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Text Summarization: Using Combinational Statistical And Linguistic Methods

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dc.contributor.advisor Tamimi, Manal
dc.contributor.author taamra, yasmin
dc.contributor.author Natsha, ghadeer
dc.contributor.author Amro, Baraa
dc.date.accessioned 2022-03-31T05:49:10Z
dc.date.accessioned 2022-05-22T08:17:18Z
dc.date.available 2022-03-31T05:49:10Z
dc.date.available 2022-05-22T08:17:18Z
dc.date.issued 2011-06-01
dc.identifier.uri http://localhost:8080/xmlui/handle/123456789/7690
dc.description no of pages 110, 25109, تكنولوجيا المعلومات 16/2011, in the store
dc.description.abstract Summaries are considered as useful indicators of the document content. Traditionally, summaries are created by humans, through reading a text and identifying the most important points in it. But the information overloading makes such manual work very difficult. Many attempts have been made to automate the summarization task. This project aims at proposing a methodology for automatic text summarization based on extractive methods. Extractive summarization needs the selection of a subset of important, meaningful sentences from the source text. The work presents a method for automatic text summarization of a single computer science article using statistical and linguistic approach. About 50 experts' persons summaries were used to evaluate the proposed method. Our results show that using the combinational statistical and linguistic methods is better than using each method alone. en_US
dc.language.iso en en_US
dc.publisher جامعة بوليتكنك فلسطين - تكنولوجيا المعلومات en_US
dc.subject Combinational Statistical And Linguistic Methods en_US
dc.subject Text en_US
dc.title Text Summarization: Using Combinational Statistical And Linguistic Methods en_US
dc.type Other en_US

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