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dc.contributor.authorSmeraldi, Fabrizioen_GB
dc.contributor.authorMartinez-Alvarez, Miguelen_GB
dc.contributor.authorFrommholz, Ingoen_GB
dc.contributor.authorRoelleke, Thomasen_GB
dc.date.accessioned2013-03-22T13:29:39Z
dc.date.available2013-03-22T13:29:39Z
dc.date.issued2011
dc.identifier.citationSmeraldi, F., Martinez-Alvarez, M., Frommholz, I. Rolleke, T. (2011) 'On the Probabilistic Logical Modelling of Quantum and Geometrically-Inspired IR', in Proceedings of the 2nd Italian Information Retrieval Workshop (IIR), Milano (Italy)en_GB
dc.identifier.urihttp://hdl.handle.net/10547/275698
dc.description.abstractInformation 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.
dc.language.isoenen
dc.publisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INCen_GB
dc.relation.urlhttp://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.189.1761en_GB
dc.subjectinformation retrievalen_GB
dc.subjectgeometric modelen_GB
dc.subjectquantum logicen_GB
dc.subjectGeneralised Vector Space Modelen_GB
dc.subjectquantum-inspired modelen_GB
dc.titleOn the probabilistic logical modelling of quantum and geometrically-inspired IRen
dc.typeConference papers, meetings and proceedingsen
dc.contributor.departmentQueen Mary University, Londonen_GB
dc.contributor.departmentUniversity of Glasgowen_GB
html.description.abstractInformation 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.


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