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An Effective Semi-Supervised Clustering Framework Integrating Pairwise Constraints and Attribute Preferences

In: Computing and Informatics, vol. 31, no. 3
J.l. Wang - S.y. Wu - C. Wen - G. Li
Detaily:
Rok, strany: 2012, 597 - 612
Kľúčové slová:
Semi-supervised clustering, pairwise, attribute preference
O článku:
Both the instance level knowledge and the attribute level knowledge can improve clustering quality, but how to effectively utilize both of them is an essential problem to solve. This paper proposes a wrapper framework for semi-supervised clustering, which aims to gracely integrate both kinds of priori knowledge in the clustering process, the instance level knowledge in the form of pairwise constraints and the attribute level knowledge in the form of attribute order preferences. The wrapped algorithm is then designed as a semi-supervised clustering process which transforms this clustering problem into an optimization problem. The experimental results demonstrate the effectiveness and potential of proposed method.
Ako citovať:
ISO 690:
Wang, J., Wu, S., Wen, C., Li, G. 2012. An Effective Semi-Supervised Clustering Framework Integrating Pairwise Constraints and Attribute Preferences. In Computing and Informatics, vol. 31, no.3, pp. 597-612. 1335-9150.

APA:
Wang, J., Wu, S., Wen, C., Li, G. (2012). An Effective Semi-Supervised Clustering Framework Integrating Pairwise Constraints and Attribute Preferences. Computing and Informatics, 31(3), 597-612. 1335-9150.