• Journal of Fashion Business
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• v.25 no.4
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• pp.79-91
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• 2021

Currently, chatbot, a conversational platform based on artificial intelligence, is drawing attention as a new marketing channel. This study attempted to verify the effect of the anthropomorphism, message type, and media self-efficacy level on purchase intention. The experimental design of this study was a 2 (anthropomorphism level of shopping chatbot: low vs. high) × 2 (message type: factual vs. evaluative) × 2 (media self-efficacy: low vs. high) three-way mixed analysis of variance (ANOVA). This study conducted a survey by the convenience sampling method of 402 women in their 20s and 30s living in Seoul and the Gyeonggi area who were aware of chatbot services. For the final analysis, 388 questionnaires were used. Data were analyzed with the SPSS 23 program and three-way ANOVA. Simple main effects analysis was conducted. The results of this study were as follows. First, there were statistically significant differences in purchase intention according to anthropomorphism level, message type, and media self-efficacy. Second, message type and media self-efficacy showed statistically significant interaction effects on purchase intention. Lastly, anthropomorphism and the media self-efficacy level and the message type of the shopping chatbots showed significant three-way interaction effects on purchase intention.

• Annual Conference of KIPS
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• 2022.11a
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• pp.11-13
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• 2022

데이터 3 법을 필두로, 기업은 개인정보가 포함된 데이터를 활용하기 위해 비식별 처리가 필요하게 되었다. 기존 방식은, 비정형 텍스트 데이터에서 정규표현식을 통한 개인정보 식별은 데이터의 다양성에 의해 한계가 명확하며, 기존의 Named Entity Recognition(NER) 태스크로 해결하기에는 언어의 중의적 표현과 2 인 대화에서 나타나는 개인정보가 누구의 것인지 판단하지 못한다는 한계가 존재한다. 따라서 우리는 기존의 한계점을 극복하고 개선하기 위해 BERT 언어 모델에 화자 정보를 학습시키고, 하나의 어절에 2 개의 tag 를 labeling 하는 방법을 제안하여 정확한 개인정보 식별을 시도하였다.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.33 no.4
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• pp.412-418
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• 2023

As advances in artificial intelligence (AI) increasingly approach areas once relegated to the realm of science fiction, there is growing public interest in using these technologies for practical everyday tasks in both the home and the workplace. This paper explores the applications of and implications for of using ChatGPT, a conversational AI model based on GPT-3.5 and GPT-4.0, in the field of occupational health and safety. After gaining over one million users within five days of its launch, ChatGPT has shown promise in addressing issues ranging from emergency response to chemical exposure to recommending personal protective equipment. However, despite its potential usefulness, the integration of AI into scientific work and professional settings raises several concerns. These concerns include the ethical dimensions of recognizing AI as a co-author in academic publications, the limitations and biases inherent in the data used to train these models, legal responsibilities in professional contexts, and potential shifts in employment following technological advances. This paper aims to provide a comprehensive overview of these issues and to contribute to the ongoing dialogue on the responsible use of AI in occupational health and safety.

• Journal of Information Science Theory and Practice
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• v.12 no.2
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• pp.79-95
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• 2024

The new AI based conversational chatbot, ChatGPT, launched in November 2022, is causing a stir. There are many opinions about this being a 'threat or a promise,' and thus it is important to understand what has been said about this tool and, based on the growing literature that has emerged on the subject, demystify its effective impact on society. To analyse this impact, a systematic literature review with the support of the preferred reporting items for systematic reviews and meta-analysis protocol was used. The data, scientific documents, were collected using the main scientific databases - SCOPUS and Web of Science - and the results were presented based on a bibliometric and thematic exploration of content. The main findings indicate that people are increasingly using this chatbot in more diverse areas. Therefore, this study contributes at the practical level, aiming to enlighten people in general - both in professional and personal life - about this tool and its impacts. Also, it contributes at the theoretical level, which involves expanding understanding and elucidation of the impacts of ChatGPT in different areas of study.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.384-389
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• 2008

Recently, the necessity of systems which effectively store and retrieve video data has increased. Conventional video retrieval systems retrieve data using menus or text based keywords. Due to the lack of information, many video clips are simultaneously searched, and the user must have a certain level of knowledge to utilize the system. In this paper, we suggest a natural language based conversational video retrieval system that reflects users' intentions and includes more information than keyword based queries. This system can also retrieve from events or people to their movements. First, an event database is constructed based on meta-data which are generated by domain analysis for collected video in an office environment. Then, a script database is also constructed based on the query pre-processing and analysis. From that, a method to retrieve a video through a matching technique between natural language queries and answers is suggested and validated through performance and process evaluation for 10 users The natural language based retrieval system has shown its better efficiency in performance and user satisfaction than the menu based retrieval system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.10B
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• pp.947-956
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• 2003

The current IP Routing Protocolspacket networks also need to provide the network QoS based of DiffServ, RSVP, MPLStraffic model which is standardized as IETF reference model for NGN. The first topic of this paper is to propose Traffic-Balanced Routing Protocol(TBRP) to process existing best effort traffic. TBRP will process low priority interactive data and background data which is not sensitive to dealy. Secondly Hierarchical Traffic-Traffic-Scheduling Routing Protocol(HTSRP) is also proposed. HTSRP is the hierarchical routing algorithm for backbone and access networkin case of fixed-wireless convergence network. Finally, HTSRP_Q is proposed to meet the QoS requirement when user want interactive or streaming packet service. This protocol will maximize the usage of resources of access layer based on the QoS parameters and process delay-sensitive traffic. Service classes are categorized into 5 types by the user request, such as conversational, streaming, high priority interactive, low priority interactive, and background class. It could be processed efficiently by the routing protocolstraffic model proposed in this paper. The proposed routing protocolstraffic model provides the increase of efficiency and stability of the next generation network thanks to the routing according to the characteristic of the specialized service categories.

