• The KIPS Transactions:PartB
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• v.14B no.7
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• pp.481-492
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• 2007

In this paper, a method for automatic indexing of contents to reduce effort for inputting paper information and constructing index is considered. Existing document analysis methods can't analyse various table of contents of journal paper formats efficiently because they have many exceptions. In this paper, various contents formats for journals, which have different features from those for general documents, are analysed and described. The principal elements that we want to represent are titles, authors, and pages for each papers. Thus, the three principal elements are modeled according to the order of their arrangement, and their features are extracted. And a table of content recognition system of journal is implemented, based on the proposed modeling method. The accuracy of exact extraction ratio of 91.5% on title, author, and page type on 660 published papers of various journals is obtained.

• Proceedings of the Korea Information Processing Society Conference
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• 2003.11b
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• pp.813-816
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• 2003

인터넷과 정보통신기술의 급속적인 발전으로 수천 또는 수억에 달하는 방대하고 다양한 정보들이 웹상에서 존재하게 되었다. 웹상에서 획득가능한 학술정보가 증가함에 따라 다량의 정보를 효율적으로 수집하기 위하여 다양한 웹 로봇기반 수집에이전트를 활용하고 있다. 본 논문에서는 웹에 산재되어 있는 해외학술정보를 체계적이고 주기적으로 수집, 분류하기 위하여 학술지목차DB(QTOC)를 활용한 해외학술정보 수집에이전트 시스템을 설계하였다.