JOURNAL ARTICLE

Survey of Automatic Spelling Correction

Daniel HládekJán StašMatúš Pleva

Year: 2020 Journal:   Electronics Vol: 9 (10)Pages: 1670-1670   Publisher: Multidisciplinary Digital Publishing Institute

Abstract

Automatic spelling correction has been receiving sustained research attention. Although each article contains a brief introduction to the topic, there is a lack of work that would summarize the theoretical framework and provide an overview of the approaches developed so far. Our survey selected papers about spelling correction indexed in Scopus and Web of Science from 1991 to 2019. The first group uses a set of rules designed in advance. The second group uses an additional model of context. The third group of automatic spelling correction systems in the survey can adapt its model to the given problem. The summary tables show the application area, language, string metrics, and context model for each system. The survey describes selected approaches in a common theoretical framework based on Shannon’s noisy channel. A separate section describes evaluation methods and benchmarks.

Keywords:
Spelling Computer science Context (archaeology) Set (abstract data type) Natural language processing Artificial intelligence Scopus Information retrieval String (physics) Linguistics Programming language Mathematics

Metrics

86
Cited By
7.78
FWCI (Field Weighted Citation Impact)
170
Refs
0.98
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Natural Language Processing Techniques
Physical Sciences →  Computer Science →  Artificial Intelligence
Topic Modeling
Physical Sciences →  Computer Science →  Artificial Intelligence
Handwritten Text Recognition Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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