Performance Enhancement of XML Parsing By Using Artificial Neural Network

Abstract

XML is used for data representation and exchange. XML data processing becomes more and more important for server workloads like web servers and database servers. One of the most time consuming part is XML document parsing. Parsing is a core operation performed before an XML document can be navigated, queried, or manipulated. Recently, high performance XML parsing has become a topic of considerable interest. This paper proposes a mechanism for efficiently processing XML documents with the help of Artificial Neural Network (ANN). Provide the set of XML documents to the system and parsing results will store in the database. With the help of Artificial Neural Network (ANN) the performance of XML parsing will improve by reducing parsing time of XML document. Levenberg-Marquardt algorithm (LMA) is used to train the neurons in the Artificial Neural Network (ANN) to recognize XML document pattern. This proposed system will improve the performance of xml parsing by reducing parsing time of XML document with the help of Artificial Neural Network (ANN).