Text Summarization Based on Conceptual Data Classification

Text Summarization Based on Conceptual Data Classification

Jihad M. ALJa’am (University of Qatar, Qatar), Ali M. Jaoua (University of Qatar, Qatar), Ahmad M. Hasnah (University of Qatar, Qatar), F. Hassan (University of Qatar, Qatar), H. Mohamed (University of Qatar, Qatar), T. Mosaid (University of Qatar, Qatar), H. Saleh (University of Qatar, Qatar) and F. Abdullah (University of Qatar, Qatar)
Copyright: © 2009 |Pages: 15
DOI: 10.4018/978-1-60566-618-1.ch011
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In this paper, we present an original approach for text summarization using conceptual data classification. We show how a given text can be summarized without losing meaningful knowledge and without using any semantic or grammatical concepts. In fact, concept date classification is used to extract the most interacting sentences from the main text and ignoring the other meaningless sentences in order to generate the text summary. The approach is tested on Arabic and English texts with different sizes and different topics and the obtained results are satisfactory. The system may be incorporated with the indexers of search engines over the Internet in order to find key words and other pertinent information of the new deployed Web pages that would be stored in databases for quick search.

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