Intelligent form generation method, device and equipment

Abstract

The invention discloses an intelligent form generation method, device and equipment, and belongs to the technical field of data processing.The to-be-processed form data is acquired, the acquired to-be-processed form data is retrieved in a template database, and then automatic filling of fields is performed, so that a form can be generated intelligently according to the to-be-processed form data, and the generation efficiency is improved. According to the method and the device, the requirements on use equipment are reduced, so that workers can intelligently carry out matching and form generation by transmitting the text information, the convenience of filling the form data by the workers is improved, and the form filling efficiency is improved.

Description

Technical Field

[0001] The present invention belongs to the field of data processing technology, and specifically relates to an intelligent form generation method, device and equipment. Background Art

[0002] In real life and work, filling out forms is a common task. However, the traditional way of manually filling out forms is time-consuming and prone to errors. Therefore, many companies and enterprises use electronic forms to fill in data. Although it can improve the efficiency and standardization of filling out to a certain extent, filling out electronic forms often requires the use of specific software (such as EXCEL), which requires staff to have devices that can run these software to fill out. For non-office offices, this greatly limits the scenarios for form filling, resulting in the problem of untimely form data filling. Summary of the invention

[0003] The present invention provides an intelligent form generation method, device and equipment, which are used to solve the problem of untimely filling of form data due to limited form filling scenarios in the prior art.

[0004] In a first aspect, the present invention provides a smart form generation method, comprising:

[0005] Acquire form data to be processed; the form data to be processed includes at least one first field, first data name information corresponding to the first field, at least one second field corresponding to the first field, and first data attribute information corresponding to the second field;

[0006] According to the form data to be processed, a smart matching algorithm is used to match in a template database to determine a target form template corresponding to the form data to be processed;

[0007] According to the first field in the form data to be processed, second data name information corresponding to the third field of the target form template is determined in the first data name information of the form data to be processed, and a field matching relationship is obtained; the third field is the field corresponding to the second data name information corresponding to the third data attribute information to be filled in the target form template;

[0008] Generate a smart form and audit items corresponding to the smart form according to the field matching relationship, the form data to be processed and the target form template;

[0009] The audit items corresponding to the smart form and the smart form are simultaneously displayed to the auditor, and the audit result input by the auditor through human-computer interaction is received; the audit result includes audit pass or audit fail;

[0010] When the audit result is passed, the smart form is archived and copied to the target staff according to preset conditions.

[0011] Furthermore, before using the intelligent matching algorithm to match in the template database, it also includes:

[0012] One-hot encoding is performed on the first data name information corresponding to the first field in the form data to be processed to obtain first encoding information corresponding to each first data name information.

[0013] Furthermore, the method further includes: after receiving the form confirmation instruction, determining a target form template according to the form confirmation instruction.

[0014] Further, according to the form data to be processed, a smart matching algorithm is used to perform matching in a template database to determine a target form template corresponding to the form data to be processed, including:

[0015] Extracting first coding information of the form data to be processed in sequence, and obtaining first coding information corresponding to a plurality of form data to be processed;

[0016] A form template is randomly selected from the template database, and the one-hot encoding of the third data attribute information corresponding to the third field in the form template is extracted to obtain the second encoding information corresponding to each third data attribute information in the form template; wherein the one-hot encoding of the third data attribute information is data pre-stored in the template database;

[0017] Determining the degree of matching between the to-be-processed form data and the form template according to the first coding information and the second coding information; the higher the degree of matching, the better;

[0018] Traverse all form templates in the template database to determine the matching degree between the form data to be processed and each form template;

[0019] According to the matching degree between the form data to be processed and each form template, the target form template corresponding to the form data to be processed is determined.

