Data verification method and device, electronic equipment and storage medium
By obtaining and inserting the target verification rules from the verification rules library, the problem of difficulty adjusting the code in the existing technology to verify the new field, and realize the flexibility and effective verification of the business data containing the new field. Essence
Patent Information
- Application Number
- CN202411381154.X
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-09-30
- Publication Date
- 2025-01-24
AI Technical Summary
The prior art is difficult to adjust to verify business data containing new fields because the verification rules for existing fields are solidified in the verification code.
By obtaining the classification category of the new field in the business data to be checked, obtain the target verification rules from the verification rules library, and insert it into the verification code according to the preset insertion rules, and then check the verification business data.
The effective verification of business data containing new fields is implemented, the problem that is difficult to adjust the code in existing technology, and improve the flexibility and adaptability of the data verification.
Smart Images
Figure CN119357236A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the field of computer technology, and in particular to a data verification method, device, electronic device and storage medium. Background Art
[0002] In the course of business processing, enterprises often generate a large amount of business data, which may include sales data, claims data, financial data, etc. Before these business data are put into storage, they usually need to be verified to determine whether there are default values, whether they are legal, etc.
[0003] In the current verification method, you can first obtain business data, which includes multiple existing fields, and then obtain a verification code, wherein the verification code has verification rules corresponding to these existing fields respectively, so that by running the verification code, each existing field in the business data can be verified.
[0004] In actual applications, with the continuous development of enterprise business, new fields may appear in business data. The new fields may be newly added fields based on existing fields, or may be fields obtained by modifying existing fields. In the current verification method, since the verification rules corresponding to the existing fields are solidified in the verification code, it is difficult to adjust the verification code to verify business data containing new fields. Summary of the invention
[0005] The embodiments of the present application provide a data verification method, device, electronic device and storage medium, which can be used to solve the problems in the prior art.
[0006] A first aspect of an embodiment of the present application provides a data verification method, including:
[0007] Acquire the business data to be verified, where the business data to be verified includes a new field;
[0008] According to the classification category of the new field, obtaining a target verification rule corresponding to the classification category from a verification rule library;
[0009] Inserting the target verification rule into the verification code according to the preset insertion rule;
[0010] The business data to be verified is verified using the verification code inserted into the target verification rule.
[0011] Preferably, the method further comprises: determining the classification category of the new field according to the field name of the new field and the data type of the field value.
[0012] Preferably, determining the classification category of the new field according to the field name and the data type of the field value of the new field specifically includes:
[0013] Finding a plurality of pending fields having field names similar to the new field from the verification rule library;
[0014] Comparing the data type of each field value in the new field with the data type of each pending field, so as to filter out the target field from each pending field;
[0015] When the number of the target fields is one, the classification category of the target field is determined as the classification category of the new field.
[0016] Preferably, the target verification rule specifically includes: a data type used for verification, and a regular rule for converting the target verification rule into a regular expression.
[0017] Preferably, the verification code is provided with an interface for inserting verification rules; and,
[0018] According to the preset insertion rules, the target verification rules are inserted into the verification code, specifically including:
[0019] Through the interface, the target verification rule is inserted into the verification code according to the preset insertion rule.
[0020] Preferably, inserting the target verification rule into the verification code through the interface according to a preset insertion rule specifically includes:
[0021] Converting the target verification rule into a regular expression using the regular rule;
[0022] The regular expression is inserted into the verification code through the interface.
[0023] Preferably, when there are multiple target fields, the method further includes:
[0024] According to the popularity of each target field, a second target field is selected from each target field; wherein the popularity of the target field reflects the number of times the target field is determined as a pending field and a target field within a preset time period;
[0025] The classification category of the second target field is determined as the classification category of the new field.
[0026] Preferably, the heat of each target field is calculated by the following formula:
[0027] Q i =a×M i +b×N i
[0028] Among them, Q i is the heat of the i-th target field; M i is the number of times the i-th target field is determined as a pending field within a preset time period; N i is the number of times the i-th target field is determined as the target field within a preset time period; a and b are both correlation coefficients greater than 0, and b is greater than a.
[0029] A second aspect of an embodiment of the present application provides an electronic device, including:
[0030] Memory for storing computer programs;
[0031] A processor is used to execute the method described in any one of the first aspects of the embodiments of the present application.
