Mining Tree Based Association Rules for XML Answering

The database research field has concentrated on the Extensible Markup Language (XML) due to its flexible hierarchical nature which can use to represent huge amounts of data  also it does not have absolute and fixed schema, but having possibly irregular and incomplete structure. It is a very hard task to extract information from semi structured documents and is going to become more and more difficult as the amount of digital information available on the Internet grows. On querying the XML document directly, the problem of information overload may occur where too much data are included in the answer because the set of keyword specified for the search capture too many meanings and the problem of information deprivation where either the use of inappropriate keywords, or wrong formulation of query prevents the user from receiving the correct answer. In this work we describe an approach to mine Tree based Association Rules (TARs) from XML documents. Such rules provide information on both the structure and the content of the XML document and the rules can be stored in XML format for the purpose of querying. The mined knowledge is used to provide the quick, approximate answers to queries and information about structural regularities that can be used as data guides for document querying. Here, we propose an algorithm that extends CMTree Miner (discovers closed and maximal frequent subtrees) to mine tree based association rules from XML document.