• Proceedings of the Korean Information Science Society Conference
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• 2004.04b
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• pp.667-669
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• 2004

적응적 웹기반 기법에서 학습자의 반응이나, 탐색 행동의 근본적인 원인이 되는 학습 동기, 지각 등에 대한 판단을 정확히 할 수 없기 때문에, 학습자에게 완전히 적응적인 수업 환경을 조성해 주는 데는 한계가 있다. 이러한 한계를 극복하기 위한 대안으로 학습자간 상호작용이나 협동 학습을 지원하는 웹기반 교수 시스템이 제안되고 있다. 본 논문에서는 웹기반 환경에서 학습자들간의 협동학습을 효과적으로 지원하는 적응형 교수 시스템을 제안한다. 본 시스템은 협동학습 공간에서 주어진 과제를 수행하기 위해 발생되는 학습자들의 대화와 서로간의 상호작용을 분석하여 적절한 조언을 제공함으로서 협동학습이 효과적으로 이루어 질 수 있도록 지원한다.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.4
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• pp.18-24
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• 2010

Mobile devices wide spread among users after the release of Apple's iPhone, especially in Korea. Mobile device has their own advantages in terms of weight, size, mobility and so on. But, on the contrary, mobile device has to provide more accurate and personalized information because of a small screen and a limited function of information retrieval. This paper presents a user"s preference element changeable recommender system by employing extended collaborative filtering as a technique to provide useful information in a mobile environment. Proposed system reflects user's similar groups by simultaneously considering users' information with preferences and demographic characteristics. Then we construct list of recommenders by user's choice. Finally, we show the implementation of a prototype based on iPhone.

• Journal of the Korea Society of Computer and Information
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• v.15 no.8
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• pp.51-58
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• 2010

Programming education needs learning which is adjusted individual learners' level of their learning abilities. Recommendation system is one way of implementing personalized service. In this research, we propose recommendation method which learning items are recommended for individual learners' learning in web-based programming education environment by. Our proposed system for leveled programming education provides appropriate programming problems for a certain learner in his learning level and learning scope employing collaborative filtering method using learners' profile of their level and correlation profile between learning topics. As a result, it resolves a problem that providing appropriate programming problems in learner's level, and we get a result that improving leaner's programming ability. Furthermore, when we compared our proposed method and original collaborative filtering method, our proposed method provides the ways to solve the scalability which is one of the limitations in recommendation systems by improving recommendation performance and reducing analysis time.

• Journal of Korea Multimedia Society
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• v.2 no.4
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• pp.476-489
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• 1999

HW/SW codesign is integrated design of systems implemented using both hardware and software components. Many design tools has been developed to support this new paradigm, so far. Current codesign tools are not widely used as been expected because of variety problems - rapidly evolving technology, platform dependency, absence of standard specification method, inconsistent user interface, varying target system, different functionality In this paper, we propose a web-based distributed HW/SW codesign environment to remedy this kinds of problem. Our codesign environment has object-based 3 tier client/server architecture. It supports collaborative workspace through session service. Fully object-oriented design of user interface(OOUI) enables easy extension without change of user Interface. Furthermore it contains transaction server and security server for efficient and safe transfer of design data. To show a validity of our design, we developed prototype of web-based HW/SW codesign environment called WebCEDA. Our model of HW/SW codesign can be used for web-based generic CAD tools.

• Journal of Microbiology and Biotechnology
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• v.14 no.5
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• pp.1081-1085
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• 2004

Genome research has become very popular in most nations. In order to enhance the efficiency of collaboration among genome research groups, ways to store and share data, communicate with each other, be guided through right research strategies, and to easily use well-established databases. In addition, since techniques and softwares for genome research groups are well established, a similar research road map could commonly be applied. In this study, we developed a web-based work place for effective genome research, named 'BioPlace.' From the beginning of writing a proposal, research members can work on the same environment with convenient aid to share files or data. BioPlace provides various ways of collaboration methods among genome researchers. The BioPlace system supports two types of workplaces, namely 'Personal Workspace' and 'Team Workspace.' For each BioPlace user, a Persona] Workspace is provided, while a Team Workspace is provided for each group with the same purpose. In addition, BioPlace provides a 'General Research Road Map' for genome research, and several Korean user interfaces for BLAST, PDB, and Primer3. We expect that BioPlace may facilitate collaboration of genome research among the experienced scientists and help beginners in many different ways as well.

• Proceedings of the Korean Information Science Society Conference
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• 2004.10c
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• pp.478-480
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• 2004

네트워크의 발달로 인하여 지역적으로 원거리에 위치한 다수의 사용자들이 공동 작업을 수행할 수 있는 다양한 기술들이 개발되었다. 공동작업을 지원하는 협업시스템은 HTTP 프로토콜을 사용하거나 또는 각자의 고유한 통신 프로토콜들을 정의하여 구현하였다. 이러한 방법은 협업시스템 간의 상호 운용성이 결여되는 문제를 발생시켰다. W3C의 IETF에서는 협업지원을 위한 WebDAV 명세가 발표되었다. WebDAV는 웹상의 공동 저작활동을 지원하기 위한 표준프로콜로서, 원거리에 있는 사용자들 간에 인터넷상의 파일을 편집하고 관리할 수 있도록 해주는 HTTP의 확장이다. 이를 이용하여 협업시스템을 구성하면 협업시스템 간의 상호 운용성을 높일 수 있을 것이 다. 협업시스템의 클라이언트는 협업지원 서버의 자원들을 효율적으로 이용할 수하고 팀원들 간의 상호작용이 원활 하게 이루어 져야한다. 이러한 요구 조건을 고려하여 본 논문에서는 WebDAV 프로토콜을 이용한 협업시스템의 클라이언트를 설계하였다. 고급기능으로 사용자가 협업지원 서버의 파일을 편집할 때 자동으로 저작프로그램을 연결하고 저작프로그램을 종료할 때 파일의 변화된 내용과 파일의 버전관리를 실시간으로 서버에 적용될 수 있게 디자인하였다. 또한 드래그앤드롭(Drag & Drop)을 통한 파일이동을 지원하고 파일의 읽기모드와 쓰기모드를 지원하는 기능을 설계하였다.

