Maintaining case-based reasoners: Dimensions and directions

Experience with the growing number of large-scale and long-term case-based reasoning (CBR) applications has led to increasing recognition of the impor tance of maintaining existing CBR systems. Recent research has focused on c ase-base maintenance (CBM), addressing such issues as maintaining consisten cy, preserving competence, and controlling case-base growth. A set of dimen sions for case-base maintenance, proposed by Leake and Wilson, provides a f ramework for understanding and expanding CBM research. However, it also has been recognized that other knowledge containers can be equally important m aintenance targets. Multiple researchers have addressed pieces of this more general maintenance problem, considering such issues as how to refine simi larity criteria and adaptation knowledge. As with case-base maintenance, a framework of dimensions for characterizing more general maintenance activit y, within and across knowledge containers, is desirable to unify and unders tand the state of the art, as well as to suggest new avenues of exploration by identifying points along the dimensions that have not yet been studied. This article presents such a framework by (1) refining and updating the ea rlier framework of dimensions for case-base maintenance, (2) applying the r efined dimensions to the entire range of knowledge containers, and (3) exte nding the theory to include coordinated cross-container maintenance. The re sult is a framework for understanding the general problem of case-based rea soner maintenance (CBRM). Taking the new framework as a starting point, the article explores key issues for future CBRM research.