Fuzzy web surfer models: theory and experiments
WImBI'06 Proceedings of the 1st WICI international conference on Web intelligence meets brain informatics
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Cycle detection in graphs and digraphs has received wide attention and several algorithms are available for this purpose. While the web may be modeled as a digraph, such algorithms would not be of much use due to both the scale of the web and the number of uninteresting cycles and sequences in it. We propose a novel sequence detection algorithm for web pages, and highlight its importance for search related systems. Here, the sequence found is such that its consecutive elements have the same relation among them. This relation is measured in terms of the positional properties of navigational links, for which we provide a method for identifying navigational links. The proposed methodology does not detect all possible sequences and cycles in the web graph, but just those that were intended by the creators of those web pages. Experimental results confirm the accuracy of the proposed algorithm.