• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.1
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• pp.28-32
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• 2004

Till now, Korean spelling proofreading system has corrected words of a sentence from the relationship of a collocation or the grammatical information of the sentence. In this paper, we propose a system that corrects a word using the relationship among the sememes in a single sentence and substitutes an apt word for a word of the sentence that has the meaningful mistake by a mistyping. The proposed system makes several sentences that are able to communicate with each sememe. The substantives forms meaning tree according to the meaning of the word and the predicate of a sentence defines the meaningful relationship between a substantives of the subject and the object. After this system compares and analyzes the relationship of meaning, it corrects the mistyping of a word in a single sentence that includes an error. If the system finds out the semantic error by the mistyping, it applies the spelling proofreading method that proposed in this paper.

• The Southeast Asian review
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• v.28 no.4
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• pp.223-252
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• 2018

The purpose of this paper is to substantially analyse the patterns of complements considering the aspects of not only syntax but also morphology since the concept of complement has been used as a term to analyse the components of a sentence. However, it cannot be denied that there seemed to be limitations due to the partial explanation or different explanations of the same sentence. Thus, this paper aims at dealing with the close relation between sentential components and suffixes to examine the sentence patterns; subject, predicate, object, complement, and adjunct focusing on the terms of complement which has been seen problematic due to incomplete explanations and different interpretations of the same sentence. Finally, this paper synthesises various opinions of many scholars and integrates them to get explicit and practical patterns of complement of a sentence based on not only syntax but also morphology through close relation between sentential components and morphological suffixes.

• Smart Media Journal
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• v.11 no.3
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• pp.31-38
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• 2022

In the document extraction summary study, various methods for selecting important sentences based on the relationship between sentences were proposed. In the Korean document summary using the summation similarity of sentences, the summation similarity of the sentences was regarded as the amount of sentence information, and the summary sentences were extracted by selecting important sentences based on this. However, the problem is that it does not take into account the various importance that each sentence contributes to the entire document. Therefore, in this study, we propose a document extraction summary method that provides a summary by selecting important sentences based on the amount of quantitative and semantic information in the sentence. As a result, the extracted sentence agreement was 58.56% and the ROUGE-L score was 34, which was superior to the method using only the combined similarity. Compared to the deep learning-based method, the extraction method is lighter, but the performance is similar. Through this, it was confirmed that the method of compressing information based on semantic similarity between sentences is an important approach in document extraction summary. In addition, based on the quickly extracted summary, the document generation summary step can be effectively performed.

• Proceedings of the Korean Society for Language and Information Conference
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• 1991.02a
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• pp.195-214
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• 1991

• Journal of Korean Medical classics
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• v.31 no.3
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• pp.109-122
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• 2018

Objectives : The teaching which states, "Pi is the source of the phlegm and lung is the container of the phlegm" is a sentence that is regarded to have been based on the understanding of the production and container of phlegm based on physiology and pathology of viscera and bowels. However, the author's suspicion that this sentence has not received enough research as to truly understand its meaning has led to further study into this sentence. Methods : Medical book database was searched and historic medical books were reviewed in order to understanding the true meaning of this sentence. First, the meaning of the sentence was pondered upon based on how it was introduced in the original text, and each of the two parts of the sentence were closely analyzed for its relations in order to get a clear meaning of the sentence. Results : The source of this sentence is Bencaogangmu, and it describes the phenomenon of cough in the phlegm appearing more than that from pi and lungs. Later, some disagreements on this sentence developed, claiming that kidney is the source of phlegm whereas stomach is the container. Pi deficiency derives from abnormality in the transportation and transformation of pi, and it originates from kidney deficiency. Thus, kidney can be understood as the origin of phlegm. When phlegm is dispersed all around the body, it's difficult to see the stomach as a container of the phlegm. Conclusions : The pathology of the production and container of phlegm is that deficiency in kidney qi leads to the malfunction of transportation and transformation of pi, and this creates the bodily fluid to become stagnant, making pathological products such as dampness, phlegm, and retained fluid. This can be expressed as "Kidney is the origin of the phlegm, and pi is the source of the phlegm." Here, phlegm is created and stored either when phlegm enters the lungs in the process of pi dissipating into the lungs, or when pi affects the lungs which inhibits the pi movement in the lungs. This is the true meaning of "lung is the container of the phelgm."

