• Title/Summary/Keyword: Collaborative system

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A Platform for Remote Collaborative Experiment (원격 공동 실험을 위한 플랫폼)

  • Kim, Sang-Wook;Jin, Min;Sonn, Jong-Kyung;Kim, Woo-Nyon;Kim, Jeong-Mi
    • Journal of KIISE:Computing Practices and Letters
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    • v.6 no.2
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    • pp.206-215
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    • 2000
  • This paper is concerned with the development of PCS(Platform for Collaborative System), which is a platform for development of remote collaborative experiment systems. Platform does not aim at the development of special-domain applications. This system implies the common development environments which can develop all-domain applications. PCS consists of collaborative experimental objects such as communication, session, user, application, media, message object and management objects that have management functions. Management objects are made up of collaborative experimental objects and operations which manipulate control information and data. It also supports application sharing for making single user interface of experimental applications to multi-user interface. Application sharing also supports instruments control on the remote site. PCS platform supports total environments for remote collaborative experiment and can be used as infrastructure to all kinds of collaboratory systems.

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Collaborative CRM using Statistical Learning Theory and Bayesian Fuzzy Clustering

  • Jun, Sung-Hae
    • Communications for Statistical Applications and Methods
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    • v.11 no.1
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    • pp.197-211
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    • 2004
  • According to the increase of internet application, the marketing process as well as the research and survey, the education process, and administration of government are very depended on web bases. All kinds of goods and sales which are traded on the internet shopping malls are extremely increased. So, the necessity of automatically intelligent information system is shown, this system manages web site connected users for effective marketing. For the recommendation system which can offer a fit information from numerous web contents to user, we propose an automatic recommendation system which furnish necessary information to connected web user using statistical learning theory and bayesian fuzzy clustering. This system is called collaborative CRM in this paper. The performance of proposed system is compared with the other methods using real data of the existent shopping mall site. This paper shows that the predictive accuracy of the proposed system is improved by comparison with others.

Development of Telemedicine which is a CBM based Collaborative Multimedia System on LAN Environment (LAN환경에서의 CBM기반의 상호 참여형 멀티미디어 시스템인 원격 진료 시스템의 개발)

  • Kim, Seok-Su
    • The Transactions of the Korea Information Processing Society
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    • v.4 no.5
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    • pp.1153-1161
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    • 1997
  • In this paper, we propose Teloemedicine system on CBM(Computer Based Multimedia) based collaborative multimedia which supports special medicine and collaborative medicine with DB, face-to-face dffedt.This system is an application developed by SDK (Software Development Kit) of DooRae(Distributed Objected Oriented Multimedia Application Crafting Environment for Collaborative)framework.And this system is devel-Oriented Multimedia Applecation Crafting Environment for Collaborative) framework, And this system is devel-oped on windows 95 and windows NT.The scenario of this system is limited within only hospital(LAN), but it is possibloe to support many applications development in various nerwork(MAN, PSYN, WAN)on DooRae.This system has a smoth interaction by video and audio, multiple session, multiple participation, application sharing, toolbox including ICON and whiteboard.Also this system supports realo or non-real type without con-straint of the and space.

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Recommendation System using 2-Way Hybrid Collaborative Filtering in E-Business (전자상거래에서 2-Way 혼합 협력적 필터링을 이용한 추천 시스템)

  • 김용집;정경용;이정현
    • Proceedings of the IEEK Conference
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    • 2003.11b
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    • pp.175-178
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    • 2003
  • Two defects have been pointed out in existing user-based collaborative filtering such as sparsity and scalability, and the research has been also made progress, which tries to improve these defects using item-based collaborative filtering. Actually there were many results, but the problem of sparsity still remains because of being based on an explicit data. In addition, the issue has been pointed out. which attributes of item arenot reflected in the recommendation. This paper suggests a recommendation method using nave Bayesian algorithm in hybrid user and item-based collaborative filtering to improve above-mentioned defects of existing item-based collaborative filtering. This method generates a similarity table for each user and item, then it improves the accuracy of prediction and recommendation item using naive Bayesianalgorithm. It was compared and evaluated with existing item-based collaborative filtering technique to estimate the accuracy.

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Proposal of Content Recommend System on Insurance Company Web Site Using Collaborative Filtering (협업필터링을 활용한 보험사 웹 사이트 내의 콘텐츠 추천 시스템 제안)

  • Kang, Jiyoung;Lim, Heuiseok
    • Journal of Digital Convergence
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    • v.17 no.11
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    • pp.201-206
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    • 2019
  • While many users searched for insurance information online, there were not many cases of contents recommendation researches on insurance companies' websites. Therefore, this study proposed a page recommendation system with high possibility of preference to users by utilizing page visit history of insurance companies' websites. Data was collected by using client-side storage that occurs when using a web browser. Collaborative filtering was applied to research as a recommendation technique. As a result of experiment, we showed good performance in item-based collaborative (IBCF) based on Jaccard index using binary data which means visit or not. In the future, it will be possible to implement a content recommendation system that matches the marketing strategy when used in a company by studying recommendation technology that weights items.

