• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.45 no.3
• /
• pp.86-96
• /
• 2008

In ubiquitous environments, invisible devices and software are connected to one another to provide convenient services to users. In order to provide such services, we must have mobile devices that connect users and services. However, the types of available services have thus far been limited due to the limited resources of mobile devices. This paper proposes a solution to the resource limitation problem of mobile devices by presenting a context-based collaboration system that allows mobile devices to share various nearby resources. Our system has a feature to enable personalized resource sharing by dynamically re-configuring user's preference and resource information.

• Proceedings of the Korea Multimedia Society Conference
• /
• 2003.11b
• /
• pp.508-511
• /
• 2003

최근에 인터넷 사용량이 증가함에 따라 자료의 양은 많아지고, 서비스 방식도 복잡해지는 문제가 생겨나게 되었다. 그에 따른 해결방안으로 P2P(Peer-to-Peer) 모델은 2000년대에 들어서 다시 컴퓨터 산업 무대의 중심으로 자리 잡게 되었다. 지금까지 잘 알려져 있는 클라이언트/서버 모델은 계속적으로 증가하고 있는 사용자와의 통신 수요에 대한 문제가 있다. 그렇기 때문에 P2P 모델은 이러한 구조에서 벗어나 사용자들 간의 직접적인 정보 교환을 가능하게 해주어 서버의 역할을 최소화 시켜 주었다. 이러한 이점 때문에 현재 많은 기업체들이 P2P 모델을 클라이언트/서버 모델 이상으로 선호하게 되었다. 자바를 이용해서 개발한 P2P용 메신저 통합 서비스에는 기존의 상대방과의 대화뿐만 아니라 파일 공유, 자료의 업/다운, 멀티미디어 채팅으로 상대방의 얼굴을 보며 대화를 할 수 있는 화상채팅 기능이 있고, 친구들을 쉽게 정리하여 사용자만이 관리를 할 수 있는 공유그룹과 폐쇄그룹을 추가하여 보안에 대비 하였다. 또 키워드 검색, 메타 검색으로 더 많은 자료를 손쉽게 찾을 수가 있다. 시스템 상에 XML, 웹 서버, WAP 게이트웨이 서버를 탑재하였고, 가상의 네트워크인 VPN 사용, 그리고 DB를 사용한 회원관리 및 여러 가지 서비스를 제공한다. 향후 P2P 기술은 P2P 검색, P2P 커뮤니케이션, 무선인터넷관련 기술, XML을 이용한 표준통합기술의 발전으로 더욱 침체된 시장에 활력소 역할을 할 것이다.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.38B no.5
• /
• pp.385-393
• /
• 2013

In the past decade, a paradigm shift from machine-centered to human-centered and from technology-driven to user-driven has been witnessed. Consequently, Social search is getting more social and Social Network Service (SNS) is a popular Web service to connect and/or find friends, and the tendency of users interests often affects his/her who have similar interests. If we can track users' preferences in certain boundaries in terms of Web search and/or knowledge sharing, we can find more relevant information for users. In this paper, we propose a novel Topic Sensitive_Social Relationship Rank (TS_SRR) algorithm. We propose enhanced Web searching idea by finding similar and credible users in a Social Network incorporating social information in Web search. The Social Relation Rank between users are Social Relation Value, that is, for a different topics, a different subset of the above attributes is used to measure the Social Relation Rank. We observe that a user has a certain common interest with his/her credible friends in a Social Network, then focus on the problem of identifying users who have similar interests and high credibility, and sharing their search experiences. Thus, the proposed algorithm can make social search improve one step forward.

• Journal of The Korean Association of Information Education
• /
• v.24 no.6
• /
• pp.623-631
• /
• 2020

In the era of COVID-19 global pandemic, e-learning has become new standards and daily life in the name of 'new normal'. This study developed dialogue e-learning contents as opposed to monologue e-learning which is unidirectional and instructor centered and conducted qualitative user experience evaluation of dialogue e-learning contents. A total number of 20 adult students participated and were individually interviewed. Qualitative data analysis was performed. The findings include students' positive perceptions of dialogue e-learning contents such as empathy for various ideas and new format. With regard to personal preference, 55% of participants preferred dialogue e-learning contents because it enables them to focus and share real experiences. Meanwhile, in terms of learning effects, 60% participants selected monologue e-learning contents and mentioned adequate explanations of concepts and explicit information delivery. Based on the results, suggestions on the design and development of dialogue e-learning contents were presented.

