## The Maximum Entropy Approach and Probabilistic IR Models (1998)

Venue: | ACM TRANSACTIONS ON INFORMATION SYSTEMS |

Citations: | 12 - 0 self |

### BibTeX

@ARTICLE{Greiff98themaximum,

author = {Warren R. Greiff and Jay M. Ponte},

title = {The Maximum Entropy Approach and Probabilistic IR Models},

journal = {ACM TRANSACTIONS ON INFORMATION SYSTEMS},

year = {1998},

volume = {18},

pages = {246--287}

}

### OpenURL

### Abstract

The Principle of Maximum Entropy is discussed and two classic probabilistic models of information retrieval, the Binary Independence Model of Robertson and Sparck Jones and the Combination Match Model of Croft and Harper are derived using the maximum entropy approach. The assumptions on which the classical models are based are not made. In their place, the probability distribution of maximum entropy consistent with a set of constraints is determined. It is argued that this subjectivist approach is more philosophically coherent than the frequentist conceptualization of probability that is often assumed as the basis of probabilistic modeling and that this philosophical stance has important practical consequences with respect to the realization of information retrieval research.