@inproceedings{427bb757e4b1440db99122d39c6f06de,
title = "An adaptive web cache access predictor using neural network",
abstract = "This paper presents a novel approach to successfully predict Web pages that are most likely to be re-accessed in a given period of time. We present the design of an intelligent predictor that can be implemented on a Web server to guide caching strategies. Our approach is adaptive and learns the changing access patterns of pages in a Web site. The core of our predictor is a neural network that uses a backpropagation learning rule. We present results of the application of this predictor on static data using log files; it can be extended to learn the distribution of live Web page access patterns. Our simulations show fast learning, uniformly good prediction, and up to 82% correct prediction for the following six months based on a one-day training data. This long-range prediction accuracy is attributed to the static structure of the test Web site.",
author = "Wen Tian and Ben Choi and Phoha, {Vir V.}",
note = "Publisher Copyright: {\textcopyright} Springer-Verlag Berlin Heidelberg 2002.; 15th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, IEA/AIE 2002 ; Conference date: 17-06-2002 Through 20-06-2002",
year = "2002",
doi = "10.1007/3-540-48035-8_44",
language = "English (US)",
isbn = "3540437819",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "450--459",
editor = "Tim Hendtlass and Moonis Ali",
booktitle = "Developments in Applied Artificial Intelligence - 15th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, IEA/AIE 2002, Proceedings",
}