A Personalized Recommender System, WebCF-PT: A Collaborative Filtering using Web Mining and Product Taxonomy (개인별 상품추천시스템, WebCF-PT: 웹마이닝과 상품계층도를 이용한 협업필터링)

  • Kim, Jae-Kyeong;Ahn, Do-Hyun;Cho, Yoon-Ho
    • Asia pacific journal of information systems
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    • v.15 no.1
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    • pp.63-79
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    • 2005
  • Recommender systems are a personalized information filtering technology to help customers find the products they would like to purchase. Collaborative filtering is known to be the most successful recommendation technology, but its widespread use has exposed some problems such as sparsity and scalability in the e-business environment. In this paper, we propose a recommendation system, WebCF-PT based on Web usage mining and product taxonomy to enhance the recommendation quality and the system performance of traditional CF-based recommender systems. Web usage mining populates the rating database by tracking customers' shopping behaviors on the Web, so leading to better quality recommendations. The product taxonomy is used to improve the performance of searching for nearest neighbors through dimensionality reduction of the rating database. A prototype recommendation system, WebCF-PT is developed and Internet shopping mall, EBIB(e-Business & Intelligence Business) is constructed to test the WebCF-PT system.

Production Flow Analysis Simulation Integration for Collaborative Process Planning (협업 공정계획을 위한 생산흐름 분석 시뮬레이션 통합)

  • Lee Ju-Yeon;Noh Sang-Do
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2005.06a
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    • pp.987-992
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    • 2005
  • Manufacturing companies should perform process planning and its evaluation concurrently with new product developments so that they can be highly competitive in the modern market. Process planners should make decisions in the manner of concurrent and collaborative engineering in order to reduce the manufacturing preparation time and cost when developing new products. Automated generation of analysis models from the integrated database, which contains process and material information, reduces time to prepare analyses and makes the models reliable. In this research, we developed a web-based system for concurrent and collaborative system for production flow analysis, using web, database, and simulation technology. An integrated database is designed to automatically generate analysis models from process and material plans without reworking the data. This system enables process planners to evaluate their decision fast and share their opinions with others easily. With this system, it is possible to save time and cost for assembly process and material planning, and reliability of process plans can be improved

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TagPlus: A Retrieval System using Synonym Tag in Folksonomy (TagPlus: 폭소노미에서 동의어 태그를 이용한 검색 시스템)

  • Lee, Sun-Sook;Yong, Hwan-Seung
    • Journal of Digital Contents Society
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    • v.8 no.3
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    • pp.255-262
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    • 2007
  • Collaborative tagging describes the process by which many users add metadata in the form of keywords to shared content. Recently, collaborative tagging has grown in popularity on the web, on sites that allow users to tag bookmarks, photographs, videos and other content. In this paper, we analyze the structure and basic knowledge of collaborative tagging systems as well as their dynamical aspects. We also present a retrieval system, TagPlus, using synonym tag that is derived from WordNet database. Specifically, TagPlus, a synonym tag based system has users retrieve images from Flickr system. The proposed system show the images tagged by not only the tag that users input but also the synonyms that are synonyms with the tag.

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Recommendation system for supporting self-directed learning on e-learning marketplace (이러닝 마켓플레이스에서 자기주도학습지원을 위한 추천시스템)

  • Kwon, Byung-Il;Moon, Nam-Mee
    • Journal of the Korea Society of Computer and Information
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    • v.15 no.2
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    • pp.135-146
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    • 2010
  • In this paper, we propose an Recommendation System for supporting self-directed learning on e-learning marketplace. The key idea of this system is recommendation system using revised collaborative filtering to support marketplace. Exisiting collaborative filtering method consists of 3 stages as preparing low data, building familiar customer group by selecting nearest neighbor, creating recommendation list. This study designs recommendation system to support self-directed learning by using collaborative filtering added nearest neighbor learning course that considered industry and learning level. This service helps to select right learning course to learner in industry. Recommendation System can be built by many method and to recommend the service content including explicit properties using revised collaborative filtering method can solve limitations in existing content recommendation.

Design and Implementation of an Industrial-Design Collaborative System to Support Scalability (확장성을 고려한 산업디자인 협력시스템 설계 및 구현)

  • Yang, Jin-Mo;Lee, Seung-Ryong;Jeon, Tae-Woong
    • Journal of KIISE:Computing Practices and Letters
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    • v.6 no.5
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    • pp.513-527
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    • 2000
  • This paper describes our experience to design and implementation of a collaborative system framework that allows to develop certain collaborative applications such as 3D animation, computer game, and industrial design. The collaborative system enables users, who located in geographically long distance, to do collaborative work in a single virtual space. The proposed system basically consists of client and server system. The goal of proposed system is to support scalability, portability, and platform independent. In order to achieve these, the server is implemented in Java platform and is adopted to the hybrid architecture which takes the advantages both in centralized and decentralized collaborative system. We construct the server base on its functional characteristics so called User Manager Server (UMS), Session Manager Server (SMS), and Information Server (IS), The UMS manages the users who are taking part in the collaborative operations. The SMS supports the conferencing in the proposed system. The IS provides the connection methods among the UMSs. For user's convenience, we implement the client using Visual C++ in Windows. We also expend the functions of 3D Studio Max to distributed environment by means of the plug-in module, and facilitate the chatting and white board functions as well.

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