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String (computer science)

About: String (computer science) is a research topic. Over the lifetime, 19430 publications have been published within this topic receiving 333247 citations. The topic is also known as: str & s.


Papers
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01 Jan 2005
TL;DR: Variations of string comparators based on the Jaro-Winkler comparator and edit distance comparator are compared to Census data to see which are better classifiers for matches and nonmatches.
Abstract: We compare variations of string comparators based on the Jaro-Winkler comparator and edit distance comparator. We apply the comparators to Census data to see which are better classifiers for matches and nonmatches, first by comparing their classification abilities using a ROC curve based analysis, then by considering a direct comparison between two candidate comparators in record linkage results.

70 citations

Book ChapterDOI
01 Aug 2015
TL;DR: Quantomatic as discussed by the authors is a tool that supports the (semi-)automatic construction of equational proofs using string diagrams, which have applications in many areas including categorical algebra, programming language semantics, representation theory, algebraic quantum information, and quantum groups.
Abstract: Monoidal algebraic structures consist of operations that can have multiple outputs as well as multiple inputs, which have applications in many areas including categorical algebra, programming language semantics, representation theory, algebraic quantum information, and quantum groups. String diagrams provide a convenient graphical syntax for reasoning formally about such structures, while avoiding many of the technical challenges of a term-based approach. Quantomatic is a tool that supports the (semi-)automatic construction of equational proofs using string diagrams. We briefly outline the theoretical basis of Quantomatic’s rewriting engine, then give an overview of the core features and architecture and give a simple example project that computes normal forms for commutative bialgebras.

70 citations

Patent
27 Feb 2008
TL;DR: In this paper, the authors describe a transaction processing process that involves processing access transaction application data for selective authorization of the transaction, where the received data comprises data from an access transaction data string that includes a transit verification value.
Abstract: Transaction processing involves receiving data from an access transaction application of a portable consumer device, wherein the received data comprises data from an access transaction data string that includes a transit verification value wherein, with the exception of the transit verification value, the access transaction data string is substantially similar to a retail data string comprising retail data, wherein the access application data string is adapted for use with an access transaction processing system and the retail data string is adapted for use with a retail processing system. The transaction processing involves processing access transaction application data for selective authorization of the transaction.

70 citations

Journal ArticleDOI
TL;DR: There do not exist pattern matching algorithms whose worst-case behavior is “sublinear” in n (that is, linear with constant less than one), in contrast with the situation for average behavior (the Boyer-Moore algorithm is known to be sublinear on the average).
Abstract: Any algorithm for finding a pattern of length k in a string of length n must examine at least $n - k + 1$ of the characters of the string in the worst case. By considering the pattern $00 \cdots 0$, we prove that this is the best possible result. Therefore there do not exist pattern matching algorithms whose worst-case behavior is “sublinear” in n (that is, linear with constant less than one), in contrast with the situation for average behavior (the Boyer-Moore algorithm is known to be sublinear on the average).

70 citations

Proceedings ArticleDOI
20 Apr 2009
TL;DR: This paper exploits web search engines in order to define new similarity functions and develops efficient techniques to facilitate approximate matching in the context of these proposed similarity functions.
Abstract: Tasks recognizing named entities such as products, people names, or locations from documents have recently received significant attention in the literature. Many solutions to these tasks assume the existence of reference entity tables. An important challenge that needs to be addressed in the entity extraction task is that of ascertaining whether or not a candidate string approximately matches with a named entity in a given reference table.Prior approaches have relied on string-based similarity which only compare a candidate string and an entity it matches with. In this paper, we exploit web search engines in order to define new similarity functions. We then develop efficient techniques to facilitate approximate matching in the context of our proposed similarity functions. In an extensive experimental evaluation, we demonstrate the accuracy and efficiency of our techniques.

70 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20222
2021491
2020704
2019759
2018816
2017806