• Journal of the Korean Society for information Management
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• v.40 no.4
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• pp.307-327
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• 2023

To analyze the impact of word embedding on book titles, this study utilized word embedding models (Word2vec, GloVe, fastText) to generate embedding vectors from book titles. These vectors were then used as classification features for automatic classification. The classifier utilized the k-nearest neighbors (kNN) algorithm, with the categories for automatic classification based on the DDC (Dewey Decimal Classification) main class 300 assigned by libraries to books. In the automatic classification experiment applying word embeddings to book titles, the Skip-gram architectures of Word2vec and fastText showed better results in the automatic classification performance of the kNN classifier compared to the TF-IDF features. In the optimization of various hyperparameters across the three models, the Skip-gram architecture of the fastText model demonstrated overall good performance. Specifically, better performance was observed when using hierarchical softmax and larger embedding dimensions as hyperparameters in this model. From a performance perspective, fastText can generate embeddings for substrings or subwords using the n-gram method, which has been shown to increase recall. The Skip-gram architecture of the Word2vec model generally showed good performance at low dimensions(size 300) and with small sizes of negative sampling (3 or 5).

• Fashion & Textile Research Journal
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• v.7 no.2
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• pp.218-224
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• 2005

The purpose of this study was to investigate the infiluence of positive and negative word-of-mouth informations on visiting intention of hairshop customers. Data were collected from 342 adult females and analyzed by using frequencies, factor analysis and regression utilizing SPSS/PC+. The results showed that positive word-of-mouth informations such as shop employees' skill/attitudes, physical benefit, comfortable facilities, time saving/consistent service, kindness and rational price had influence on the visiting intention of hairshop customers. The negative word-of-mouth informations that consumers had experienced using hairshop were categorized as untrustworthy face-to-face customer management, non-customer service oriented mind, and unskilled employees/inefficient hairshop environment. The negative word-of-mouth informations had no effect on the visiting intention.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1307-1312
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• 2004

Word sense disambiguation is one of the most important problems in natural language processing research topics such as information retrieval and machine translation. Many approaches can be employed to resolve word ambiguity with a reasonable degree of accuracy. These strategies are: knowledge-based, corpus-based, and hybrid-based. This paper pays attention to the corpus-based strategy. The purpose of this paper is to compare three famous machine learning techniques, Snow, SVM and Naive Bayes in Word-Sense Disambiguation on Thai language. 10 ambiguous words are selected to test with word and POS features. The results show that SVM algorithm gives the best results in solving of Thai WSD and the accuracy rate is approximately 83-96%.

• 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.

• Annual Conference on Human and Language Technology
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• 2017.10a
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• pp.209-212
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• 2017

고도화된 머신러닝과 딥러닝 기술은 영상처리, 자연어처리 등의 분야에서 많은 문제를 해결하고 있다. 특히 사용자가 입력한 문장을 분석하고 그에 따른 문장을 생성하는 자연어처리 기술은 기계 번역, 자동 요약, 자동 오류 수정 등에 널리 이용되고 있다. 딥러닝 기반의 자연어처리 기술은 학습을 위해 여러 계층의 신경망을 구성하여 단어 간 의존 관계와 문장 구조를 학습한다. 그러나 학습 과정에서의 계산양이 방대하여 모델을 구성하는데 시간과 비용이 많이 필요하다. 그러나 Word2Vec 모델은 신경망과 유사하게 학습하면서도 선형 구조를 가지고 있어 딥러닝 기반 자연어처리 기술에 비해 적은 시간 복잡도로 고차원의 단어 벡터를 계산할 수 있다. 따라서 본 논문에서는 Word2Vec 모델을 활용하여 한국어 문장을 생성하는 방법을 제시하였다. 본 논문에서는 지정된 문장 템플릿에 유사도가 높은 각 단어들을 적용하여 문장을 구성하는 Word2Vec 모델을 설계하였고, 서로 다른 학습 데이터로부터 생성된 문장을 평가하고 제안한 모델의 활용 방안을 제시하였다.

• Culinary science and hospitality research
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• v.20 no.5
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• pp.106-110
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• 2014

Little is known about the impact of ambience on customers' emotions, satisfaction, and word of mouth recommendation within the context of coffee shops. This study examined the relationships among ambience, emotions, customer satisfaction, and word of mouth recommendation in a coffee shop setting. A total of 303 visitors at 5 coffee shops in a Southwestern state in the U.S. completed questionnaires. Utilizing a structural equation modeling technique, this study demonstrated that ambience significantly influenced emotions and customer satisfaction. In addition, emotions significantly affected customer satisfaction and word of mouth recommendation.

• Journal of Korean Library and Information Science Society
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• v.12
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• pp.199-232
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• 1985

Word processor having the functions of a typewriter and a computer together have been used as a powerful tools for office automation. The purpose of this study is to find out the possible areas of the word processing a n.0, pplication in the library operations. For the study, the general concept, developmental process, structure, functions, kinds and suggested a n.0, pplicable areas in the library operations of word processor were investigated. Then, the cases of real a n.0, pplications of word processor in the library field were examplified. In conclusion, the areas where word processor can be of benefit to library workers can be summarized as follows, 1) Orders of books and periodical acquisitions, 2) On-line searching, and storage and editing of input as required, 3) Production of catalogues, and abstracting and indexing bulletin, 4) Budget control, circulation control, and serial control.

• Speech Sciences
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• v.11 no.3
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• pp.83-93
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• 2004

The objectives of this study are to analyze Korean speakers' pronunciations of various Japanese /p/ patterns and to provide desirable pronunciation models. This is a part of an ongoing research that aims to propose a useful method of teaching Japanese pronunciation of /p/ to Koreans. The experimental data consist of /p/ phonemes in word initial, word medial, and 'yoon' positions. Yoon must be written in small size after a letter and it only makes a syllable with the preceding letter in Japanese. There were 22 different phoneme positions. They were pronounced by 48 Japanese majoring students (24 females and 24 males), who were in their twenties and were raised in Daejeon and vicinity. The individual pronunciations were collected and digitized into 528 files. The results show that Koreans pronounced the Japanese phoneme /p/ in a variety of ways, according to the auditory environments in which the phoneme was tested: as [ph] in word initial, [pp] or [ph] in word medial, and [ph] in 'yoon', unlike native speakers who pronounced Japanese /p/ as [ph] in word initial, [pp] in word medial and, and [pp] or [ph] in 'yoon'.

• 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.

• MALSORI
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• no.46
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• pp.13-24
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• 2003

This experimental study shows that, in reading of the English isolated words that are enumerated, the releasing of the word-final stop is employed for signaling enumeration in company with the well-known intonational pattern for it. Furthermore, this study tries to find the aspects of the releasing of the stops in the word-final positions, focusing on the association of the stop releasing/nonreleasing with i) the POA (Place of Articulation) distinction of the word-final stop, ii) the various qualities of the vowel before the final stop, and iii) the voice distinction of the stop in the word-final position.