[0032] A third aspect of the embodiments of the present application provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the method described in any one of the first aspects of the embodiments of the present application is implemented.
[0033] The table file generation method provided by the embodiment of the present application includes first obtaining the business data to be verified, the business data to be verified includes a new field, and then according to the classification category of the new field, obtaining the target verification rule corresponding to the classification category from the verification rule library, and then according to the preset insertion rule, inserting the target verification rule into the verification code, and then using the verification code inserted into the target verification rule to verify the business data to be verified. Since the method stores the target verification rule in the verification rule library instead of solidifying it into the verification code, and only obtains the target verification rule from the verification rule library when needed, and then inserts it into the verification code, and then uses it to verify the business data to be verified, the problems in the prior art are solved. BRIEF DESCRIPTION OF THE DRAWINGS
[0034] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments of the present application will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.
[0035] Figure 1 A schematic diagram of the structure of an electronic device provided in one embodiment of the present application;
[0036] Figure 2 A schematic diagram of a specific process of a data verification method provided in an embodiment of the present application;
[0037] Figure 3 A schematic diagram of a specific structure of a business system provided in one embodiment of the present application;
[0038] Figure 4 A schematic diagram of the specific structure of a data verification device provided in one embodiment of the present application. DETAILED DESCRIPTION
[0039] The technical solutions in the embodiments of the present application will be described below in conjunction with the accompanying drawings in the embodiments of the present application. In the description of the present application, terms such as "first", "second", "third", etc. are only used to distinguish the description and cannot be understood as indicating or implying relative importance or sequence.
[0040] As mentioned above, the current verification code has verification rules corresponding to the existing fields, so that each existing field in the business data can be verified by running the verification code. However, when the business data includes new fields, the verification code is difficult to adjust to verify the business data containing the new fields.
[0041] Based on this, the embodiments of the present application provide a data verification method, device, electronic device and storage medium. Figure 1 The electronic device 1 is a schematic diagram of a specific structure. The electronic device 1 includes: at least one processor 11 and a memory 12, Figure 1 A processor is used as an example. The processor 11 and the memory 12 may be connected via a bus 10, and the memory 12 stores instructions executable by the processor 11, and the instructions are executed by the processor 11, so that the electronic device 1 can execute all or part of the process of the method in the following embodiment.
[0042] In practical applications, the electronic device 1 can be used as a server-side electronic device, such as a server, etc. Of course, multiple electronic devices 1 can also be built into a cluster to serve as the server. Of course, the electronic device can also be a user-side electronic device, such as a user's mobile phone, computer, etc.
[0043] like Figure 2 The figure is a flow chart of a data verification method provided by an embodiment of the present application. Some or all steps of the method can be performed by Figure 1 The electronic device 1 shown is used to perform the method. Here, the method is described by taking the electronic device 1 as a server to perform the method as an example. The method includes the following steps:
[0044] Step S21: Acquire the business data to be verified, where the business data to be verified includes a new field.
[0045] The business data to be verified may be the business data obtained by the server, such as Figure 3It is a structural diagram of the business system of an enterprise, and the business system includes a client 31 and a server 32. The server 32 may also include a server 321 and a database 322, wherein the client 31 is connected to the server 321 in the server 32, and the server 321 is connected to the database 322. In this way, the client 31 can communicate with the server 321, for example, the client 31 can send business data to the server 321, so that the server 321 stores the business data in the database 322.
[0046] However, before storing the business data in the database 322, the server 321 needs to verify the business data first. Therefore, the business data to be verified in step S21 can be the business and data received by the server 321 and sent by the client, that is, the server 321 obtains the business data sent by the client 31 as the business data to be verified.
[0047] In addition, considering that the server 321 is usually connected to multiple clients 31, these clients 31 may all send business data to the server 321. In order to reduce the computing pressure of the server 321, a message queue may be pre-established in the server 321. In this way, each piece of business data received by the server 321 (these business data may be sent by multiple different clients 31) can be added to the message queue first according to the order of the timestamps when received, so that the server 321 can obtain the corresponding business data in sequence according to its own load, business processing conditions and other factors when needed, and then according to the order in the message queue, as the business data to be verified in step S21.
[0048] It should be noted that the business data to be verified in step S21 includes new fields, which may be, for example, fields newly added based on the original business data, or fields obtained by modifying existing fields in the original business data. In addition, the business data to be verified may include existing fields in addition to new fields.
