• Proceedings of the Korea Information Processing Society Conference
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• 2024.05a
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• pp.371-373
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• 2024

디지털 헬스케어 기술이 고도화되면서 디지털 치료제와 원격 의료 서비스가 의료 산업과 일상생활에 널리 활용되고 있다. 그러나 빅데이터 기반의 AI 서비스가 보편화될 수 있도록 데이터 수집, 가공, 활용 과정에서 개인정보가 남용되거나 유출되는 보안 위협도 증가하고 있다. 본 논문에서는 AI 챗봇을 활용한 정신건강 서비스를 위한 보안 위협 대응책을 마련하고 개인정보보호 가이드라인을 수립하여 사용자들에게 안전한 서비스를 제공하고 개인정보보호를 강화하는 AI 챗봇 서비스를 위한 데이터 보안 가이드라인을 제안한다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.07a
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• pp.309-311
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• 2023

본 논문에서는 만성질환자 건강관리서비스 플랫폼 개발을 위항여 건강측정기 모바일 연계기술 개발 및 적용하고 IoT 기반 생체정보 획득 및 라이프로그 건강관리 플랫폼 API 연계 기술을 통하여 지역 만성질환자를 위한 언택트 헬스 모니터링 플랫폼 개발을 수행하였다. 해당 시스템을 통하여 지역 보건소 협력 및 가족 중심 만성질환자 입체적 건강관리 모니터링 시스템 개발에 적용하고 IoT 장비 인터페이스기술, 개인 건강관리기술, 플랫폼 운영 및 구현기술, 데이터 관리기술 개발을 통하여 효율적으로 개인 라이프로그를 활용할 수 있도록 하였으며, 효율적인 관리를 위하여 AI 챗봇 서비스 시스템을 통한 효율성을 극대화를 추진하였다. 본 논문에서는 개인 라이프로그를 활용한 AI 챗봇 기반 만성질환자 건강관리서비스 플랫폼을 구현하여 만성질환자에 대한 서비스를 제공하고 만족도를 실증하여 서비스의 우수함을 입증하였다.

• The Journal of the Convergence on Culture Technology
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• v.8 no.3
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• pp.463-468
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• 2022

The prolonged of the Post Corona made many industry's paradigm. It's become very important In the industries products that customers directly touch and use. To cope with this situation, The Cosmetics industry has recently introduced various untact services. many customers would like to try these new services. Typically, online survey services recommend personalized products. but these services reached its limit later. This paper research how to recommend products and define skine type with AI Image diagnosis module combine with legacy survey system.

• Proceedings of the Korean Society of Computer Information Conference
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• 2024.01a
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• pp.55-58
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• 2024

최근 각 기업의 AI 면접시스템 도입이 증가하고 있으며, AI 면접에 대한 실효성 논란 또한 많은 상황이다. 본 논문에서는 AI 면접 과정에서 지원자를 평가하는 방식을 시각, 음성, 자연어처리 3영역에서 구현함으로써, 면접 지원자를 다방면으로 분석 방법론의 적절성에 대해 평가하고자 한다. 첫째, 시각적 측면에서, 면접 지원자의 감정을 인식하기 위해, 합성곱 신경망(CNN) 기법을 활용해, 지원자 얼굴에서 6가지 감정을 인식했으며, 지원자가 카메라를 응시하고 있는지를 시계열로 도출하였다. 이를 통해 지원자가 면접에 임하는 태도와 특히 얼굴에서 드러나는 감정을 분석하는 데 주력했다. 둘째, 시각적 효과만으로 면접자의 태도를 파악하는 데 한계가 있기 때문에, 지원자 음성을 주파수로 환산해 특성을 추출하고, Bidirectional LSTM을 활용해 훈련해 지원자 음성에 따른 6가지 감정을 추출했다. 셋째, 지원자의 발언 내용과 관련해 맥락적 의미를 파악해 지원자의 상태를 파악하기 위해, 음성을 STT(Speech-to-Text) 기법을 이용하여 텍스트로 변환하고, 사용 단어의 빈도를 분석하여 지원자의 언어 습관을 파악했다. 이와 함께, 지원자의 발언 내용에 대한 감정 분석을 위해 KoBERT 모델을 적용했으며, 지원자의 성격, 태도, 직무에 대한 이해도를 파악하기 위해 객관적인 평가지표를 제작하여 적용했다. 논문의 분석 결과 AI 면접의 다면적 평가시스템의 적절성과 관련해, 시각화 부분에서는 상당 부분 정확도가 객관적으로 입증되었다고 판단된다. 음성에서 감정분석 분야는 면접자가 제한된 시간에 모든 유형의 감정을 드러내지 않고, 또 유사한 톤의 말이 진행되다 보니 특정 감정을 나타내는 주파수가 다소 집중되는 현상이 나타났다. 마지막으로 자연어처리 영역은 면접자의 발언에서 나오는 말투, 특정 단어의 빈도수를 넘어, 전체적인 맥락과 느낌을 이해할 수 있는 자연어처리 분석모델의 필요성이 더욱 커졌음을 판단했다.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.820-821
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• 2023

본 프로젝트는 Azure OpenAI Service (large language models and generative AI) 를 이용하여 IT 기술 및 현황을 생성형 AI (GPT-4)를 활용한 IT 카드 뉴스 서비스로서 업계 현직자들에게 정보를 제공하는 시스템을 구현하였다. IT 카드 뉴스 서비스의 부재와 뉴스 제작의 비용 및 시간 소요의 문제를 해결하기 위해 생성형 AI 시스템을 고안하였다. 해당 서비스를 통해 IT 업계에 관심이 많은 사용자에게 정리된 뉴스를 한 번에 제공하는 효과를 가져올 것으로 예상한다.

