A Classification-based XML Information Retrieval Model

Abstract

The main problem of content-based XML information retrieval is how to select the relevant unit of information that answers the user’s query composed of only key words (content only). Our objective is to select relevant elements that can belong to different parts of XML documents of the corpus for user’s information need. To do this, we propose a neural XML information retrieval model using Kohonen self-organizing maps. Kohonen self-organizing map lets classification of XML elements producing density map that form the foundations of the XML information retrieval system.