• 산업경영시스템학회지
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• 제29권3호
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• pp.79-86
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• 2006

Especially, MTO(Make-To-Order) companies take collaborative approaches with their partner companies to make low-price products and/or technologically low intensive products. The collaborative approach to manufacturing requires collaboration with partner companies for inventory review, production plan, and manufacturing to fulfill customer's orders. However, frequent changes of partnerships binder partner companies from sharing production information in effective ways since their information systems have different data architectures and platforms. Therefore, it is required flexible and standardized system integration approach fir effective information sharing. This research studies current status and problems of collaborative production system, proposes an architecture for collaborative production systems based on Web Services which is a standard information technology, and discusses expected effects and the vision of Web Services.

• 한국전자거래학회지
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• 제7권2호
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• pp.129-141
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• 2002

This paper deals with the collaborative procurement process in a two-echelon supply chain that a manufacturing company and a contractor are connected through the information system. The real time information about inventory and production processing becomes available through this information system. We raise two issues related to the collaborative procurement process. First, we propose a VMI(Vendor-Managed Inventory) type of the procurement policy which focuses on the cost minimization for the total supply chain rather than individual companies. Second, based on the simulation study, we demonstrate that a collaborative procurement process is more cost-effective over classical procurement processes such as (Q, r). The result obtained in this paper can be applied to the quantitative evaluation of the cost saving effect when companies build the information sharing based, collaborative procurement system.

• 한국산학기술학회:학술대회논문집
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• 한국산학기술학회 2003년도 Proceeding
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• pp.105-110
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• 2003

Collaborative filtering is one of the methodologies that are most widely used for recommendation system. It is based on a data matrix of each customer's preferences of products. There could be a lot of missing values in such preference. data matrix. This incomplete data is one of the reasons to deteriorate the accuracy of recommendation system. Multiple imputation method imputes m values for each missing value. It overcomes flaws of single imputation approaches through considering the uncertainty of missing values.. The objective of this paper is to suggest multiple imputation-based collaborative filtering approach for recommendation system to improve the accuracy in prediction performance. The experimental works show that the proposed approach provides better performance than the traditional Collaborative filtering approach, especially in case that there are a lot of missing values in dataset used for recommendation system.

• 한국CDE학회논문집
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• 제14권4호
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• pp.254-260
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• 2009

Most commercial PDM (product data management) systems, which have been released recently by overseas famous software vendors, are still expensive and heavy to apply to small and medium enterprises (SMEs). Proposed in this paper are an architecture and functions of collaborative BOM (bill-of-material) management system (cBOM-MS) which supports the internal BOM management by BOM Navigator, provides SMEs with constructing the collaborative BOM via Collaborative BOM Portal, and proposes an interface to extract BOM automatically from commercial CAD systems. In the design of cBOM-MS, BOM Navigator and cBOM Portal are positioned separately to reinforce the information security about product data during product development process.

• 한국CDE학회논문집
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• 제9권4호
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• pp.387-396
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• 2004

In order to keep and increase a competitive potential, industrial enterprises have to reduce their costs for product development as well as shorten lead time in product development processes. Moreover they have to respond to market factors and conditions such as increasing demands for functionality and individuality of products, short product life cycles, high pressure on prices and time to market. The improved functional requirement in connection with high time and cost pressure lead to high risk in product development. Technological fine improvements in connection with high time and cost pressure lead to high development risk. To cope with these challenges many enterprises have to collaborate globally. The collaborative engineering in product development is aimed to create distributed collaborative corporations and to facilitate the management of design conflicts. This paper provides a methodology for analyzing collaborative design process as well as the tools and the framework to support collaborative product development. The methodology can identify the interdependences among design tasks and teams. The tools and framework are implemented to facilitate the management of product development process.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 ITC-CSCC -3
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• pp.1752-1755
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• 2002

The world wide web (WWW) already accounts f3r more Internee network traffic than any other application, including il and simple file transfer. It is also a collaborative technology in a weak sense of the word - it allows people to share information. Synchronous collaboration is where an interactive activity is simultaneous and in teal-time. Computer based real time collaborative systems like shared whiteboards. collaborative editor etc. are only beginning to emerge recently. These applications invoking more than two users exchanging information, require Multicast communication. Multicast communication is a transmission mode that is now supported by a variety of local and wide area networks. Multicasting enables multiparty communication across a wide area to sparsely distributed groups by minimizing the network load. Multicasting itself is one of the key technologies in the nut generation of the Internet This paper describes the technical issues from the aspect of multicast communication and its reliability in synchronous collaborative application.

• 정보교육학회논문지
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• 제3권2호
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• pp.41-53
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• 2000

본 연구는 웹 기반 협력학습을 위한 시스템에서 학습자의 학습을 돕기 위한 멀티에이전트간의 통신에 관한 연구이다. 우선, 에이전트 시스템에 대한 전반적인 내용과 특정을 고찰하였고 에이전트 상호간의 통신인 KQML에 대하여 살펴보았다. 또한 협력학습을 위한 에이전트 기반의 시스템 구조와 에이전트간의 상호 통신 방법을 제시하였다. Java 언어를 이용하여 협력학습 시스템을 설계 구현하였으며 실험을 통하여 에이전트간의 통신에 의한 협력학습 시스템의 효율성을 고찰하였다.

• 경영과학
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• 제20권2호
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• pp.81-93
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• 2003

These days we come across many wicked problems whose solutions are beyond individuals intellectual ability. These problems can be resolved through collaborative group interaction. We developed an internet-based asynchronous group interaction support system, after looking into the collaborative problem solving process and the IBIS (Issue-Based Information System) argumentation model. It has the following characteristics ; 1) it is developed based on the modified IBIS model which is a model for group interaction to resolve wicked problems ; 2) it supports both processes of seeking and comparing solutions, while most similar systems do not have a feature to support the latter process ; 3) different structures can be defined dynamically according to the purpose of group interaction, so that it could be used for collaborative problem solving in a specific domain. To show the usability of the system, we carried out an experiment, whose result is shown at the end.

• 기술혁신학회지
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• 제12권3호
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• pp.499-524
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• 2009

최근 국가연구개발사업의 추진에 있어서 국제공동연구의 비중이 점차 높아지고 있으나 국제공동연구로부터 발생되는 지식재산권 등의 성과물 관리제도는 미흡한 실정이다. 국제공동연구의 대부분을 수행하고 있는 대학이나 출연(연) 등 공공연구기관의 자체적인 성과관리체계가 미흡하고, 정부차원의 관련 법령도 제대로 정비되지 않고 있다. 본 논문에서는 국제공동연구 수행과 관련한 성과물 관리제도의 실태와 문제점을 분석하고 그 개선방안을 제시하였다.

• 한국멀티미디어학회논문지
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• 제23권2호
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• pp.343-350
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• 2020

In the era of the Fourth Industrial Revolution in the digital revolution is taking place, various attempts have been made to provide various contents in a digital environment. In this paper, agent-recruitment service system based on collaborative deep learning is proposed for the intelligent head hunting service. The service system is improved from previous research [7] using collaborative deep learning for more reliable recommendation results. The Collaborative deep learning is a hybrid recommendation algorithm using "Recurrent Neural Network(RNN)" specialized for exponential calculation, "collaborative filtering" which is traditional recommendation filtering methods, and "KNN-Clustering" for similar user analysis. The proposed service system can expect more reliable recommendation results than previous research and showed high satisfaction in user survey for verification.