Salim, Naomie and M., Syafrullah (2010) Improving term extraction using particle swarm optimization techniques. Journal of Computer Science, 6 (3). 323 - 329. ISSN 1549-3636
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Official URL: http://dx.doi.org/10.3844/jcssp.2010.323.329
Term extraction is one of the layers in the ontology development process which has the task to extract all the terms contained in the input document automatically. The purpose of this process is to generate list of terms that are relevant to the domain of the input document. In the literature there are many approaches, techniques and algorithms used for term extraction. In this paper we propose a new approach using particle swarm optimization techniques in order to improve the accuracy of term extraction results. We choose five features to represent the term score. The approach has been applied to the domain of religious document. We compare our term extraction method precision with TFIDF, Weirdness, GlossaryExtraction and TermExtractor. The experimental results show that our propose approach achieve better precision than those four algorithm.
|Uncontrolled Keywords:||term extraction, particle swarm optimization, feature selection, text mining|
|Subjects:||Q Science > QA Mathematics > QA75 Electronic computers. Computer science|
|Divisions:||Computer Science and Information System (Formerly known)|
|Deposited By:||Liza Porijo|
|Deposited On:||28 Jun 2012 02:01|
|Last Modified:||08 Feb 2017 07:37|
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