| COMPUTER SCIENCE AND TECHNOLOGY |
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SimRank calculations for large temporal graphs |
| MIAO Zhuang, YUAN Ye, QIAO Baiyou, WANG Yishu, MA Yuliang, WANG Guoren |
| School of Computer Science and Engineering, Northeastern University, Shenyang 110819, China |
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Abstract Similarity calculations have many real life applications. The research on similarity calculations have mainly been focused on static graphs with many similarity calculation models based on SimRank. In real life, many systems, such as communication networks, are modeled by temporal graphs. However, the traditional SimRank algorithm cannot be implemented in temporal graphs. Therefore, this study analyzes the similarity calculation problem for large temporal graphs. A temporal-aware SimRank (TaSimRank) algorithm was developed to compute the node similarity through an efficient iterative method based on the topological structure and time constraints of the graph. An approximate algorithm is then used to implement the similarity calculations using a tree-based index built by a random walk and the Monte Carlo method. The algorithm balances the calculational time and efficiency. Tests on real temporal graphs demonstrate the effectiveness and extensibility of these approaches.
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| Keywords
temporal graph
similarity
random walk
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Issue Date: 13 December 2018
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2018,
Vol. 58
