CN116911270A - Form template generation method, apparatus, device, storage medium and program product - Google Patents
Form template generation method, apparatus, device, storage medium and program product Download PDFInfo
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Abstract
The present application relates to a form template generation method, apparatus, device, storage medium, and program product. The method comprises the following steps: form filling information and form demand information of a target form template are obtained; the form requirement information comprises requirement content of a target form by a user; determining form core information according to the form demand information; and constructing a target form template according to the form filling information and the form core information. The method can process the acquired form filling information and form requirement information, then can automatically generate a form template, and can clearly know which form to fill and how to fill the form when the form requirement party fills the automatically generated form template, thereby reducing form mistakes.
Description
Technical Field
The present application relates to the field of financial technology, and in particular, to a form template generating method, apparatus, device, storage medium, and program product.
Background
At present, after enterprises carry out digital transformation, various technological project tasks in a financial and technological system are increased, and forms such as development, test and maintenance are also remarkably increased. Among them, development test requirements and maintenance requirements of different types of scientific projects are different, so different form requirements are generated.
The existing forms are usually manually maintained by a party handling the forms using Excel forms and version control tools, which easily causes the form demander to make it unclear which form to fill and how to fill the form, thus presenting a form dispatching error problem.
Disclosure of Invention
In view of the foregoing, it is desirable to provide a form generation method, apparatus, device, storage medium, and program product capable of solving the problem of labor-hour errors.
In a first aspect, the present application provides a form template generation method. The method comprises the following steps:
form filling information and form demand information of a target form template are obtained; the form requirement information comprises requirement content of a target form by a user;
determining form core information according to the form demand information;
and constructing a target form template according to the form filling information and the form core information.
In one embodiment, determining form core information from the form requirement information includes:
and inputting the form demand information into a pre-trained information recognition model to obtain form core information output by the information recognition model.
In one embodiment, the method further comprises:
constructing a training input sample and a training output sample; the training input samples comprise sample requirement information, and the training output samples comprise field items for constructing a form template;
and performing model training according to the training input sample and the training output sample to obtain an information identification model.
In one embodiment, the method further comprises:
obtaining a test sample of an information identification model;
constructing a test form template according to the test sample and the information identification model;
and acquiring an evaluation value of the test form template, and updating the information identification model according to the evaluation value of the test form template.
In one embodiment, constructing a test form template from a test sample and an information recognition model includes:
inputting the test sample into the information identification model to obtain a test result output by the information identification model;
and constructing a test form template according to the test result.
In one embodiment, the method further comprises:
determining the importance degree of each training output sample through an information gain evaluation algorithm;
determining an optimized output sample according to the importance degree;
and updating the information identification model according to the optimized output sample of the training input sample.
In a second aspect, the application further provides a form template generating device. The device comprises:
the information acquisition module is used for acquiring form filling information and form demand information of the target form template; the form requirement information comprises requirement content of a target form by a user;
the information determining module is used for determining form core information according to the form demand information;
the template construction module is used for constructing a target form template by form filling information and form core information.
In a third aspect, the present application also provides a computer device. The computer device comprises a memory and a processor, wherein the memory stores a computer program, and the processor realizes the following steps when executing the computer program:
form filling information and form demand information of a target form template are obtained; the form requirement information comprises requirement content of a target form by a user;
determining form core information according to the form demand information;
and constructing a target form template according to the form filling information and the form core information.
In a fourth aspect, the present application also provides a computer-readable storage medium. The computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of:
form filling information and form demand information of a target form template are obtained; the form requirement information comprises requirement content of a target form by a user;
determining form core information according to the form demand information;
and constructing a target form template according to the form filling information and the form core information.
In a fifth aspect, the present application also provides a computer program product. The computer program product described above, comprising a computer program which, when executed by a processor, performs the steps of:
form filling information and form demand information of a target form template are obtained; the form requirement information comprises requirement content of a target form by a user;
determining form core information according to the form demand information;
and constructing a target form template according to the form filling information and the form core information.
