本頁只刊出中文翻譯與中文說明；英文原文請見下方原文連結。
原文連結
論文資訊
- 類型：已發表論文
- 日期：2011
摘要
Many real-world 網絡s tend to be very dense. Particular examples of interest arise in the construction of 網絡s that represent pairwise similarities between objects. In these cases, the 網絡s under consideration are weighted, generally with positive weights between any two nodes. Visualization and analysis of such 網絡s, especially when the number of nodes is large, can pose significant challenges which are often met by reducing the edge set. Any effective "sparsification" must retain and reflect the important structure in the 網絡. A common method is to simply apply a hard threshold, keeping only those edges whose weight exceeds some predetermined value. A more principled approach is to extract the multiscale "backbone" of a 網絡 by retaining 統計ly significant edges through hypothesis testing on a spe
※ 此為已發表論文，全文需透過期刊付費取得