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Ensemble Learning for Keyphrases Extraction from Scientific Document.

Authors :
Wang, Jun
Yi, Zhang
Zurada, Jacek M.
Lu, Bao-Liang
Yin, Hujun
Wang, Jiabing
Peng, Hong
Hu, Jing-song
Zhang, Jun
Source :
Advances in Neural Networks - ISNN 2006; 2006, p1267-1272, 6p
Publication Year :
2006

Abstract

Keyphrase extraction is a task with many applications in information retrieval, text mining, and natural language processing. In this paper, a keyphrase extraction approach based on neural network ensemble is proposed. To determine whether a phrase is a keyphrase, the following features of a phrase in a given document are adopted: its term frequency, whether to appear in the title, abstract or headings (subheadings), and its frequency appearing in the paragraphs of the given document. The approach is evaluated by the standard information retrieval metrics of precision and recall. Experiment results show that the ensemble learning can significantly increase the precision and recall. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISBNs :
9783540344391
Database :
Supplemental Index
Journal :
Advances in Neural Networks - ISNN 2006
Publication Type :
Book
Accession number :
32883803
Full Text :
https://doi.org/10.1007/11759966_188