• Journal of Korea Multimedia Society
• /
• v.9 no.4
• /
• pp.377-387
• /
• 2006

Digital documents takes place of paper (off-line) documents, because of the advantages of digital (on-line) documents: supply of information using dynamic contents and good to communize. However, users prefer paper documents to digital documents with the advantages of paper documents: inexpensive, handy to carry, and good to read. Therefore, for providing advantages of digital documents to users who prefer paper documents, many laboratories study about methods which augment digital documents to paper documents. In this paper, we propose the Hybrid Documents Authoring Tool (HDAT), which can insert, delete, and modify on-line information to the off-line. The proposed system is a unified authoring tool for reading and writing of on-line information. And we provide the most natural environment to users using computer vision technology without additional devices such as markers or patterns to retrieve documents. As shown by experimental results, we make sure that our proposed system has high usability and good efficiency on various environments through we measure the low-level of system requirement.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2012.11a
• /
• pp.1767-1769
• /
• 2012

최근 여가활동에 대한 관심이 증대되고 있으며, 모바일 인프라가 널리 보급되었다. 하지만 공유되는 정보의 양이 급속하게 증가함에 따라 원하는 정보를 정확하게 얻는 것은 쉽지 않다. 본 논문은 한국관광공사의 Open API를 이용하여 보다 객관적이고 정확한 관광 명소의 정보를 안드로이드 폰에서 볼 수 있도록 제공하고, 더불어 사용자의 취향에 알맞은 관광 명소를 추천해주는 시스템을 소개한다.

• Journal of Digital Convergence
• /
• v.10 no.1
• /
• pp.301-307
• /
• 2012

The development of mobile devices and the spread of wireless network help share and exchange information and resources more easily. The bond them to Cloud Computing technology help pay attention to "Mobile Cloud" service, so there have been being a lot of studies on "Mobile Cloud" service. Especially, the important of 'Personalization Service' which is customized for each user's preference and context has been increasing. In order to provide appropriate personalization services, it enables to recognize user's current state, analyze the user's profile like user's tendency and preference, and draw the service answering the user's request. Most existing frameworks, however, are not very suitable for mobile devices because they were proposed on the web-based. And other context information except location information among user's context information are not much considered. Therefore, this paper proposed the context-aware framework, which provides more suitable services by using user's context and profile.

• Journal of Internet Computing and Services
• /
• v.11 no.6
• /
• pp.1-11
• /
• 2010

While a supply of GPS-enabled smartphone is increased, LBS which is studied and developed for special function is changed to personal solution. In this paper, we propose and implement on personalized method of individual LBS using collaborative filtering-based recommend system. Proposed personalized LBS system recommends contents which is expected to be interest for individual user, by predicting location-based contents within a user's setting radius. To evaluate performance of proposed system, we observed prediction accuracy with various experimental condition using our prototype. As a result, we confirmed that the convergence of collaborative filtering and LBS is effective for personalized LBS.

• Spatial Information Research
• /
• v.23 no.5
• /
• pp.53-64
• /
• 2015

Several countries have built National Spatial Data Infrastructure (NSDI) for information sharing among various fields. One of the important factors of NSDI is framework data, which is the most commonly used geospatial data across various fields. Previous studies on the framework data suggest components based on frequency survey and case study. However, such research methods do not have objectivity in setting the components of the framework data. This research uses factor analysis with 104 medium-level layers from the most widely used National Base Map and 5 layers from the other sources including cadastre and aerial image. Each layer is scaled with usage level as four different patterns of 1) background data, 2) reference data, 3) base data, and 4) other data, respectively. The analysis results show that the layers are grouped into 5 to 7 factors according to the patterns. ANOVA reveals that the mean differences between the factors with high values and the other factors with low values under each pattern are statistically significant. Such high value factors under each pattern consist of similar layers, close to identical, with those under the other categories. This research proposes framework data system, including transportation, building, hydrography, elevation, administrative district, digital orthoimagery, geodetic control, and cadastral based on the analysis results. Proposed framework in this research will be a basis of establishing spatial data sharing system. For sharing proposed framework data in various fields, these data must be established and distributed as actual standard and also related future researches should be performed.

• Journal of Korea Multimedia Society
• /
• v.11 no.10
• /
• pp.1338-1346
• /
• 2008

In this paper, we propose a new P2P-based music recommendation system. In comparison with previous system in client-server environment, the proposed system shows higher quality of music recommendation through real-time sharing of music preference information between peers. A collaborative filtering is implemented as a recommendation algorithm. As a user preference profile, we use the inherit KID music genre index contained in all legitimate music file instead of music feature vectors as in previous research so that the proposed system can mitigate the performance degradation and high computational load caused by feature inaccuracy and feature extraction. The performance of the proposed system is evaluated in various ways with real 16-weeks transaction data provided by Korean music portal, 5 company and it shows comparative quality of recommendation with only small amount of computational load.