Approaches to Conceptual Clustering.
Interim rept. Jan-Jun 85,
CALIFORNIA UNIV IRVINE DEPT OF INFORMATION AND COMPUTER SCIENCE
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Methods for Conceptual Clustering may be explicated in two lights. Conceptual Clustering methods may be viewed as extensions to techniques of numerical taxonomy, a collection of methods developed by social and natural scientists for creating classification schemes over object sets. Alternatively, conceptual clustering may be viewed as a form of learning by observation or concept formation, as opposed to methods of learning from examples or concept identification. This paper surveys and compares a number of conceptual clustering methods along dimensions suggested by each of these views. The point the authors most wish to clarify is that conceptual clustering processes can be explicated as being composed of three distinct but inter-dependent subprocesses the process of deriving a hierarchical classification scheme the process of aggregating objects into individual classes and the process of aggregating objects into individual classes and the process of assigning conceptual descriptions to object classes. Each subprocess may be characterized along a number of dimensions related to search, thus facilitating a better understanding of the conceptual clustering process as a whole. Additional keywords Data processing Algorithms Input output processing. Author