• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.5
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• pp.1097-1104
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• 2011

In this paper, we propose a semantic web approach for personalized book recommendation. Our approach takes advantage of the content-based recommendation and improves its disadvantage that users should input their interesting fields into all book search systems they use. Our approach provides the sharing of users' profile with their interesting fields by enabling user's interesting fields to be described over each book classification ontology of various book information providers. We also provide a middleware that manages users' profiles written in RDF and analizes similarity between user's interesting field and each concept over the book classification ontology. Our approach provide better performance than traditional keyword-based search by sharing the user's profile among book recommendation systems.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.303-321
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• 2023

Metaverse shopping has emerged as a new phenomenon in social commerce. This study aims to investigate the user experience of metaverse stores shopping based on the S-O-R model. The results of the study show that telepresence, entertainment, personalized recommendation, and social interaction have significant positive effects on flow experience and satisfaction in metaverse shopping. Additionally, satisfaction and flow experience are shown to have significant positive effects on user intentions. This study provides valuable implications for the design and management of metaverse stores to improve user experience and increase user intention.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.44 no.3
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• pp.57-67
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• 2007

Researchers in mobile AR systems have so far put the value on the technical challenges involved in the limitations imposed from mobility. Beyond such immediate technical questions, however, are questions regarding the possible contents that are to be used for the user’s interaction in ubiquitous computing environment. Various aspects of context of user and environment can be utilized easily as well as effectively. Moreover, the environment will be equipped with lots of pervasive but invisible computing resources. However, it is difficult for users to have access to those computing resources. At the same time, as the smart appliances get to have more features, their user interfaces tend to become harder to use. Thus, in this paper, we propose Context-Aware Mobile Augmented Reality (CAMAR) system. In our system, users only need to take a picture of smart appliances with a built-in camera in a mobile device when they intend to control the appliances. It lets users interact with the smart appliances through personalized control interfaces on their mobile devices. Also, it supports enabling contents to be not only personalized but also shared selectively and interactively among user communities.

• Journal of Internet Computing and Services
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• v.10 no.2
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• pp.85-98
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• 2009

Recently, there are a number of researches and developments for the personalized software platform for mobility based on SaaS. The platform requires an optimal virtual machine in order to satisfy the operating systems of various users for the software. In addition, the platform must guarantee the mobility of the users' working environments by supporting fast and secure services between internal and external networks in the platform operating systems. In order to verify the optimal behaviors of virtual machines for the platform, the performance of the virtual machines must be measured and analyzed in various perspectives. In the previous research, unfortunately, the performance of a virtual machine were conducted in the condition that a guest operating system was installed on the virtual machine and considered as a computer, by measuring the network traffic between the guest operating system and an external client operating system. This performance measurement was not suitable for a virtual machine for the platform since a number of different software must be handled in the virtual machine. In order to overcome this limitation, this paper presents a measurement method for network performance and proposes the most optimal virtual machine by the method.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.3
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• pp.1740-1748
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• 2014

In this paper, we propose an RBAC based personalized health care service platform in order to provide smart management of personal health record using smart devices. It helps to guide healthful service and provide useful information according to one's individual health record. Personalized health care services platform supports a healthy lifestyle by measuring personal health information in a hospital clinical, imaging, and drug data, as well as that can be obtained from smart devices. Everyone can enter his health related data in everyday life such as food, sleeping time, mood, movement and exercise so that one can manage his personal health information of modern smart features. In addition, if necessary, personal health information can be provided to the hospital information system and staff with the consent of the individual. It can be contributed to simplify the complex process for remote medical. The proposed platform, which applies role based access control model to protect security and privacy, supports a smart health care services for users by providing personalized health care services through the smart applications.

• Journal of the Korea Society of Computer and Information
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• v.11 no.5 s.43
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• pp.39-52
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• 2006

As accelerates the technical evolution of high-speed network and progresses the digitalization of broadcasting network, TV channel service through satellite/cable/terrestrial networks becomes more stable and mature. However, TV channel service using IP network such as IPTV is recently emerging. Especially, when it comes to current mosaic EPG(Electronic Program Guide) as a channel guide, the implementation of EPG via IP network is under developing. Furthermore, the personal target mosaic EPG is not provided at all in the IPTV. This paper proposes a construction method of mosaic system which can support fixed and personalized mosaic EPG using IP network for viewers. The fixed mosaic EPG is made several steps as follows ; First, H/E generates several mosaic A/V streams. Then, which are transmitted to the STB in terms of multicasting via IP network. Finally, mosaic EPG is displayed on TV through STB. In addition, this paper describes a construction model of the personalized A/V mosaic EPG that represents each person's favorite channels according to their tastes and interests. As for the contributions. The TV channel guide using IP network enable viewer to select channel more easily with practical adaptation of multi-channel expansibility and sufficient usability. In addition, through personal mosaic EPG, a number of viewers can compose their own mosaic EPG and enjoy a variety of channel easily in accordance with their preferences. Finally, the personal mosaic EPG can prohibit non-adult users from connecting adult-only contents more efficiently.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.11
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• pp.3-11
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• 2013

