A graph-based optimization algorithm for website topology using interesting association rules

The Web serves as a global information service center that contains vast amount of data. The Website structure should be designed effectively so that users can efficiently find their information. The main contribution of this paper is to propose a graph-based optimization algorithm to modify Website topology using interesting association rules. The interestingness of an association rule A ⇒ B is defined based on the probability measure between two sets of Web pages A and B in the Website. If the probability measure between A and B is low (high), then the association rule A ⇒ B has high (low) interest. The hyperlinks in the Website can be modified to adapt user access patterns according to association rules with high interest. We present experimental results and demonstrate that our method is effective.