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      Towards a better understanding of language model information retrieval

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      2nd BCS IRSG Symposium: Future Directions in Information Access 2008 (FDIA)

      Future Directions in Information Access

      22nd September 2008

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          Abstract

          Language models form a class of successful probabilistic models in information retrieval. However, knowledge of why some methods perform better than others in a particular situation remains limited. In this study we analyze what language model factors influence information retrieval performance. Starting from popular smoothing methods we review what data features have been used. Document length and a measure of document word distribution turned out to be the important factors, in addition to a distinction in estimating the probability of seen and unseen words. We propose a class of parameter-free smoothing methods, of which multiple specific instances are possible. Instead of parameter tuning however, an analysis of data features should be used to decide upon a specific method. Finally, we discuss some initial experiments.

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          Author and article information

          Contributors
          Conference
          September 2008
          September 2008
          : 30-37
          Affiliations
          Radboud University Nijmegen
          Radboud University Nijmegen

          Donders Institute for Brain Cognition and Behavior
          Radboud University Nijmegen

          Institute for Computing and Information Science
          Article
          10.14236/ewic/FDIA2008.4
          © M. van der Heijden et al. Published by BCS Learning and Development Ltd. 2nd BCS IRSG Symposium: Future Directions in Information Access 2008

          This work is licensed under a Creative Commons Attribution 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

          2nd BCS IRSG Symposium: Future Directions in Information Access 2008
          FDIA
          2
          London
          22nd September 2008
          Electronic Workshops in Computing (eWiC)
          Future Directions in Information Access
          Product
          Product Information: 1477-9358BCS Learning & Development
          Self URI (journal page): https://ewic.bcs.org/
          Categories
          Electronic Workshops in Computing

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