• Science of Emotion and Sensibility
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• v.22 no.2
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• pp.49-58
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• 2019

In the era of the 4th Industrial Revolution, artificial intelligence (AI) has become one of the core technologies in terms of the business strategy among information technology companies. Both international and domestic major portal companies are launching AI search services. These AI search services utilize voice, images, and other unstructured data to provide different experiences from existing text-based search services. An unfamiliar experience is a factor that can hinder the usability of the service. Therefore, the usability testing of the AI search services is necessary. This study examines the usability of the AI search service on the Naver App 8.9.3 beta version by comparing it with the search services of the current Naver App and targets 30 people in their 20s and 30s, who have experience using Naver apps. The usability of Smart Lens, Smart Voice, Smart Around, and AiRS, which are the Naver App beta versions of their artificial intelligence search service, is evaluated and statistically significant usability changes are revealed. Smart Lens, Smart Voice, and Smart Around exhibited positive changes, whereas AiRS exhibited negative changes in terms of usability. This study evaluates the change in usability according to the application of the artificial intelligence search services and investigates the correlation between the evaluation factors. The obtained data are expected to be useful for the usability evaluation of services that use AI.

• The Journal of the Korea Contents Association
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• v.20 no.11
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• pp.38-48
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• 2020

The domestic AI speaker market is growing into a full-fledged early audience market beyond the innovative consumer market with 3 million domestic supply units at the end of 2018, but the reality is that for various reasons, we are not satisfied with the use. There are many previous papers on AI Speaker, but the majority of research so far tends to be biased towards the acceptance of the device's own performance. Many changes are being made, such as OTT providers trying to secure the market through collaboration with AI speaker providers. This study tried to identify the priorities for content services, which can be another major selection factor for AI speakers, excluding the factors of unsatisfactory technology. First, this study identified the priorities among AI speaker selection factors using AHP (Analytic Hierarchy Process), based on the AI speaker selection factors derived through literature research. The most important hierarchical factor are Concierge Service, Education Service, and Entertainment Service order in AI speaker selection, and the primary content among the individual factors was the one that ranked weather/temperature/fine dust (11.6%) and child caring content was in the second place (10.8%), and then music service was in the third place (9.8%). The three top priorities were derived from the items in the top tier 1, 2 and 3 priorities. Of the total 15 individual services, 6 sub-layers of Concierge Service (weather/temperature/fine dust, news, voice schedule notification) and Education Service (foreign language, toddler, reading books) were in the top 8, and two of the Entertainment Service Music service and movie service ranked third and sixth.

• Journal of Service Research and Studies
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• v.13 no.4
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• pp.191-205
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• 2023

Artificial Intelligence (AI), especially in the domain of text-generative services, has witnessed a significant surge, with forecasts indicating the AI-as-a-Service (AIaaS) market reaching a valuation of $55.0 Billion by 2028. This research set out to explore the quality dimensions characterizing synthetic text media software, with a focus on four key players in the industry: ChatGPT, Writesonic, Jasper, and Anyword. Drawing from a comprehensive dataset of over 4,000 reviews sourced from a software evaluation platform, the study employed the Latent Dirichlet Allocation (LDA) topic modeling technique using the Gensim library. This process resulted the data into 11 distinct topics. Subsequent analysis involved comparing these topics against established AI service quality dimensions, specifically AICSQ and AISAQUAL. Notably, the reviews predominantly emphasized dimensions like availability and efficiency, while others, such as anthropomorphism, which have been underscored in prior literature, were absent. This observation is attributed to the inherent nature of the reviews of AI services examined, which lean more towards semantic understanding rather than direct user interaction. The study acknowledges inherent limitations, mainly potential biases stemming from the singular review source and the specific nature of the reviewer demographic. Possible future research includes gauging the real-world implications of these quality dimensions on user satisfaction and to discuss deeper into how individual dimensions might impact overall ratings.

• Journal of Information Technology Services
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• v.20 no.5
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• pp.189-207
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• 2021

Voice interaction combined with artificial intelligence is poised to revolutionize human-computer interactions with the advent of virtual assistants. This paper is analyzing interactive elements of AI-based voice recognition services such as sympathy, assurance, intimacy, and trust on intention to use. The questionnaire was carried out for 284 smartphone/smart TV users in Korea. The collected data was analyzed by structural equation model analysis and bootstrapping. The key results are as follows. First, AI-based voice recognition service characteristics such as sympathy, assurance, intimacy, and trust have positive effects on interactivity with the AI-based voice recognition service. Second, the interactivity with the AI-based voice recognition service has positive effects on intention to use. Third, AI-based voice recognition service characteristics such as interactional enjoyment and intimacy have directly positive effects on intention to use. Fourth, AI-based voice recognition service characteristics such as sympathy, assurance, intimacy and trust have indirectly positive effects on intention to use the AI-based voice recognition service by mediating the effect of the interactivity with the AI-based voice recognition service. It is meaningful to investigate factors affecting the interactivity and intention to use voice recognition assistants. It has practical and academic implications.

• Smart Media Journal
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• v.13 no.1
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• pp.67-75
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• 2024

The purpose of this research is to investigate consumer responses to production recommendations by AI. In order to test hypotheses of this study, we conducted experimental study that was a 2(Brand reputation: high vs. low) X 2(Social comparison: high vs. low). The results of this study showed the interaction effects of brand reputation and social comparison on brand attitude. Based on the results, we provide theoretical implications to extent the existing research regarding product recommendations. Moreover, the results of this study provide some practical implications and a new aspect about AI recommendations.