Data Mining For XML Query-Answering Support

Abstract

XML has become a defacto standard for storing, sharing and exchanging information across heterogeneous platforms. The XML content is growing day by day in rapid pace. Enterprises need to make queries on XML databases frequently. As huge XML data is available, it is challenging task to extract required data from XML database. It is computationally expensive to answer queries without any support. Towards this, in this paper we present a technique known as Tree-based Association Rules (TARs) mined rules that provide required information on structure and content of XML file and the TARs are also stored in XML format. The mined knowledge (TARs) used later for XML query answering support. This enables quick and accurate answering. We also developed a prototype application to demonstrate the efficiency of the proposed system. The empirical results are very positive and query answering is expected to be useful in real time applications.