کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
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430980 | 688239 | 2007 | 13 صفحه PDF | دانلود رایگان |
Indexing methods for the approximate string matching problem spend a considerable effort generating condensed neighborhoods. Condensed neighborhoods, however, are not a minimal representation of a pattern neighborhood. Super condensed neighborhoods, proposed in this work, are smaller, provably minimal and can be used to locate approximate matches that can later be extended by on-line search. We present an algorithm for generating Super Condensed Neighborhoods. The algorithm can be implemented either by using dynamic programming or non-deterministic automata. The time complexity is O(ms)O(ms) for the first case and O(kms)O(kms) for the second, where m is the pattern size, s is the size of the super condensed neighborhood and k the number of errors. Previous algorithms depended on the size of the condensed neighborhood instead. These algorithms can be implemented using Bit-Parallelism and Increased Bit-Parallelism techniques. Our experimental results show that the resulting algorithms are fast and achieve significant speedups, when compared with the existing proposals that use condensed neighborhoods.
Journal: Journal of Discrete Algorithms - Volume 5, Issue 3, September 2007, Pages 501–513