Automatic keyphrases extraction from document using neural network

Authors:
Jiabing Wang;Hong Peng;Jing-song Hu
Affiliations:
School of Computer Science and Engineering, South China University of Technology, Guangzhou, China;School of Computer Science and Engineering, South China University of Technology, Guangzhou, China;School of Computer Science and Engineering, South China University of Technology, Guangzhou, China
Venue:
ICMLC'05 Proceedings of the 4th international conference on Advances in Machine Learning and Cybernetics
Year:
2005

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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 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 and inverted document frequency, whether to appear in the title or headings (subheadings) of the given document, and its frequency appearing in the paragraphs of the given document. The algorithm is evaluated by the standard information retrieval metrics of precision and recall, and human assessment.