Schema Independent XML Compressor

Schema Independent XML Compressor

Baydaa Al-Hamadani (University of Huddersfield, UK), Zhongyu (Joan) Lu (University of Huddersfield, UK) and Raad F. Alwan (Philadelphia University, Jordan)
Copyright: © 2011 |Pages: 21
DOI: 10.4018/ijirr.2011070102
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Abstract

XML has become the standard way for representing and transforming data over the World Wide Web. The problem with XML documents is that they have a very high ratio of redundancy, which makes these documents demanding a large storage capacity and large network band-width for transmission. This study designs a system for compressing and querying XML documents (XMLCQ) which compresses the XML document without the need to its schema or DTD to minimize the amount of technologies associated with these documents. XMLCQ first compressed the XML document by separating its data into containers according to the path of these data from the root to the leaf, then it compressed these containers using a back-end compression technique. The compressed file then could be retrieved with any kind of queries applied. Only the required information is decompressed and submitted to the user. Depending on several experiments, the query processor part of the system showed the ability to answer different kinds of queries ranging from simple exact match queries to complex ones. Furthermore, this paper introduced the idea of retrieving information from more than one compressed XML documents.
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Recently, large numbers of XML compression techniques have been proposed. Each of which has different characteristics. This section discusses the differences between these compressors and their main features.

XML compressors can be classified into two classes either to be XML-blind or XML-conscious compressors. XML-blind or general purpose compressors deal with the XML document as a traditional text document ignoring its structure and apply the general purpose text compression techniques to compress them. These techniques can be classified into two main classes (Salomon, 2007), either to be statistical or dictionary based compressors (Augeri et al., 2007; Augeri, 2008). The statistical or the arithmetic compressors represent each string of characters using a fixed number of bits per character. PPM, CACM3, and PAQ are examples of this kind of compressors (Cleary & Witten, 1984; Moffat, 1990; Alistair et al., 1998). On the other hand, dictionary compression techniques substitute each string in the input by its reference in a dictionary maintained by the encoder. WinZip (http://www.bzip.org/) are examples of this compression class.

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