Application of modified nearest neighbor method on case-based reasoning

Case-based reasoning can deal with those cases that are difficult to describe in exact rules, so it is very important in infer engine, and similarity is usually applied to search the case in it. At present, the nearest neighbor method is broadly adopted, but it has some shortcomings such as aimless searching, much work to calculate and so on. Therefore, a modified method is produced to reasonably decide the case using cluster algorithm, and to find out the mean for each duster. Then, the new case is compared directly with these means to find out the closest duster and the nearest case. Therefore aimless searching is avoided and the algorithm is optimized.