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An Experimental Study on the Performance Improvement of Automatic Classification for the Articles of Korean Journals Based on Controlled Keywords in International Database

Kim, Pan Jun 1 Lee, Jae Yun 2

1신라대학교
2명지대학교

Accredited

ABSTRACT

As a major factor for efficient management and retrieval of the articles in databases, keywords are classified into uncontrolled keywords and controlled keywords. Most of Korean scholarly databases fail to provide controlled vocabularies to indexing research articles which help users to retrieve relevant papers exhaustively. In this paper, we carried out automatic descriptor assignment experiments to Korean articles using automatic classifiers learned with descriptors in international database. The results of the experiments show that the classifier learning with descriptors in international database can potentially offer controlled vocabularies to Korean scholarly articles having English abstracts. Also, we sought to improve the performance of automatic descriptor assignment using various classifiers and combination of them.

Citation status

* References for papers published after 2023 are currently being built.