[0020] Further, determining the matching degree between the to-be-processed form data and the form template according to the first coding information and the second coding information includes:

[0021] According to the first coding information and the second coding information, data sequence correction is performed to obtain sorted first coding information and sorted second coding information respectively;

[0022] The first eigenvector is constructed by using the sorted first coded information and the second eigenvector is constructed by using the sorted second coded information, the similarity between the first eigenvector and the second eigenvector is obtained, and the matching degree between the form data to be processed and the form template is obtained.

[0023] Further, according to the first coding information and the second coding information, data sequence correction is performed to obtain sorted first coding information and sorted second coding information respectively, including:

[0024] Set counter t=1;

[0025] For the tth first coded information, obtaining the cosine similarity between the first coded information and each second coded information;

[0026] According to the cosine similarity between the first coded information and each second coded information, determining the second coded information with the largest cosine similarity as the t-th second coded information;

[0027] Determine whether the count value of counter t is equal to the total number of first coded information. If so, obtain the sorted first coded information and the sorted second coded information. Otherwise, add one to the count value of counter t and return to the step of obtaining the cosine similarity between the first coded information and each second coded information.

[0028] Further, the first feature vector is constructed by using the sorted first coding information and the second feature vector is constructed by using the sorted second coding information, the similarity between the first feature vector and the second feature vector is obtained, and the matching degree between the form data to be processed and the form template is obtained, including:

[0029] constructing a first feature vector using the sorted first encoding information and constructing a second feature vector using the sorted second encoding information;

[0030] The similarity between the first feature vector and the second feature vector is obtained, and the matching degree between the form data to be processed and the form template is obtained as follows:

[0031]

[0032] Among them, Sim represents the matching degree between the form data to be processed and the form template, and x n represents the nth dimension parameter in the first eigenvector, y n represents the nth dimension parameter in the second eigenvector, and N represents the total number of parameter dimensions in the first eigenvector.

[0033] Further, determining the matching degree between the to-be-processed form data and the form template according to the first coding information and the second coding information includes:

[0034] According to the first coding information and the second coding information, data sequence correction is performed to obtain sorted first coding information and sorted second coding information respectively;

[0035] constructing a first feature vector using the sorted first encoding information and constructing a second feature vector using the sorted second encoding information;

[0036] Constructing input data of a pre-trained neural network model using the first feature vector and the second feature vector to obtain output data of the neural network model and obtain a matching degree between the form data to be processed and the form template;

[0037] The output data of the neural network model is the probability that the first feature vector and the second feature vector are the same data.

[0038] In a second aspect, the present invention provides an intelligent form generation device, including: a data acquisition module, an intelligent matching module, a field matching module, a form generation module, an audit module and a data storage module;

[0039] The data acquisition module is used to acquire the form data to be processed; the form data to be processed includes at least one first field, first data name information corresponding to the first field, at least one second field corresponding to the first field, and first data attribute information corresponding to the second field;

[0040] The intelligent matching module is used to match the form data to be processed in the template database using an intelligent matching algorithm to determine the target form template corresponding to the form data to be processed;

[0041] The field matching module is used to determine, according to the first field in the form data to be processed, the second data name information corresponding to the third field of the target form template in the first data name information of the form data to be processed, and obtain a field matching relationship; the third field is the field corresponding to the second data name information corresponding to the third data attribute information to be filled in the target form template;

[0042] The form generation module is used to generate a smart form and the audit items corresponding to the smart form according to the field matching relationship, the form data to be processed and the target form template;

[0043] The audit module is used to simultaneously display the audit items corresponding to the smart form and the smart form to the auditor, and receive the audit result input by the auditor through human-computer interaction; the audit result includes audit pass or audit fail;

[0044] The data storage module is used to archive the smart form when the audit result is passed, and copy the smart form to the target staff according to preset conditions.

[0045] In a third aspect, the present invention provides an intelligent form generation device, including a processor and a memory;

[0046] The memory stores computer-executable instructions;

[0047] The processor executes the computer-executable instructions stored in the memory, so that the processor executes the smart form generation method as described in the first aspect.

