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原文連結
論文資訊
- 類型：已發表論文
- 日期：2010
摘要
Change is a fundamental ingredient of interaction patterns in biology, technology, the economy, and science itself: Interactions within and between organisms change; ransportation patterns by air, land, and sea all change; the global financial flow changes; and the frontiers of scientific research change. 網絡s and clustering methods have become important tools to comprehend instances of these large-scale structures, but without methods to distinguish between real trends and noisy data, these approaches are not useful for studying how 網絡s change. Only if we can assign significance to the partitioning of single 網絡s can we distinguish meaningful structural changes from random fluctuations. Here we show that bootstrap resampling accompanied by significance clustering provides a solution to this
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