10results about How to "Improve error correction accuracy" patented technology

The invention discloses a structured query language error correction method and device and a volatile storage medium. The method comprises the steps that first grammar error information output by a grammar detector is acquired, and data structure information of a grammar error association table is determined according to the first grammar error information; determining a correlation score, corresponding to the first grammar error information, of each historical error correction sample, and determining a target error correction sample in each historical error correction sample according to the correlation score; according to the first grammar error information, the data structure information of the grammar error association table and the target error correction sample, constructing error prompt information; inputting the error prompt information into an error correction model, obtaining an error correction result returned by the error correction model, inputting the error correction result into the error correction model, obtaining an analysis result of the error correction model on the error correction result, and updating the error correction result according to the analysis result. According to the method and the device, the technical problem of low error correction efficiency caused by inaccurate error correction effect of the existing structured query language is solved.

The embodiment of the invention provides a text error correction method, a text error correction device, electronic equipment and a medium, and belongs to the technical field of financial science and technology. The method comprises the following steps: inputting a target text into a text error detection model for text error detection to obtain text marking data, wherein the text marking data is used for marking correct characters and error characters in text characters; inputting the target text into a text error correction model based on the text marking data; extracting text character and pronunciation features of the text characters based on a character and pronunciation feature extraction sub-model; extracting text font features based on the font feature extraction sub-model, wherein the text font features comprise first mask features of error characters; extracting text semantic features based on the semantic feature extraction sub-model, wherein the text font features comprise second mask features of error characters; and performing text prediction on the text character pronunciation features, the text font features and the text semantic features based on the error correction sub-model to obtain a target error correction text. According to the embodiment of the invention, the error correction accuracy of the text can be improved.

The present application discloses a method, device, computer equipment and storage medium for obtaining training samples, and relates to the field of computer technology. The method comprises: obtaining a first text set and a second text set; obtaining the longest common subsequence in the correct text and the erroneous text corresponding to the correct text in the first text set; obtaining a text unit that does not belong to the longest common subsequence from the correct text as a rewritten text unit, and obtaining a text unit that does not belong to the longest common subsequence from the erroneous text as an erroneous text unit corresponding to the rewritten text unit; generating a confusion set based on the rewritten text unit and the erroneous text unit; replacing the specified text unit in the second text set with the erroneous text unit corresponding to the specified text unit in the confusion set, and obtaining a third text set. In this way, model training is performed based on the first text set and the third text set, which expands the text set for model training, thereby improving the generalization effect of the trained text error correction model.

The invention relates to the medical field and the voice text processing field, and discloses an error correction method for a voice recognition result, which comprises the following steps: matching a text to be corrected to obtain a first word group and a second word group; performing pinyin matching on the second phrase by using a pinyin fuzzy matching module to obtain a third phrase and a fourth phrase; generating a first candidate text based on the first and third phrases, calculating a vector of the first candidate text to generate a first word vector, generating a second candidate text based on the first and fourth phrases, and calculating a vector of the second candidate text to generate a second word vector; and correcting the first candidate text and the second candidate text based on a correction module, the first word vector and the second word vector to obtain a first correction result value and a second correction result value, and selecting the candidate text with the maximum correction result value as a target text. According to the method, optimization of global features between words and phrases of text information by an error correction model is improved in digital medical application, online medical popularization and use are realized, the efficiency is improved, and the cost is saved.

The application discloses a kind of based on knowledge graph's name and post error correction method, system, equipment and medium, it is related to text correction technical field, wherein, based on knowledge graph's name and post error correction method includes: step S1, obtains to be corrected text, the to be corrected text includes name and post name;Step S2, according to the knowledge graph that is constructed in advance, by multi-mode matching algorithm, to the to be corrected text is carried out error text correction, obtains target text;The knowledge graph is used to indicate the association between each entity, and the entity includes name and post name, and the error text correction includes at least one of homonym word correction, shape near word correction, multi-word correction and few words correction.The application improves the error correction efficiency and accuracy of name and post name in text by combining knowledge graph and multi-mode matching algorithm.

The text correction method, device, computer equipment and readable storage medium provided by the application comprise: obtaining a character sequence corresponding to a text to be corrected, a confidence degree of each character in the character sequence and an image sequence composed of images of each character; obtaining semantic information features corresponding to the text to be corrected according to the character sequence and image information features according to the image sequence through a correction model; the correction model further comprises a first full connection layer, a transformer layer and a second full connection layer connected in sequence; predicting a candidate word set at each character position after fusing the semantic information features and the image information features; correcting a target character with a confidence degree less than a preset confidence threshold in the character sequence based on the candidate word set at the character position of the target character. The application fully considers semantic information and character shape information, determines candidate words according to fused feature information, more fully utilizes information and can help improve correction accuracy.

The invention discloses a radar real-time double-frequency radio wave refraction error correction method. According to the method, the principle that instantaneous propagation paths of electromagnetic waves are approximately the same when two working frequency points of the radar are switched for detection is utilized, the error correction amount of the required frequency points is directly obtained, and the working time sequence of the radar can be adaptively adjusted according to the importance of a target and the radar resource utilization rate. The radio wave refraction error correction method can directly complete radio wave refraction error correction without participation of a GNSS receiver, and has high real-time performance and correction precision.

The invention discloses a multi-decision text adaptive error correction system, which comprises an identification module used for performing error correction prompt on an error correction part during text error correction; the multi-decision correction module is used for performing correction processing on the error correction part according to feedback of the user on the error correction prompt to obtain correction content; the secondary auditing module is used for performing multi-standard auditing on the correction content to obtain an auditing result; re-correcting the correction content according to the audit result; according to the method, the error text can be automatically identified, the error text is corrected by different strategies, the corrected text is subjected to secondary verification, and the method has relatively high error correction accuracy.

The invention discloses a text error correction method and device and a medium, and the method comprises the following steps: carrying out error correction prompt on an error correction part during text error correction; performing correction processing on the error correction part according to feedback of the user on the error correction prompt to obtain correction content; performing multi-standard auditing on the correction content to obtain an auditing result; re-correcting the correction content according to the audit result; according to the method, the error text can be automatically identified, the error text is corrected by different strategies, the corrected text is subjected to secondary verification, and the method has relatively high error correction accuracy.

The present application provides a text processing method and device, wherein the text processing method comprises: obtaining a text to be corrected; processing the text to be corrected according to a preset text error detection rule to obtain an initial error correction text; inputting the initial error correction text into a text error correction model for processing, and determining a target correction text corresponding to the text to be corrected according to the processing result. The method improves the accuracy of error correction by combining rules and models for error correction, and covers a wider range of error correction, so as to solve the problem of difficulty in rule maintenance caused by using rule correction alone in the prior art.