Memory-based learning (MBL) has enjoyed considerable success in corpus-based natural language processing (NLP) tasks and is thus a reliable method of getting a high-level of performance when building corpus-based NLP systems.
there is a bottleneck in MBL whereby any novel testing item has to be compared against all the training items in memory base.