• The Journal of Society for e-Business Studies
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• v.23 no.3
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• pp.145-157
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• 2018

The social curation service that selectively provides information generated by individuals or groups with the same interests can have a synergistic effect when combined with the recently used SNS-based chatting function. If these kinds of chatting-based curation technologies are applied to the Internet shopping malls, particularly, buyers can obtain more reliable information in real time basis, and sellers can provide them with more differentiated and rich information in a continuous manner. This research suggests a chatting-based commerce platform that provides the social curation service based on chats among sellers, existing buyers, and potential buyers. The proposed commerce platform can organize a chat channel for each store and product not only to immediately respond to new and existing customer inquiries about stores, brands, and detailed products, but also to continuously activate differentiated sales strategies to customers subscribed to the channel. In particular, MongoDB is used to permanently save and archive the information and chatting history of each channel, so that the buyer can search and refer to them recorded in the corresponding channel at any time.

• Journal of Convergence for Information Technology
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• v.9 no.6
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• pp.202-210
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• 2019

The purpose of this study was to analyze the relationships between sexuality recognition and life satisfaction of the elderly. 256 structured questionnaires were collected from the elderly who were 65 years old plus and live Suwon city and in the vicinity of this city. Findings of the study were as follows. First, the sexuality recognition of the elderly is composed of four(4) sub-variables such as Belief on sexuality, Value of Sexuality, Conversation on sexuality, and Attitude to sexuality. Second, some differences in sexuality recognition and satisfaction of the elderly according to the demographic factors of the sample were found. Third, in case of having spouse, being good health and economic status, and being high level of sexuality recognition variables such as conversation on sexuality and attitude to sexuality, the level of life satisfaction of the elderly were high. In other words, it is necessary to develop education program of sexual education to revitalize the education of the elderly's awareness about sex.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.6
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• pp.1223-1230
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• 2020

Due to the aging of the population, the number of the elderly is increasing, and the nuclear family is rapidly progressing. Today's AI speakers respond to user's commands rather than conversations that occur on a daily basis. If the elderly living alone do not talk first, the usability of the AI speaker will decrease. In this paper, it describes the development of AI speakers for active interaction tailored to the aged. This speaker can identify the movements of the elderly who live alone and their surroundings, actively speak to them, and display emotional expressions appropriate to the content of the conversation. Through this, users will be able to anthropomorphize AI speakers, so they can feel familiarity and emotional conversation is expected to play a positive role in easing their loneliness.

• Journal of Popular Narrative
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• v.27 no.1
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• pp.341-357
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• 2021

Didier Éribon's dialogue with Ernst Gombrich, first published in 1991 in France, stands as a curious example of interpreting a scientific mind into a popular narrative. On the occasion of its brand new translation in Korean, this essay examines the encounter of two different languages, that of scholarly art history and the other, of "entretien". Éribon's previous interviews with Georges Dumézil and Claude Lévi-Strauss have already shown the perfect use of dialogue that interprets in simple words some currents of European thoughts of 20th century at its highest level. The double identity found in the extraordinary profile of the author of The Story of Art should help us deal with this particular form of dialogue in depth, and expect another possibility of explaining and reconstructing academia.

• The Journal of the Convergence on Culture Technology
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• v.7 no.2
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• pp.427-436
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• 2021

The purpose of this study is to implement a machine learning language model that learns literary texts. Literary texts have an important characteristic that pairs of question-and-answer are not frequently clearly distinguished. Also, literary texts consist of pronouns, figurative expressions, soliloquies, etc. They hinder the necessity of machine learning using literary texts by making it difficult to learn algorithms. Algorithms that learn literary texts can show more human-friendly interactions than algorithms that learn general sentences. For this goal, this paper proposes three text correction tasks that must be preceded in researches using literary texts for machine learning language model: pronoun processing, dialogue pair expansion, and data amplification. Learning data for artificial intelligence should have clear meanings to facilitate machine learning and to ensure high effectiveness. The introduction of special genres of texts such as literature into natural language processing research is expected not only to expand the learning area of machine learning, but to show a new language learning method.