[0048] The present invention provides an intelligent form generation method, device and equipment, which can intelligently generate a form based on the form data to be processed by obtaining the form data to be processed, searching the form data to be processed in a template database, and then automatically filling in the fields, thereby reducing the requirements for the use of equipment, allowing staff to intelligently match and generate forms by transmitting text information, thereby improving the convenience of staff filling in form data and improving the efficiency of form filling. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0050] Figure 1 A flowchart of a smart form generation method provided by an embodiment of the present invention.

[0051] Figure 2 A schematic diagram of the structure of an intelligent form generating device provided by an embodiment of the present invention.

[0052] Figure 3 A schematic diagram of the structure of an intelligent form generating device provided in an embodiment of the present invention.

[0053] Among them, 201-data acquisition module, 202-intelligent matching module, 203-field matching module, 204-form generation module, 205-audit module, 206-data storage module.

[0054] The above drawings have shown clear embodiments of the present invention, which will be described in more detail below. These drawings and text descriptions are not intended to limit the scope of the present invention in any way, but to illustrate the concept of the present invention for those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0055] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. Instead, they are merely examples of devices and methods consistent with some aspects of the present invention as detailed in the appended claims.

[0056] The embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0057] like Figure 1 As shown, the present invention provides a smart form generation method, comprising:

[0058] S101, obtaining form data to be processed; the form data to be processed includes at least one first field, first data name information corresponding to the first field, at least one second field corresponding to the first field, and first data attribute information corresponding to the second field.

[0059] The form data to be processed can be information in different forms such as text information, table information, etc. sent by staff through the network, wherein the first field and the second field are separated by a first separator (that is, the first field, the first separator and the second field constitute a triplet), and different triplets are separated by a second separator (that is, triplet, second separator, triplet...), so that the first field and the second field can be quickly identified by detecting the first separator and the second separator, which not only makes it convenient for staff to fill in data, but also effectively improves data recognition effect and reduces the complexity of data recognition.

[0060] S102: According to the form data to be processed, a smart matching algorithm is used to perform matching in a template database to determine a target form template corresponding to the form data to be processed.

[0061] Various form templates are pre-stored in the template database. After the staff enters the data, they need to find the form template they want to enter, thereby realizing intelligent form filling.

[0062] Optionally, the intelligent matching algorithm can be set to a deep learning algorithm. By introducing the deep learning algorithm, automatic recognition and matching of data can be achieved, which can effectively replace manual intelligent filling of forms.

[0063] S103. According to the first field in the form data to be processed, determine the second data name information that corresponds one-to-one to the third field of the target form template in the first data name information of the form data to be processed, and obtain a field matching relationship; the third field is the field corresponding to the second data name information corresponding to the third data attribute information to be filled in the target form template.

[0064] In the process of matching the form data to be processed, the third field corresponding to each first field can be determined, and then the relationship can be directly pulled to obtain the field matching relationship.

[0065] S104, generating a smart form and audit items corresponding to the smart form according to the field matching relationship, the form data to be processed and the target form template;

[0066] Generating a smart form based on the field matching relationship, the form data to be processed and the target form template may include: based on the field matching relationship, filling the first data attribute information corresponding to the second field corresponding to the first field into the fourth field corresponding to the third field, thereby realizing the filling of data attributes in the form and finally generating a smart form.

[0067] Generating audit items corresponding to the smart form may include: generating an audit task for the role of the auditor, so that the auditor can audit the correctness of the smart form, which can further ensure the accuracy of the data.

[0068] S105, displaying the audit items corresponding to the smart form and the smart form to the auditor at the same time, and receiving the audit result input by the auditor through human-computer interaction; the audit result includes audit pass or audit fail;

[0069] S106. When the audit result is passed, the smart form is archived and copied to the target staff according to preset conditions.

[0070] Optionally, when the audit result is failure to pass the audit, data anomaly information should be sent to the staff who fills in the form data to be processed to remind the staff to correct the data.

