Case-Based Information Retrieval

Malika Smail

C.R.I.N./C.N.R.S.
Btiment Loria, B.P. 239
F54506 Vandoeuvre-ls-Nancy Cedex
e-mail : malika@loria.fr
Tel : (033) 83.59.20.65


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 systems 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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