Artificial Intelligence Review - Special issue on lazy learning
ICCBR '99 Proceedings of the Third International Conference on Case-Based Reasoning and Development
Proceedings of the Fifteenth International Florida Artificial Intelligence Research Society Conference
Lucene in Action (In Action series)
Lucene in Action (In Action series)
Retrieval, reuse, revision and retention in case-based reasoning
The Knowledge Engineering Review
The Knowledge Engineering Review
Building CBR systems with jcolibri
Science of Computer Programming
Improving the performance of recommender systems that use critiquing
ITWP'03 Proceedings of the 2003 international conference on Intelligent Techniques for Web Personalization
Modified naïve bayes classifier for e-catalog classification
DEECS'06 Proceedings of the Second international conference on Data Engineering Issues in E-Commerce and Services
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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.