• KIPS Transactions on Software and Data Engineering
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• v.12 no.9
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• pp.381-386
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• 2023

Many existing test case generation researchers extract test cases from models. However, research on generating test cases from natural language requirements is required in practice. For this purpose, the combination of natural language analysis and requirements engineering is very necessary. However, Requirements analysis written in Korean is difficult due to the diverse meaning of sentence expressions. We research test case generation through natural language requirement definition analysis, C3Tree model, cause-effect graph, and decision table steps as one of the test case generation methods from Korean natural requirements. As an intermediate step, this paper generates test cases from C3Tree model-based decision tables using meta-modeling. This method has the advantage of being able to easily maintain the model-to-model and model-to-text transformation processes by modifying only the transformation rules. If an existing model is modified or a new model is added, only the model transformation rules can be maintained without changing the program algorithm. As a result of the evaluation, all combinations for the decision table were automatically generated as test cases.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.267-286
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• 2023

The conversational agents such as AI speakers utilize voice conversation for human-computer interaction. Voice recognition errors often occur in conversational situations. Recognition errors in user utterance records can be categorized into two types. The first type is misrecognition errors, where the agent fails to recognize the user's speech entirely. The second type is misinterpretation errors, where the user's speech is recognized and services are provided, but the interpretation differs from the user's intention. Among these, misinterpretation errors require separate error detection as they are recorded as successful service interactions. In this study, various text separation methods were applied to detect misinterpretation. For each of these text separation methods, the similarity of consecutive speech pairs using word embedding and document embedding techniques, which convert words and documents into vectors. This approach goes beyond simple word-based similarity calculation to explore a new method for detecting misinterpretation errors. The research method involved utilizing real user utterance records to train and develop a detection model by applying patterns of misinterpretation error causes. The results revealed that the most significant analysis result was obtained through initial consonant extraction for detecting misinterpretation errors caused by the use of unregistered neologisms. Through comparison with other separation methods, different error types could be observed. This study has two main implications. First, for misinterpretation errors that are difficult to detect due to lack of recognition, the study proposed diverse text separation methods and found a novel method that improved performance remarkably. Second, if this is applied to conversational agents or voice recognition services requiring neologism detection, patterns of errors occurring from the voice recognition stage can be specified. The study proposed and verified that even if not categorized as errors, services can be provided according to user-desired results.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.34 no.3
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• pp.297-318
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• 2023

The purpose of this study is to propose criteria for selecting picture books as various reading education materials for middle school students and to check whether it can be applied to book selection. First, identified the educational value of picture books as reading materials and the criteria for selecting picture books by academic field through previous studies. After integrating the commonalities of various picture book selection criteria presented in previous studies by categorizing them into illustrations, text, and other categories. And it devised selection criteria that can be applied after selecting middle school students as readers. Based on the unified picture book selection criteria, a survey was conducted to ask in-service librarians about the main criteria to consider when selecting picture books for middle school students, and intensive interviews were conducted with experts who have experience in picture book education. As a result, the picture book selection criteria from previous studies were revised and supplemented with two criteria related to text, four criteria related to pictures, and five other criteria, and presented as picture book selection criteria for middle school students. To verify the practicality of the picture book selection criteria, it checked the applicability of each category of criteria to picture books recommended by the Children's Book Research Society (ages 13 and older). Out of 22 picture books for middle school students, 15 books could be applied to all categories of the selection criteria, showing significant practicality.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.4
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• pp.171-181
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• 2018

As the proportion of sports events in the sports industry grows, the official sponsor market for sports events is also increasing. But because official sponsors are limited and expensive, some companies approach sporting events by way of Ambush marketing. This study is to analyze the differences of media exposure between official sponsors and general companies of mega sport events. To accomplish the purpose of the study, we collected text articles and analyzed them from the period of 2016 Rio Olympics, one year before the Olympics and one year after the Olympics. Web crawling was performed using Python for the collection of articles. Morphological and frequency analysis was performed using the KoNLP package and the TM package of statistical program R. In addition, the opinions of the related experts group were gathered to classify the companies or organizations in the media as the Organizing Committees for the Olympic Games(OCOGs), official sponsor, and general companies. As a result of the analysis, 5,220 times appeared related to the OCOGs, 7,845 times appeared related to the official sponsor, and 7,028 times appeared related to general companies. There isn't much difference in the frequency of exposure between official sponsors and general companies. It implies that Ambush marketing is recognized as a strategic marketing technique. The International Olympic Committee(IOC) has to recognize these social phenomena and establish reasonable standards for the marketing activities of official sponsors and general companies. And this study will serve as a basis for fair sponsor activities or marketing activities of sports events.

• Knowledge Management Research
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• v.24 no.2
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• pp.65-85
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• 2023

This paper investigates how TMT's cognitive traits affect R&D investment. Drawing on the attention-based view, we propose that TMT's future orientation and risk preference increase the level of R&D investment. As R&D activities have long-term goal of generating proprietary knowledge, it is important to understand how TMT's attention toward future and risk affect R&D investment. Also, we test the moderating effect of CEO duality on R&D investment. As the CEO plays a leadership role in the TMT, if the CEO's decision-making authority is highly concentrated, the impact of TMT on R&D may decrease. We measure CEO duality and CEO ownership stake as CEO characteristics. Based on a sample of 837 U.S. manufacturing firms, the results show that when TMT has a higher tolerance for risk and higher future orientation, R&D intensity increases. However, when CEO also serves as chairman of board and CEO has higher ownership, TMT's influence on R&D investment weakens. This implies that TMT and CEO has power dynamic that can change based on CEO power supporting status. Overall, it suggests that TMT's attention and CEO power are important factors to improve longer-term knowledge accumulation of firm.

