Showing papers on "Approximate string matching published in 1982"
TL;DR: It is shown that the Boyel-Moore algorithm is extremely efficient in most cases and that, contrary to the impression one might get from the analytical results, the Knuth-Morris-Pratt algorithm is not significantly better on the average than the straightforward algorithm.
Abstract: Three string matching algorithms—straightforward, Knuth-Morris-Pratt and Boyer-Moor—re examined and their time complexities discussed. A comparison of their actual average behaviour is made, based on empirical data presented. It is shown that the Boyel-Moore algorithm is extremely efficient in most cases and that, contrary to the impression one might get from the analytical results, the Knuth-Morris-Pratt algorithm is not significantly better on the average than the straightforward algorithm.
43 citations
06 Apr 1982
TL;DR: In programming systems it can be a built-in language facility as string matching in SNOBOL4 or a language extension for matching of list structures as in INTERLISP.
Abstract: Pattern matching is a technique which is used in many application areas such as text manipulation in editors, manipulation of arithmetic formulas in computer algebra systems and in artificial intelligence applications. In programming systems it can be a built-in language facility as string matching in SNOBOL4 or a language extension for matching of list structures as in INTERLISP.
8 citations
01 May 1982
TL;DR: It is shown that one of the key problems in Image Understanding is the matching of two symbolic structures, a model and the result of a segmentation and a formalism is presented which can deal with the inexact or fuzzy matching of such structures in a highly parallel fashion.
Abstract: We show that one of the key problems in Image Understanding is the matching of two symbolic structures, a model and the result of a segmentation. These symbolic structures are conveniently represented as labeled graphs and we present on two examples a formalism which can deal with the inexact or fuzzy matching of such structures in a highly parallel fashion.
4 citations
01 Jan 1982
TL;DR: The paper presents the calculation of a subdistance matrix omitting serious constraints required by other algorithms and discusses a threshold method of approximate string matching, which frequently allows omitting the calculations of most of the sub distance matrix without decrease in recall and precision.
Abstract: A threshold method of approximate string matching is discussed. It is applied to problems which require both high precision and recall, such as patient identification retrieval and automated error correction. The paper presents the calculation of a subdistance matrix omitting serious constraints required by other algorithms. In addition, strings are grouped into subsets of strings of equal lengths, stored in a special tree structure. Furthermore, a threshold frequently allows omitting the calculation of most of the subdistance matrix without decrease in recall and precision. Some practical results are presented and discussed.
2 citations
TL;DR: A pattern matching system which has been implemented as a set of library procedures that provides a concise and consistent method of pattern definition and facilities for defining context sensitive pattern matching, defining repetitive patterns and defining alternatives.
Abstract: This paper describes a pattern matching system which has been implemented as a set of library procedures. The system provides a concise and consistent method of pattern definition and facilities for defining context sensitive pattern matching, defining repetitive patterns and defining alternatives. The operations available to the user allow him to identify if a substring matches a pattern, to extract that substring, to replace that substring and to associate a name with that substring. The system has applications in information retrieval, text manipulation and language processing.
2 citations