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Predictive modeling in XML compression

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2 Author(s)
Luoma, Olli ; Department of Information Technology and Turku Centre for Computer Science 20014 University of Turku, FINLAND ; Teuhola, J.

Since its advent, the Extensible Markup Language (XML) has gained tremendous popularity in many different application areas. However, XML data is generally very verbose and redundant, and thus it requires a lot of disk space to store and bandwidth to transfer. To overcome this problem, many methods for compressing XML documents have been proposed. In general, data compression requires a model which is used to predict the next symbol in the data. In this paper, we compare different models suitable for XML compression. We also present a novel modeling method and measure the information content in a set of XML documents using different modeling methods.

Published in:

Digital Information Management, 2007. ICDIM '07. 2nd International Conference on  (Volume:2 )

Date of Conference:

28-31 Oct. 2007

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