Ontology based clustering algorithm for information retrieval

The explosive growth of mobile devices has increased the need for information on the move. As the number of web users through mobile devices is increasing day by day, it is very challenging for the search engines to provide the specific result in response to user query. We present a clustering algorithm which is based on decision tree structure in order to improve the clustering results and visualize only the relevant results to the user. In this paper, the objective is to integrate domain ontology as background knowledge and study the clustering performance. We have computed multiple clusters using standard K-means based on various similarity metrics as well. Our results are compared with previous baseline approaches to find the performance and overheads. The experimental results show that more refinement to be done in the clustering technique to retrieve documents with fewer navigations and less data traffic, which is important especially for mobile devices.