• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2006.05a
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• pp.804-806
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• 2006

There have been presented many solutions to improve Web accessibilities. A bookmark system is one of those convenient solutions. The convenience and usefulness of bookmark system is decreased when the registered contents arc increased. In this study, we proposed the personalized bookmark system. With this system, the bookmark contents are automatically updated by reflecting personal user's web preferences. And by managing the bookmark system with the server system, users can access the bookmark system at any place.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06c
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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.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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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.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.324-327
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• 2014

This paper describes a study on the intelligent LED lighting system implementation applicated environmental reservation setting. The environment variables are preset by ON and OFF time of illuminator and brightness data. The setting data enables to be changed by personal preferences on the selecting menu. It is possible to reduce unnecessary consumption and operation for the lighting system. The system customized by user's environment is convenient for disability by using bluetooth. Thus the system results in cost effective and energy savings. The system performances are examined for convenient operation and energy saving for practicality in implemented system.

• Journal of the Korea Society of Computer and Information
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• v.26 no.10
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• pp.185-198
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• 2021

With the development of Internet technology, because traditional recommendation algorithms cannot learn the in-depth characteristics of users or items, this paper proposed a recommendation algorithm based on the AMITI(attention mechanism and improved TF-IDF) to solve this problem. By introducing the two-layer attention mechanism into the CNN, the feature extraction ability of the CNN is improved, and different preference weights are assigned to item features, recommendations that are more in line with user preferences are achieved. When recommending items to target users, the scoring data and item type data are combined with TF-IDF to complete the grouping of the recommendation results. In this paper, the experimental results on the MovieLens-1M data set show that the AMITI algorithm improves the accuracy of recommendation to a certain extent and enhances the orderliness and selectivity of presentation methods.

• Journal of the Semiconductor & Display Technology
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• v.20 no.3
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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.

• Journal of the Korean Society of Clothing and Textiles
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• v.44 no.5
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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.

• Journal of Korea Society of Digital Industry and Information Management
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• v.10 no.4
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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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• v.9 no.4
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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.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.05a
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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.