A new probabilistic ranking model

Connor, Richard and Moss, Robert and Harvey, Morgan; Kurland, Orlen and Metzler, Donald and Lioma, Christina and Larsen, Birger and Ingwersen, Peter, eds. (2013) A new probabilistic ranking model. In: Proceeding ICTIR '13 Proceedings of the 2013 Conference on the Theory of Information Retrieval. ACM, DNK, pp. 109-112. ISBN 9781450321075 (https://doi.org/10.1145/2499178.2499185)

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Abstract

Over the years a number of models have been introduced as solutions to the central IR problem of ranking documents given textual queries. Here we define another new model. It is a probabilistic model and has no term inter-dependencies, thus allowing calculation from inverted indices. It is based upon a simple core hypothesis, directly calculating a ranking score in terms of probability theory. Early results show that its performance is credible, even in the absence of parameters or heuristics. Its semantic basis gives absolute results, allowing different rankings to be compared with each other. The investigation of this model is at a very early stage; here, we simply propose the model for further investigation.

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