• Journal of Korean Medical classics
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• v.32 no.3
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• pp.47-57
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• 2019

Objectives : We aim to assist in choosing an appropriate method for word extraction when analyzing East Asian Traditional Medical texts based on unsupervised learning. Methods : In order to assign ranks to substrings, we conducted a test using one method(BE:Branching Entropy) for exterior boundary value, three methods(CS:cohesion score, TS:t-score, SL:simple-ll) for interior boundary value, and six methods(BExSL, BExTS, BExCS, CSxTS, CSxSL, TSxSL) from combining them. Results : When Miss Rate(MR) was used as the criterion, the error was minimal when the TS and SL were used together, while the error was maximum when CS was used alone. When number of segmented texts was applied as weight value, the results were the best in the case of SL, and the worst in the case of BE alone. Conclusions : Unsupervised-Learning-Based Word Extraction is a method that can be used to analyze texts without a prepared set of vocabulary data. When using this method, SL or the combination of SL and TS could be considered primarily.

• Journal of Information Technology Applications and Management
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• v.25 no.4
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• pp.123-143
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• 2018

The domestic multiplex industry provides consumers with a choice of movies and a variety of contents and entertainment facilities and services. In addition, the number of movie theaters with the significant market potential is also steadily increasing in the competitive multiplex market environment. For the analysis, we conducted research on 300 adolescents who have experienced using domestic multiplex mobile service within the recent year. This study examined the structural relationship among the multi-dimensional mobile service quality of multiple, enjoyment of use, and online word of mouth intention. Also, it explored the mediating effect of enjoyment of use and the moderating effect of gender in the structural model. As a result, the mobile service quality of multiplex has a significant effect on the online word of mouth intention through the enjoyment of use. However, there was no moderating effect of gender of participating adolescents in the relationships. Based on the analysis of empirical results, this study discussed a series of theocratical and practical implications for the marketing strategies of multiplex in the highly competitive market.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.8
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• pp.229-240
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• 2021

The environment friendly lifestyle and the green product trend have motivated corporates to develop and adopt sustainable business practices. However, an increasing number of corporations have engaged in greenwashing practices to create the appearance of environmental responsibility. By employing the theory of reasoned action, the paper investigated a model linking corporate greenwashing and consumers' green purchase intentions with the mediating role of green trust and green word-of-mouth about green electronic devices in Vietnam. Using an online survey via Email, Zalo, and Wechat, data was obtained from 308 Vietnamese consumers who have been purchasing green electronic devices. Based on the responses of the participants from the questionnaires conducted, data analysis was conducted by using SEM in AMOS version 23. This investigation shows that corporate greenwashing negatively affects consumers' green trust, green word-of-mouth, and their green buying intentions. Additionally, the paper verifies that green trust and green word-of-mouth mediate the relationships between greenwashing and consumers' green purchase intentions. These results reinforce the extant understanding of greenwashing and its consequences. Finally, the study not only stimulates future research but serves as a reference for business managers, scholars, and students who are interested on the topic of environmental sustainability, new product development, and green brands.

• Journal of the Korea Society of Computer and Information
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• v.18 no.9
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• pp.131-138
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• 2013

In this paper, I propose and evaluate the method that classifies emotional type of characters with their emotional words. Emotional types are classified as three types such as positive, negative and neutral. They are selected by classification of emotional words that characters speak. I propose the method to extract emotional words based on WordNet, and to represent as emotional vector. WordNet is thesaurus of network structure connected by hypernym, hyponym, synonym, antonym, and so on. Emotion word is extracted by calculating its emotional distance to each emotional category. The number of emotional category is 30. Therefore, emotional vector has 30 levels. When all emotional vectors of some character are accumulated, her/his emotion of a movie can be represented as a emotional vector. Also, thirty emotional categories can be classified as three elements of positive, negative, and neutral. As a result, emotion of some character can be represented by values of three elements. The proposed method was evaluated for 12 characters of four movies. Result of evaluation showed the accuracy of 75%.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.12
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• pp.881-888
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• 2013

A pre-analyzed dictionary is used to increase the speed and the accuracy of morphological analyzers and to decrease the over-generation. However, if the dictionary includes 'Insufficiently-analyzed word-phrases', which do not include all the possible analysis of the word-phrase, it may cause the decrease of the analysis accuracy. In this paper, we measure the accuracy changes according to the number of word-phrase frequency and the size changes of corpus by Sejong corpus. And performance of integrate system(SMA with pre-dictionary) is highest when sufficient analysis rate of pre-dictionary is more than 99.82%. Also pre-dictionary is constructed with word-phrase that frequency more than 32(64) when size of corpus is 1,600,000(6,300,000) word-phrase.

• The Journal of the Korea Contents Association
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• v.12 no.7
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• pp.40-53
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• 2012

In the past, the elements that determine the movie performance were directors, movie stars, the number of opening screens, on-line ratings or distributing agencies. However, the word-of-mouth effect has changed this trends. So the influence of word of mouth grows more and more strong at this stage of the Internet and smart phones being widely prevalent. I fix my sight upon SNS which is one of the medium of arousing the word-of-mouth effect, and I have a purpose to cast light upon a real example of the influence of SNS on the movie performance. The way is to analyze SNS activities that accompany the process of production and showing of , which is said to have had an beneficial effect of SNS among the enormously successful movies last year. It is relevant to provide a new milestone regarding the movie performance through the successful case of SNS activities by examining the word-of-mouth activities through SNS in the manner of the period division of the pre-release, the early stage of release and the maturity.

