Complete inverted files for efficient text retrieval and analysis
Journal of the ACM (JACM)
Fast text searching: allowing errors
Communications of the ACM
A fast string searching algorithm
Communications of the ACM
Efficient string matching: an aid to bibliographic search
Communications of the ACM
Flexible pattern matching in strings: practical on-line search algorithms for texts and biological sequences
A String Matching Algorithm Fast on the Average
Proceedings of the 6th Colloquium, on Automata, Languages and Programming
Efficient Experimental String Matching by Weak Factor Recognition
CPM '01 Proceedings of the 12th Annual Symposium on Combinatorial Pattern Matching
Average complexity of exact and approximate multiple string matching
Theoretical Computer Science
Multipattern string matching with q-grams
Journal of Experimental Algorithmics (JEA)
An aggressive algorithm for multiple string matching
Information Processing Letters
Revisiting multiple pattern matching algorithms for multi-core architecture
Journal of Computer Science and Technology - Special issue on Community Analysis and Information Recommendation
Exact online two-dimensional pattern matching using multiple pattern matching algorithms
Journal of Experimental Algorithmics (JEA)
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Filtering plays an important role in the Internet security and information retrieval fields, and usually employs multiple-strings matching algorithm as its key part. All the classical matching algorithms, however, perform badly when the number of the keywords exceeds a critical point, which made large scale multiple-strings matching problem a great challenge. Based on the observation that the speed of the classical algorithms depends mainly on the length of the shortest keyword, a partition strategy was proposed to decompose the keywords set into a series of subsets on which the classical algorithms was performed. For the optimal partition, it was proved that the keywords with same length locate in one subset, and length of keywords in different subsets would not interlace each other. In this paper, we proposed a shortest-path model for the optimal partition finding problem. Experiments on both random and real data demonstrate that our algorithms generally has about a 100-300% speed-up compared with the classical ones.