Efficient string matching with wildcards and length constraints

Research on Pattern Matching with Wildcards and Length Constraints: Methods and Completeness

“…Fischer and Paterson were the first to generalized pattern matching with wildcards (Fischer & Paterson, 1974): given a pattern P and a text T, either of which may contain wildcards, denoted by ¢, the goal is to locate all P's occurrences in T. ¢ can match any letter in a given alphabet, such as a¢¢c¢t. Unlike previous work, Chen, et al proposed a PMWL problem integrating two problems (Chen et al, 2006): one is complex local constraints which means the user can specify a different range of wildcards between each two consecutive letters of P, for example, a¢ [0,3]c¢ [1,3]t. Another one is global length constraints.…”

“…On one hand, this definition of pattern is more suitable for areas such as bioinformatics; on the other hand, the size of the matching candidate positions is in the exponential increment which greatly increases the complexity of the problem solving. From a view of practical point, they also proposed two issues: with and without the one-off condition (Chen et al, 2006;Min et al, 2009). In their problem definition, users have more flexibility to search on sequences and the one-off condition has both theoretical and practical significance.…”

“…Since it is difficult to develop a complete matching strategy in this problem, almost existed algorithms for PMWL are using greedy matching strategies, which is the root reason why matching algorithm is not complete. This article will focus on SAIL algorithm (Chen et al, 2006) which is a representative algorithm for PMWL problem and will also describe RSAIL (Wang et al, 2010), SBO ), BPBM (Guo et al, 2011 algorithm which are all designed to solve PMWL problem in different conditions. The each of above algorithms has its own characteristics in the data structures and matching strategies, which will be analyzed in this paper.…”

“…This problem was so-called exact string matching with variable-length don't cares. Chen et al sum up all these definitions into three conditions (Chen et al, 2006): firstly, there is a wildcard between two consecutive letters in P, for example A¢[0,1]T¢[0,2]G¢[1,3]C; secondly, every letter in T can only be used once for matching; thirdly, there is a global constraint to limit the matching occurrence length. We call the problem satisfying above definition PMWL problem, which has been used in approximate matching, pattern mining, information retrieval, etc.…”

“…Mining such typical user mode, which is obviously a pattern matching with wildcards, will has a great influence on the market. (Chen et al, 2006). 1.…”