Towards improving XML search by using structure clustering technique

Searching large XML repositories is a challenging research problem. The application of clustering on a large repository before performing a search enhances the search process significantly. Clustering reduces a search space into smaller XML collections that can be better searched. In this work, we present an enhanced XML clustering by structure method. Also, we introduce a new representation of XML structure that keeps all characteristics of XML structure without summarization. Then, we perform a benchmark comparison between the search results of our improved method to SAXON and Qizx XML XQuery processors. The comparison focuses on search processing time and accuracy of the results using different sizes of datasets for both homogeneous and heterogeneous XML documents. The attained results show better accuracy at the same level of performance.