Industry spelling mistake checking method based on user feedback

Abstract

The invention discloses an industry spelling mistake checking method based on user feedback. According to the industry spelling mistake checking method based on user feedback, spelling mistake checking is carried out on English text by using an N-gram method and a user dictionary which is designed in a classified mode, recommendation of correct words is accomplished by searching for a large corpus database, and thus checking of spelling mistakes related to a user is achieved. The N-gram method serves as a basic method for natural language processing, and the mistakes in the text are checked according to the characteristics of words or statements and statistical information in a corpus; recommended words which are most related to wrong words in the text input by the user are selected through cooperation between the user dictionary designed in the classified mode and statistical data of the corpus according to historical information of the user at present; the database is searched for a word chain with the largest conditional probability product by using the Viterbi algorithm, and computational efficiency of a hidden Markov model in the large corpus and use efficiency of the statistical information in the database are improved.

Description

technical field [0001] The invention relates to an English spelling error checking method, which utilizes a corpus containing a large amount of language information, a natural language statistical model, a hidden Markov model and other related technologies, and relates to natural language processing, especially the field of English spelling checking. Background technique [0002] First the abbreviations used in the present invention are defined: [0003] NLP (Natural Language Processing): natural language processing; [0004] BNC (British National Corpus): British National Corpus; [0005] LDC (Linguistic Data Consortium): Linguistic Data Consortium; [0006] LD (Levenshtein Distance): edit distance; [0007] N-gram: N-gram. [0008] Spelling Checker (Spelling Checker) is an important branch and basic link of NLP. It processes natural language into error-free and understandable text, and has a natural support for advanced NLP technologies such as machine translation, spe...

AI Technical Summary

Problems solved by technology

If the corpus is based on grammatical rules or only counts the frequency of words, it is easy to cause poor performance caused by rule explosion or inaccurate calculation results due to insufficient statistical data during the query process.

Aiming at the problem that multiple corpora cannot be effectively used, a method of combining user dictionaries, industry corpora and core corpora and weighted calculations is adopted

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