Zip： An Algorithm Based on Loser Tree for Common Contacts Searching in Large Graphs
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 e？ciency of the k-hop reachability between two vertices in a graph. However, searching...
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| Published in | Journal of computer science and technology Vol. 30; no. 4; pp. 799 - 809 |
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| Main Author | |
| Format | Journal Article |
| Language | English |
| Published |
New York
Springer US
01.07.2015
Springer Nature B.V |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1000-9000 1860-4749 |
| DOI | 10.1007/s11390-015-1561-y |
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| Summary: | 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 e？ciency 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 e？ciently 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 e？cient 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, the graph stratification algorithm）. |
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| Bibliography: | 11-2296/TP Hong Tang, Shuai Mu,Jin Huang ,Jia Zhu , Jian Chen, Rui Ding （1School of Information Science and Technology, Sun Yat-sen University, Guangzhou 510006, China; 2School of Software Engineering, South China University of Technology, Guangzhou 510006, China ;3School of Computer Science, South China Normal University, Guangzhou 510631, China） 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 e？ciency 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 e？ciently 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 e？cient 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, the graph stratification algorithm）. common contact, k-hop query, reachability, social network ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 |
| ISSN: | 1000-9000 1860-4749 |
| DOI: | 10.1007/s11390-015-1561-y |