• Korean Journal of Computational Design and Engineering
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• v.9 no.1
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• pp.62-76
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• 2004

Many customers are no longer satisfied with mass-produced goods. They are demanding customization and rapid delivery of innovative products. Many companies are now realizing that the best way to reduce life cycle costs is to evolve a more effective product development paradigm using Internet and web based technologies. Yet there remains a gap between current market demands and product development paradigms. The existing CAD systems require that product developers possess all the design analysis tools in-house making it impractical to employ all the needed and newest tools. Hence, this paper addresses how assembly operation analysis can be embedded transparently and remotely into a service-oriented collaborative assembly design environment. A new assembly operation analysis framework is introduced and a relevant architecture and tools are developed to realize the framework. Instead of the current sequential process for verifying and validating an assembly design, a new Virtual Assembly Analysis (VAA) method is introduced in the paper to predict the various effects of joining during actual collaborative design. As a case study, arc welding and riveting processes are investigated. New service-oriented VAA architecture and its VAA components are proposed and implemented on prototype mechanical assemblies.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.8
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• pp.1409-1417
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• 2003

In the 21st century, the concept of remote design and manufacture is strongly required in manufacturing processes to reduce cost and time-to-market. The objective of this paper is the development of an internet-based dimensional verification system for reverse engineering. An inspection client can register measurement data at the developed web server. Collaborators related to the development of a new product can confirm geometrical form from measurement data, check dimensional information and mark up the important parts, as well as make a statement of their views through the Internet. The developed system is realized through the ActiveX-Server architecture. Functions of the dimensional verification module are constructed as ActiveX by using the visual C＋＋ and OpenGL. The usefulness of the developed system is confirmed through a case study.

• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.1-18
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• 2015

Collaborative filtering(CF) algorithm has been popularly used for recommender systems in both academic and practical applications. A general CF system compares users based on how similar they are, and creates recommendation results with the items favored by other people with similar tastes. Thus, it is very important for CF to measure the similarities between users because the recommendation quality depends on it. In most cases, users' explicit numeric ratings of items(i.e. quantitative information) have only been used to calculate the similarities between users in CF. However, several studies indicated that qualitative information such as user's reviews on the items may contribute to measure these similarities more accurately. Considering that a lot of people are likely to share their honest opinion on the items they purchased recently due to the advent of the Web 2.0, user's reviews can be regarded as the informative source for identifying user's preference with accuracy. Under this background, this study proposes a new hybrid recommender system that combines with users' review mining. Our proposed system is based on conventional memory-based CF, but it is designed to use both user's numeric ratings and his/her text reviews on the items when calculating similarities between users. In specific, our system creates not only user-item rating matrix, but also user-item review term matrix. Then, it calculates rating similarity and review similarity from each matrix, and calculates the final user-to-user similarity based on these two similarities(i.e. rating and review similarities). As the methods for calculating review similarity between users, we proposed two alternatives - one is to use the frequency of the commonly used terms, and the other one is to use the sum of the importance weights of the commonly used terms in users' review. In the case of the importance weights of terms, we proposed the use of average TF-IDF(Term Frequency - Inverse Document Frequency) weights. To validate the applicability of the proposed system, we applied it to the implementation of a recommender system for smartphone applications (hereafter, app). At present, over a million apps are offered in each app stores operated by Google and Apple. Due to this information overload, users have difficulty in selecting proper apps that they really want. Furthermore, app store operators like Google and Apple have cumulated huge amount of users' reviews on apps until now. Thus, we chose smartphone app stores as the application domain of our system. In order to collect the experimental data set, we built and operated a Web-based data collection system for about two weeks. As a result, we could obtain 1,246 valid responses(ratings and reviews) from 78 users. The experimental system was implemented using Microsoft Visual Basic for Applications(VBA) and SAS Text Miner. And, to avoid distortion due to human intervention, we did not adopt any refining works by human during the user's review mining process. To examine the effectiveness of the proposed system, we compared its performance to the performance of conventional CF system. The performances of recommender systems were evaluated by using average MAE(mean absolute error). The experimental results showed that our proposed system(MAE = 0.7867 ~ 0.7881) slightly outperformed a conventional CF system(MAE = 0.7939). Also, they showed that the calculation of review similarity between users based on the TF-IDF weights(MAE = 0.7867) leaded to better recommendation accuracy than the calculation based on the frequency of the commonly used terms in reviews(MAE = 0.7881). The results from paired samples t-test presented that our proposed system with review similarity calculation using the frequency of the commonly used terms outperformed conventional CF system with 10% statistical significance level. Our study sheds a light on the application of users' review information for facilitating electronic commerce by recommending proper items to users.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.8
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• pp.1877-1893
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• 2009

Folksonomy is a user-generated taxonomy to organize information by which a user assigns tags to resources published on the web. Triadic datas that indicate relations of between users, tags, and resources, are created by collaborative tagging from many users in folksonomy-based system. Such the folksonomy data has been utilized in the field of the semantic web and web2.0 as metadata about web resources. In this paper, we propose FCA-based folksonomy data mining approach in order to extract the useful information from folksonomy data with various points of view. And we developed tool for supporting our approach. In order to verify the usefulness of our proposed approach and FMT, we have done some experiments for data of del.icio.us, which is a popular folksonomy-based bookmarking system. And we report about result of our experiments.