[0049] For example, with the continuous development of an enterprise's business, the enterprise's business data (i.e., original business data) adds a new field on the basis of the original 10 fields (i.e., existing fields). In this way, when the enterprise's business data is used as business data to be verified, the business data to be verified includes one field and 10 existing fields.
[0050] Step S22: According to the classification category of the new field, a target verification rule corresponding to the classification category is obtained from a verification rule library.
[0051] In the present application, each field of the business data is classified in advance so that the classification category of each field can be obtained. For example, the classification category can be a digital category, an identity relationship category, an address category, etc. Of course, these classification categories can further include the next level of classification categories. For example, the digital category can also include payment amount, mobile phone number, etc. Therefore, for the existing fields and new fields in the business data to be verified, their corresponding classification categories can be determined.
[0052] In the method provided in the embodiment of the present application, the classification category of a field can be determined based on the field name and the data type of the field value of a certain field (for example, the field can be a new field or an existing field in the business data to be verified in the embodiment of the present application). Specifically, for example, the verification rule library can be searched according to the field name of the field to obtain the classification category of the field, or the classification category of the field can be determined based on the data type of the field value of the field. For example, if the data type of the field value of the field is all numbers, the classification category of the field can be determined as a digital category.
[0053] However, when these two methods are used alone, the classification category may be inaccurate. For example, if the field name of the new field is not found in the verification rule library, it is difficult to determine the classification category of the new field. Or, if there are many types of data types for the field values in the new field, it may also be difficult to determine the classification category of the new field. In this case, the field name of the new field and the data type of the field value can be combined to more accurately determine the classification category of the new field. For example, multiple pending fields with similar field names to the new field can be found in the verification rule library, and then the data type of each field value in the new field is compared with the data type of each pending field, so as to finally filter out the target field from the pending fields. Among them, the data type of the filtered target field needs to be the same as the data type of each field value in the new field, so that the two can be matched.
[0054] At this time, after the target field is finally screened out from various pending fields, one method is to directly determine the classification category of the target field as the classification category of the new field. For example, this method can be used when the number of the target field is one.
[0055] In addition, when there are multiple target fields, it means that multiple pending fields with similar field names to the new field can be found in the verification rule library, and among these pending fields, multiple data types of the pending fields are the same as the data types of the field values in the new field. At this time, the popularity of these target fields can be further combined to filter out the second target field from these target fields, and then the classification category of the second target field can be determined as the classification category of the new field, wherein the popularity of a field (or target field) reflects the number of times the field is determined as a pending field and a target field within a preset time period.
[0056] For example, the preset time period may be 1 week. For a certain field or target field, the popularity of the field may be calculated by the number of times the field or target field is determined as a pending field and the number of times the field or target field is determined as a target field within 1 week. Of course, the preset time period may also be 1 month, 1 year, etc. For example, the popularity of a certain field or target field may be calculated by the following formula 1:
[0057] Q i =a×M i +b×N i Formula 1
[0058] In the formula 1, i is the number of the field (or target field); Q i is the heat of the i-th field; M i N is the number of times the i-th field is determined as a pending field within a preset time period; i is the number of times the i-th field is determined as the target field within a preset time period; a and b are both correlation coefficients greater than 0, and b is greater than a.
[0059] Therefore, when there are multiple target fields, the number of times M that the target field is determined as a pending field within a preset time period can be obtained for each target field. i and the number of times N is determined as the target field i , and then the M i and N i Substitute into the above formula 1 to calculate the heat Q of the target field i In this way, when there are multiple target fields, the popularity of each target field can be obtained in this way, and then the target field with the largest popularity is selected as the second target field, and then the classification category of the second target field is determined as the classification category of the new field.
[0060] The method of finding multiple pending fields with similar field names to the field from the verification rule base may be to respectively calculate the similarity between the field (that is, the new field) and each field in the verification rule base, thereby filtering out multiple fields with the greatest similarity from the verification rule base, or multiple fields with similarity greater than a preset threshold, as the multiple filtered pending fields. The similarity may be cosine similarity, for example, the field name may be first converted into a word vector, and then the cosine similarity between the word vectors may be calculated.