• Journal of the Korea Society of Computer and Information
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• v.28 no.7
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• pp.155-164
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• 2023

In this paper, we examine the influence of Environmental, Social, and Governance (ESG)-related content on the success of online crowdfunding proposals. Along with the increasing significance of ESG standards in business, investment proposals incorporating ESG concepts are now commonplace. Due to the ESG trend, conventional wisdom holds that the majority of proposals with ESG concepts will have a higher rate of success. We investigate by analyzing over 9000 online business presentations found in a Kickstarter dataset to determine which characteristics of these proposals led to increased investment. We first utilized lexicon-based measurement and Feature Engineering to determine the relationship between environment and society scores and financial indicators. Next, Logistic Regression is utilized to determine the effect of including environmental and social terms in a project's description on its ability to obtain funding. Contrary to popular belief, our research found that microentrepreneurs were less likely to succeed with proposals that focused on ESG issues. Our research will generate new opportunities for research in the disciplines of information science and crowdfunding by shedding new light on the environment of online micro-entrepreneurship.

• Industry Promotion Research
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• v.8 no.3
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• pp.181-199
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• 2023

E-commerce is gradually upgrading from traditional text and image formats to short video and livestreaming formats. Livestreaming e-commerce enriches the content and forms of information dissemination and product display, enhances the consumer's shopping experience, and gradually becomes the mainstream new consumer scene. However, there are many negative phenomena in the development of livestreaming e-commerce, such as false propaganda, counterfeit goods, and various negative events, which seriously affect the level of consumer trust in livestreaming e-commerce. Trust is the core competitive factor of livestreaming e-commerce. Based on previous research on trust theory and combined with the characteristic elements of "people, goods, and scenes" of livestreaming e-commerce, this article constructs a trust model for livestreaming e-commerce, proposes hypotheses, and proves through empirical research that factors such as store characteristics, livestream host characteristics, brand image, product information, platform reputation, livestreaming situation, and trust tendency have a significant positive impact on consumer trust. Based on the research conclusions, this article provides insights and management suggestions, such as emphasizing the construction of store characteristic indicators, creating desirable livestream host characteristics, focusing on product brand building and selection, maintaining the display of product information, selecting suitable livestreaming platforms, and creating rich content for livestreaming situations.

• Journal of Industrial Convergence
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• v.21 no.8
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• pp.23-33
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• 2023

Consumer review analysis is important for product development, customer satisfaction, competitive advantage, and effective marketing. Increased use of wireless earphones is expected to reach $45.7 billion by 2026 with growth in lifestyle. Therefore, in consideration of the growth and importance of the market, consumer reviews of wireless earphones from Apple and Samsung were analyzed. In this study, 11,320 wireless earphone reviews from Apple and Samsung sold on Coupang were collected to analyze consumers' purchase intentions and analyze consumer satisfaction through analysis of the frequency, sensitivity, and LDA topic model of text mining. As a result of topic modeling, 16 topics were derived and classified into sound quality, connection, shopping mall service, purchase intention, battery, delivery, and price. As a result of brand comparison, Samsung purchased a lot for gift purposes, had a high positive sentiment for price, and Apple had a high positive sentiment for battery, sound quality, connection, service, and delivery. The results of this study can be used as data for related industries as a result of research that can obtain improvements and insights on customer satisfaction, quality and market trends, including manufacturing, retail, marketers, and consumers.

• Journal of the Korea Society of Computer and Information
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• v.28 no.12
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• pp.239-248
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• 2023

The purpose of this study is to analyze the factors for service contracts that affect the successful bid price rate, focusing on the case of the country market. In the study, ordering organizations and bidders differentiated themselves from existing studies by analyzing service contracts that affect the successful bid price rate in a wide range of country markets. Comparative analysis of the awarding price ratio for services, this work provides a comparable result to the existing results in the previous literature. The analytical model used five independent variables such as budget, contract method, the days of the public notice, the awarding method, and the lowest awarding ratio. In the survey and analysis, big data was collected using text mining for service bids for Nara Market over the past 18 years and data was analyzed in a multi-dimensional way. The results of the analysis are as follows, (1) if budget does not determine the awarding price ratio. This is not the case in small amounts. (2) The contract method affects the awarding price ratio. (3) The days of the public notice increase, the awarding price ratio decrease. (4) the awarding method affects the awarding price ratio. (5) The lowest awarding ratio determines the awarding price ratio. Based on the results of empirical analysis, policy implications were sought.

• The Transactions of the Korea Information Processing Society
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• v.13 no.3
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• pp.148-155
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• 2024

Despite the increasing importance of irony and sarcasm detection in the field of natural language processing, research on the Korean language is relatively scarce compared to other languages. This study aims to experiment with various models for irony detection in Korean text. The study conducted irony detection experiments using KoBERT, a BERT-based model, and ChatGPT. For KoBERT, two methods of additional training on sentiment data were applied (Transfer Learning and MultiTask Learning). Additionally, for ChatGPT, the Few-Shot Learning technique was applied by increasing the number of example sentences entered as prompts. The results of the experiments showed that the Transfer Learning and MultiTask Learning models, which were trained with additional sentiment data, outperformed the baseline model without additional sentiment data. On the other hand, ChatGPT exhibited significantly lower performance compared to KoBERT, and increasing the number of example sentences did not lead to a noticeable improvement in performance. In conclusion, this study suggests that a model based on KoBERT is more suitable for irony detection than ChatGPT, and it highlights the potential contribution of additional training on sentiment data to improve irony detection performance.