• Proceedings of the KSPS conference
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• 2006.05a
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• pp.117-120
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• 2006

This paper examined two hypotheses. Firstly, if the first syllable of word play an important role in visual word recognition, it may be the unit of word neighbor. Secondly, if the first syllable is the unit of lexical access, the neighborhood size effect and the neighborhood frequency effect would appear in a lexical decision task and a form primed lexical decision task. We conducted two experiments. Experiment 1 showed that words had large neighbors made a inhibitory effect in the LDT(lexical decision task). Experiment 2 showed the interaction between the neighborhood frequency effectand the word form similarity in the form primed LDT. We concluded that the first syllable in Korean words might be the unit of word neighborhood and play a central role in a lexical access.

• The Research Journal of the Costume Culture
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• v.6 no.3
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• pp.6-10
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• 1998

The purpose of this study was to identify and to trace origins of the names of boshon(보션) and Chung(쳥) used in Chosun period. Comparative linguistic analytical approaches were employed for this research. Conclusions and summary of finds and results of this study can be summarized as follows: It was found that the name, boshon had its origin in Aramaic, while the name, chung had its origin in Chinese. The word, boshon (보션) is a transliteration of Aramaic pattashehon, leggins. The name, boshon is a borrowed word from Aramaic. The word, bai shu(背戍) of Koryo period and the word, boshon(보션) of Chosun period were originated in one word, ai shu was taken from a singular form, while boshon was taken from a plural form. Because these two words in Koran have different phonetic values, ′they ar treated as tow different words. The name, chung(쳥) is a transliteration of Chinese cheuan, ch′"uan, Korean chung is a corrupted form of cheunan or ch′"uan.

• Journal of Korea Multimedia Society
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• v.25 no.3
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• pp.493-501
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• 2022

This paper is a study on context-sensitive spelling error correction and uses the Korean WordNet (KorLex)[1] that defines the relationship between words as a graph to improve the performance of the correction[2] based on the vector information of the word embedded in the correction technique. The Korean WordNet replaced WordNet[3] developed at Princeton University in the United States and was additionally constructed for Korean. In order to learn a semantic network in graph form or to use it for learned vector information, it is necessary to transform it into a vector form by embedding learning. For transformation, we list the nodes (limited number) in a line format like a sentence in a graph in the form of a network before the training input. One of the learning techniques that use this strategy is Deepwalk[4]. DeepWalk is used to learn graphs between words in the Korean WordNet. The graph embedding information is used in concatenation with the word vector information of the learned language model for correction, and the final correction word is determined by the cosine distance value between the vectors. In this paper, In order to test whether the information of graph embedding affects the improvement of the performance of context- sensitive spelling error correction, a confused word pair was constructed and tested from the perspective of Word Sense Disambiguation(WSD). In the experimental results, the average correction performance of all confused word pairs was improved by 2.24% compared to the baseline correction performance.

• Journal of Korean Medical classics
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• v.29 no.3
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• pp.75-80
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• 2016

Objectives : The paper raises an objection to the word '涕' being used to refer to nasal discharge, and proposes a word for nasal discharge upon studying a set of medical books. Methods : The author finds and confirms the dictionary definition of '涕' and studies how they are used differently in medical books. Through this study, the author shows how the word '涕' is used incorrectly and makes deductions for its reason. The author takes a look at the old form of the word '涕', its etymological origin, takes a guess as to the real word that should have been used to refer to nasal discharge, and find examples of instances where this correct word for nasal discharge are more appropriate. Results & Conclusions : In medical books such as Huangdineijing Suwen, '涕' is used to mean nasal discharge, but the word's dictionary definition does not validate such usage. Yugunryeombu (劉君廉夫), in its commentary for Somun, used '?' and '鼻夷' for '涕', and '?' means nasal discharge and used as same as '涕' when its used to mean tear. This is a phenomenon that originated from '弟' and '夷' being used interchangeably which led to the incorrect usage of '?'. If someone were to refer to nasal discharge, he needs to use '?'. '鼻夷' is believed to be the same word as '弟鼻', which is the old form of '?', and it means both tear(pronounced 'Che') and nasal discharge(pronounced 'Je'). However, the pronunciation different between 'Che' and 'Je', and its definition as tear, is divided in later periods into '涕' following the shape of '弟'. Following the shape of '夷', the meaning of nasal discharge remains in '?' while retaining the pronunciation of 'yi'. Therefore, the word '涕' used to mean nasal discharge is an incorrect form of '?', and should all be re-written to '?'.

• MALSORI
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• no.60
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• pp.29-45
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• 2006

We investigated whether the first syllable plays an important role in lexical access in Korean visual word recognition. To do so, one lexical decision task (LDT) and two form primed LDT experiments examined the nature of the syllabic neighborhood effect. In Experiment 1, the syllabic neighborhood density and the syllabic neighborhood frequency was manipulated. The results showed that lexical decision latencies were only influenced by the syllabic neighborhood frequency. The purpose of experiment 2 was to confirm the results of experiment 1 with form-primed LDT task. The lexical decision latency was slower in form-related condition compared to form-unrelated condition. The effect of syllabic neighborhood density was significant only in form-related condition. This means that the first syllable plays an important role in the sub-lexical process. In Experiment 3, we conducted another form-primed LDT task manipulating the number of syllabic neighbors in words with higher frequency neighborhood. The interaction of syllabic neighborhood density and form relation was significant. This result confirmed that the words with higher frequency neighborhood are more inhibited by neighbors sharing the first syllable than words with no higher frequency neighborhood in the lexical level. These findings suggest that the first syllable is the unit of neighborhood and the unit of representation in sub-lexical representation is syllable in Korea.

