Abstract
Keyphrases are concise representation of documents and usually are extracted directly from the original text. This paper proposes a novel approach to extract keyphrases. This method proposes two metrics, named topic relevance and term association respectively, for determining whether a term is a keyphrase. Using Wikipedia knowledge and betweenness computation, we compute these two metrics and combine them to extract important phrases from the text. Experimental results show the effectiveness of the proposed approach for keyphrases extaction.
Original language | English |
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Pages (from-to) | 293-299 |
Number of pages | 7 |
Journal | Journal of Information and Computational Science |
Volume | 7 |
Issue number | 1 |
Publication status | Published - 1 Jan 2010 |
Keywords
- Betweenness
- Keyphrase extraction
- Term association
- Topic relevance
ASJC Scopus subject areas
- Information Systems
- Computer Graphics and Computer-Aided Design
- Computational Theory and Mathematics
- Library and Information Sciences