• Journal of the Korea Society of Computer and Information
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• v.10 no.4 s.36
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• pp.123-132
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• 2005

A version control system is used in a rapidly changed environment or a program which developed in a complicated environment. And configuration thread information supporting and it's processing method has an important part in version control. Configuration thread tool such as a system model of DSEE, a view of ClearCase, a label of SourceSafe, and the package of CCC/Harvest have applied to formalized configuration rule by user and obtained a desired configuration information of the version. But it is a problem of configuration thread in supporting information that we. in this method. can't know a exactly well-defined configuration rule information and a predefined information. And these information have a demerit that can't supported the close connection along with undefined version and a meta-information. In this paper. we have modeling a system for these problems to solve and a efficiently configuration thread supported. We also proposed a mixed retrieval model included a boolean retrieval model and a vector retrieval model for support efficiently configuration thread information. We applied and designed the libraries using extended facet method.

• The Journal of the Korea Contents Association
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• v.9 no.11
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• pp.54-62
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• 2009

To avoid the redundant investment on the project selection process, it is necessary to check whether the submitted research topics have been proposed or carried out at other institutions before. This is possible through the search engines adopted by the keyword matching algorithm which is based on boolean techniques in national-sized research results database. Even though the accuracy and speed of information retrieval have been improved, they still have fundamental limits caused by keyword matching. This paper examines implemented TFIDF-based algorithm, and shows an experiment in search engine to retrieve and give the order of priority for similar and redundant documents compared with research proposals, In addition to generic TFIDF algorithm, feature weighting and K-Nearest Neighbors classification methods are implemented in this algorithm. The documents are extracted from NDSL(National Digital Science Library) web directory service to test the algorithm.