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
MPIS: Maximal-Profit Item Selection with Cross-Selling Considerations
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
Data Mining for Inventory Item Selection with Cross-Selling Considerations
Data Mining and Knowledge Discovery
Temporal pre-fetching of dynamic web pages
Information Systems
Semantic web access prediction
CompSysTech '07 Proceedings of the 2007 international conference on Computer systems and technologies
Temporal pre-fetching of dynamic web pages
Information Systems
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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.