Determining information retrieval and filtering performance without experimentation

摘要

The performance of an information retrieval or text and media filtering system may be determined through analytic methods as well as by traditional simulation or experimental methods. These analytic methods can provide precise statements about expected performance. They can thus determine which of two similarly performing systems is superior. For both a single query term and for a multiple query term retrieval model, a method for comparing the performance of different probabilistic retrieval methods is developed. This method may be used in computing the average search length for a query, given only knowledge of database parameter values. Predictive models for inverse document frequency, binary independence, and relevance feedback based retrieval and filtering are described. Simulations illustrate how the single term model performs and sample performance predictions are given for single term and multiple term problems.