[0061] It should be noted that the verification rule base stores the classification categories of each field and the verification rules corresponding to the fields of each classification category. Therefore, in the present application, the verification rules are not solidified into the verification code, but after the fields are classified, the verification rules of the fields of each classification category are stored in the verification rule base. For example, after adding a new field to the business data according to business requirements, if the classification category of the new field belongs to a classification category already in the verification rule base, no processing is required. On the contrary, if the classification category of the new field does not belong to the classification category already in the verification rule base, the corresponding classification category and the verification rules corresponding to the classification category can be configured for the new field in the verification rule base.
[0062] In this way, the classification category of the new field in the business data to be verified can be obtained, and then through step S22, according to the classification category of the new field, the verification rule corresponding to the classification category is obtained from the verification rule library, that is, the target verification rule. Among them, for each verification rule in the verification rule library (including the target verification rule), it can usually include a data type for verification, that is, the verification rule can verify the data of the data type. Of course, in order to facilitate the insertion of the verification rule into the verification code, the verification rule can also include a regular rule for converting the verification rule into a regular expression, so that it can be converted into a regular expression through the regular rule, and then it is convenient to insert it into the verification code.
[0063] Step S23: inserting the target verification rule into the verification code according to the preset insertion rule.
[0064] The verification code is provided with an interface for inserting verification rules, so that the target verification rule can be inserted into the verification code through the interface according to the preset insertion rule, so that the verification code includes the target verification rule, and the business data to be verified can be verified. Of course, the number of interfaces provided in the verification code can be one or more, and the number of interfaces is not limited here.
[0065] Thus, step S23 in the embodiment of the present application can be specifically as follows: inserting the target verification rule into the verification code according to the preset insertion rule through the interface set in the verification code. Among them, it is mentioned above that in order to facilitate the insertion of the verification rule (here, the target verification rule) into the verification code, the verification rule may include a regular rule. At this time, the method of inserting the target verification rule into the verification code can be specifically as follows: first converting the target verification rule into a regular expression using the regular rule, and then inserting the regular expression into the verification code through the interface, thereby achieving the purpose of inserting the target verification rule into the verification code.
[0066] Step S24: Verify the service data to be verified using the verification code inserted into the target verification rule.
[0067] After the target verification rule is inserted into the verification code through the above-mentioned step S23, in this step S24, the verification code inserted into the target verification rule can be used to verify the business data to be verified. Specifically, for example, the verification code inserted into the target verification rule can be run to verify the business data to be verified.
[0068] The table file generation method provided by the embodiment of the present application includes first obtaining the business data to be verified, the business data to be verified includes a new field, and then according to the classification category of the new field, obtaining the target verification rule corresponding to the classification category from the verification rule library, and then according to the preset insertion rule, inserting the target verification rule into the verification code, and then using the verification code inserted into the target verification rule to verify the business data to be verified. Since the method stores the target verification rule in the verification rule library instead of solidifying it into the verification code, and only obtains the target verification rule from the verification rule library when needed, and then inserts it into the verification code, and then uses it to verify the business data to be verified, the problems in the prior art are solved.
[0069] For example, in the prior art, the verification rules corresponding to the existing fields are solidified into the verification code, such as the verification code of the field name is "attrName=accidentMobile", and the verification code of the category field is "attrType=mobile". These detection codes are usually solidified into the verification code. However, for new fields of business data, this method solidifies the verification rules of the existing fields into the verification code, making it difficult to adjust the verification code to verify the business data containing the new fields.
[0070] In the method provided in the embodiment of the present application, a verification rule base is pre-established, so that after the fields are classified, the verification rules of the fields of each classification category are stored in the verification rule base, and an interface is provided in the verification code. In this way, for the business data containing a new field, the target verification rule corresponding to the classification category can be obtained from the verification rule base according to the classification category of the new field, and then the target verification rule is inserted into the verification code through the interface in the verification code, and then the verification code of the inserted target verification rule can be used to verify the business data to be verified. Therefore, in the method provided in the embodiment of the present application, it is not necessary to solidify the target verification rule corresponding to the new field into the verification code, but to obtain the target verification rule from the verification rule base when necessary, and insert the verification code through the interface, which can be applicable to the verification of the business data containing the new field.
[0071] Of course, after the business data to be verified is verified through the above-mentioned step S24, the verification result may be a passed verification or a failed verification. At this time, if the verification is passed, the method may further include storing the business data to be verified in a database, or if the verification fails, the method may further include discarding the business data to be verified and feeding back a prompt message to the client, thereby prompting the user of the client that the business data to be verified (that is, the data submitted by the user through the client) has failed the verification.