[0071] It is worth noting that, although the embodiment of the present invention provides an intelligent form filling method, staff are still allowed to fill in the form online and through electronic forms.

[0072] In the embodiment of the present invention, before using the intelligent matching algorithm to match in the template database, the method further includes:

[0073] One-hot encoding is performed on the first data name information corresponding to the first field in the form data to be processed to obtain first encoding information corresponding to each first data name information.

[0074] It is worth noting that the data name information is encoded here mainly for the convenience of the subsequent matching process, so other encoding methods can also be used for encoding.

[0075] In the embodiment of the present invention, the method further includes: after receiving the form confirmation instruction, determining the target form template according to the form confirmation instruction.

[0076] The embodiment of the present invention supports manual determination of a target form template, for example, when a unique code corresponding to a form template is found in the transmitted form data to be processed, the target form template is directly determined according to the unique code.

[0077] In an embodiment of the present invention, according to the form data to be processed, a smart matching algorithm is used to perform matching in a template database to determine a target form template corresponding to the form data to be processed, including:

[0078] Extracting first coding information of the form data to be processed in sequence, and obtaining first coding information corresponding to a plurality of form data to be processed;

[0079] A form template is randomly selected from the template database, and the one-hot encoding of the third data attribute information corresponding to the third field in the form template is extracted to obtain the second encoding information corresponding to each third data attribute information in the form template; wherein the one-hot encoding of the third data attribute information is data pre-stored in the template database;

[0080] Determining the degree of matching between the to-be-processed form data and the form template according to the first coding information and the second coding information; the higher the degree of matching, the better;

[0081] Traverse all form templates in the template database to determine the matching degree between the form data to be processed and each form template;

[0082] According to the matching degree between the form data to be processed and each form template, the target form template corresponding to the form data to be processed is determined.

[0083] In an embodiment of the present invention, determining the matching degree between the to-be-processed form data and the form template according to the first coding information and the second coding information includes:

[0084] According to the first coding information and the second coding information, data sequence correction is performed to obtain sorted first coding information and sorted second coding information respectively;

[0085] The first eigenvector is constructed by using the sorted first coded information and the second eigenvector is constructed by using the sorted second coded information, the similarity between the first eigenvector and the second eigenvector is obtained, and the matching degree between the form data to be processed and the form template is obtained.

[0086] In an embodiment of the present invention, data sequence correction is performed according to the first coding information and the second coding information to obtain sorted first coding information and sorted second coding information, respectively, including:

[0087] Set counter t=1;

[0088] For the tth first coded information, obtaining the cosine similarity between the first coded information and each second coded information;

[0089] According to the cosine similarity between the first coded information and each second coded information, determining the second coded information with the largest cosine similarity as the t-th second coded information;

[0090] Determine whether the count value of counter t is equal to the total number of first coded information. If so, obtain the sorted first coded information and the sorted second coded information. Otherwise, add one to the count value of counter t and return to the step of obtaining the cosine similarity between the first coded information and each second coded information.

[0091] In an embodiment of the present invention, the first feature vector is constructed by using the sorted first coding information and the second feature vector is constructed by using the sorted second coding information, the similarity between the first feature vector and the second feature vector is obtained, and the matching degree between the form data to be processed and the form template is obtained, including:

[0092] constructing a first feature vector using the sorted first encoding information and constructing a second feature vector using the sorted second encoding information;

[0093] The similarity between the first feature vector and the second feature vector is obtained, and the matching degree between the form data to be processed and the form template is obtained as follows:

[0094]

[0095] Among them, Sim represents the matching degree between the form data to be processed and the form template, and x n represents the nth dimension parameter in the first eigenvector, y n represents the nth dimension parameter in the second eigenvector, and N represents the total number of parameter dimensions in the first eigenvector.

