Identifying relevant full-text articles for database curation

Chih Lee*, Wen-Juan Hou, Hsin His Chen

*此作品的通信作者

研究成果: 雜誌貢獻會議論文同行評審

摘要

In this paper, we propose an approach for identifying curatable articles from a large pool. Our system currently considers three parts of an article as three individual representations of the article, and utilizes two domain-specific resources to reveal the deep knowledge contained in the article in order to generate more representations of the article. Cross-validation is employed to find the best combination of representations and an SVM classifier is trained out of this combination. The cross-validation results and results of the official runs are listed. The experimental results show overall high performance.

原文英語
期刊NIST Special Publication
出版狀態已發佈 - 2005 十二月 1
事件14th Text REtrieval Conference, TREC 2005 - Gaithersburg, MD, 美国
持續時間: 2005 十一月 152005 十一月 18

ASJC Scopus subject areas

  • 工程 (全部)

指紋

深入研究「Identifying relevant full-text articles for database curation」主題。共同形成了獨特的指紋。

引用此