Web Prefetching Method Based on Weighted Semantic Distance

To embody the relations between terms and provide a better personalized service for the(user,) the idea of constructing the user interest model under the semantic network is proposed.According to the user's navigation history and the concept relations living in the HowNet,a user interest forest model based on the relative relations of concepts is constructed.By computing the average weighted semantic distance of texts in the hyperlinks,Web pages that a user may visit in the future are prefetched.The Web prefetching method based on weighted semantic distance induces the user interests and reflects the concept relations of the terms by weighted semantic distance.Experiments showed that this method had a higher hit-ratio and a lower miss-ratio,and the average hit-ratio was about 61 percent.