• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2012년도 한국컴퓨터종합학술대회논문집 Vol.39 No.1(C)
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• pp.36-38
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• 2012

최근 사용자들의 궤적 분석을 통해 사용자의 성향에 적합한 정보를 추천해주는 연구들이 진행되고 있다. 이러한 연구들은 여행지 추천, 친구 추천 등과 같은 응용 서비스를 위해서 클러스터링 기법과 패턴 매칭 기법을 많이 사용하고 있다. 그러나 클러스터링 기법은 추천 받는 사용자의 선호도가 반영되지 않고, 다른 사용자들의 선호도에 따라 추천을 해주는 단점이 존재한다. 또한, 패턴 매칭 기법은 다른 사용자와의 POI(Point of Interest)의 유형과 거리를 비교하여 추천을 수행하기 때문에 사용자의 세부적인 선호도를 반영할 수 없는 단점이 존재한다. 이러한 기존 연구들을 보완하기 위해 본 논문에서는 POI의 속성 정보와 사용자의 이동 패턴을 고려한 POI을 추천 기법을 제안한다. 제안하는 기법은 크게 사용자의 속성 정보를 이용해서 선호도를 계산하고 선호도가 다른 궤적을 필터링하는 부분과 패턴 매칭 기법을 사용하여 근접한 궤적을 찾는 부분으로 구성된다. 제안하는 기법의 우수성을 입증하기 위해서 추천된 POI 궤적과 사용자 POI 궤적을 비교하여 두 궤적의 이동 패턴이 유사함을 확인하였다.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2015년도 추계학술발표대회
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• pp.1281-1284
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• 2015

Multi-day trip itinerary planning is complex and time consuming task, from selecting a list of worth visiting POIs to arranging them into an itinerary with various constraints and requirements. In this paper, we present CYTRIP, a multi-day trip itinerary planning system that engages human computation (i.e. crowd recommendation) to collaboratively recommend POIs by providing a shared workspace. CYTRIP takes input the collective intelligence of crowd (i.e. recommended POIs) to build a multi-day trip itinerary taking into account user's preferences, various time constraints and locations. Furthermore, we explain how we engage crowd in our system. The planning problem and domain are formulated as AI planning using PDDL3. The preliminary empirical experiments show that our domain formulation is applicable to both single-day and multi-day trip planning.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2014년도 추계학술대회
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• pp.324-327
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• 2014

본 논문은 환경 예약설정을 적용한 지능형 LED 조명시스템 구현에 관한 연구이다. 환경 설정은 조명의 ON/OFF 시간 및 밝기와 같은 정보를 미리 설정 저장된다. 설정 정보는 개인의 취향에 맞게 선택 항목에서 변경 가능하다. 사용자의 환경에 맞춤화된 조명시스템은 불필요한 조작을 줄일 수 있다. 블루투스 원격제어가 가능하여 장애인도 사용이 용이하다. 따라서 편리성과 절전효과 및 비용절감을 얻을 수 있다. 구현된 시스템의 성능은 실용성과 조작의 편의성 및 에너지 절감 등을 평가한다.

• 한국컴퓨터정보학회논문지
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• 제26권10호
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• pp.185-198
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• 2021

인터넷 기술의 발달로 기존의 추천 알고리즘은 사용자나 항목의 심층적인 특성을 학습할 수 없기 때문에 본 논문은 이 문제를 해결하기 위해 AMITI(주의 메커니즘 및 개선된 TF-IDF)에 기반한 추천 알고리즘을 제안했다. CNN(Convolutional Neural Network)에 2중 주의 메커니즘을 도입함으로써 CNN의 특징 추출 능력이 향상되고, 항목 특징에 다른 선호도 가중치가 할당되며, 사용자 선호도와 더 일치하는 권고사항이 달성되었다. 대상 사용자에게 항목을 추천할 때 점수 데이터와 항목 유형 데이터를 TF-IDF와 결합하여 권장 결과의 그룹화를 완료하였다. 본 논문에서 진행한 MovieLens-1M 데이터 세트에 대한 실험 결과는, AMITI 알고리즘이 권장 사항의 정확도를 향상시키고 프레젠테이션 방법의 순서와 선택성을 향상시킨다는 것을 보여준다.

• 반도체디스플레이기술학회지
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• 제20권3호
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• pp.97-102
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• 2021

In this study, we developed the service that can efficiently making friends among college students in metaverse world. Metaverse technology has recently emerged as an important topic across the industry.' The development of virtual and augmented reality technologies, which have emerged as a new paradigm to drive the next generation of the Internet, is bringing us closer to the metaverse world. Metaverse is spreading around the gaming, entertainment, music, and content industries[1]. In particular, as non-face-to-face transitions have accelerated since the COVID-19 outbreak, lifestyles and industrial sites are rapidly changing beyond untacting to metaverseization, a three-dimensional virtual space. After discovering the needs of users through surveys and interviews, the research method added functions to the service that matched those needs. Users were pleased that they could make friends who matched their preferences and tastes, play like a game in a virtual world called metaverse, and customize their avatars to their liking. It was also very fresh to customize the goods so that they could be gifted and kept by themselves.