[0096] In an embodiment of the present invention, determining the matching degree between the to-be-processed form data and the form template according to the first coding information and the second coding information includes:

[0097] According to the first coding information and the second coding information, data sequence correction is performed to obtain sorted first coding information and sorted second coding information respectively;

[0098] constructing a first feature vector using the sorted first encoding information and constructing a second feature vector using the sorted second encoding information;

[0099] Constructing input data of a pre-trained neural network model using the first feature vector and the second feature vector to obtain output data of the neural network model and obtain a matching degree between the form data to be processed and the form template;

[0100] The output data of the neural network model is the probability that the first feature vector and the second feature vector are the same data.

[0101] Optionally, the neural network model can be set to CNN (Convolutional Neural Networks), and the method for pre-training the neural network model can adopt the gradient descent method. A two-row data matrix is ​​constructed with the first eigenvector and the second eigenvector of the sample to store two types of data respectively, and the data matrix is ​​used as the input of CNN, and whether the two belong to the same form is used as the expected output (i.e., 1 if they belong to the same form, otherwise 0), so that CNN can be trained to output the probability of the same form, that is, the matching degree between the form data to be processed and the form template.

[0102] The gradient descent method has a technical problem of being easily trapped in a local optimum during the training process. Therefore, the embodiment of the present invention provides a variable learning rate to solve this problem, specifically:

[0103] η t+1 =η t +αη t (β||r t+1 ||-η t )

[0104]

[0105] Among them, η t represents the learning rate during the tth round of training, η t+1 represents the adjusted η t , α represents the first constant, β represents the second constant, r t+1 represents the intermediate variable, δ represents the auxiliary variable update coefficient, Indicates the differential symbol, E t represents the objective function value at the tth training, w t Represents the parameters of the tth training.

[0106] The variable learning rate can effectively adjust the learning speed of the algorithm before and after, thereby balancing the global search and the local search.

[0107] An intelligent form generation method provided by the present invention can intelligently generate a form based on the form data to be processed by acquiring form data to be processed, searching the acquired form data to be processed in a template database, and then automatically filling in fields, thereby reducing the requirements for the use of equipment, allowing staff to intelligently match and generate forms by transmitting text information, thereby improving the convenience of staff in filling in form data and improving the efficiency of filling in forms.

[0108] like Figure 2 As shown, an embodiment of the present invention provides an intelligent form generation device, including: a data acquisition module 201, an intelligent matching module 202, a field matching module 203, a form generation module 204, an audit module 205 and a data storage module 206;

[0109] The data acquisition module 201 is used to acquire the form data to be processed; the form data to be processed includes at least one first field, first data name information corresponding to the first field, at least one second field corresponding to the first field, and first data attribute information corresponding to the second field;

[0110] The intelligent matching module 202 is used to match the form data to be processed in the template database using an intelligent matching algorithm to determine the target form template corresponding to the form data to be processed;

[0111] The field matching module 203 is used to determine, according to the first field in the form data to be processed, the second data name information corresponding to the third field of the target form template in the first data name information of the form data to be processed, and obtain a field matching relationship; the third field is the field corresponding to the second data name information corresponding to the third data attribute information to be filled in the target form template;

[0112] The form generation module 204 is used to generate a smart form and the audit items corresponding to the smart form according to the field matching relationship, the form data to be processed and the target form template;

[0113] The review module 205 is used to simultaneously display the review items corresponding to the smart form and the smart form to the reviewer, and receive the review result input by the reviewer through human-computer interaction; the review result includes review pass or review fail;

[0114] The data storage module 206 is used to archive the smart form when the audit result is passed, and copy the smart form to the target staff according to preset conditions.

[0115] The intelligent form generation device provided in the embodiment of the present invention can implement the method and technical solution described in Embodiment 1, and its principle and beneficial effects are similar, which will not be described in detail here.

[0116] like Figure 3 As shown, an embodiment of the present invention provides an intelligent form generating device, including a memory 301 and a processor 302 , and the memory 301 and the processor 302 are connected to each other via a bus 303 .

