This paper outlines the design of a web crawler implemented for IBM
Almaden’s WebFountain project and describes an optimization model for controlling the
crawl strategy. This crawler is scalable and incremental. The model makes no assumptions
about the statistical behaviour of web page changes, but rather uses an adaptive approach to
maintain data on actual change rates which are in turn used as inputs for the optimization.
Computational results with simulated but realistic data show that there is no ‘magic bullet’
-different, but equally plausible, objectives lead to conflicting ‘optimal’ strategies. However,
we find that there are compromise objectives which lead to good strategies that are robust
against a number of criteria.
By: Jenny Edwards,Kevin McCurley, John Tomlin,
Published in: RJ10210 in 2001
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