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- W3199336422 abstract "Loose constraints have great effects on the study of message passing through social networks. This paper proposes a novel EEM-LC model who joints the pairwise loose constraints existing in social networks and the exemplar-based clustering model together, and also observes the application prospects of this model. Exemplar-based clustering model directly selects cluster centers from actual samples, so the structure and semantics of the comments on social networks would be preserved accordingly. Besides, EEM-LC unifies the two pairwise link constraints by one mathematical definition, and looses the restrictions of strong constraints. Moreover, on the basis of the Bayesian probability framework, EEM-LC implants loose pairwise constraints into its target function. That is to say, enhanced (alpha )-expansion move algorithm is capable of optimizing this new model. Experimental results based on several real-world data sets have shown very convincing performance of the proposed EEM-LC model." @default.
- W3199336422 created "2021-09-27" @default.
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- W3199336422 date "2021-01-01" @default.
- W3199336422 modified "2023-10-17" @default.
- W3199336422 title "An Exemplar-Based Clustering Model with Loose Constraints in Social Network" @default.
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- W3199336422 doi "https://doi.org/10.1007/978-3-030-82562-1_22" @default.
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