[0117] Memory 301 stores computer-executable instructions.

[0118] The processor 302 executes the computer-executable instructions stored in the memory, so that the processor executes a smart form generation method as described in Example 1.

[0119] For example, the memory may include, but is not limited to, random access memory (RAM), read only memory (ROM), flash memory, first input first output (FIFO) and / or first in last out (FILO) memory, etc. Specifically, the processor may include one or more processing cores, such as a 4-core processor, an 8-core processor, etc. The processor may be implemented in at least one hardware form of DSP (Digital Signal Processing), FPGA (Field-Programmable Gate Array), and PLA (Programmable Logic Array). At the same time, the processor may also include a main processor and a coprocessor. The main processor is a processor for processing data in the awake state, also known as a CPU (Central Processing Unit). The coprocessor is a low-power processor for processing data in the standby state.

[0120] Example 4

[0121] This embodiment provides a computer-readable storage medium, in which computer-executable instructions are stored. When the computer-executable instructions are executed by a processor, they are used to implement a smart form generation method as described in Embodiment 1.

[0122] Example 5

[0123] This embodiment provides a computer program product, including a computer program. When the computer program is executed by a processor, the computer program implements a smart form generation method as described in Embodiment 1.

[0124] Those skilled in the art will readily appreciate other embodiments of the present invention after considering the specification and practicing the invention disclosed herein. The present invention is intended to cover any variations, uses or adaptations of the present invention that follow the general principles of the present invention and include common knowledge or customary techniques in the art that are not disclosed by the present invention. It should be understood that the present invention is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from the scope thereof. The scope of the present invention is limited only by the appended claims.

Claims

1. A smart form generation method, characterized in that: include: Get the form data to be processed; The form data to be processed includes at least one first field, first data name information corresponding to the first field, at least one second field corresponding to the first field, and first data attribute information corresponding to the second field; According to the form data to be processed, a smart matching algorithm is used to match in a template database to determine a target form template corresponding to the form data to be processed; According to the first field in the form data to be processed, second data name information corresponding to the third field of the target form template is determined in the first data name information of the form data to be processed, and a field matching relationship is obtained; the third field is the field corresponding to the second data name information corresponding to the third data attribute information to be filled in the target form template; Generate a smart form and audit items corresponding to the smart form according to the field matching relationship, the form data to be processed and the target form template; The audit items corresponding to the smart form and the smart form are simultaneously displayed to the auditor, and the audit result input by the auditor through human-computer interaction is received; the audit result includes audit pass or audit fail; When the audit result is passed, the smart form is archived and copied to the target staff according to preset conditions.

2. The intelligent form generation method according to claim 1, characterized in that: Before using the intelligent matching algorithm to match in the template database, it also includes: One-hot encoding is performed on the first data name information corresponding to the first field in the form data to be processed to obtain first encoding information corresponding to each first data name information.

3. The intelligent form generation method according to claim 1, characterized in that: Also includes: After receiving the form confirmation instruction, the target form template is determined according to the form confirmation instruction.

4. The intelligent form generation method according to claim 2, characterized in that: According to the form data to be processed, a smart matching algorithm is used to match in a template database to determine a target form template corresponding to the form data to be processed, including: Extracting first coding information of the form data to be processed in sequence, and obtaining first coding information corresponding to a plurality of form data to be processed; A form template is randomly selected from the template database, and the one-hot encoding of the third data attribute information corresponding to the third field in the form template is extracted to obtain the second encoding information corresponding to each third data attribute information in the form template; wherein the one-hot encoding of the third data attribute information is data pre-stored in the template database; Determining the degree of matching between the to-be-processed form data and the form template according to the first coding information and the second coding information; the higher the degree of matching, the better; Traverse all form templates in the template database to determine the matching degree between the form data to be processed and each form template; According to the matching degree between the form data to be processed and each form template, the target form template corresponding to the form data to be processed is determined.

