The stringdist Package for Approximate String Matching

By Mark P. J. van der Loo. The R Journal, 2014

440 citations recorded by the source corpus.

Comparing text strings in terms of distance functions is a common and fundamental task in many statistical text-processing applications. Thus far, string distance functionality has been somewhat scattered around R and its extension packages, leaving users with inconistent interfaces and encoding handling. The stringdist package was designed to offer a low-level interface to several popular string distance algorithms which have been re-implemented in C for this purpose. The package offers distances based on counting q -grams, edit-based distances, and some lesser known heuristic distance functions. Based on this functionality, the package also offers inexact matching equivalents of R’s native exact matching functions match and %in% .

Subfields: Artificial Intelligence, Hardware and Architecture, Information Systems

View Paper: https://www.semanticscholar.org/paper/6541e66a37350fc9460daa08c9bbf05490286828

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Caroline Chin
2. B. Seegmiller
3. David H. Autor
4. A. Salomons

In Hardware and Architecture

1. Caroline Chin
2. B. Seegmiller
3. David H. Autor
4. A. Salomons

In Information Systems

1. Caroline Chin
2. B. Seegmiller
3. David H. Autor
4. A. Salomons

Citations in the corpus

• New Frontiers: The Origins and Content of New Work, 1940–2018 (2022, methodology): “We use a fuzzy-matching Jaro-Winkler algorithm which matches based on letter-swaps, implemented in R as the package stringdist (van der Loo, 2014).”