The method, the device, the equipment, the storage medium and the program product for generating the form template acquire the form filling information and the form demand information of the target form template, then determine the form core information according to the form demand information, and finally construct the target form template according to the form filling information and the form core information.
Drawings
FIG. 1 is an application environment diagram of form template generation in one embodiment;
FIG. 2 is a flow diagram of form template generation in one embodiment;
FIG. 3 is a flow diagram of determining an information recognition model in one embodiment;
FIG. 4 is a flow diagram of updating an information recognition model in one embodiment;
FIG. 5 is a schematic flow chart of another embodiment for constructing a test form template;
FIG. 6 is a flowchart of another embodiment of optimizing a sample output update model;
FIG. 7 is a flow diagram of form template generation in another embodiment;
FIG. 8 is a block diagram of the structure of form template generation in one embodiment;
fig. 9 is an internal structural diagram of a computer device in one embodiment.
Detailed Description
The present application will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present application more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the application.
First, before the technical scheme of the embodiment of the present application is specifically described, a description is first given of a technical background on which the embodiment of the present application is based.
At present, after enterprises get cloud and digital transformation is carried out, various technological project tasks are increased, work orders such as development, test and maintenance are also remarkably increased, and especially in a financial and technological system, different project demands are different, so that different form demands are generated. The existing forms in enterprises are usually manually maintained by one party processing the forms by using an Excel form and a version control tool, the quantity of the forms is numerous, the projects are complicated, details of which form should be filled by a demand party, how to fill in and the like are unclear, so that the actual demands are confused by the worker staff, communication cost is increased because of the ambiguous filling of the demands in the processing process of the work orders, and the processing flow of the work orders is further prolonged.
The form template generation method provided by the embodiment of the application can be applied to an application environment shown in fig. 1. Wherein the terminal 102 communicates with the server 104 via a network. The data storage system may store data that the server 104 needs to process. The data storage system may be integrated on the server 104 or may be located on a cloud or other network server. The terminal 102 first obtains the form filling information and the form requirement information of the target form template, then determines form core information according to the form requirement information, and finally constructs the target form template according to the form filling information and the form core information. The terminal 102 may be, but not limited to, various personal computers, notebook computers, smart phones, tablet computers, internet of things devices, and portable wearable devices, where the internet of things devices may be smart speakers, smart televisions, smart air conditioners, smart vehicle devices, and the like. The portable wearable device may be a smart watch, smart bracelet, headset, or the like. The server 104 may be implemented as a stand-alone server or as a server cluster of multiple servers.
In one embodiment, as shown in fig. 2, a form template generating method is provided, and the method is applied to the terminal in fig. 1 for illustration, and includes the following steps:
step 201, form filling information and form demand information of a target form template are obtained; the form requirement information includes the user's requirement content for the target form.
The target form template refers to a form which needs to be filled in by a form demander; the form filling information refers to information which needs to be filled by a demander in a target form template, and the form filling information can be header information of a form, a system name, a system IP and the like; the required content of the target form refers to the actual requirement of the form of the requiring party, and the required content of the target form can be a sentence input by the requiring party or can be the required content generated according to the selection of the requiring party.
In the embodiment of the application, after receiving a request for generating a form template sent by a demand party, the terminal can input form filling information and form demand information through an input box of the demand party on the interface by displaying the interface to the demand party, or the terminal can input voice to the demand party by displaying a voice interface, and the terminal can obtain the form filling information and the form demand information through voice recognition according to the voice input by the demand party.
And step 202, determining form core information according to the form requirement information.
The form core information refers to core filling content of the form, namely core requirements of the form, and can be determined according to a neural network model or a deep learning model.
In the embodiment of the application, the terminal firstly acquires the form requirement information, and then performs keyword extraction, word segmentation, entity identification and other processes on the acquired form requirement information to obtain the form core information corresponding to the form requirement information.
