Correction to "Recognition of Noisy Subsequences Using Constrained Edit Distances"
IEEE Transactions on Pattern Analysis and Machine Intelligence
A noisy clock-controlled shift register cryptanalysis concept based on sequence comparison approach
EUROCRYPT '90 Proceedings of the workshop on the theory and application of cryptographic techniques on Advances in cryptology
The Normalized String Editing Problem Revisited
IEEE Transactions on Pattern Analysis and Machine Intelligence
Numerical Similarity and Dissimilarity Measures Between Two Trees
IEEE Transactions on Computers
Twenty Years of Document Image Analysis in PAMI
IEEE Transactions on Pattern Analysis and Machine Intelligence
On the Pattern Recognition of Noisy Subsequence Trees
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Normalized Levenshtein Distance Metric
IEEE Transactions on Pattern Analysis and Machine Intelligence
Application of q-Gram Distance in Digital Forensic Search
IWCF '08 Proceedings of the 2nd international workshop on Computational Forensics
Fuzzy automata with ε-moves compute fuzzy measures between strings
Fuzzy Sets and Systems
| Hi-index | 0.15 |
Let X* be any unknown word from a finite dictionary H. Let U be any arbitrary subsequence of X*. We consider the problem of estimating X* by processing Y, which is a noisy version of U. We do this by defining the constrained edit distance between XH and Y subject to any arbitrary edit constraint involving the number and type of edit operations to be performed. An algorithm to compute this constrained edit distance has been presented. Although in general the algorithm has a cubic time complexity, within the framework of our solution the algorithm possesses a quadratic time complexity. Recognition using the constrained edit distance as a criterion demonstrates remarkable accuracy. Experimental results which involve strings of lengths between 40 and 80 and which contain an average of 26.547 errors per string demonstrate that the scheme has about 99.5 percent accuracy.