Improvement of KEA Based on Lexical Chain
- 10.2991/iccia.2012.164How to use a DOI?
- keyphrases extraction, KEA, lexcial chain,semantic similarity.
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.
- © 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/).
Cite this article
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 -