[0072] As mentioned above, Figure 2 The description is given by taking the server executing the method provided in the embodiment of the present application as an example. Figure 3 As shown, specifically, the client sends business data to the server. After the server receives the business data, before storing the business data in the database, the server uses the business data as business data to be verified and verifies it by executing the method provided in the embodiment of the present application. Of course, if the verification passes, the business data to be verified can be stored in the database again.
[0073] In actual applications, the client can also execute the method provided by the embodiment of the present application. For example, before sending the business data to the server, the client can also use the business data as business data to be verified, and verify it by executing the method provided by the embodiment of the present application. If the verification passes, the business data can be sent to the server. Of course, if the verification fails, the business data to be verified can be discarded, and a prompt message can be displayed to prompt the user of the client that the business data verification has failed.
[0074] In addition, when there are multiple servers on the service side, these servers may also transmit business data to each other. At this time, before a server transmits business data to another server, it can use the method provided in the embodiment of the present application to verify it. After a server receives business data transmitted by another server, it can also use the method provided in the embodiment of the present application to verify it.
[0075] The above is a specific description of the method provided in the embodiment of the present application. For ease of understanding, the method can be further described here in conjunction with a specific example. In this example, the client first sends business data to the server, so that the server can obtain the business data sent by the client, and then use the business data as the business data to be verified, and verify it through the method provided in the embodiment of the present application, wherein the business data to be verified includes a new field.
[0076] The server searches the verification rule library for multiple pending fields with similar field names to the new field, and then compares the data type of each field value in the new field with the data type of each pending field, thereby filtering out the target field from the pending fields. At this time, when the number of target fields is one, the classification category of the target field can be determined as the classification category of the new field; and when the number of target fields is multiple, the popularity of each target field can be further calculated by the above formula one, and then the target field with the largest popularity is selected as the second target field, and the classification category of the second target field is determined as the classification category of the new field.
[0077] After obtaining the classification category of the new field, the target verification rule corresponding to the classification category can be obtained from the verification rule library, and the target verification rule can be inserted into the verification code according to the preset insertion rule, and then the verification code inserted into the target verification rule can be used to verify the business data to be verified. Of course, if the verification passes, the business data to be verified can be stored in the database, or if the verification fails, the business data to be verified can be discarded and a prompt message can be fed back to the client.
[0078] Based on the same inventive concept as the data verification method provided in the embodiment of the present application, the embodiment of the present application also provides a data verification device. For the embodiment of the device, if there is anything not specifically described, please refer to the corresponding content of the method embodiment. Figure 4 FIG. 4 is a schematic diagram of a specific structure of the device 40, which includes: a first acquisition unit 401, a second acquisition unit 401, an insertion unit 403 and a verification unit 404, wherein:
[0079] A first acquisition unit 401 is used to acquire the service data to be verified, where the service data to be verified includes a new field;
[0080] The second acquisition unit 401 is used to acquire a target verification rule corresponding to the classification category from a verification rule library according to the classification category of the new field;
[0081] An inserting unit 403 is used to insert the target verification rule into the verification code according to a preset insertion rule;
[0082] The verification unit 404 is used to verify the business data to be verified by using the verification code inserted into the target verification rule.
[0083] The device 40 provided in the embodiment of the present application is adopted. Since the device 40 adopts the same inventive concept as the method provided in the embodiment of the present application, on the premise that the method can solve the technical problem, the device 40 can also solve the technical problem, which will not be repeated here.
[0084] In addition, in actual applications, the technical effects achieved by combining the device 40 with specific hardware equipment, cloud technology, etc. are also within the scope of protection of the present application. For example, different units in the device 40 are deployed in different nodes in the distributed cluster in a distributed cluster manner, or some units are deployed in a cloud server, etc., to improve efficiency and reduce costs.
[0085] The device 40 may further include a determining unit, configured to determine the classification category of the new field according to the field name of the new field and the data type of the field value.
[0086] Wherein, determining the classification category of the new field according to the field name of the new field and the data type of the field value may specifically include:
[0087] Finding a plurality of pending fields having field names similar to the new field from the verification rule library;
[0088] Comparing the data type of each field value in the new field with the data type of each pending field, so as to filter out the target field from each pending field;
[0089] When the number of the target fields is one, the classification category of the target field is determined as the classification category of the new field.
