An improved evolutionary algorithm for extractive text summarization
The main challenge of extractive-base text summarization is in selecting the top representative sentences from the input document. Several techniques were proposed to enhance the process of selection such as feature-base, cluster-base, and graph-base methods. Basically, this paper proposed to enhanc...
Saved in:
Main Authors: | Abuobieda, A., Salim, N., Kumar, Y. J., Osman, A. H. |
---|---|
Format: | Conference or Workshop Item |
Published: |
2013
|
Subjects: | |
Online Access: | http://eprints.utm.my/id/eprint/50887/ https://doi.org/10.1007/978-3-642-36543-0_9 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Text summarization features selection method using pseudo genetic-based model
by: Abuobieda, A., et al.
Published: (2012) -
Opposition differential evolution based method for text summarization
by: Abuobieda, Albaraa, et al.
Published: (2013) -
Genetic algorithm based sentence extraction for text summarization
by: Suanmali, Ladda, et al.
Published: (2011) -
Differential evolution cluster-based text summarization methods
by: Abuobieda, Albaraa, et al.
Published: (2013) -
Hybrid differential evolution based automatic single document text summarization
by: Mohammed Ali Abuobieda, Albaraa Abuobieda
Published: (2013)