Korean Journal of Archival Studies
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• no.24
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• pp.73-112
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• 2010

With progress of the sound and moving picture recording technology, sound and moving picture have been a tool for evidence and memory on human activities. Accordingly, in archival science the importance of oral history as a record is disseminating and the production of oral record is carried out actively. But for producing oral record in archival institutions, the identity of oral record need to be established more firmly. Archival science is the task which delivers the current appearance of life to future through records. Therefore producing oral record in archival science must have unique characters. And archival science is the task which is building current memory. Therefore the identity of oral more firmly. This article intends to explore the meaning and role of oral record from a perspective of archival science. All these days, the theories and methodologies had been developed focusing on written records mainly in the deep-rooted influence of positivism. But as it is enabled the creation and preservation of records through 'speech', it need to be noted that oral record is the very core of tool for delivering the current society shape and collective memory. Therefore this article will intend to explore the meaning and role of oral record as a part of effort to establish the identity of oral record.

• Industry Promotion Research
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• v.7 no.1
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• pp.81-87
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• 2022

This study used a method of comparing and analyzing various editions of Jeokcheonsu, and aims to confirm why different views have arisen on commentaries that differ according to the perspective of one original text, which interpretation is more valid among them. The biggest part of the misunderstanding of Myeongri theory in Jeokcheonsu is Kyeokguk theory. Jeokcheonsu does not set a high value on Kyeokguk, and it is highly regarded as the Myeongri classics that emphasizes Eokbuyongsin. However, as a result of classifying the original text by theory, we can see there are about 5 sentences that directly mention Eokbu theory, but 9 sentences that explain Kyeokguk theory and 15 sentences if we include the sentences that explain Jonggyeok and Hwagyeok. Even looking that metaphoric speech is mainly used, it is also clear that it's not a book written to be read by a beginner of Myeongri. This is Myeongri texts written to convey more profound logic and enlightenment to a person who has sufficient knowledge by having learned the principle of Myeongri. A single sentence of 'Jaegwaninsubunpyeonjeong Gyeomronsiksanggyeokgukjeong' would have been sufficient to explain the Kyeokguk theory, because it's written on the assumption of the reader's level. Among the later commentaries about the theory of Myeongri contained in Jeokcheosu, 4 persons'commentaries on the original text of 'Palkyeok', 'Gwansal', Sangkwan', 'Wolryeong', 'Saengsi', 'Cheongtak' related to Kyeokguk theory was compared and analyzed.

• Journal of the Korea Society of Computer and Information
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• v.26 no.4
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• pp.105-112
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• 2021

In the era of big data, interest in data is exploding. In particular, the development of the Internet and social media has led to the creation of new data, enabling the realization of the era of big data and artificial intelligence and opening a new chapter in convergence technology. Also, in the past, there are many demands for analysis of data that could not be handled by programs. In this paper, an analysis model was designed and verified for classification of unstructured data, which is often required in the era of big data. Data crawled DBPia's thesis summary, main words, and sub-keyword, and created a database using KoNLP's data dictionary, and tokenized words through morpheme analysis. In addition, nouns were extracted using KAIST's 9 part-of-speech classification system, TF-IDF values were generated, and an analysis dataset was created by combining training data and Y values. Finally, The adequacy of classification was measured by applying three analysis algorithms(random forest, SVM, decision tree) to the generated analysis dataset. The classification model technique proposed in this paper can be usefully used in various fields such as civil complaint classification analysis and text-related analysis in addition to thesis classification.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.43 no.6 s.312
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• pp.43-51
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• 2006

This paper proposes a metrics for example matching under the example-based machine translation for English-Korean machine translation. Our metrics served as similarity measure is based on edit-distance algorithm, and it is employed to retrieve the most similar example sentences to a given query. Basically it makes use of simple information such as lemma and part-of-speech information of typographically mismatched words. Edit-distance algorithm cannot fully reflect the context of matched word units. In other words, only if matched word units are ordered, it is considered that the contribution of full matching context to similarity is identical to that of partial matching context for the sequence of words in which mismatching word units are intervened. To overcome this drawback, we propose the context-weighting scheme that uses the contiguity information of matched word units to catch the full context. To change the edit-distance metrics representing dissimilarity to similarity metrics, to apply this context-weighted metrics to the example matching problem and also to rank by similarity, we normalize it. In addition, we generalize previous methods using some linguistic information to one representative system. In order to verify the correctness of the proposed context-weighted metrics, we carry out the experiment to compare it with generalized previous methods.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.4
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• pp.169-178
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• 2022

