A toy model of information retrieval system based on quantum probability

Abstract

Recent numerical results show that non-Bayesian knowledge revision may be helpful in search engine training and optimization. In order to demonstrate how basic assumption about about the physical nature (and hence the observed statistics) of retrieved documents can affect the performance of search engines we suggest an idealized toy model with minimal number of parameters.

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