• 한국의류학회지
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• 제44권5호
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• pp.923-949
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• 2020

Improving work efficiency and satisfying customers through personalized services is becoming more important in an increasingly competitive hair industry. Wearables may help to improve hair designers' work efficiency and customer satisfaction by analyzing customer and hair designers' conditions and provide hair stylingrelated data. However, there is limited research on developing wearables for hair designers (WHDs), and many existing wearables were developed without understanding user needs and perceptions. This research investigated preferences, perceptions, and intentions on WHDs based on hair designers in the U.S., which is the largest hair market. Specific design options that hair designers preferred and possible options to meet requirements that hair designers expect for wearables were identified and suggested in WHD design guidelines. Second, most people preferred a WHD design of a black-colored bracelet/watch that can be a necklace designed with preferred functions; in addition, 3D virtual images and 3D printed models were prototyped. Third, developed designs were evaluated. More than 70% of users were satisfied and considered it as useful and easy to use, with an intention to purchase. The results are expected to provide insights to designers when developing WHDs.

• 디지털산업정보학회논문지
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• 제10권4호
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• pp.197-209
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• 2014

The smart paradigm in the modern society is bringing about a rapid smart sensation and there are means of informational communications being developed with the smart technology in various fields. Accordingly, for an effective smart education, it is necessary to create the customized educational contents for the learners, the users of the education. In this study, the contents of smart education are categorized based on the user experiences. As a result of the analysis, the 3 types of UX are found to have a playful influence on the learning concentration and it is also deduced that such concentration of a learner positively affects his or her attitude towards learning. Moreover, by the age and gender groups, there were differences in the preferences for each of the UX type, so that, in result, gave the valid data for designing and applying the suitable UX type for creating contents of smart education for different main target groups.

• The Journal of Asian Finance, Economics and Business
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• 제9권4호
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• pp.109-120
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• 2022

This study has incorporated the mechanics-dynamics-emotions (MDE) and two behavioral learning paths to investigate the customers' co-creation behavior in Taiwan. The intuitive path begins with a gamification design that reflects the customers' proactive and innovative behavior; the cognitive path begins with persuasion knowledge remarks based on rational and reactive reasoning. These two paths conclude what forms user co-creation. The study collects data of 505 active social media users in Taiwan and employs structural equation modeling. The empirical findings demonstrate persuasive knowledge and gamification design are significantly associated with self-reference, and in turn, positively associated with co-creation. It indicates that cognitive behavior plays the main role in forming co-creation. Participants are more drawn to co-creation behaviors by the marketing contents that prompt reactive behaviors than proactive ones. Therefore, marketing managers can use appropriate stimuli to enhance co-creation behavior. Companies can design activities related to users, and more accessible for reactive, instead of proactive behavior, i.e., asking for their initiatives. It also suggests that companies' marketing campaigns should involve key opinion leaders matching the product image and the target audience's preferences. The novelty of this study is to introduce a novel augmented MDE framework to extend the "dynamics" into the incubation and implementation stage.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2022년도 춘계학술발표대회
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• pp.385-387
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• 2022

With the tremendous rise in popularity of the Internet and technological advancements, many news keeps generating every day from multiple sources. As a result, the information (News) on the network has been highly increasing. The critical problem is that the volume of articles or news content can be overloaded for the readers. Therefore, the people interested in reading news might find it difficult to decide which content they should choose. Recommendation systems have been known as filtering systems that assist people and give a list of suggestions based on their preferences. This paper studies a personalized news recommendation system to help users find the right, relevant content and suggest news that readers might be interested in. The proposed system aims to build a hybrid system that combines collaborative filtering with content-based filtering to make a system more effective and solve a cold-start problem. Twitter social media data will analyze and build a user's profile. Based on users' tweets, we can know users' interests and recommend personalized news articles that users would share on Twitter.

• Journal of Smart Tourism
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• 제3권1호
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• pp.41-47
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• 2023

Tourism and hospitality have encountered significant changes in recent years as a result of the rapid development of information technology (IT). Customers now expect more expedient services and customized travel experiences, which has intensified competition among service providers. To meet these demands, businesses have adopted sophisticated IT applications such as ChatGPT, which enables real-time interaction with consumers and provides recommendations based on their preferences. This paper focuses on the AI support-prompt middleware system, which functions as a mediator between generative AI and human users, and discusses two operational rules associated with it. The first rule is the Information Processing Rule, which requires the middleware system to determine appropriate responses based on the context of the conversation using techniques for natural language processing. The second rule is the Information Presentation Rule, which requires the middleware system to choose an appropriate language style and conversational attitude based on the gravity of the topic or the conversational context. These rules are essential for guaranteeing that the middleware system can fathom user intent and respond appropriately in various conversational contexts. This study contributes to the planning and analysis of service design by deriving design rules for middleware systems to incorporate artificial intelligence into tourism services. By comprehending the operation of AI support-prompt middleware systems, service providers can design more effective and efficient AI-driven tourism services, thereby improving the customer experience and obtaining a market advantage.