Improving pattern quality in web usage mining by using semantic information

Frequent Web navigation patterns generated by using Web usage mining techniques provide valuable information for several applications such as Web site restructuring and recommendation. In conventional Web usage mining, semantic information of the Web page content does not take part in the pattern generation process. In this work, we investigate the effect of semantic information on the patterns generated for Web usage mining in the form of frequent sequences. To this aim, we developed a technique and a framework for integrating semantic information into Web navigation pattern generation process, where frequent navigational patterns are composed of ontology instances instead of Web page addresses. The quality of the generated patterns is measured through an evaluation mechanism involving Web page recommendation. Experimental results show that more accurate recommendations can be obtained by including semantic information in navigation pattern generation, which indicates the increase in pattern quality.