• Korean Journal of Computational Design and Engineering
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• v.14 no.4
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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.

• IE interfaces
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• v.19 no.1
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• pp.70-77
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• 2006

One of the problems in developing a collaborative recommendation system is the scalability. To alleviate the scalability problem efficiently, enhancing the performance of the recommendation system, we propose a new recommendation system using feature selection. In our experiments, the proposed system using about a third of all features shows the comparable performances when compared with using all features in light of precision, recall and number of computations, as the number of users and products increases.

• Proceedings of the KSME Conference
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• 2001.06c
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• pp.351-356
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• 2001

Recently, advanced information technologies including Internet-related technology and distributed object technology have opened new possibilities for collaborative designs. In this paper, we discuss computer supports for collaborative design in a distributed environment. The proposed system is the Internet-centric system composed of an engineering framework, collaborative virtual workspace and engineering service. It allows the distributed designers to more efficiently and collaboratively work their engineering tasks throughout the design process.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.33 no.3
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• pp.87-92
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• 2010

In this paper, we suggest a PLCS-based architecture and operation method for providing interoperability in SBA integrated collaborative environment. Specifically, the suggested architecture is based on the distributed collaborative environment which employes the PLCS application protocol and integrated repository for representing and sharing product data information between collaborators remotely located. As an example of data representation, a military vehicle system is considered and two kinds of information, including state and activity/process, are explained. We expect that the suggested architecture can be used as a reference model to develop an efficient SBA integrated collaborative environment.

• Journal of Information Processing Systems
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• v.9 no.1
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• pp.157-172
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• 2013

There are many recommendation systems available to provide users with personalized services. Among them, the most frequently used in electronic commerce is 'collaborative filtering', which is a technique that provides a process of filtering customer information for the preparation of profiles and making recommendations of products that are expected to be preferred by other users, based on such information profiles. Collaborative filtering systems, however, have in their nature both technical issues such as sparsity, scalability, and transparency, as well as security issues in the collection of the information that becomes the basis for preparation of the profiles. In this paper, we suggest a movie recommendation system, based on the selection of optimal personal propensity variables and the utilization of a secure collaborating filtering system, in order to provide a solution to such sparsity and scalability issues. At the same time, we adopt 'push attack' principles to deal with the security vulnerability of collaborative filtering systems. Furthermore, we assess the system's applicability by using the open database MovieLens, and present a personal propensity framework for improvement in the performance of recommender systems. We successfully come up with a movie recommendation system through the selection of optimal personalization factors and the embodiment of a safe collaborative filtering system.

• Journal of Intelligence and Information Systems
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• v.14 no.1
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• pp.101-115
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• 2008

Combining collaborative filtering with some other technique is most common in hybrid recommender systems. As many recommended items from collaborative filtering seem to be similar with respect to content, the collaborative-content hybrid system suffers in terms of quality recommendation and recommending new items as well. To alleviate such problem, we have developed a novel method that uses a diversity metric to select the dissimilar items among the recommended items from collaborative filtering, which together with the input when fed into content space let us improve and include new items in the recommendation. We present experimental results on movielens dataset that shows how our approach performs better than simple content-based system and naive hybrid system.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.687-690
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• 1995

The configuration of design technology in 21st century must require collaborative design system, in which distributed design organizations and their related enterprises can mutually cooperate by overcoming time and regional restictions, and by exactily exchanging and sharing desing data. To achieve these objectives, it is necessary that the design system can propery deal with the dynamic change between regionally distributed modules. In this paper, we will discuss developing the dynamic virtual collaborative design system based on WWW by implementing recent web technologies such as Java and VRML.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.10a
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• pp.159-162
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• 1997

Since customer's demand is various and product life cycle is getting shorter, many manufacturing company is trying to reduce product development time and cost. For that reason they make an effort to design product on collaborative environment. The various activities in a product development are highly distributed. This distributed nature of the activities implies that teams will be working indifferent place and technical environments. Thus at a given time, teams might work on he same product from different perspectives. This will require efficient communication amongst the various individuals and the various softwaretools that are used by them. Therefore, there is a need for a computerized frame work that can support distributed design such that participants from different backgrounds collaborate towards one common goal. This paper presents the architecture of a collaborative design system. It then reports on the study of computerized frame work focused on collaboration for product development.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.877-880
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• 2003

In a competitive and globalized business environment, the need for the green products becomes stronger. To meet these trends, the environmental assessment besides delivery, cost and quality of products should be considered as an important factor in new product development phase. In this paper. a knowledge-based approximate life cycle assessment system (KALCAS) for the collaborative design environment is developed to assess the environmental impacts in context of product concept development. It aims at improving the environmental efficiency of the product using artificial neural networks consisting of high-level product attributes and LCA results. The overall framework of the collaborative environment including KALCAS is proposed. This architecture uses the CO environment to allow users on a wide variety of platforms to access the product data and other related information. It enables us to trade-off the evaluation results between the objectives of the product development including the approximate environmental assessment in the collaborative design environment.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.1
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• pp.101-107
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• 2014

This paper presents an efficient distributed recommendation system using clustering collaborative filtering algorithm in distributed computing environments. The system was built based on Hadoop distributed computing platform, where distributed Min-hash clustering algorithm is combined with user based collaborative filtering algorithm to optimize recommendation performance. Experiments using Movie Lens benchmark data show that the proposed system can reduce the execution time for recommendation compare to sequential system.