作者
Danai Koutra, Hanghang Tong, David Lubensky
发表日期
2013/12/7
研讨会论文
2013 IEEE 13th international conference on data mining
页码范围
389-398
出版商
IEEE
简介
How can we find the virtual twin (i.e., the same or similar user) on Linked In for a user on Facebook? How can we effectively link an information network with a social network to support cross-network search? Graph alignment - the task of finding the node correspondences between two given graphs - is a fundamental building block in numerous application domains, such as social networks analysis, bioinformatics, chemistry, pattern recognition. In this work, we focus on aligning bipartite graphs, a problem which has been largely ignored by the extensive existing work on graph matching, despite the ubiquity of those graphs (e.g., users-groups network). We introduce a new optimization formulation and propose an effective and fast algorithm to solve it. We also propose a fast generalization of our approach to align unipartite graphs. The extensive experimental evaluations show that our method outperforms the state-of …
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学术搜索中的文章
D Koutra, H Tong, D Lubensky - 2013 IEEE 13th international conference on data …, 2013