【摘要】：對(duì)復(fù)雜網(wǎng)絡(luò)中節(jié)點(diǎn)的重要性進(jìn)行排序在理論和現(xiàn)實(shí)中都有著重要的意義。傳統(tǒng)K-shell分解方法有著排序結(jié)果分辨率不高的缺陷,針對(duì)這一問(wèn)題,提出了一種改進(jìn)的K-shell方法,通過(guò)利用K-shell分解過(guò)程中節(jié)點(diǎn)被刪除時(shí)的迭代層數(shù)來(lái)進(jìn)一步區(qū)分不同節(jié)點(diǎn)的重要性程度。在三類(lèi)不同的現(xiàn)實(shí)網(wǎng)絡(luò)中的實(shí)驗(yàn)表明,該方法能夠有效解決傳統(tǒng)方法的缺陷,在提高排序結(jié)果分辨率的同時(shí)有著較好的時(shí)間復(fù)雜度。
[Abstract]:Ranking the importance of nodes in complex networks is of great significance both in theory and in practice. The traditional K-shell decomposition method has the defect of low resolution of sorting result. In order to solve this problem, an improved K-shell method is proposed. By using the number of iterative layers when nodes are deleted during K-shell decomposition, the importance of different nodes is further distinguished. Experiments in three different real networks show that the proposed method can effectively solve the shortcomings of traditional methods and has better time complexity while improving the resolution of sorting results.
【作者單位】： 國(guó)家數(shù)字交換系統(tǒng)工程技術(shù)研究中心;
【基金】：國(guó)家自然科學(xué)基金資助項(xiàng)目(61171108) 國(guó)家“973”計(jì)劃資助項(xiàng)目(2012CB315901,2012CB315905) 國(guó)家科技支撐計(jì)劃資助項(xiàng)目(2014BAH30B01)
【分類(lèi)號(hào)】：O157.5
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本文編號(hào)：2137852