›› 2015, Vol. 30 ›› Issue (4): 799-809.doi: 10.1007/s11390-015-1561-y

Special Issue: Data Management and Data Mining

• Special Section on Data Management and Data Mining • Previous Articles     Next Articles

Zip: An Algorithm Based on Loser Tree for Common Contacts Searching in Large Graphs

Hong Tang1(唐宏), Shuai Mu2(牟帅), Jin Huang3(黄晋), Member, CCF, Jia Zhu3*(朱佳), Member, CCF, Jian Chen2(陈健), Member, CCF, ACM, IEEE, Rui Ding3(丁蕊), Member, CCF, ACM   

  1. 1. School of Information Science and Technology, Sun Yat-sen University, Guangzhou 510006, China;
    2. School of Software Engineering, South China University of Technology, Guangzhou 510006, China;
    3. School of Computer Science, South China Normal University, Guangzhou 510631, China
  • Received:2015-02-01 Revised:2015-05-24 Online:2015-07-05 Published:2015-07-05
  • Contact: Jia Zhu is currently an associate professor in the School of Computer Science at South China Normal University, Guangzhou,after finishing his postdoctoral research at United Nations University, Tokyo. E-mail:jzhu@m.scnu.edu.cn
  • About author:Hong Tang is a Ph.D. candidate in Sun Yat-sen University, Guangzhou. He received his B.S. and M.S. degrees from Huazhong University of Science and Technology, Wuhan, in 1997, and Jinan University, Guangzhou, in 2006, respectively. His research interests include cloud computing and large scale data mining.
  • Supported by:

    This work was supported by the Youth Teacher Startup Fund of South China Normal University of China under Grant No. 14KJ18 and the National High Technology Research and Development 863 Program of China under Grant No. 2013AA01A212.

The problem of k-hop reachability between two vertices in a graph has received considerable attention in recent years. A substantial number of algorithms have been proposed with the goal of improving the searching efficiency of the k-hop reachability between two vertices in a graph. However, searching and traversing are challenging tasks, especially in large-scale graphs. Furthermore, the existing algorithms propounded by different scholars are not satisfactory in terms of feasibility and scalability when applied to different kinds of graphs. In this work we propose a new algorithm, called Zip, in an attempt to efficiently determine the common contacts between any two random vertices in a large-scale graph. First, we describe a novel algorithm for constructing the graph index via binary searching which maintains the adjacent list of each vertex in order. Second, we present the ways to achieve a sequential k-hop contact set by using the loser tree, a merge sorting algorithm. Finally, we develop an efficient algorithm for querying common contacts and an optimized strategy for k-hop contact set serialization. Experimental results on synthetic and real datasets show that the proposed Zip algorithm outperforms existing state-of-the-art algorithms (e.g., breadth-first Searching, GRAIL, Graph Stratification algorithm).

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