Showing papers on "Edit distance published in 1990"
TL;DR: This work presents an algorithm for finding a shortest edit distance of A and B whose worst-case running time is O( NP ) and whose expected running time was O( N + PD ).
124 citations
TL;DR: A comparison of inductive inference known as minimum message length encoding is applied to string comparison in molecular biology and the posterior odds-ratio of two string alignments or of two models of string mutation to be computed.
33 citations
TL;DR: Two new string matching heuristics are presented which reduce the hardware requirement and improve the computation speed of the systolic string matcher due to Lipton and Lopresti.
Abstract: Two new string matching heuristics are presented which reduce the hardware requirement and improve the computation speed of the systolic string matcher due to Lipton and Lopresti (see 1st International Workshop on Systolic Arrays, Oxford, p.181-91, Adam-Hilger, 1987). The new array requires A=m/2+n/2-1 basic cells, T=m/2+n/2-1+max (m,n) steps to match strings of size n and m, respectively, and has efficiency e=1 (100%). A measure of the heuristic effectiveness compared with the minimum edit distance is also given.
9 citations
TL;DR: The instructional value of text markup is considered and how to extract markup information from the matrix normally generated in the calculation of edit distance is shown.
Abstract: Instructional systems that accept text responses entered by the learner must be capable of dealing with the inevitable occurrence of misspellings. A widely known procedure which finds the edit distance between two strings, and has been found effective in recognizing misspellings, can be easily extended to also annotate the response to give the learner feedback on the precise nature of the error. This paper considers the instructional value of text markup and shows how to extract markup information from the matrix normally generated in the calculation of edit distance. Included is a listing of a short Pascal program that illustrates the main concepts discussed.
5 citations
TL;DR: An algorithm is introduced that encodes pairs of strings as binary numbers such that the Hamming distance between the binary codewords is equal to the Levenshtein Distance between the original strings.
4 citations
TL;DR: An extension is proposed which attends to word boundaries and thereby recommends corrections that appear more reasonable to users, and a much faster but nonadmissible version of other applications is presented, thereby bringing the technique within range of current microcomputers.
Abstract: In some instructional situations, such as foreign language dictation, the degree of correctness of a student's text response can be determined without reference to grammar and semantics by comparison with a target string provided by a course author. The standard sequence comparison procedure, which assesses the distance between two strings in terms of edit costs, makes demands on machine time proportional to the product of the string lengths. This characteristic renders it impractical for real-time correction of multi-word responses on current instructional computer systems. We present a much faster but nonadmissible version of other applications, thereby bringing the technique within range of current microcomputers. The usual method for generating markup for single word responses does not generalize well to multi-word responses because it fails to recognize word boundaries, and will sometimes suggest edits that seem unnatural to users. We propose an extension which attends to word boundaries and thereby recommends corrections that appear more reasonable.
4 citations