Knowledge discovery in molecular databases
Darrell Conklin, S. Fortier, Janice Glasgow · IEEE Transactions on Knowledge and Data Engineering · 1993
An approach to knowledge discovery in complex molecular databases is described. The machine learning paradigm used is structured concept formation, in which object's described in terms of components and their interrelationships are clustered and organized in a knowledge base. Symbolic images are used to represent classes of structured objects. A discovered molecular knowledge base is successfully used in the interpretation of a high resolution electron density map.>