And 203, constructing a target form template according to the form filling information and the form core information.
The target form template refers to a form filled in by a demand party and can be used for performing form dispatching work according to the target form template; the target form template may be a form template or an html form template.
In the embodiment of the application, the terminal firstly processes the acquired form demand information to obtain the form core information corresponding to the form demand information, and then constructs and processes the acquired form filling information and the form core information to obtain the target form template. The target form template can be constructed through a Tranformer model or through a form construction program.
In the form template generation method, firstly, the form filling information and the form requirement information of the target form template are acquired, then the form core information is determined according to the form requirement information, and finally the target form template is constructed according to the form filling information and the form core information.
The above embodiments describe the process of form template generation, and the following describes the steps in detail.
The step of determining the form core information according to the form requirement information may include: and inputting the form demand information into a pre-trained information recognition model to obtain form core information output by the information recognition model.
The information identification model is used for carrying out identification processing on the form demand information through an internal algorithm to obtain form core information corresponding to the form demand information, and the information identification model can be a BERT model.
In the embodiment of the application, the terminal inputs the acquired form demand information into a pre-trained information identification model, and the information identification model carries out identification processing on the form demand information through an internal algorithm to obtain form core information output by the information identification model.
According to the form template generation method, firstly, the form demand information is input into the pre-trained information recognition model, and then the form core information is output by the information recognition model.
In one embodiment, as shown in fig. 3, before the form requirement information is input into the pre-trained information recognition model, the embodiment of the present application may further include the steps of:
step 301, constructing a training input sample and a training output sample; the training input samples include sample requirement information and the training output samples include field entries that construct a form template.
The sample requirement information refers to form type information required by the requirement party, and the sample requirement information is obtained empirically and can be a sentence or form type selected according to the requirement party; the field items of the form template refer to core fields constituting the form template, and the field items of the form template are also empirically derived.
In the embodiment of the application, a training input sample is constructed according to sample demand information, and a training output sample is constructed according to field items of a form template.
Illustratively, tables 1 and 2 are constructed training input samples and training output samples.
TABLE 1
TABLE 2
And 302, performing model training according to the training input sample and the training output sample to obtain an information identification model.
Model training is a process of setting model parameters until the model is optimally adapted to the training set.
In the embodiment of the application, the information recognition model is trained according to the set model parameters, and the model parameters are continuously adjusted according to the input sample and the output sample, so that the final information recognition model is obtained.
According to the form template generation method, firstly, the training input sample and the training output sample are constructed, then the model parameters are adjusted according to the training input sample and the training output sample, the information identification model is continuously trained, and the information identification model is obtained.
In one embodiment, as shown in fig. 4, after model training is completed, the embodiment of the present application may further include the following steps:
in step 401, a test sample of an information recognition model is obtained.
The test sample is a sample for testing the constructed information recognition model and is used for testing and training the constructed information recognition model.
In the embodiment of the application, the terminal can input the test sample to the demander through the display interface, the demander inputs the test sample through the input box on the interface, or the terminal can also input the voice through the display voice interface, and the terminal obtains the voice input by the user and carries out voice recognition to obtain the test sample.
Step 402, building a test form template according to the test sample and the information identification model.
The test form template is composed of form core information and form filling information output by the information identification model, and a form construction model, such as a transducer model, can be adopted for constructing the test form template.
In the embodiment of the application, a test sample is firstly input into an information identification model to be tested to obtain test form core information, and the test form core information and form filling information are input into a form construction model to obtain a test form template.
And step 403, acquiring an evaluation value of the test form template, and updating the information identification model according to the evaluation value of the test form template.
The evaluation value refers to a scoring value obtained by jointly scoring the generated test form template by the requiring party and the disposal party, and the updating refers to updating parameters of the information identification model, and pruning compression processing can be performed on the information identification model.
