document: Compressing and searching XML data via two zips XML is fast becoming the standard format to store , exchange and publish over the web , and is getting embedded in applications . Two challenges in handling XML are its size ( the XML representation of a document is significantly larger than its native state ) and the complexity of its search ( XML search involves path and content searches on labeled tree structures ) . We address the basic problems of compression , navigation and searching of XML documents . In particular , we adopt recently proposed theoretical algorithms ( 11 ) for succinct tree representations to design and implement a compressed index for XML , called XBZIPiNDEX , in which the XML document is maintained in a highly compressed format , and both navigation and searching can be done uncompressing only a tiny fraction of the data . This solution relies on compressing and indexing two arrays derived from the XML data . With detailed experiments we compare this with other compressed XML indexing and searching engines to show that XBZIPiNDEX has compression ratio up to 35 % better than the ones achievable by those other tools , and its time performance on some path and content search operations is order of magnitudes faster : few milliseconds over hundreds of MBs of XML files versus tens of seconds , on standard XML data sources .
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