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Erschienen in:
2013 | OriginalPaper | Buchkapitel
A Constraint Acquisition Method for Data Clustering
verfasst von : João M. M. Duarte, Ana L. N. Fred, Fernando Jorge F. Duarte
Erschienen in: Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
Verlag: Springer Berlin Heidelberg
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A new constraint acquisition method for parwise-constrained data clustering based on user-feedback is proposed. The method searches for non-redundant intra-cluster and inter-cluster query-candidates, ranks the candidates by decreasing order of interest and, finally, prompts the user the most relevant query-candidates. A comparison between using the original data representation and using a learned representation (obtained from the combination of the pairwise constraints and the original data representation) is also performed. Experimental results shown that the proposed constraint acquisition method and the data representation learning methodology lead to clustering performance improvements.