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Revisiting Exhaustivity and Specificity Using Propositional Logic and Lattice Theory

Published: 29 September 2013 Publication History

Abstract

Exhaustivity and Specificity in logical Information Retrieval framework were introduced by Nie [16]. However, even with some attempts, they are still theoretical notions without a clear idea of how to be implemented. In this study, we present a new approach to deal with them. We use propositional logic and lattice theory in order to redefine the two implications and their uncertainty P(d → q) and P(q → d). We also show how to integrate the two notions into a concrete IR model for building a new effective model. Our proposal is validated against six corpora, and using two types of terms (words and concepts). The experimental results showed the validity of our viewpoint, which state: the explicit integration of Exhaustivity and Specificity into IR models will improve the retrieval performance of these models. Moreover, there should be a type of balance between the two notions.

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Cited By

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  • (2022)Roots and trends in knowledge organizationBoosting the Knowledge Economy10.1016/B978-1-84334-772-9.00007-5(39-61)Online publication date: 2022
  • (2016)Logics, Lattices and Probability: The Missing Links to Information RetrievalThe Computer Journal10.1093/comjnl/bxw034Online publication date: 29-Jul-2016

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  1. Revisiting Exhaustivity and Specificity Using Propositional Logic and Lattice Theory

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      ICTIR '13: Proceedings of the 2013 Conference on the Theory of Information Retrieval
      September 2013
      148 pages
      ISBN:9781450321075
      DOI:10.1145/2499178
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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      • Findwise: Findwise AB
      • Google Inc.
      • Spinque: Spinque
      • Univ. of Copenhagen: University of Copenhagen
      • LARM: LARM Audio Research Archive
      • Royal School of Library and Information Science: Royal School of Library and Information Science
      • Yahoo! Labs

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      Published: 29 September 2013

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      Author Tags

      1. Exhaustivity
      2. Information retrieval
      3. Specificity

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      Sponsor:
      • Findwise
      • Spinque
      • Univ. of Copenhagen
      • LARM
      • Royal School of Library and Information Science

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      ICTIR '13 Paper Acceptance Rate 11 of 51 submissions, 22%;
      Overall Acceptance Rate 235 of 527 submissions, 45%

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      Cited By

      View all
      • (2022)Roots and trends in knowledge organizationBoosting the Knowledge Economy10.1016/B978-1-84334-772-9.00007-5(39-61)Online publication date: 2022
      • (2016)Logics, Lattices and Probability: The Missing Links to Information RetrievalThe Computer Journal10.1093/comjnl/bxw034Online publication date: 29-Jul-2016

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