BibTeX
@MISC{n.n._computationallytractable,
author = {n.n.},
title = {Computationally Tractable Probabilistic Modeling of Boolean Operators},
year = {}
}
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Abstract
The inference network model of information retrieval allows for a probabilistic interpretation of Boolean query operators. Prior work has shown, however, that these operators do not perform as well as the the pnorm operators developed in the context of the vector space model. The design of alternative operators in the inference network framework must contend with the issue of computational tractability. We define a flexible class of link matrices that are natural candidates for the implementation of Boolean operators and an O(n²) algorithm for the computation of probabilities involving link matrices of this class. We present experimental results indicating that Boolean operators implemented in terms of link matrices from this class perform at least as well as pnorm operators.
Keyphrases
boolean operator tractable probabilistic modeling link matrix pnorm operator flexible class vector space model alternative operator inference network framework natural candidate boolean query operator prior work computational tractability probabilistic interpretation class perform information retrieval inference network model present experimental result