5. The intelligent form generation method according to claim 4, characterized in that: Determining the matching degree between the to-be-processed form data and the form template according to the first coding information and the second coding information includes: According to the first coding information and the second coding information, data sequence correction is performed to obtain sorted first coding information and sorted second coding information respectively; The first eigenvector is constructed by using the sorted first coded information and the second eigenvector is constructed by using the sorted second coded information, the similarity between the first eigenvector and the second eigenvector is obtained, and the matching degree between the form data to be processed and the form template is obtained.

6. The intelligent form generation method according to claim 5, characterized in that: According to the first coding information and the second coding information, data sequence correction is performed to obtain sorted first coding information and sorted second coding information respectively, including: Set counter t=1; For the tth first coded information, obtaining the cosine similarity between the first coded information and each second coded information; According to the cosine similarity between the first coded information and each second coded information, determining the second coded information with the largest cosine similarity as the t-th second coded information; Determine whether the count value of counter t is equal to the total number of first coded information. If so, obtain the sorted first coded information and the sorted second coded information. Otherwise, add one to the count value of counter t and return to the step of obtaining the cosine similarity between the first coded information and each second coded information.

7. The intelligent form generation method according to claim 5, characterized in that: The first feature vector is constructed by using the sorted first coding information and the second feature vector is constructed by using the sorted second coding information, and the similarity between the first feature vector and the second feature vector is obtained to obtain the matching degree between the form data to be processed and the form template, including: constructing a first feature vector using the sorted first encoding information and constructing a second feature vector using the sorted second encoding information; The similarity between the first feature vector and the second feature vector is obtained, and the matching degree between the form data to be processed and the form template is obtained as follows: Among them, Sim represents the matching degree between the form data to be processed and the form template, and x n represents the nth dimension parameter in the first eigenvector, y n represents the nth dimension parameter in the second eigenvector, and N represents the total number of parameter dimensions in the first eigenvector.

8. The intelligent form generation method according to claim 4, characterized in that: Determining the matching degree between the to-be-processed form data and the form template according to the first coding information and the second coding information includes: According to the first coding information and the second coding information, data sequence correction is performed to obtain sorted first coding information and sorted second coding information respectively; constructing a first feature vector using the sorted first encoding information and constructing a second feature vector using the sorted second encoding information; Constructing input data of a pre-trained neural network model using the first feature vector and the second feature vector to obtain output data of the neural network model and obtain a matching degree between the form data to be processed and the form template; The output data of the neural network model is the probability that the first feature vector and the second feature vector are the same data.

9. An intelligent form generation device, characterized in that: include: Data acquisition module, intelligent matching module, field matching module, form generation module, review module and data storage module; The data acquisition module is used to acquire the form data to be processed; The form data to be processed includes at least one first field, first data name information corresponding to the first field, at least one second field corresponding to the first field, and first data attribute information corresponding to the second field; The intelligent matching module is used to match the form data to be processed in the template database using an intelligent matching algorithm to determine the target form template corresponding to the form data to be processed; The field matching module is used to determine, according to the first field in the form data to be processed, the second data name information corresponding to the third field of the target form template in the first data name information of the form data to be processed, and obtain a field matching relationship; the third field is the field corresponding to the second data name information corresponding to the third data attribute information to be filled in the target form template; The form generation module is used to generate a smart form and the audit items corresponding to the smart form according to the field matching relationship, the form data to be processed and the target form template; The audit module is used to simultaneously display the audit items corresponding to the smart form and the smart form to the auditor, and receive the audit result input by the auditor through human-computer interaction; the audit result includes audit pass or audit fail; The data storage module is used to archive the smart form when the audit result is passed, and copy the smart form to the target staff according to preset conditions.

10. An intelligent form generation device, characterized in that: including a processor and a memory; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory, so that the processor executes the smart form generation method according to any one of claims 1 to 8.

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