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This paper describes a dynamic Information Retrieval System (IRS) based on the neural approach. Our goal is to construct an IRS able to evolve in respect with the user's tendency. We propose a network containing document, term and author nodes where the links between these different nodes express the different relationships which may exist between them. A set of activation/propagation rules on which is based the information retrieval and the queries expansion processes are presented. At last, we propose a learning strategy inspired by the backpropagation algorithm to dynamically organize the information base.

Application of the Backpropagation Algorithm to an Information Retrieval System