DocumentCode :
1578242
Title :
Differential evolution cluster-based text summarization methods
Author :
Abuobieda, Albaraa ; Salim, Naomie ; Binwahlan, Mohammed Salem ; Osman, Ahmed Hamza
Author_Institution :
Fac. of Comput. Studies, Int. Univ. of Africa, Khartoum, Sudan
fYear :
2013
Firstpage :
244
Lastpage :
248
Abstract :
In this paper, three similarity measures; Normalized Google Distance (NGD), Jaccard and Cosine Similarity measures were employed and tested for textual based clustering problem. A robust evolutionary algorithm called Differential Evolution algorithm was also used to optimize the data clustering process and increase the quality of the generated text summaries. The Recall Oriented Under Gisting Evaluation (ROUGE) was used as an evaluation measure toolkit to assess the quality of the summaries. Experimental results showed that all of our proposed methods outperformed the benchmark methods. More importantly, the Jaccard-similarity based method surpassed all the other proposed methods in this study.
Keywords :
evolutionary computation; pattern clustering; text analysis; Jaccard-similarity based method; NGD; ROUGE; cosine similarity measure; data clustering process; differential evolution cluster-based text summarization method; evaluation measure toolkit; normalized Google distance; recall oriented under gisting evaluation; robust evolutionary algorithm; similarity measure; summary quality assessment; text summaries; textual based clustering problem; Benchmark testing; Biological cells; Clustering algorithms; Equations; Evolutionary computation; Google; Linear programming; Cosine; Differential Evolution; Jaccard; NGD; Text Clustering;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computing, Electrical and Electronics Engineering (ICCEEE), 2013 International Conference on
Conference_Location :
Khartoum
Print_ISBN :
978-1-4673-6231-3
Type :
conf
DOI :
10.1109/ICCEEE.2013.6633941
Filename :
6633941
Link To Document :
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