• Journal of Distribution Science
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• v.20 no.7
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• pp.87-95
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• 2022

Purpose: This study aims to analyze the effects of Brand Coolness, Brand Love, and Self-brand Connections on Word-of-mouth positively. The retail format of Starbuck in Vietnam is successful in distribution applied when it becomes the place for customers to express themselves. Consumers are now aware about Brand Coolness of the Starbucks developed in Vietnam then turn to love the brand of store and connect themselves to the brand. In this study, the closest relationship to form the basis for consumer Word-of-mouth about a brand is the relationship between Brand Coolness and Brand Love. Results: The findings show that Brand Coolness and Brand Love are important value factors in customers' minds toward their behavior, form there, it will contribute to the brand store in distribution. Research design, data and methodology: This article used the quantitative technique utilizing PLS-SEM software to test the hypothesis with 600 samples. The data obtained shows that people have Word-of-mouth about the retail format of Starbucks in Ho Chi Minh City. Conclusion: The study has demonstrated the conclusions and proposed solutions to help beverage brands build Brand Love, thereby achieving coolness, connecting brands with themselves, leading to customer Word-of-mouth in a positive way towards retail format.

• Journal of the Korean Society of Food Culture
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• v.34 no.2
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• pp.112-128
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• 2019

The history of modern Korean 'kimchi' can be traced through the history of the wordforms 'dihi' (디히), 'dimchʌi' (딤?), and 'thimchʌi' (팀?) in ancient Korean texts. As native Korean words, the 'dihi' word line ('dihi', 'dii', 'jihi', and 'ji') constitutes an old substratum. This word line coexisted with the 'dimchʌi' word line (dimchʌi, jimchʌi, and kim∫chi) from the Hanja '沈菜'. 'Ji', which is the last word variation of 'dihi', and is still used today as the unique form in several Korean dialects. In standard Korean, however, it only serves as a suffix to form the derivative names of various kimchi types. 'Dimchʌi' is believed to have appeared around the $6^{th}-7^{th}$ centuries, when Silla began to master Chinese characters. Hence,'dimchʌi' reflects either the Archaic Chinese (上古音) or the Old Chinese (中古音) pronunciation of the Hanja, '沈菜'. With the palatalization of the plosive alveolar [t], 'dimchʌi' changed to 'jimchʌi'. The Yangban intellectuals' rejection of the palatalization of the plosive velar [k] led to the hypercorrection of 'jimchʌi' into 'kimchʌi'. It is precisely the hypercorrect 'kimchʌe' that gave the wordform 'kim∫chi', which has eventually become the standard and predominant form in today's Korean language. Regarding 'thimchʌe', it reflects the Middle Chinese (Yuan Dynasty) pronunciation of the Hanja '沈菜' and was used mainly in writing by Yangban intellectuals.

• Cross-Cultural Studies
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• v.25
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• pp.743-773
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• 2011

In this research, the writer has done a comparative analysis of 4,791 trisyllabic modern Chinese vocabularies from "a dictionary for trisyllabic modern Chinese word" and the corresponding Korean words written in Chinese characters out of 170,000 vocabularies hereupon that are collected in "new age new Korean dictionar y". Aa a result, we have the total 407 pairs of corresponding group with the following 3 types: 1) Chinese : Korean 3(2) : 3 syllable Chinese characters with completely same form-morpheme and same meaning, use, class (376pairs, 92.38% of 407), 2) Chinese : Korean 3 : 3 syllable Chinese characters with completely same form-morpheme and partly same meaning, use, class (18pairs, 4.42% of 407), 3)Chinese : Korean 3 : 3 syllable Chinese characters with completely same form-morpheme and different meaning, use, class (13pairs, 3.19% of 407).

• Journal for History of Mathematics
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• v.21 no.3
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• pp.97-112
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• 2008

In this study, the research results up to now on original word form and its meaning of Korean number words hana, dul, ..., yeol are looked out from math-historically. In fact, finding out original word form and its meaning of hana, dul, and set(ses) may not be possible in the respect of history of mathematics. There might have been a gap between set(ses) and net(nes), and between net(nes) and daseot(daseos). Original word form and its meaning of hana, dul, set(ses), and net(nes) must be found out in different aspect from those of daseot(daseos), yeoseot(yeoseos), ..., yeol. There might have been a gap between yeoseot(yeoseos) and ilgop(ilgob). Coining number word mechanism for ilgop(ilgob), yeodeol,(yeodeolb) and ahop(ahob) might have been same each other. There might have been a gap between ahop(ahob) and yeol. The research results up to now have not paid attention to this gaps sufficiently. But according to history of mathematics, there must have existed several gaps.

• Proceedings of the Acoustical Society of Korea Conference
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• 1993.06a
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• pp.121-124
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• 1993

This paper is a study on the word recognition using neural network. A limited vocabulary, speaker independent, isolated word recognition system has been built. This system recognizes isolated word without performing segmentation, phoneme identification, or dynamic time wrapping. It needs a static pattern approach to recognize a spatio-temporal pattern. The preprocessing only includes preceding and tailing silence removal, and word length determination. A LPC analysis is performed on each of 24 equally spaced frames. The PARCOR coefficients plus 3 other features from each frame is extracted. In order to simplify a structure of neural network, we composed binary code form to decrease output nodes.