• Proceedings of the KSPS conference
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• 2003.05a
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• pp.36-39
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• 2003

The purpose of this paper is to correct the errors in the isolated word speech database under the PC environment, and to analyze the various errors. The importance and procedures of the error detection are also described.

• Journal of Digital Convergence
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• v.6 no.4
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• pp.91-104
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• 2008

This study notes the growing importance of online community as a means of building customer relationships. The author aims to identify how to communicate in an online community on preannounced new products, and test social influence that influence word-of-mouth of consumers, and confirm moderate effect of market maven between social influence and word-of-mouth activity in on-line community. The main findings are that social influence such as internalization and conformity positively influence word-of-mouth communication on online community. And moderate effect of market maven confirm between social influence(internalization and confirmity) and word-of-mouth activity.

• Korean Journal of Organic Agriculture
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• v.24 no.4
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• pp.645-663
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• 2016

The purpose of this study was to look at the mediating effect of social support and interests on the relationship between characteristics of agricultural education program and word of mouth intentions. As a results of analysis of structural model, first, social support had a mediating effect on the relationship between characteristics of agricultural education program and word of mouth intentions. Second, interests had a mediating effect on the relationship between characteristics of agricultural education program and word of mouth intentions. The results highlight the importance of promoting social support and individuals' interests on the agricultural education program to increase the word of intention for agricultural education program. This eventually leads the revitalization and development of agricultural education.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.1
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• pp.136-146
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• 1995

In this paper, a Japanese morphological analyzer for Japanese to Korean Machine Translation System is designed. The analyzer reconstructs the Japanese input sentence into word phrases that include grammatical and dictionary informations. Thus we propose the algorithm to separate morphemes and then connect them by reference to a corresponding Korean word phrases. And we define the connector to control Japanese word phrases It is used in controlling the start and the end point of the word phrase in the Japanese sentence which is without a space. The proposed analyzer uses the analysis dictionary to perform more efficient analysis than the existing analyzer. And we can decrease the number of its dictionary searches. Since the analyzer, proposed in this paper, for Japanese to Korean Machine Translation System processes each word phrase in consideration of the corresponding Korean word phrase, it can generate more accurate Korean expressions than the existing one which places great importance on the generation of the entire sentence structure.

• English Language & Literature Teaching
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• v.10 no.3
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• pp.159-175
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• 2004

This paper investigated the types of errors on English pronunciation and intelligibility of Korean EFL students, and the relationship between the pronunciation accuracy and intelligibility. Thirty one students were evaluated by six English native speakers in terms of overall intelligibility and accuracy In five areas such as nuclear stress, word stress, syllable structure, consonants and vowels. According to the findings of the study, pronunciation errors were made by the subjects more frequently In word stress than any other area of pronunciation accuracy. The Pearson correlation analysis showed that intelligibility was related with word stress, syllable structure, consonants and vowels, and the stepwise multiple regression analysis indicated that, among the above five areas of pronunciation accuracy, word stress best accounted for the intelligibility of a given sentence. In the conclusion, the importance of teaching pronunciation of in those five areas with a special focus on word stress was emphasized m terms of intelligibility.

• Language and Information
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• v.12 no.1
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• pp.27-65
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• 2008

This paper presents a set of methodologies for aligning hypernym-hyponym noun pairs between Korean and English, based on the EuroWordNet approach. Following the methods conducted in EuroWordNet, our approach makes extensive use of WordNet in four steps of the building process: 1) Monolingual dictionaries have been used to extract proper hypernym-hyponym noun pairs, 2) bilingual dictionary has converted the extracted pairs, 3) Word Net has been used as a backbone of alignment criteria, and 4) WordNet has been used to select the most similar pair among the candidates. The importance of this study lies not only on enriching semantic links between two languages, but also on integrating lexical resources based on a language specific and dependent structure. Our approaches are aimed at building an accurate and detailed lexical resource with proper measures rather than at fast development of generic one using NLP technique.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.16 no.3
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• pp.38-49
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• 2008