• The Journal of Information Systems
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• v.30 no.1
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• pp.45-64
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• 2021

Purpose The traditional topic modeling technique makes it difficult to distinguish the semantic of topics because the key words assigned to each topic would be also assigned to other topics. This problem could become severe when the number of online reviews are small. In this paper, the extended model of topic modeling technique that can be used for analyzing a small amount of online reviews is proposed. Design/methodology/approach The extended model of being proposed in this paper is a form that combines the traditional topic modeling technique and the Word2Vec technique. The extended model only allocates main words to the extracted topics, but also generates discriminatory words between topics. In particular, Word2vec technique is applied in the process of extracting related words semantically for each discriminatory word. In the extended model, main words and discriminatory words with similar words semantically are used in the process of semantic classification and naming of extracted topics, so that the semantic classification and naming of topics can be more clearly performed. For case study, online reviews related with Udo in Tripadvisor web site were analyzed by applying the traditional topic modeling and the proposed extension model. In the process of semantic classification and naming of the extracted topics, the traditional topic modeling technique and the extended model were compared. Findings Since the extended model is a concept that utilizes additional information in the existing topic modeling information, it can be confirmed that it is more effective than the existing topic modeling in semantic division between topics and the process of assigning topic names.

• Journal of Information Processing Systems
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• v.18 no.4
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• pp.549-561
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• 2022

In the Khmer writing system, the Khmer script is the official letter of Cambodia, written from left to right without a space separator; it is complicated and requires more analysis studies. Without clear standard guidelines, a space separator in the Khmer language is used inconsistently and informally to separate words in sentences. Therefore, a segmented method should be discussed with the combination of the future Khmer natural language processing (NLP) to define the appropriate rule for Khmer sentences. The critical process in NLP with the capability of extensive data language analysis necessitates applying in this scenario. One of the essential components in Khmer language processing is how to split the word into a series of sentences and count the words used in the sentences. Currently, Microsoft Word cannot count Khmer words correctly. So, this study presents a systematic library to segment Khmer phrases using the bi-directional maximal matching (BiMM) method to address these problematic constraints. In the BiMM algorithm, the paper focuses on the Bidirectional implementation of forward maximal matching (FMM) and backward maximal matching (BMM) to improve word segmentation accuracy. A digital or prefix tree of data structure algorithm, also known as a trie, enhances the segmentation accuracy procedure by finding the children of each word parent node. The accuracy of BiMM is higher than using FMM or BMM independently; moreover, the proposed approach improves dictionary structures and reduces the number of errors. The result of this study can reduce the error by 8.57% compared to FMM and BFF algorithms with 94,807 Khmer words.

• Journal of Distribution Science
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• v.21 no.1
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• pp.85-93
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• 2023

Purpose: This research is intended to analyze how distribution of brand communication of a Soft Drink brand on brand image mediated through electronic word of mouth on packaged carbonated drink in Indonesian Gen-Z. This research also aims to find out how electronic word of mouth can have a role in creating a brand image for Indonesia Gen-Z. Research design, data and methodology: This research is using a quantitative approach with purposive sampling technique, a survey was conduct online and the number of samples being 384 responders who are spread all over Indonesia. The questionnaire construct was designed based on several variables, such as brand communication, brand image, and e-WOM. E-WOM was positioned as a mediating variable in this research. Brand Communication indicators consist of event and experience, public relation and publicity, direct marketing and personal selling. Meanwhile brand image consists of Attributes, Benefits, and Attitudes. E-WOM indicators consist of intensity, balance of opinion, and content. Results: The result of this research being (1) There is a significant influence between brand communication and brand image. (2) There is a significant influence between brand communication and electronic word-of-mouth. And (3) There is a significant influence between brand communication and brand image mediated through electronic word-of-mouth. Conclusion: The findings of this research prove that there is significant influence between brand communication, brand image and electronic word-of-mouth, this study also provide several information about how other factor affect the distribution of brand communication.

• Journal of the Korean School Mathematics Society
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• v.20 no.2
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• pp.141-161
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• 2017

As it's important to understand the order of operation in the mixed calculation of natural number and perform it, mathematics curriculums and textbooks focused that students can calculate with understanding the order of operation and its principles. For attaining the implications of teaching about the mixed calculations, this study analyzed the problem solving abilities and error types of 67 elementary students and 57 pre-service teachers using questionnaire which was developed in this study and composed of numeric expressions and word problems. The conclusions drawn from this study were as follows: Students were revealed the correct rates(86.2% and 73.5%) in numeric expressions and word problems, but they were showed the paradigmatic error types-the errors of the order of operation and the composition of numeric expression from word problems. Even though the correct rates of the preservice teachers were extremely high, the result of problem solving processes required that it's needed to be interested in teaching the principles of the order of operation in the mixed calculations. In addition, subjects were revealed the problems about using parentheses and equal sign.