• Journal of the Korea Society of Computer and Information
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• v.10 no.6 s.38
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• pp.137-152
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• 2005

In this Paper, we Propose an efficient web-based video learning evaluation system that is tailored to individual student's characteristics through the use of user profile-based information filtering. As a means of giving video-based questions, keyframes are extracted based on the location, size, and color information, and question-making intervals are extracted by means of differences in gray-level histograms as well as time windows. In addition, through a combination of the category-based system and the keyword-based system, questions for examination are given in order to ensure efficient evaluation. Therefore, students can enhance school achievement by making up for weak areas while continuing to identify their areas of interest.

• Annual Conference of KIPS
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• 2008.05a
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• pp.40-43
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• 2008

This paper describes a Grid-based context-aware doctor recommender system which recommends appropriate doctors for a patient or user at the right time in the right place. The core of the system is a recommendation mechanism that analyzes a user's demographic profile, user's current context information (i.e., location, time, and weather), and user's position so that doctor information can be ranked according to the match with the preferences of a user. The performance of our architecture is evaluated compare to centralized recommender system.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2003.11a
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• pp.1231-1232
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• 2003

This paper reports results of a recent survey of 184 Information Technology(IT) development practitioners and 90 User Interface (UI)/usability practitioners. This survey covered a broad range of issues including the respondents' profile, current development environment, usability and user-centered design (UCD) adoption issues in development, overall assessment of usability/UCD in Korea, and the most widely used methods and techniques. The results of this study are expected to provide an empirical basis for usability and UCD planning, training, adoption and execution in IT industry of Korea.

• The Journal of Korean Institute of Information Technology
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• v.17 no.4
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• pp.87-97
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• 2019

SRS was proposed for immediate processing of the meaning of sensor data on mobile devices independent from specific sensor networks and sensor type. However, each time new sensor data is received, sensor data inspection operations are performed repeatedly, and it cause resulting in low performance. App profile-based SRS has been proposed to resolve the problem. The app profile-based SRS has improved the SRS problem through the profile, but has been tested in a virtual simulation environment. After that the test was experimented in a real-time environment, but has not been tested with a variety of dynamic factors. Therefore, this paper experiment considering such as user mobility and sensor density in real-time environment. And this paper also evaluate performance of the App profile-based through analysis of the results of the experiment. As a result, app profile-based SRS is high influence by density and sensor type, and the number of sensor node is not influence.

• Journal of KIISE:Software and Applications
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• v.33 no.3
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• pp.356-364
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• 2006

'Ubiquitous Computing' is the most important paradigm of the next generation Information-Communication technology. The one of important problems to develop ubiquitous computing service system get hold of relations between times of transfer objects and events of transfer objects. Another problem is what reason transfer-pattern through location data of transfer objects. In this paper, we propose an approach to offer temporal-relation service in ubiquitous computing environment. The first is temporal reasoning in service viewpoint. The second is temporal reasoning to record user's preference. Users have preferences that are closely connected with time. These preferences are recorded at user profile. Therefore, the user profile-based ubiquitous service system can offer suitable service to users.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.316-318
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• 2019

Recently, healthy life has become an issue in an aging society, and the number of people who have been interested in continuous health care for better life is increasing. In this paper, we implemented a personalized recommendation systm to provide convenient healthcare management for user. The PHR (Personal Health Record) of user could be stored in the server along with health related information such as lifestyle, disease, and physical condition. The users could be classified into similar clusters according to the PHR profile in order to provide healthcare contents to the users who had similar PHR profile. K-Means clustering was applied to generate clusters based on PHR profile and ACDT(Ant Colony Decision Tree) algorithm was used to provide personalised recommendation of health information stored in knowledge base. The app system developed in this paper is useful for users to perform healthcare themselves by providing information on serious diseases and lifestyle habits to be improved according to the clusters classified by PHR profile.

• Proceedings of the Korean Information Science Society Conference
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• 2001.10a
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• pp.601-603
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• 2001

본 논문에서는 사용자의 요구사항을 만족하는 최적의 상품을 검색하는 전자 상거래 검색 시스템을 설계하고자 한다. 우리는 전자 상거래의 물품 구입에 대한 사용자 설문 조사를 통하여 소비자에게 영향을 미치는 요소들을 추출한다. 이러한 요소들 중에서 검색 엔진이 비교할 수 있는 요소들을 소비자 프로파일(Profile) 요소로 결정하고, 인터넷의 많은 상품 중에서 퍼지(Fuzzy) 이론을 적용하여 사용자의 프로파일에 적당한 상품 검색 알고리즘을 제안해 소비자가 상품 검색을 쉽게 할 수 있는 검색 시스템을 설계한다.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2004.11a
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• pp.242-248
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• 2004

Personalized reminder systems have to identify the user's current needs dynamically and proactively based on the user's current context. However, need identification methodologies and their feasible architectures for personalized reminder systems have so far been rare. Hence, this paper aims to propose a proactive need identification mechanism by applying agent and semantic web technologies and RFID-based context subsystem for a personalized reminder system, which is one of the supporting systems for a robust ubiquitous service support environment. We have created a prototype system, RFID-based NAMA (Need Aware Multi-Agent), to demonstrate the feasibility of the methodology and of the mobile settings framework that we propose in this paper. NAMA considers the context, user profile with preferences, and information about currently available services, to discover the user's current needs and then link the user to a set of services, which are implemented as web services.

• Journal of KIISE:Computing Practices and Letters
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• v.9 no.5
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• pp.487-497
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• 2003

There have been many filtering systems covering mail or news. Documents filtered by them consist of general text or HTML. XML is emerging as a new standard for information exchange. So, filtering systems need new approaches in dealing with XML documents. Our system suggests a method to describe user profiles with XML's ability to represent schema and structure. An user profile is made from DTD information and it is supposed to point the specific part of a document conforming to the DTD. More, it is different from the existing systems in extracting part of a document. An user profile is reflected in XML query to get part of an XML document.

• 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.