Recently industries have started to recognize the importance of word-of-mouth marketing and human resource management especially for airline industries who suffer from pilot shortage. Pilots are very important component of airline company and require a lot of money and time to assession, training and maintaining certified license validity. This study is to test the effect of airline pilot's organizational identification, emotional exhaustion and perceived justice on turnover intention and negative word-of-mouth on airline union pilots returned from the strike. This study used both literary method and empirical method. The researcher did literary study based on the previous study, designed the research model and hypothesis, did questionnaire survey to the Union member pilot from year 2005 strike for the subject of study to verify hypothesis and analysed empirically the finding using SPSS12.0 program. The major findings of this study may be summarized as follows, (1) organizational identification has a negative effect on turnover intention and negative word-of-mouth, (2) emotional exhaustion has a positive effect on turnover intention and negative word-of-mouth, (3) perceived justice has a negative effect on turnover intention and negative word-of-mouth.

• The Korean Journal of Applied Statistics
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• v.27 no.3
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• pp.373-386
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• 2014

A word cloud is a visualization of word frequency in a given text. The importance of each word is shown in font size or color. This plot is useful for quickly perceiving the most prominent words and for locating a word alphabetically to determine its relative prominence. With dynamic graphics, we can find the changing pattern of prominent words and their frequencies according to the changing selection of chapters in a given text. We can define the word frequency matrix. In this matrix, rows are chapters in text and columns are ranks corresponding to word frequency about the words in the text. We can draw the word frequency matrix plot with this matrix. Dynamic graphic can indicate the changing pattern of the word frequency matrix according to the changing selection of the range of ranks of words. We execute an English Bible text visualization using word clouds and dynamic graphics technology.

• Journal of the Korean Society for Library and Information Science
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• v.53 no.3
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• pp.247-271
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• 2019

Uncertainty in scientific knowledge means an uncertain state where propositions are neither true or false at present. The existing studies have analyzed the propositions written in the academic literature, and have conducted the performance evaluation based on the rule based and machine learning based approaches by using the corpus. Although they recognized that the importance of word construction, there are insufficient attempts to expand the word by analyzing the meaning of uncertainty words. On the other hand, studies for analyzing the structure of networks by using bibliometrics and text mining techniques are widely used as methods for understanding intellectual structure and relationship in various disciplines. Therefore, in this study, semantic relations were analyzed by applying Word2Vec to existing uncertainty words. In addition, WordNet, which is an English vocabulary database and thesaurus, was applied to perform a network analysis based on hypernyms, hyponyms, and synonyms relations linked to uncertainty words. The semantic and lexical relationships of uncertainty words were structurally identified. As a result, we identified the possibility of automatically expanding uncertainty words.

• MALSORI
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• v.68
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• pp.115-126
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• 2008

In this paper, we propose a vocabulary coverage improvement method for embedded continuous speech recognition (CSR) using knowledgebase. A vocabulary in CSR is normally derived from a word frequency list. Therefore, the vocabulary coverage is dependent on a corpus. In the previous research, we presented an improved way of vocabulary generation using part-of-speech (POS) tagged corpus. We analyzed all words paired with 101 among 152 POS tags and decided on a set of words which have to be included in vocabularies of any size. However, for the other 51 POS tags (e.g. nouns, verbs), the vocabulary inclusion of words paired with such POS tags are still based on word frequency counted on a corpus. In this paper, we propose a corpus independent word inclusion method for noun-, verb-, and named entity(NE)-related POS tags using knowledgebase. For noun-related POS tags, we generate synonym groups and analyze their relative importance using Google search. Then, we categorize verbs by lemma and analyze relative importance of each lemma from a pre-analyzed statistic for verbs. We determine the inclusion order of NEs through Google search. The proposed method shows better coverage for the test short message service (SMS) text corpus.