Learning an Integrated Distance Metric for Comparing Structure of Complex Networks
نویسندگان
چکیده
Graph comparison plays a major role in many network applications. We often need a similarity metric for comparing networks according to their structural properties. Various network features – such as degree distribution and clustering coefficient – provide measurements for comparing networks from different points of view, but a global and integrated distance metric is still miss-
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ورودعنوان ژورنال:
- CoRR
دوره abs/1307.3626 شماره
صفحات -
تاریخ انتشار 2013