Multi-decision text adaptive error correction system

Abstract

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.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to a multi-decision text adaptive error correction system. Background Art

[0002] At present, the text error correction scheme of the Internet platform is that the user inputs the content into the text publishing page, and the published text content is manually reviewed when or after the text is published. When non-compliant words are found, the published text is removed from the shelves and the publisher is notified at the same time. This manual review method cannot perform content review before the text is published. At the same time, manual review also has certain omissions and lacks accuracy, which affects the user experience. Summary of the invention

[0003] The object of the present invention is to provide a multi-decision text adaptive error correction system to solve all or one of the above problems existing in the prior art.

[0004] In order to solve the above technical problems, the specific technical solutions of the present invention are as follows: The present invention provides a multi-decision text adaptive error correction system, comprising: The recognition module is used to: provide a correction prompt for the correction part when correcting text errors; A multi-decision correction module is used to: perform correction processing on the error correction part according to the user's feedback on the error correction prompt to obtain correction content; The secondary review module is used to: conduct a multi-standard review on the correction content to obtain the review result; and perform a second review on the correction content according to the review result.

[0005] In one embodiment, the multi-decision correction module includes: a first correction unit; The first correction unit is used to: in response to the user selecting a custom correction according to the error correction prompt, update the non-compliant part in the error correction part according to the content input by the user to obtain the correction content.

[0006] In one embodiment, the multi-decision correction module further includes: a second correction unit; The second correction unit is used to: in response to the user selecting system correction according to the error correction prompt, correct the non-compliant part in the error correction part into a compliant expression based on the deep learning model to obtain the correction content.

[0007] In one embodiment, the multi-decision correction module further includes: a third correction unit; The third correction unit is used to: in response to a user's judgment that the error correction prompt is a false alarm, re-identify the non-compliant segments in the error correction part based on a deep learning model; and input the false alarm non-compliant segments into the deep learning model for model updating.

[0008] In one embodiment, the secondary review module includes: a specification calling unit; The specification calling unit is used to: call the deep learning model to review the correction content according to the review specifications based on several non-compliant sensitive words.

[0009] In one embodiment, the secondary audit module further includes: a result determination unit; The result determination unit is used to: when the corrected content meets the review specifications of several non-compliant sensitive words, set the review result to passed; when the corrected content does not meet the review specifications of any non-compliant sensitive words, set the review result to failed.

[0010] In one embodiment, the secondary audit module further includes: a secondary correction unit; The secondary correction unit is used to prompt the user to correct the correction content again when the audit result is that the audit fails.

[0011] In one embodiment, the secondary audit module further includes: a prompt unit; The prompt unit is used to prompt the user that the calibration is successful when the audit result is passed.

[0012] The beneficial effects of the technical solution of the present invention are: The multi-decision text adaptive error correction system described in the present invention can realize automatic recognition of erroneous texts, perform correction processing on the erroneous texts with different strategies, and perform secondary verification on the corrected texts, thereby having high error correction accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0014] Figure 1 It is a flow chart of the multi-decision text adaptive error correction system described in Example 1 of the present invention. DETAILED DESCRIPTION

[0015] The preferred embodiments of the present invention are described in detail below in conjunction with the accompanying drawings so that the advantages and features of the present invention can be more easily understood by those skilled in the art, thereby making a clearer and more definite definition of the protection scope of the present invention.

[0016] In the description of the present invention, it should be noted that the embodiments described in the present invention are only part of the embodiments of the present invention, rather than all of the embodiments; based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of the present invention.

[0017] The terms "first", "second", etc. in the specification and claims of this article and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of this article described here can be implemented in an order other than those illustrated or described here. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, device, product or equipment that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or equipment.

[0018] This embodiment provides a multi-decision text adaptive error correction system, such as Figure 1 As shown, including: The recognition module is used to: provide a correction prompt for the correction part when correcting text errors; A multi-decision correction module is used to: perform correction processing on the error correction part according to the user's feedback on the error correction prompt to obtain correction content; The secondary review module is used to: conduct a multi-standard review on the correction content to obtain the review result; and perform a second review on the correction content according to the review result.

[0019] In one embodiment, the multi-decision correction module includes: a first correction unit; The first correction unit is used to: in response to the user selecting a custom correction according to the error correction prompt, update the non-compliant part in the error correction part according to the content input by the user to obtain the correction content.

