Abstract

Combining Web caching and Web pre-fetching techniques results in obtaining the required information almost instantaneously. It also results in improved bandwidth utilization, load reduction on the origin server and reduces access delay. Web Pre-fetching is the process of fetching some of the predicted Web pages in advance which is assumed to be used by the user in the near future and the caching is the process of storing the pre-fetched Web pages in the cache memory. In the literature many interesting works have been reported separately for Web caching and for Web pre-fetching. In this study we combine pre-fetching (using clustering) and caching (using SVM) to keep track of the tourist spots that are likely to be visited by the tourists in the near future based on the previous history of visits. With the help of real data it is demonstrated that our approach is superior than clustering based pre-fetching technique using traditional LRU based caching policy which does not use SVM.

Keywords:

Classification, clustering, confidence , hit-ratio , support , Support Vector Machine (SVM),

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Competing interests

The authors have no competing interests.

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The authors have no competing interests.