Classification and Clustering: Problems for the Future

This paper reviews various basic achievements in classification during the last fifteen years and points to a series of unsolved mathematical, statistical and applied problems. It suggests the investigation of new methodological aspects, a better adaptation between methods and applications, the extension of cluster and data analysis into fields like information processing, machine learning and artificial intelligence, and a formal investigation of information retrieval problems in the clustering and database framework. Furthermore, we comment on computational aspects and software tools required for future applications.

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