Abstract: The invention provides a method and system for automatically detecting semantic errors in a text. In order to detect the semantic errors in the text, the method generates a first set of features and a second set of features corresponding to each word in the text. A first set of features corresponds to statistical features of a word and a second set of features for a word corresponds to the features generated for a plurality of words surrounding the word in the text using matrix factorization techniques. The method, then, combines a first set of features and a second set of features to generate a third set of features corresponding to each word in the text. Thereafter, the method utilizes an Artificial Neural Network (ANN) model to detect semantic validity of each word based on a corresponding third set of features.

Abstract: The invention provides a method and system for automatically scoring a written essay using plurality of linguistic levels. The method and system includes an essay analysis module for analyzing each sentence of the essay written in Arabic language using a trained model. The essay analysis module utilizes the trained model for analyzing each sentence of the essay at plurality of linguistic levels and generates different scores at plurality of linguistic levels. The scores generated at plurality of linguistic levels are computed to generate a final score by using a weighted combination of the different scores.

Abstract: The invention provides a method and system for automatically detecting semantic errors in a text. In order to detect the semantic errors in the text, the method generates a first set of features and a second set of features corresponding to each word in the text. A first set of features corresponds to statistical features of a word and a second set of features for a word corresponds to the features generated for a plurality of words surrounding the word in the text using matrix factorization techniques. The method, then, combines a first set of features and a second set of features to generate a third set of features corresponding to each word in the text. Thereafter, the method utilizes an Artificial Neural Network (ANN) model to detect semantic validity of each word based on a corresponding third set of features.

Abstract: The invention provides a method and system for automatically scoring a written essay using plurality of linguistic levels. The method and system includes an essay analysis module for analyzing each sentence of the essay written in Arabic language using a trained model. The essay analysis module utilizes the trained model for analyzing each sentence of the essay at plurality of linguistic levels and generates different scores at plurality of linguistic levels. The scores generated at plurality of linguistic levels are computed to generate a final score by using a weighted combination of the different scores.

Abstract: Methods and systems for large-scale statistical misspelling correction are provided. A method implemented in a computer infrastructure includes reviewing the input text to detect spelling errors in one or more words and calculating a variable cost distance of letters associated with the one or more words. Furthermore, the method can detect space-deletion errors and space-insertion errors. The method further includes determining a best candidate solution for correcting the spelling errors based on the variable cost distance. The method includes correcting the spelling errors using the best candidate solution.

Abstract: A system and method for rating an essay writing using a statistical system so it can be applied on any language with very few changes. The system comprising multiple modules capable of providing a style score, a punctuation score, a spelling score, a quotation score, an enrichment score, a syntax analysis score, a focus score, an idea score and a cohesion score. The scores are then combined to provide a final overall rating of the essay.

Abstract: Methods and systems for large-scale statistical misspelling correction are provided. A method implemented in a computer infrastructure includes reviewing the input text to detect spelling errors in one or more words and calculating a variable cost distance of letters associated with the one or more words. Furthermore, the method can detect space-deletion errors and space-insertion errors. The method further includes determining a best candidate solution for correcting the spelling errors based on the variable cost distance. The method includes correcting the spelling errors using the best candidate solution.

Abstract: A system and method for rating an essay writing using a statistical system so it can be applied on any language with very few changes. The system comprising multiple modules capable of providing a style score, a punctuation score, a spelling score, a quotation score, an enrichment score, a syntax analysis score, a focus score, an idea score and a cohesion score. The scores are then combined to provide a final overall rating of the essay.

Abstract: A system and method for rating an essay writing using a statistical system so it can be applied on any language with very few changes. The system comprising multiple modules capable of providing a style score, a punctuation score, a spelling score, a quotation score, an enrichment score, a syntax analysis score, a focus score, an idea score and a cohesion score. The scores are then combined to provide a final overall rating of the essay.

Abstract: A system and method for rating an essay writing using a statistical system so it can be applied on any language with very few changes. The system comprising multiple modules capable of providing a style score, a punctuation score, a spelling score, a quotation score, an enrichment score, a syntax analysis score, a focus score, an idea score and a cohesion score. The scores are then combined to provide a final overall rating of the essay.