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- W2054930101 abstract "In this paper, we present a document clustering framework incorporating instance-level knowledge in the form of pairwise constraints and attribute-level knowledge in the form of keyphrases. Firstly, we initialize weights based on metric learning with pairwise constraints, then simultaneously learn two kinds of knowledge by combining the distance-based and the constraint-based approaches, finally evaluate and select clustering result based on the degree of users? satisfaction. The experimental results demonstrate the effectiveness and potential of the proposed method." @default.
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- W2054930101 date "2011-01-01" @default.
- W2054930101 modified "2023-10-16" @default.
- W2054930101 title "Integrating instance-level and attribute-level knowledge into document clustering" @default.
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- W2054930101 doi "https://doi.org/10.2298/csis100906003w" @default.
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