A web page usage prediction scheme using sequence indexing and clustering techniques ?
In this paper we consider the problem of web page usage prediction in a web site by modeling users navigation history and web page content with weighted suffix trees. This users navigation prediction can be exploited either in an on-line recommendation system in a web site or in a web page cache system. The method proposed has the advantage that it demands a constant amount of computational effort per one users action and consumes a relatively small amount of extra memory space. These features make the method ideal for an on-line working environment. Finally, we have performed an evaluation of the proposed scheme with experiments on various web site log files and web pages and we have found that its quality performance is fairly well and in many cases an outperforming one.
world wide web web mining on-line web page recommendation weighted sequences