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Usability Analysis of Structured Abstracts in Journal Articles for Document Clustering
Abstract
Structured abstracts have been regarded as an essential information factor to represent topics of journal articles. This study aims to provide an unconventional view to utilize structured abstracts with the analysis on sub fields of a structured abstract in depth. In this study, a structured abstract was segmented into four fields, namely, purpose, design, findings, and values/implications. Each field was compared in the performance analysis of document clustering. In result, the purpose statement of an abstract affected on the performance of journal article clustering more than any other fields. Furthermore, certain types of keywords were identified to be excluded in the document clustering to improve clustering performance, especially by Within group average clustering method. These keywords had stronger relationship to a specific abstract field such as research design than the topic of an article.
- keywords
- 구조적 초록, 학술지 초록, 문서 클러스터링, 클러스터링 자질, 클러스터링 기법, structured abstract, journal abstract, document clustering, clustering feature, clustering method, structured abstract, journal abstract, document clustering, clustering feature, clustering method
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