Abstract
A variable-length-don’t-care pattern (VLDC pattern) is an element of set Π = (∑∪{⋆})*, where ∑ is an alphabet and ⋆ is a wildcard matching any string in ∑*. Given two sets of strings, we consider the problem of finding the VLDC pattern that is the most common to one, and the least common to the other. We present a practical algorithm to find such best VLDC patterns exactly, powerfully sped up by pruning heuristics. We introduce two versions of our algorithm: one employs a pattern matching machine (PMM) whereas the other does an index structure called the Wildcard Directed Acyclic Word Graph (WDAWG). In addition, we consider a more generalized problem of finding the best pair <q,k>, where k is the window size that specifies the length of an occurrence of the VLDC pattern q matching a string ω. We present three algorithms solving this problem with pruning heuristics, using the dynamic programming (DP), PMMs and WDAWGs, respectively. Although the two problems are NP-hard, we experimentally show that our algorithms run remarkably fast.
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Inenaga, S., Bannai, H., Shinohara, A., Takeda, M., Arikawa, S. (2002). Discovering Best Variable-Length-Don’t-Care Patterns. In: Lange, S., Satoh, K., Smith, C.H. (eds) Discovery Science. DS 2002. Lecture Notes in Computer Science, vol 2534. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36182-0_10
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DOI: https://doi.org/10.1007/3-540-36182-0_10
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