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Case-based information retrieval

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Topics in Case-Based Reasoning (EWCBR 1993)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 837))

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Abstract

This paper discusses a Case-Based Reasoning (CBR) approach as a good way of incrementally improving an information retrieval strategy. The proposed approach, Cabri-n, achieves a synergy between CBR and information retrieval that aims to exploit users feedback for improving the retrieval short-term performances (during a single retrieval session) and the long-term performances (over the system's life time). The long-term improvement is achieved by managing a memory of sessions which exploits successes as well as failures of information retrieval. A typology defined over the set of potential information needs serves as a meta-index for the long-term memory, so allows a context-sensitive retrieval and adaptation of former sessions. Besides, we discuss some common issues of CBR and information retrieval making their combination a promising paradigm.

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Author information

Authors and Affiliations

  1. C.R.I.N./C.N.R.S., Bâtiment Loria, B.P. 239, F54506, Vandœuvre-lès-Nancy Cedex

    Malika Smaïl

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  1. Malika Smaïl
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Editor information

Stefan Wess Klaus-Dieter Althoff Michael M. Richter

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© 1994 Springer-Verlag Berlin Heidelberg

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Smaïl, M. (1994). Case-based information retrieval. In: Wess, S., Althoff, KD., Richter, M.M. (eds) Topics in Case-Based Reasoning. EWCBR 1993. Lecture Notes in Computer Science, vol 837. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-58330-0_103

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  • DOI: https://doi.org/10.1007/3-540-58330-0_103

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-58330-1

  • Online ISBN: 978-3-540-48655-8

  • eBook Packages: Springer Book Archive

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