Morphemes are most primitive units in a language that lose their original meaning when segmented into smaller parts. In Korean, a sentence is a sequence of eojeols (words) separated by spaces. Each eojeol comprises one or more morphemes. Korean morphological analysis (KMA) is to divide eojeols in a given Korean sentence into morpheme units. It also includes assigning appropriate part-of-speech(POS) tags to the resulting morphemes. KMA is one of the most important tasks in Korean natural language processing (NLP). Improving the performance of KMA is closely related to increasing performance of Korean NLP tasks. Recent research on KMA has begun to adopt the approach of machine translation (MT) models. MT is to convert a sequence (sentence) of units of one domain into a sequence (sentence) of units of another domain. Neural machine translation (NMT) stands for the approaches of MT that exploit neural network models. From a perspective of MT, KMA is to transform an input sequence of units belonging to the eojeol domain into a sequence of units in the morpheme domain. In this paper, we propose a deep learning model for KMA. The backbone of our model is based on the BERT-fused model which was shown to achieve high performance on NMT. The BERT-fused model utilizes Transformer, a representative model employed by NMT, and BERT which is a language representation model that has enabled a significant advance in NLP. The experimental results show that our model achieves 98.24 F1-Score.

• Journal of Korea Entertainment Industry Association
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• v.14 no.8
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• pp.91-102
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• 2020

The purpose of this study is to analyze musical songs from an academic perspective by applying vocal techniques that can express songs in depth in three dimensions. Singing a musical song cannot be completed with just the musical part, rather, it should be accompanied by the analysis of various aspects such as the emotional state of the scenes and the characters. To this end, this study performed a multi-dimensional analysis of fields such as theatrical structure, lyrics, musical structure, and dynamics. In addition, the study explored and applied Estill Voice Training(EVT) that actors can best express songs with the emotions of the theater and music. EVT categorizes voice into six tones: speech, sob/cry, falsetto, twang, opera, and belting. In this study, in addition to these six sounds, the positions of vocal cords and larynx were also applied to seek ways to effectively express songs using "Gar Nichts" from the musical "Elisabeth" as a case study. "Gar Nichts" is a song sung by the protagonist Elisabeth, which expresses the self and the conflict at the peak of pain. Musically, this song requires various sound and voice-changing techniques to cover the range of "G#3-Gb5." As a result, it was confirmed that in order to embody the emotions of the characters and the songs in depth, the analysis of scenes and characters as well as various singing techniques need to be applied in harmony.

• 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.

• Korean Journal of Cognitive Science
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• v.22 no.1
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• pp.57-78
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• 2011

Paraphrasing is the act of writing a text using other words without altering the meaning. Paraphrases can be used in many fields of natural language processing. In particular, paraphrases can be incorporated in machine translation in order to improve the coverage and the quality of translation. Recently, the approaches on paraphrase extraction utilize bilingual parallel corpora, which consist of aligned sentence pairs. In these approaches, paraphrases are identified, from the word alignment result, by pivot phrases which are the phrases in one language to which two or more phrases are connected in the other language. However, the word alignment is itself a very difficult task, so there can be many alignment errors. Moreover, the alignment errors can lead to the problem of selecting incorrect pivot phrases. In this study, we propose a method in paraphrase extraction that discriminates good pivot phrases from bad pivot phrases. Each pivot phrase is weighted according to its reliability, which is scored by considering the lexical and part-of-speech information. The experimental result shows that the proposed method achieves higher precision and recall of the paraphrase extraction than the baseline. Also, we show that the extracted paraphrases can increase the coverage of the Korean-English machine translation.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.6
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• pp.514-523
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• 2021

Recently, the proliferation of mobile simple payment services has been increasingly affecting people's lives. In addition, the increase in research from both China and Korea shows that the continuous development of simple mobile payment services will be very important in the future. The blog posts mentioning Kakao Pay and Alipay were collected, and keyword analysis was performed to investigate differences in consumers' responses to Kakao Pay and Alipay on social media. The frequency of keywords for each part of speech and the frequency of co-occurred words mentioned in one sentence were analyzed. Specifically, common words that appear in both Kakao Pay and Alipay blogs were extracted. The cooccurred words were analyzed to examine how different reactions were made on the same subject. As a result of the analysis, there were concerns among consumers about the trust of Kakao Pay and Alipay's benefits. For a mobile payment service to become competitive, it is necessary to add various additional services or solve security problems.

• Journal of the Korea Convergence Society
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• v.8 no.12
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• pp.55-62
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• 2017

The Named Entity Recognition system is a system that recognizes words or phrases with object names such as personal name (PS), place name (LC), and group name (OG) in the document as corresponding object names. Traditional approaches to named entity recognition include statistical-based models that learn models based on hand-crafted features. Recently, it has been proposed to construct the qualities expressing the sentence using models such as deep-learning based Recurrent Neural Networks (RNN) and long-short term memory (LSTM) to solve the problem of sequence labeling. In this research, to improve the performance of the Korean named entity recognition system, we used a hand-crafted feature, part-of-speech tagging information, and pre-built lexicon information to augment features for representing sentence. Experimental results show that the proposed method improves the performance of Korean named entity recognition system. The results of this study are presented through github for future collaborative research with researchers studying Korean Natural Language Processing (NLP) and named entity recognition system.