Improvement of KEA Based on Lexical Chain

DOI

10.2991/iccia.2012.164How to use a DOI?

Keywords

keyphrases extraction, KEA, lexcial chain,semantic similarity.

Abstract

Keyphrases are very useful and significant for information retrieval, automatic summarizing, text clustering, etc. KEA is a traditional and classical algorithm in keyphrase automatic extraction. But it is mainly based on the statistical information without considering the semantic information. In this paper, We propose a method which combine semantic information with KEA by constructing lexical chain that based on Reget’s thesaurus. In our method, the semantic similarity between terms is used to construct the lexical chain, and then we use the length of the chain as a feature to build the extraction model. The experiment result shows that the performance of the system has a big improvement compare with the KEA.

Copyright

© 2013, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Zefeng Li
AU  - Xianghui Zhao
AU  - Jin Yi
AU  - Bin He
PY  - 2014/05
DA  - 2014/05
TI  - Improvement of KEA Based on Lexical Chain
BT  - Proceedings of the 2012 2nd International Conference on Computer and Information Application (ICCIA 2012)
PB  - Atlantis Press
SP  - 681
EP  - 684
SN  - 1951-6851
UR  - https://doi.org/10.2991/iccia.2012.164
DO  - 10.2991/iccia.2012.164
ID  - Li2014/05
ER  -