The anatomy of a large-scale hypertextual Web search engine
WWW7 Proceedings of the seventh international conference on World Wide Web 7
Predicting users' requests on the WWW
UM '99 Proceedings of the seventh international conference on User modeling
Elementary Numerical Analysis: An Algorithmic Approach
Elementary Numerical Analysis: An Algorithmic Approach
WhatNext: A Prediction System for Web Requests using N-gram Sequence Models
WISE '00 Proceedings of the First International Conference on Web Information Systems Engineering (WISE'00)-Volume 1 - Volume 1
Exploring the bounds of web latency reduction from caching and prefetching
USITS'97 Proceedings of the USENIX Symposium on Internet Technologies and Systems on USENIX Symposium on Internet Technologies and Systems
An adaptive network prefetch scheme
IEEE Journal on Selected Areas in Communications
A note on the paper: optimizing web servers using page rank prefetching for clustered accesses
Information Sciences—Informatics and Computer Science: An International Journal
Automatic seed set expansion for trust propagation based anti-spam algorithms
Information Sciences: an International Journal
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This paper presents a Page rank-based prefetching technique for accesses to Web page clusters. The approach uses the link structure of a requested page to determine the "most important" linked pages and to identify the page(s) to be prefetched. The underlying premise of our approach is that in the case of cluster accesses, the next pages requested by users of the Web server are typically based on the current and previous pages requested. Furthermore, if the requested pages have a lot of links to some "important" page, that page has a higher probability of being the next one requested. An experimental evaluation of the prefetching mechanism is presented using real server logs. The results show that the Page rank-based scheme does better than random prefetching for clustered accesses, with hit rates of 90% in some cases.