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Title:
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PERSONALIZING TEXT SUMMARIZATION BASED ON SENTENCE WEIGHTING |
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Author(s):
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Christos Bouras , Vassilis Poulopoulos , Vassilis Tsogkas |
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ISBN:
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978-972-8924-40-9 |
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Editors:
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Jörg Roth, Jairo Gutiérrez and Ajith P. Abraham (series editors: Piet Kommers, Pedro Isaías and Nian-Shing Chen) |
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Year:
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2007 |
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Edition:
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Single |
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Keywords:
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Text summarization, Personalizing the Web, Text Categorization, Sentence Weighting |
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Type:
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Full Paper |
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First Page:
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3 |
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Last Page:
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10 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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The amount of data that exists on the Internet is enormous enough to distract users when trying to find useful
information. In addition, the expansive use of small screen devices for browsing the World Wide Web generates huge
problems when trying to find and read information. A solution to these problems is to personalize the web and try to
reduce algorithmically the amount of text. Many text summarizers have been presented in order to reduce the valueless
information that is presented to the users and many web sites, especially news portals, introduce personalization features
for the users, though, still these techniques are not often used in combination in order to create more effective results. In
this paper a mechanism for creating personalized summaries for the members of a news portal that reproduces articles
collected from major portals is presented, together with evaluation both of the summarizer and the personalized
summaries. The evaluators of the personalized summaries are members of the news portal. The personalized summary
mechanism can also be utilized by users of small screen devices, for easier reading of less but inclusive information. |
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