• Journal of the Korea Society of Computer and Information
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• v.26 no.10
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• pp.37-43
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• 2021

Using the acoustic features of speech, important social and linguistic information about the speaker can be obtained, and one of the key features is the dialect. A speaker's use of a dialect is a major barrier to interaction with a computer. Dialects can be distinguished at various levels such as phonemes, syllables, words, phrases, and sentences, but it is difficult to distinguish dialects by identifying them one by one. Therefore, in this paper, we propose a lightweight Korean dialect classification model using only MFCC among the features of speech data. We study the optimal method to utilize MFCC features through Korean conversational voice data, and compare the classification performance of five Korean dialects in Gyeonggi/Seoul, Gangwon, Chungcheong, Jeolla, and Gyeongsang in eight machine learning and deep learning classification models. The performance of most classification models was improved by normalizing the MFCC, and the accuracy was improved by 1.07% and F1-score by 2.04% compared to the best performance of the classification model before normalizing the MFCC.

• Journal of Fashion Business
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• v.27 no.3
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• pp.50-62
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• 2023

The e-commerce fashion market has experienced a remarkable growth, leading to an overwhelming availability of shared information and numerous choices for users. In light of this, chatbots have emerged as a promising technological solution to enhance personalized services in this context. This study aimed to develop user-product attributes for a chatbot-based personalized fashion recommendation service using big data text mining techniques. To accomplish this, over one million consumer reviews from Coupang, an e-commerce platform, were collected and analyzed using frequency analyses to identify the upper-level attributes of users and products. Attribute terms were then assigned to each user-product attribute, including user body shape (body proportion, BMI), user needs (functional, expressive, aesthetic), user TPO (time, place, occasion), product design elements (fit, color, material, detail), product size (label, measurement), and product care (laundry, maintenance). The classification of user-product attributes was found to be applicable to the knowledge graph of the Conversational Path Reasoning model. A testing environment was established to evaluate the usefulness of attributes based on real e-commerce users and purchased product information. This study is significant in proposing a new research methodology in the field of Fashion Informatics for constructing the knowledge base of a chatbot based on text mining analysis. The proposed research methodology is expected to enhance fashion technology and improve personalized fashion recommendation service and user experience with a chatbot in the e-commerce market.

• Journal of Practical Engineering Education
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• v.16 no.4
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• pp.513-520
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• 2024

This study investigates the changes in teachers' roles as the impact of AI on school education expands. Traditionally, teachers have been responsible for core aspects of classroom instruction, curriculum development, assessment, and feedback. AI can automate these processes, particularly enhancing efficiency through personalized learning. AI also supports complex classroom management tasks such as student tracking, behavior detection, and group activity analysis using integrated camera and microphone systems. However, AI struggles to automate aspects of counseling and interpersonal communication, which are crucial in student life guidance. While direct conversational replacement by AI is challenging, AI can assist teachers by providing data-driven insights and pre-conversation resources. Key competencies required for teachers in the AI era include expertise in advanced instructional methods, dataset analysis, personalized learning facilitation, student and parent counseling, and AI digital literacy. Teachers should collaborate with AI to emphasize creativity, adjust personalized learning paths based on AI-generated datasets, and focus on areas less amenable to AI automation, such as individualized learning and counseling. Essential skills include AI digital literacy and proficiency in understanding and managing student data.

• The Research Journal of the Costume Culture
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• v.19 no.3
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• pp.473-487
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• 2011

The purpose of this study is to analyze the body type and fashion of posthuman in SF movies. The method of this study was to analyze documentaries, internet web site, fashion books and so forth. The results were as follows: The body types of posthuman were expressed as mutation type, prosthetic type, clone type by biological hybrid or renovation and digital type by computer simulation. The mutation type was expressed as reinforcement of masculinity or feminity and reinforcement of body functions. The fashion item was expressed as a black tailored suit, leather jacket, cat suit, whip, black sunglass, garter belt, high heel shoes, short pants, black one piece dress and functional body suit. The prosthetic type was expressed as reinforcement of body functions and reinforcement of masculinity or feminity. The fashion item was expressed as a military item, high-tech power suit and ergonomic armor suit. The clone type was expressed as the plural ego with reinforcement of body functions. The fashion item was expressed as a power shoulder jacket, fake fur coat, vinyl, black see-through look and functional suit. The digital type was expressed as reinforcement of masculinity or feminity and the plural ego with reinforcement of body functions. The fashion item was expressed as a data suit, leather jacket, black over coat, boots, black sun glass, ethnic items and military items. The meanings of posthuman fashion in SF movies were impurity of posthuman, display of superhuman's power by sexuality, metaphor of power and fantasy of superhero in opposition futuristic dystopia. As mentioned above, posthuman body type and fashion in SF movies become the conversational topic in the real world. The fact that we think about utopia and identity of posthuman in the future is of great significance.