Abstract
We present in this paper the design of ELISE, an interactive GP system for document retrieval tasks in very large medical databases. The components of ELISE have been tailored in order to produce a system that is capable of suggesting documents related to the query that may be of interest to the user, thanks to evolved profiling information. Tests on the “Cystic Fibrosis Database” benchmark [2] show that, while suggesting original documents by adaptation of its internal rules to the context of the user, ELISE is able to improve its recall rate.
This research is partly funded by Novartis-Pharma (IK@N/KE)
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Landrin-Schweitzer, Y., Collet, P., Lutton, E. (2003). Interactive GP for Data Retrieval in Medical Databases. In: Ryan, C., Soule, T., Keijzer, M., Tsang, E., Poli, R., Costa, E. (eds) Genetic Programming. EuroGP 2003. Lecture Notes in Computer Science, vol 2610. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36599-0_9
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