An enhanced model for effective navigation of a website using clustering technique

Designing well structured websites has long been a challenge to facilitate effective user navigation. The reason for poor website design is that the web developers understanding of website structure is considerably different from that of the users. The reorganization of a website structure changes the location of familiar items. They would not be frequently performed to improve the navigability. The existing Mathematical Programming model facilitates user navigation on a website with minimal changes to its current structure. It is appropriate for informational websites whose content are static and relatively stable over time. It allows a page to have more links than the out-degree threshold if the cost is reasonable. Number of relevant mini sessions decreases as path threshold increases. Thus the Mathematical Programming model focuses on enhancing the design of existing links before adding new links. To improve the navigability further, an enhanced model using Graph Partitioned Clustering algorithm is proposed. It is used to group the potential users with similar navigation pattern from preprocessed web log data. Clustering results include number of visits made to a single webpage, most frequently viewed page and navigation behavior of the users. To minimize the average weighted shortest distance between pages and the average surfing distance, the enhanced mathematical programming model is proposed and applied to the clustered results. After identifying the existing links to be improved and new links to be added, the web site current structure has to be reorganized. Thus, it will improve the user navigation on a website effectively.