In this paper we present a k-Nearest Neighbour case-based reasoning system for classifying products into an ontology of classes. Such a classifier is of particular use in the business-to-business electronic commerce industry, where maintaining accurate products catalogues is critical for accurate spend-analysis and effective trading. Universal classification schemas, such as the United Nations Standard Products and Services Code hierarchy, have been created to aid this process, but classifying items into such a hierarchical schema is a critical and costly task. While (semi)-automated classifiers have previously been explored, items not initially classified still have to be classified by hand in a costly process. To help overcome this issue, we develop a conversational approach which utilises the known relationship between classes to allow the user to come to a correct classification much more often with minimal effort.
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