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