Mining Search Engine Query Log for Evaluating Content and Structure of a Web Site

Abstract

Mining search engine query log is a new method for evaluating web site link structure and information architecture. In this paper we propose a new query-URL co-clustering for a web site useful to evaluate information architecture and link structure. Firstly, all queries and clicked URLs corresponding to particular web site are collected from a query log as bipartite graph, one side for queries and the other side for URLs. Then a new content free clustering is applied to cluster queries and URLs concurrently. Afterwards, based on information entropy, clusters of URLs and queries will be used for evaluating link structure and information architecture respectively. Data sets of different web sites have been extracted from a huge query log to evaluate our method, and experiments show promising result.