Abstract
In this paper, we proposed an novel PageRank algorithm, which segmented each page into several paragraphs. Then we built links between paragraphs by using N-Gram method. The regular PageRank algorithm were applied on paragraphs and score of PageRank for each paragraph was obtained. The average of the paragraph scores of each page, denoted as Value of Paragraph Content, was used to give scores to the pages. In the N-Gram method, we proposed a solution to limit the memory usage through a hash table.
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© 2003 Springer-Verlag Berlin Heidelberg
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Miao, J., Lin, S. (2003). A Novel Value of Paragraph Content Based PageRank Approach. In: Sembok, T.M.T., Zaman, H.B., Chen, H., Urs, S.R., Myaeng, SH. (eds) Digital Libraries: Technology and Management of Indigenous Knowledge for Global Access. ICADL 2003. Lecture Notes in Computer Science, vol 2911. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24594-0_14
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DOI: https://doi.org/10.1007/978-3-540-24594-0_14
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-20608-8
Online ISBN: 978-3-540-24594-0
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