Abstract
Maximum Pattern Matching with Gaps and the One-Off Condition(MPMGOOC) is an interesting and challenging pattern matching problem,which seeks to find the maximal number of occurrences of a pattern in a sequence.In this paper,a heuristic algorithm based on a new nonlinear data structure,Nettree,is proposed for this problem.A Nettree is different from a regular tree in that a node may have more than one parent.The algorithm is named Selecting Better Occurrence(SBO).SBO uses some special concepts and properties of the Nettree to solve the task.In the loop of finding an occurrence,SBO uses two strategies,Strategy of Greedy-Search Parent(SGSP) and Strategy of RightMost Parent(SRMP) to find two occurrences with the same leaf,and then selects a better occurrence from the results of SGSP and SRMP.The main ideas of SGSP and SRMP are to find an Approximately Optimal Parent(AOP) and the rightmost parent of the current node at each step in the process of searching for an occurrence,respectively.Extensive experimental results on real-world biological data demonstrate that SBO achieves the best performance among all competitive algorithms in terms of solution quality.This paper not only provides a heuristic solution for the MPMGOOC problem,but also shows that the Nettree can be used to solve other complex problems.
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