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• W562550776 abstract "A common task in many domains with a temporal aspect involves identifying and tracking clusters over time. Often dynamic data will have a feature-based representation. In some cases, a direct mapping will exist for both objects and features over time. But in many scenarios, smaller subsets of objects or features alone will persist across successive time periods. To address this issue, we propose a dynamic spectral co-clustering method for simultaneously clustering objects and features over time, as represented by successive bipartite graphs. We evaluate the method on a benchmark text corpus and Web 2.0 bookmarking data." @default.
• W562550776 created "2016-06-24" @default.
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• W562550776 date "2010-09-24" @default.
• W562550776 modified "2023-09-28" @default.
• W562550776 title "Spectral co-clustering for dynamic bipartite graphs" @default.
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