[0020] In one embodiment, the multi-decision correction module further includes: a second correction unit; The second correction unit is used to: in response to the user selecting system correction according to the error correction prompt, correct the non-compliant part in the error correction part into a compliant expression based on the deep learning model to obtain the correction content.

[0021] In one embodiment, the multi-decision correction module further includes: a third correction unit; The third correction unit is used to: in response to a user's judgment that the error correction prompt is a false alarm, re-identify the non-compliant segments in the error correction part based on a deep learning model; and input the false alarm non-compliant segments into the deep learning model for model updating.

[0022] In one embodiment, the secondary review module includes: a specification calling unit; The specification calling unit is used to: call the deep learning model to review the correction content according to the review specifications based on several non-compliant sensitive words.

[0023] In one embodiment, the secondary audit module further includes: a result determination unit; The result determination unit is used to: when the corrected content meets the review specifications of several non-compliant sensitive words, set the review result to passed; when the corrected content does not meet the review specifications of any non-compliant sensitive words, set the review result to failed.

[0024] In one embodiment, the secondary audit module further includes: a secondary correction unit; The secondary correction unit is used to prompt the user to correct the correction content again when the audit result is that the audit fails.

[0025] In one embodiment, the secondary audit module further includes: a prompt unit; The prompt unit is used to prompt the user that the calibration is successful when the audit result is passed.

[0026] Different from the prior art, the present application adopts a multi-decision text adaptive error correction system, which can automatically identify erroneous texts, correct the erroneous texts with different strategies, and perform secondary verification on the corrected texts, with high error correction accuracy.

[0027] It should be understood that in the various embodiments of this document, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this document.

[0028] It should also be understood that in the embodiments of this article, the term "and / or" is only a description of the association relationship of the associated objects, indicating that three relationships may exist. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship.

[0029] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in terms of function in the above description. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this article.

[0030] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0031] In the several embodiments provided herein, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of the units is only a logical function division, and there may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, or can be electrical, mechanical or other forms of connection.

[0032] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the embodiments of this article.

[0033] In addition, each functional unit in each embodiment of this invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above integrated unit may be implemented in the form of hardware or in the form of software functional unit.

[0034] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this article is essentially or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of this article. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0035] The above descriptions are merely embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A multi-decision text adaptive error correction system, characterized in that: include: The recognition module is used to: provide a correction prompt for the correction part when correcting text errors; A multi-decision correction module is used to: perform correction processing on the error correction part according to the user's feedback on the error correction prompt to obtain correction content; The secondary review module is used to: conduct a multi-standard review on the correction content to obtain the review result; and perform a second review on the correction content according to the review result.

2. The multi-decision text adaptive error correction system according to claim 1, characterized in that: The multi-decision correction module includes: a first correction unit; The first correction unit is used to update the non-compliant part of the correction part according to the content input by the user in response to the user selecting the custom correction according to the correction prompt to obtain the correction content.

3. The multi-decision text adaptive error correction system according to claim 1, characterized in that: The multi-decision correction module further includes: a second correction unit; The second correction unit is used to respond to the user selecting system correction according to the error correction prompt, and correct the non-compliant part in the error correction part into a compliant expression based on the deep learning model to obtain the correction content.

4. The multi-decision text adaptive error correction system according to claim 1, characterized in that: The multi-decision correction module further includes: a third correction unit; The third correction unit is used to re-identify the non-compliant segments in the error correction part based on the deep learning model in response to the user's judgment that the error correction prompt is a false alarm; and input the false alarm non-compliant segments into the deep learning model for model updating.

5. The multi-decision text adaptive error correction system according to claim 1, characterized in that: The secondary review module includes: a specification calling unit; The specification calling unit is used to call the deep learning model to review the correction content according to the review specifications based on several non-compliant sensitive words.

6. The multi-decision text adaptive error correction system according to claim 5, characterized in that: The secondary review module further includes: a result determination unit; The result determination unit is used to set the audit result as passed when the corrected content meets the audit specifications of several non-compliant sensitive words; and to set the audit result as failed when the corrected content does not meet the audit specifications of any non-compliant sensitive words.

7. The multi-decision text adaptive error correction system according to claim 1, characterized in that: The secondary audit module further includes: a secondary correction unit; The secondary correction unit is used to prompt the user to correct the correction content again when the audit result is that the audit fails.

8. The multi-decision text adaptive error correction system according to claim 1, characterized in that: The secondary review module further includes: a prompt unit; The prompting unit is used to prompt the user that the calibration is successful when the audit result is audit passed.

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