图的相似性:核与邻近测度
Similarities on Graphs: Kernels versus Proximity Measures
摘要:
我们分析研究的各种内核和相似性措施图的接近和距离属性。这有助于理解这些措施的数学性质,并可能是有用的,建议采用特定的相似性措施,在数据分析。
英文摘要:
We analytically study proximity and distance properties of various kernels and similarity measures on graphs. This helps to understand the mathematical nature of such measures and can potentially be useful for recommending the adoption of specific similarity measures in data analysis.
机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。