Murty, MN and Jain, AK (1996) Knowledge-based clustering. In: International Conference on Ordinal and Symbolic Data Analysis (OSDA 95), JUN 20-23, 1995, PARIS, FRANCE.Full text not available from this repository.
In the knowledge-based clustering approaches reported in the literature, explicit know ledge, typically in the form of a set of concepts, is used in computing similarity or conceptual cohesiveness between objects and in grouping them. We propose a knowledge-based clustering approach in which the domain knowledge is also used in the pattern representation phase of clustering. We argue that such a knowledge-based pattern representation scheme reduces the complexity of similarity computation and grouping phases. We present a knowledge-based clustering algorithm for grouping hooks in a library.
|Item Type:||Conference Paper|
|Additional Information:||Copyright of this article belongs to Springer verlag berlin.|
|Department/Centre:||Division of Electrical Sciences > Computer Science & Automation (Formerly, School of Automation)|
|Date Deposited:||29 Apr 2011 07:24|
|Last Modified:||29 Apr 2011 07:24|
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