Two Phase Semi-Supervised Clustering Using Background Knowledge

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Provided by: Springer Healthcare
Topic: Big Data
Format: PDF
Using background knowledge in clustering, called semi-clustering, is one of the actively researched areas in data mining. In this paper, the authors illustrate how to use background knowledge related to a domain more efficiently. For a given data, the number of classes is investigated by using the must-link constraints before clustering and these must-link data are assigned to the corresponding classes. When the clustering algorithm is applied, they make use of the cannot-link constraints for assignment.
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