Text Summarization Based on Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@Misc{oai:CiteSeerX.psu:10.1.1.372.7511,

• author = "Pooya Khosraviyan Dehkordi and Farshad Kumarci and Hamid Khosravi",
• title = "Text Summarization Based on Genetic Programming",
• year = "2013",
• month = oct # "~30",
• number = "1/",
• keywords = "genetic algorithms, genetic programming, automatic text summarisation, vectorial model",
• annote = "The Pennsylvania State University CiteSeerX Archives",
• bibsource = "OAI-PMH server at citeseerx.ist.psu.edu",
• issue = "57-64",
• language = "en",
• oai = "oai:CiteSeerX.psu:10.1.1.372.7511",
• rights = "Metadata may be used without restrictions as long as the oai identifier remains attached to it.",
• URL = "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.372.7511",
• broken = "http://ijcir.org/volume3-number1/issue 57-64.pdf",
• abstract = "This work proposes an approach to address the problem of improving content selection in automatic text summarisation by using some statistical tools. This approach is a trainable summariser, which takes into account several features, for each sentence to generate summaries. First, we investigate the effect of each sentence feature on the summarization task. Then we use all features in combination to train genetic programming (GP), vector approach and fuzzy approach in order to construct a text summariser for each model. Furthermore, we use trained models to test summarisation performance. The proposed approach performance is measured at several compression rates on a data corpus composed of 17 English scientific articles.",

}

Genetic Programming entries for Pooya Khosraviyan Dehkordi Farshad Kumarci Hamid Khosravi

Citations