• The Journal of Korean Philosophical History
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• no.25
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• pp.411-437
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• 2009

Generally transition of Thought from Wang Yangming(王陽明) to Liu Zongzhou(劉宗周) is construed from emphasis of subjectivity to emphasis of intention(意; Yi). This Transition from emphasis of subjectivity to emphasis of intention is definitely expressed between Wang Yangming's Four-Sentence Teaching(四句敎) and Liu Zongzhou's explanation of Wang Yangming's Four-Sentence Teaching. Wang Yangming's Four-Sentence Teaching evoked much controversy among scholars of Yangming school. Consequently Four-Sentence Teaching's controversy caused Yangming school's division. Also this was a representative controversy on the transition period from The Ming Dynasty to The Ching Dynasty. Liu Zongzhou's critique and exposition of Four-Sentence Teaching was result from this controversy. The difference between Wang Yangming's Xinxue(心學) and Liu Zongzhou' Xinxue(心學) is due to different interpretation of intention. As is generally known Wang Yangming interprets intention is in heart stiring, but Liu Zongzhou interprets intention is being before heart stiring, immanence in heart. Liu Zongzhou suggests new exposition of Four-Sentence Teaching on intention being before heart stiring, immanence in heart. Liu Zongzhou's critique and exposition is not only criticizing Yangming's Four-Sentence Teaching, but also solves troubles of the times. As a result he promotes theory of Xinxue(心學) being peculiar his own.

• Journal of The Korean Association For Science Education
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• v.44 no.3
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• pp.231-248
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• 2024

This study developed a chatbot for first-year high school students, employing open-source software and the Korean Sentence-BERT model for AI-powered document classification. The chatbot utilizes the Sentence-BERT model to find the six most similar Q&A pairs to a student's query and presents them in a carousel format. The initial dataset, built from online resources, was refined and expanded based on student feedback and usability throughout over the operational period. By the end of the 2023 academic year, the chatbot integrated a total of 30,819 datasets and recorded 3,457 student interactions. Analysis revealed students' inclination to use the chatbot when prompted by teachers during classes and primarily during self-study sessions after school, with an average of 2.1 to 2.2 inquiries per session, mostly via mobile phones. Text mining identified student input terms encompassing not only science-related queries but also aspects of school life such as assessment scope. Topic modeling using BERTopic, based on Sentence-BERT, categorized 88% of student questions into 35 topics, shedding light on common student interests. A year-end survey confirmed the efficacy of the carousel format and the chatbot's role in addressing curiosities beyond integrated science learning objectives. This study underscores the importance of developing chatbots tailored for student use in public education and highlights their educational potential through long-term usage analysis.

• ETRI Journal
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• v.35 no.1
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• pp.89-99
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• 2013

The problem of the sentence-based pronunciation evaluation task is defined in the context of subjective criteria. Three subjective criteria (that is, the minimum subjective word score, the mean subjective word score, and first impression) are proposed and modeled with the combination of word-based assessment. Then, the subjective criteria are approximated with objective sentence pronunciation scores obtained with the combination of word-based metrics. No a priori studies of common mistakes are required, and class-based language models are used to incorporate incorrect and correct pronunciations. Incorrect pronunciations are automatically incorporated by making use of a competitive lexicon and the phonetic rules of students' mother and target languages. This procedure is applicable to any second language learning context, and subjective-objective sentence score correlations greater than or equal to 0.5 can be achieved when the proposed sentence-based pronunciation criteria are approximated with combinations of word-based scores. Finally, the subjective-objective sentence score correlations reported here are very comparable with those published elsewhere resulting from methods that require a priori studies of pronunciation errors.

• Phonetics and Speech Sciences
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• v.1 no.4
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• pp.47-59
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• 2009

The purpose of this paper is to propose an automatic evaluation technique for the prosodic aspect of an English sentence uttered by Korean speakers learning English. The underlying hypothesis is that the consistency of the manual prosody scoring is reflected in an imaginary space of prosody evaluation model constructed out of the three physical properties of the prosody considered in this paper, namely: the fundamental frequency (F0) contour, the intensity contour, and the segmental durations. The evaluation proceeds first by building a prosody evaluation model for the sentence. For the creation of the model, utterances from native speakers of English and Korean learners for the target sentence are manually scored by either native teachers of English or Korean phoneticians in terms of their prosody. Multiple native utterances from the manual scoring are selected as the "model" native utterances against which all the other Korean learners' utterances as well as the model utterances themselves can be semi-automatically evaluated by comparison in terms of the three prosodic aspects [7]. Each learner utterance, when compared to the multiple model native utterances, produces multiple coordinates in a three-dimensional space of prosody evaluation, each axis of which corresponds to the three prosodic aspects. The 3D coordinates from all the comparisons form a prosody evaluation model for the particular sentence and the associated manual scores can display regions of particular scores. The model can then be used as a predictive model against which other Korean utterances of the target sentence can be evaluated. The model from a Korean phonetician appears to support the hypothesis.

• Proceedings of the Korea Contents Association Conference
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• 2004.11a
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• pp.470-475
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• 2004

In this paper, we propose a method to extract a definitional answer sentence for a Definitional Question-Answering System. definitional answer sentence patterns are manually constructed with restriction rules to patterns, and a ranking information of the pattern using its frequency from the corpus. answer sentence pattern consists of the syntactic structure of a definitional answer sentence, and clue words. this system show 83% accuracy for untrained corpus.