SIAM Journal on Computing
Tree pattern matching and subset matching in deterministic O(n log3 n)-time
Proceedings of the tenth annual ACM-SIAM symposium on Discrete algorithms
A fast string searching algorithm
Communications of the ACM
Approximate subset matching with Don't Cares
SODA '01 Proceedings of the twelfth annual ACM-SIAM symposium on Discrete algorithms
Verifying candidate matches in sparse and wildcard matching
STOC '02 Proceedings of the thiry-fourth annual ACM symposium on Theory of computing
STRING-MATCHING AND OTHER PRODUCTS
STRING-MATCHING AND OTHER PRODUCTS
Simple deterministic wildcard matching
Information Processing Letters
Probabilistic Arithmetic Automata and Their Application to Pattern Matching Statistics
CPM '08 Proceedings of the 19th annual symposium on Combinatorial Pattern Matching
From coding theory to efficient pattern matching
SODA '09 Proceedings of the twentieth Annual ACM-SIAM Symposium on Discrete Algorithms
| Hi-index | 0.00 |
In the classical pattern matching problem, one is given a text and a pattern, both of which are sequences of letters, and is required to find all occurrences of the pattern in the text. We study two modifications of the classical problem, where each letter in the text and pattern is a set (Set Intersection Matching problem) or a sequence (Sequence Matching problem). Two "letters" are considered to be match if the intersection of the two corresponding sets is not empty, or if the two sequences have a common element in the same index. We show the first known non-trivial and efficient algorithms for these problems, for the case the maximum set/sequence size is small. The first, randomized, that takes $\Theta\left( 2^dn\ln n\log m\right)$ time, where d is the maximum set/sequence size, and can also fit, with slight modifications, for the case one is also interested in up to k mismatches. The second is deterministic and takes $\Theta\left( 4^{d}n\log m\right)$. The third algorithm, also deterministic, is able to count the number of matches at each index of the text in total running time $\Theta\left( \sum_{i=1}^{d} {|\Sigma| \choose i} n\log m \right)$.