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Predictive Modeling in XML Compression

Olli Luoma, Jukka Teuhola, Predictive Modeling in XML Compression. In: Proceedings of the Second International Conference on Digital Information Management, IEEE Engineering Management Society, 2007.

Abstract:

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.

Files:

Abstract in PDF-format

BibTeX entry:

@INPROCEEDINGS{inpLuTe07a,
  title = {Predictive Modeling in XML Compression},
  booktitle = {Proceedings of the Second International Conference on Digital Information Management},
  author = {Luoma, Olli and Teuhola, Jukka},
  publisher = {IEEE Engineering Management Society},
  year = {2007},
}

Belongs to TUCS Research Unit(s): Algorithmics and Computational Intelligence Group (ACI)

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