Pattern matching with wildcards and gap-length constraints based on a centrality-degree graph

  • Authors:

  • Dan Guo;Xuegang Hu;Fei Xie;Xindong Wu

  • Affiliations:

  • College of Computer Science and Information Engineering, Hefei University of Technology, Hefei, China 230009;College of Computer Science and Information Engineering, Hefei University of Technology, Hefei, China 230009;College of Computer Science and Information Engineering, Hefei University of Technology, Hefei, China 230009 and Department of Computer Science and Technology, Hefei Normal University, Hefei, Chin ...;College of Computer Science and Information Engineering, Hefei University of Technology, Hefei, China 230009 and Department of Computer Science, University of Vermont, Burlington, USA

  • Venue:
  • Applied Intelligence
  • Year:
  • 2013

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Abstract

Pattern matching with wildcards is a challenging topic in many domains, such as bioinformatics and information retrieval. This paper focuses on the problem with gap-length constraints and the one-off condition (The one-off condition means that each character can be used at most once in all occurrences of a pattern in the sequence). It is difficult to achieve the optimal solution. We propose a graph structure WON-Net (WON-Net is a graph structure. It stands for a network with the weighted centralization measure based on each node's centrality-degree. Its details are given in Definition 4.1) to obtain all candidate matching solutions and then design the WOW (WOW stands for pattern matching with wildcards based on WON-Net) algorithm with the weighted centralization measure based on nodes' centrality-degrees. We also propose an adjustment mechanism to balance the optimal solutions and the running time. We also define a new variant of WOW as WOW-驴. Theoretical analysis and experiments demonstrate that WOW and WOW-驴 are more effective than their peers. Besides, the algorithms demonstrate an advantage on running time by parallel processing.