[0090] The target verification rule may specifically include: a data type used for verification, and a regular rule for converting the target verification rule into a regular expression.
[0091] Wherein, the verification code is provided with an interface for inserting verification rules; and,
[0092] Inserting the target verification rule into the verification code according to the preset insertion rule may specifically include:
[0093] Through the interface, the target verification rule is inserted into the verification code according to the preset insertion rule.
[0094] Wherein, inserting the target verification rule into the verification code through the interface according to the preset insertion rule may specifically include:
[0095] Converting the target verification rule into a regular expression using the regular rule;
[0096] The regular expression is inserted into the verification code through the interface.
[0097] Wherein, when there are multiple target fields, the device 40 may further include:
[0098] According to the popularity of each target field, a second target field is selected from each target field; wherein the popularity of the target field reflects the number of times the target field is determined as a pending field and a target field within a preset time period;
[0099] The classification category of the second target field is determined as the classification category of the new field.
[0100] The heat of each target field can be calculated by the following formula:
[0101] Q i =a×M i +b×N i
[0102] Among them, Q i is the heat of the i-th target field; M i is the number of times the i-th target field is determined as a pending field within a preset time period; N i is the number of times the i-th target field is determined as the target field within a preset time period; a and b are both correlation coefficients greater than 0, and b is greater than a.
[0103] The embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon, characterized in that the computer program implements all or part of the process of the method in the above embodiment when executed by a processor. The storage medium may be a disk, an optical disk, a read-only memory (ROM), a random access memory (RAM), a flash memory, a hard disk drive (HDD) or a solid-state drive (SSD). The storage medium may also include a combination of the above-mentioned types of memory.
[0104] Although the embodiments of the present invention have been described in conjunction with the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the present invention, and such modifications and variations are all within the scope defined by the appended claims.
Claims
1. A data verification method, characterized in that: include: Acquire the business data to be verified, where the business data to be verified includes a new field; According to the classification category of the new field, obtaining a target verification rule corresponding to the classification category from a verification rule library; Inserting the target verification rule into the verification code according to the preset insertion rule; The business data to be verified is verified using the verification code inserted into the target verification rule.
2. The method according to claim 1, characterized in that The method further includes: determining the classification category of the new field according to the field name of the new field and the data type of the field value.
3. The method according to claim 2, characterized in that Determine the classification category of the new field according to the field name and the data type of the field value of the new field, specifically including: Finding a plurality of pending fields having field names similar to the new field from the verification rule library; Comparing the data type of each field value in the new field with the data type of each pending field, so as to filter out the target field from each pending field; When the number of the target fields is one, the classification category of the target field is determined as the classification category of the new field.
4. The method according to claim 1 or 3, characterized in that: The target verification rule specifically includes: a data type used for verification, and a regular rule for converting the target verification rule into a regular expression.
5. The method according to claim 4, characterized in that The verification code is provided with an interface for inserting verification rules; and, According to the preset insertion rules, the target verification rules are inserted into the verification code, specifically including: Through the interface, the target verification rule is inserted into the verification code according to the preset insertion rule.
6. The method according to claim 5, characterized in that Through the interface, according to the preset insertion rule, the target verification rule is inserted into the verification code, specifically including: Converting the target verification rule into a regular expression using the regular rule; The regular expression is inserted into the verification code through the interface.
7. The method according to claim 3, characterized in that In the case where there are multiple target fields, the method further includes: According to the popularity of each target field, a second target field is selected from each target field; wherein the popularity of the target field reflects the number of times the target field is determined as a pending field and a target field within a preset time period; The classification category of the second target field is determined as the classification category of the new field.
8. The method according to claim 7, characterized in that The heat of each target field is calculated using the following formula: Q i =a×M i +b×N i Among them, Q i is the heat of the i-th target field; M i is the number of times the i-th target field is determined as a pending field within a preset time period; N i is the number of times the i-th target field is determined as the target field within a preset time period; a and b are both correlation coefficients greater than 0, and b is greater than a.
9. An electronic device, characterized in that: include: Memory for storing computer programs; A processor, for executing the insurance claim material image processing method as claimed in any one of claims 1 to 8.
10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the insurance claim material image processing method according to any one of claims 1 to 8 is implemented.