• The Journal of the Korea Contents Association
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• v.21 no.12
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• pp.384-399
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• 2021

This study aims to identify the characteristics and meanings that Korean musical enthusiasts take on as cultural intermediaries of musical content by analyzing the real-time conversations they have while watching musicals performed in online spaces. To this end, the 'Live TALK' chat during the 'ontact' (online contact) performance of the musical Marie Curie was observed in real-time and subsequently analyzed in terms of the characteristics of online cultural intermediaries: their owned capital, their mediating language, and their relationship with the consumers. As a result of the analysis, musical enthusiasts were found to possess a wealth of cultural capital based on practical experience and inquiry, and to be utilizing specific identifying expressions in their language use. In addition, they appeared to be interactive in their communication with the general audience, which could be seen in the flow of spontaneous conversations as well as questions and answers occurring in the live chat. This study is significant in confirming that musical enthusiasts are positioning themselves as new cultural intermediaries through their cultural practices: taking on the role of guides and mediators in the online space 'Live TALK.'

• Journal of the Korea Society of Computer and Information
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• v.27 no.5
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• pp.181-188
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• 2022

In this paper, we proposed of the results of the noise level and appropriate conversation distance by applying the noise characteristics generated during treatment at a dental clinic to the NR-curve and PSIL. As a result of analyzing the noise characteristics during treatment at a dental clinic, it was analyzed that the noise level exceeded 60dB(A), which is the health preservation limit value caused by noise, and the noise level increased as the frequency increased. the result of evaluation applying it to the NR curve, some treatment exceeded the workplace noise standard, and as a result of analyzing the level of conversational disturbance between the worker and the patient, it is desirable to have the conversation at a distance of less than 1M for accurate communication. In order to improve the quality of medical service in dental clinic and to reduce dental fear, it is judged that soundproofing protective equipment is provided to workers, and soundproofing measures are needed for noise sources (treatment devices used in treatment) and sound sources (patients and workers).

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.1
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• pp.9-16
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• 2023

The importance of team activities increases as the problem to be solved in the industrial field become more diverse and complex. Team performance is not simply the sum of team members' performances, but synergies are gained or reduced depending on the team's interactions. Analytical research on team activities using ICT has been conducted, but developing and utilizing these technologies is time-consuming and costly, making it difficult for field practitioners and researchers to utilize them. In this study, we design a system that collects interaction information during conversations at a low cost using Arduino and Raspberry Pi and verify that conversation interaction information is collected from multiple devices and correctly stored in the database. Through the low-cost information collection system proposed in this study, we intend to create an environment where follow-up research can be conducted in various fields of industrial information.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.9
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• pp.381-390
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• 2022

Influenced by a culture that prefers non-face-to-face activity during the COVID-19 pandemic, chatbot usage is accelerating. Chatbots have been used for various purposes, not only for customer service in businesses and social conversations for fun but also for mental health. Chatbots are a platform where users can easily talk about their depressed moods because anonymity is guaranteed. However, most relevant research has been on social media data, especially Twitter data, and few studies have analyzed the commercially used chatbots data. In this study, we identified the characteristics of depressive discourse in user-chatbot interaction data by analyzing the chats, including the word 'depress,' using the topic modeling algorithm and the text-mining technique. Moreover, we compared its characteristics with those of the depressive moods in the Twitter data. Finally, we draw several design guidelines and suggest avenues for future research based on the study findings.

• Journal of the Korea Society of Computer and Information
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• v.27 no.8
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• pp.41-47
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• 2022

In this paper, we propose how to implement text summaries for colloquial data that are not clearly organized. For this study, SAMSum data, which is colloquial data, was used, and the BERTSumExtAbs model proposed in the previous study of the automatic summary model was applied. More than 70% of the SAMSum dataset consists of conversations between two people, and the remaining 30% consists of conversations between three or more people. As a result, by applying the automatic text summarization model to colloquial data, a result of 42.43 or higher was derived in the ROUGE Score R-1. In addition, a high score of 45.81 was derived by fine-tuning the BERTSum model, which was previously proposed as a text summarization model. Through this study, the performance of colloquial generation summary has been proven, and it is hoped that the computer will understand human natural language as it is and be used as basic data to solve various tasks.