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On the probabilistic logical modelling of quantum and geometrically-inspired IR

  • Ingo Frommholz
    ,
  • Fabrizio Smeraldi
    ,
  • Miguel Martinez-Alvarez
    ,
  • Thomas Roelleke
  • Queen Mary University of London
Research Output: Chapter in Book/Report/Conference proceeding Conference contribution Peer-review

Open access

Abstract

Information Retrieval approaches can mostly be classed into probabilistic, geometric or logic-based. Recently, a new unifying framework for IR has emerged that integrates a probabilistic description within a geometric framework, namely vectors in Hilbert spaces. The geometric model leads naturally to a predicate logic over linear subspaces, also known as quantum logic. In this paper we show the relation between this model and classic concepts such as the Generalised Vector Space Model, highlighting similarities and differences. We also show how some fundamental components of quantum-based IR can be modelled in a descriptive way using a well-established tool, i.e. Probabilistic Datalog.

Publication Information

Output type

Research Output: Chapter in Book/Report/Conference proceeding Conference contribution Peer-review

Original language

English

Publication milestones

  • Published - 01/01/2011

Publication status

Published - 01/01/2011

Publisher

Institute of Electrical and Electronics Engineers Inc., United States

External Publication IDs

  • handle.net: 10547/275698

Host publication title

nan

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