1. Xml database compression by adaptive huffman coding algorithm techniques.
Authors : Rashmi Gadbail, Aniket Asole
Pages : 67-72
DOI : http://dx.doi.org/10.21172/1.73.010
Keywords : : Compression, decompression, , Efficient XML compression and decompression, Adaptive Huffman coding Techniques. Abstract :Abstract- The Extensible Markup Language (XML) is one of the most important formats for data interchange on the Internet. XML documents are used for data exchange and to store large amount of data over the web. These documents are extremely verbose and require specific compression for efficient transformation. In this proposed work we are enhancing the existing compressors which use Adaptive Huffman coding. It is based on the principle of extracting data from the document, and grouping it based on semantics. The document is encoded as a sequence of integers, while the data grouping is based on XML tags/attributes/comments. The main disadvantage of using XML documents is their large sizes caused by highly repetitive (sub) structures of those documents and often long tag and attribute names. Hence there is need to compress XML both efficiently and conveniently to use. The re-organized data is now compressed by adaptive Huffman coding. The special feature of adaptive Huffman coding algorithm is that, it has extremely accurate compression as well as it eliminates the repetition of dictionary based words in xml database. Using Adaptive Huffman algorithm, we derived probabilities which dynamically changed with the incoming data, through Binary tree construction techniques.
Citing this Journal Article :Rashmi Gadbail, Aniket Asole, "Xml database compression by adaptive huffman coding algorithm techniques.", Summer Special Issue - - June 2016, 67-72
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