Add to ORKGThis article focuses on the evaluation of a novel algorithm for the detection of context-sensitive spelling errors. We present a fully automatic evaluation procedure with no requirements of manual work or resources annotated with spelling errors. The evaluation method is applicable to any language and tag set, and is easily adaptable to other NLP systems such as taggers and parsers. 1
For an advanced implementation of spelling correction via machine learning, a multi-level featurebas...
We propose a deep graphical model for the correction of isolated spelling errors in text. The model ...
This paper presents a comparative study of spelling errors that are corrected as you type, vs. those...
Context-sensitive spelling errors are those errors resulting from mistyping or mispronouncing a word...
We present TISC, a language-independent and context-sensitive spelling checking and correction syste...
We present two algorithms for automatically improving the quality of texts which contain a large num...
In computing, spell checking is the process of detecting and sometimes providing spelling suggestion...
Spelling checkers, frequently used nowadays, do not allow to correct real-word errors. Thus, the err...
In this thesis we did research on context-based spellchecking approaches for the Dutch language. Con...
A large class of machine-learning problems in natural language require the characterization of lingu...
Abstract. A large class of machine-learning problems in natural language require the characterizatio...
A context-based spelling error is a spelling or typing error that turns an intended word into anothe...
We present TISC, a multilingual, language-independent and context-sensitive spelling checking and co...
AbstractAutomatic spell checker systems aim to verify and correct erroneous words through a suggeste...
Nowadays, a large amount of documents is generated daily. These documents may contain some spelling ...
For an advanced implementation of spelling correction via machine learning, a multi-level featurebas...
We propose a deep graphical model for the correction of isolated spelling errors in text. The model ...
This paper presents a comparative study of spelling errors that are corrected as you type, vs. those...
Context-sensitive spelling errors are those errors resulting from mistyping or mispronouncing a word...
We present TISC, a language-independent and context-sensitive spelling checking and correction syste...
We present two algorithms for automatically improving the quality of texts which contain a large num...
In computing, spell checking is the process of detecting and sometimes providing spelling suggestion...
Spelling checkers, frequently used nowadays, do not allow to correct real-word errors. Thus, the err...
In this thesis we did research on context-based spellchecking approaches for the Dutch language. Con...
A large class of machine-learning problems in natural language require the characterization of lingu...
Abstract. A large class of machine-learning problems in natural language require the characterizatio...
A context-based spelling error is a spelling or typing error that turns an intended word into anothe...
We present TISC, a multilingual, language-independent and context-sensitive spelling checking and co...
AbstractAutomatic spell checker systems aim to verify and correct erroneous words through a suggeste...
Nowadays, a large amount of documents is generated daily. These documents may contain some spelling ...
For an advanced implementation of spelling correction via machine learning, a multi-level featurebas...
We propose a deep graphical model for the correction of isolated spelling errors in text. The model ...
This paper presents a comparative study of spelling errors that are corrected as you type, vs. those...