Towards Dynamic Maintenance of Retrieval Knowledge in CBR

David Patterson, Niall Rooney, Mykola Galushka, and Sarab S. Anand

The utility problem is observable in many learning systems including case-based reasoning (CBR). In-dexing strategies have been implemented in CBR to overcome the effects of the utility problem but have been criticised as although improving retrieval effi-ciency they can reduce the competency of solutions and can be difficult to maintain. Here we present a novel indexing strategy based on a modified k-means clustering algorithm. We demonstrate that such an indexing strategy improves retrieval efficiency with-out adversely affecting solution competency. Impor-tantly it also provides a means for the dynamic real time maintenance of retrieval knowledge thus ensur-ing that the index is always optimal.

This page is copyrighted by AAAI. All rights reserved. Your use of this site constitutes acceptance of all of AAAI's terms and conditions and privacy policy.