Topic
Approximate string matching
About: Approximate string matching is a research topic. Over the lifetime, 1903 publications have been published within this topic receiving 62352 citations. The topic is also known as: fuzzy string-searching algorithm & fuzzy string-matching algorithm.
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TL;DR: By introducing a concept of String Matching Points (SMP) in string comparison, string matching accuracy and efficiency are improved, compared with other commonly-applied field matching algorithms.
Abstract: Redundant or duplicate data are the most troublesome problem in database management and applications. Approximate field matching is the key solution to resolve the problem by identifying semantically equivalent string values in syntactically different representations. This paper considers token-based solutions and proposes a general field matching framework to generalize the field matching problem in different domains. By introducing a concept of String Matching Points (SMP) in string comparison, string matching accuracy and efficiency are improved, compared with other commonly-applied field matching algorithms. The paper discusses the development of field matching algorithms from the developed general framework. The framework and corresponding algorithm are tested on a public data set of the NASA publication abstract database. The approach can be applied to address the similar problems in other databases.
6 citations
TL;DR: Wavelet-type discrete transforms for signal analysis on strings of finite length are used for edge and hidden Markov process detection and new approaches for string matching and for measures of the diversity of chaotic strings are presented.
Abstract: We use wavelet-type discrete transforms for signal analysis on strings of finite length. We apply these transforms for edge and hidden Markov process detection. We also present new approaches for string matching and for measures of the diversity of chaotic strings.
6 citations
Journal Article•
6 citations
TL;DR: An improved version of IndelMYE that makes a better use of the bit-operations and runs 24.5 percent faster in practice and presents a complete set of experimental results to support the findings.
Abstract: The task of approximate string matching is to find all locations at which a pattern string p of length m matches a substring of a text string t of length n with at most k differences. It is common to use Levenshtein distance [5], which allows the differences to be single-character insertions, deletions, substitutions. Recently, in [3], the IndelMYE, IndelWM and IndelBYN algorithms where introduced as modified version of the bit-parallel algorithms of Myers [6], Wu&Manber [10] and Baeza-Yates&Navarro [1], respectively. These modified versions where made to support the indel distance (only single-character insertions and/or deletions are allowed). In this paper we present an improved version of IndelMYE that makes a better use of the bit-operations and runs 24.5 percent faster in practice. In the end we present a complete set of experimental results to support our findings.
6 citations