A new probabilistic ranking model

Richard Connor, Robert Moss, Morgan Harvey

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

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.

Original languageEnglish
Title of host publicationInternational Conference on the Theory of Information Retrieval, ICTIR 2013 Proceedings
Pages109-112
Number of pages4
DOIs
Publication statusPublished - 30 Oct 2013
Event4th International Conference on the Theory of Information Retrieval, ICTIR 2013 - Copenhagen, Denmark
Duration: 29 Sept 20132 Oct 2013

Publication series

NameACM International Conference Proceeding Series

Conference

Conference4th International Conference on the Theory of Information Retrieval, ICTIR 2013
Country/TerritoryDenmark
CityCopenhagen
Period29/09/132/10/13

Keywords

  • Information retrieval
  • Jensen-Shannon Divergence
  • Probabilistic retrieval
  • Ranking

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