In smart healthcare service, the accurate and prompt emergency detection and notification are very critical to patients' lives. Since these detection and notification of emergency situation are usually performed by the medical staffs, it is difficult to simultaneously support many patients in real-time. This article presents a methodology for emergency bio-data transmission for smart healthcare using personalized emergency policy. It consists of three steps: In step 1, the bio-data is collected by wireless body area network. In step 2, the decision on emergency is made using personalized emergency policy. In step 3, the emergency message including the health condition information is converted between IEEE 11073 PHD message and HL7 CDA. By doing this, the emergency status of the individual bio-data collected from wireless body area network is detected automatically using personalized emergency policy. When the emergency is detected, the quick emergency rescue service can be provided to the patient by delivering to the emergency notification and the emergency bio-data. We have verified the service and functions of the proposed system architecture by realizing it.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.2060-2077
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• 2019

Recently, mobile healthcare services have attracted significant attention because of the emerging development and supply of diverse wearable devices. Smartwatches and health bands are the most common type of mobile-based wearable devices and their market size is increasing considerably. However, simple value comparisons based on accumulated data have revealed certain problems, such as the standardized nature of health management and the lack of personalized health management service models. The convergence of information technology (IT) and biotechnology (BT) has shifted the medical paradigm from continuous health management and disease prevention to the development of a system that can be used to provide ground-based medical services regardless of the user's location. Moreover, the IT-BT convergence has necessitated the development of lifestyle improvement models and services that utilize big data analysis and machine learning to provide mobile healthcare-based personal health management and disease prevention information. Users' health data, which are specific as they change over time, are collected by different means according to the users' lifestyle and surrounding circumstances. In this paper, we propose a prediction model of user physical activity that uses data characteristics-based long short-term memory (DC-LSTM) recurrent neural networks (RNNs). To provide personalized services, the characteristics and surrounding circumstances of data collectable from mobile host devices were considered in the selection of variables for the model. The data characteristics considered were ease of collection, which represents whether or not variables are collectable, and frequency of occurrence, which represents whether or not changes made to input values constitute significant variables in terms of activity. The variables selected for providing personalized services were activity, weather, temperature, mean daily temperature, humidity, UV, fine dust, asthma and lung disease probability index, skin disease probability index, cadence, travel distance, mean heart rate, and sleep hours. The selected variables were classified according to the data characteristics. To predict activity, an LSTM RNN was built that uses the classified variables as input data and learns the dynamic characteristics of time series data. LSTM RNNs resolve the vanishing gradient problem that occurs in existing RNNs. They are classified into three different types according to data characteristics and constructed through connections among the LSTMs. The constructed neural network learns training data and predicts user activity. To evaluate the proposed model, the root mean square error (RMSE) was used in the performance evaluation of the user physical activity prediction method for which an autoregressive integrated moving average (ARIMA) model, a convolutional neural network (CNN), and an RNN were used. The results show that the proposed DC-LSTM RNN method yields an excellent mean RMSE value of 0.616. The proposed method is used for predicting significant activity considering the surrounding circumstances and user status utilizing the existing standardized activity prediction services. It can also be used to predict user physical activity and provide personalized healthcare based on the data collectable from mobile host devices.

• International Journal of Air-Conditioning and Refrigeration
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• v.11 no.2
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• pp.67-72
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• 2003

A partition integrated air supply system can provide highly personalized environmental control. The supply air is brought up through raised floors and supplied to outlets located on the partition panels. The purpose of this paper is to find out the best design of outlets for optimal occupant comfort within a personal task area. Real scale experiments were conducted to allow for comparisons of outlet designs within a personal task area. Experimental results indicate that the location of an outlet is the most critical factor in improving the efficiency of supply air distribution of a personal task area. Thermal characteristic comparisons were made between the under-floor and the partition supply systems. Experimental results suggest that the partition supply system is more efficient than the under-floor supply system in terms of cooling. Such a system allows occupants to personally control their immediate environment, resulting in higher productivity.

• Journal of Korea Multimedia Society
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• v.21 no.2
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• pp.224-231
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• 2018

Recently, the importance of intelligent personalized services is increasing in the era of the 4th Industrial Revolution. In this paper, we proposes design and implementation of the agent recruitment service system for the intelligent headhunting service. The proposed service system has designed and implemented an intelligent service system to efficiently recruit and manage applicants(job seekers). In addition, we develops the modules that can analyze the profile information of the applicant(job seeker), and implement the algorithm to predict the talent verification and analyze the talent type. The proposed service system is expected to contribute to designing the innovative and new service models for the intelligent agent recruitment service system.