• 디지털콘텐츠학회 논문지
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• 제4권2호
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• pp.191-202
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• 2003

본 논문에서는 디지털 콘텐츠 학과의 고가 장비들을 효율적으로 관리하기 위해 구축된 지능형 기자재 관리 시스템의 설계 및 구현사례를 제시한다. 시스템 운영을 지원 하기위해 사용자, 장비, 사용기록의 데이터를 기반으로 데이터마이닝을 수행했으며 데이터 마이닝 과정에서 나타난 여러 유용한 규칙들을 제시했다. 분석된 정보를 이용해 사용자 위주의 운영정책과 동적 인터페이스를 제공하기 위한 웹사이트의 개인화 계획을 제시하였다.

• Journal of Computational Design and Engineering
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• 제1권3호
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• pp.161-172
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• 2014

This paper presents three different search engines for the detection of CAD-parts in large databases. The analysis of the contained information is performed by the export of the data that is stored in the structure trees of the CAD-models. A preparation program generates one XML-file for every model, which in addition to including the data of the structure tree, also owns certain physical properties of each part. The first search engine is specializes in the discovery of standard parts, like screws or washers. The second program uses certain user input as search parameters, and therefore has the ability to perform personalized queries. The third one compares one given reference part with all parts in the database, and locates files that are identical, or similar to, the reference part. All approaches run automatically, and have the analysis of the structure tree in common. Files constructed with CATIA V5, and search engines written with Python have been used for the implementation. The paper also includes a short comparison of the advantages and disadvantages of each program, as well as a performance test.