In the embodiment of the application, a test form template is constructed according to a test sample and an information identification model, then a demander and a disposal party score the test form template to obtain an evaluation value, then a terminal obtains the evaluation value, and the parameters in the information identification model are updated according to the evaluation value.
According to the form template generation method, the test sample of the information identification model is firstly obtained, then the test form template is constructed according to the test sample and the information identification model, finally the evaluation value of the test form template is obtained, and the information identification model is updated according to the evaluation value of the test form template.
The above embodiments describe the process of updating the information recognition model, and the construction of the test form template will be described in detail.
In one embodiment, as shown in fig. 5, the step of constructing a test form template according to the test sample and the information recognition model may include:
and step 501, inputting the test sample into the information identification model to obtain a test result output by the information identification model.
In the embodiment of the application, the terminal inputs the acquired test sample into the constructed information identification model, and the information identification model processes the test sample and outputs the test result.
Illustratively, table 3 is a test sample and test results:
TABLE 3 Table 3
Step 502, building a test form template according to the test result.
In the embodiment of the application, the terminal firstly acquires the form filling information, and then inputs the test result output by the information identification model and the acquired form filling information into the transducer model to obtain the test form template.
According to the form template generation method, firstly, a test sample is input into an information identification model to obtain a test result output by the information identification model, and then, a test form template is constructed according to the test result. According to the embodiment of the application, the test form template is constructed according to the test result output by the information identification model, so that the information identification model is conveniently optimized based on the test form template.
In one embodiment, as shown in fig. 6, after testing the information recognition model, the embodiment of the present application may further include the following steps:
in step 601, the importance degree of each training output sample is determined through an information gain evaluation algorithm.
The information gain evaluation algorithm evaluates importance of form core information output by the information identification model.
In the embodiment of the application, a terminal acquires each training output sample, carries out importance evaluation on each training output sample by using an information gain evaluation algorithm to obtain an evaluation value, and then determines the evaluation value as the importance degree of each training output sample.
And step 602, determining an optimized output sample according to the importance degree.
Wherein, the optimization refers to preferentially outputting training output samples with high importance when the output samples are too many.
In the embodiment of the application, the terminal determines the importance degree of each training output sample according to the evaluation value, and outputs the optimized output sample according to the importance degree of each training output sample when the training samples output by the information identification model are too many.
Illustratively, the output samples and the optimized output samples are shown in table 4.
TABLE 4 Table 4
Step 603, updating the information recognition model according to the optimized output samples of the training input samples.
In the embodiment of the application, after the optimized output samples are output according to the importance degree of each training output sample, the information recognition model is updated according to the optimized output samples of the training input samples to obtain the updated information recognition model.
According to the form template generation method, the importance degree of each training output sample is determined through the information gain evaluation algorithm, the optimized output sample is determined according to the importance degree, and finally the information identification model is updated according to the optimized output sample of the training input sample. According to the embodiment of the application, the form core information is output through the importance degree of the information gain evaluation form core information, so that the information identification model is optimized, and the information identification model is more accurate in output, faster in identification speed and higher in efficiency.
In one embodiment, as shown in fig. 7, a form template generation method is provided, which may include the steps of:
in step 701, training input samples and training output samples are constructed.
And step 702, performing model training according to the training input sample and the training output sample to obtain an information identification model.
In step 703, a test sample of the information recognition model is obtained.
Step 704, building a test form template according to the test sample and the information identification model.
Step 705, obtaining the evaluation value of the test form template, and updating the information identification model according to the evaluation value of the test form template.
In step 706, the importance level of each training output sample is determined by the information gain evaluation algorithm.
And step 707, determining an optimized output sample according to the importance level.
Step 708, updating the information recognition model according to the optimized output samples of the training input samples.
Step 709, obtaining form filling information and form requirement information of the target form template.
And 710, inputting the form requirement information into a pre-trained information recognition model to obtain form core information output by the information recognition model.
And 711, constructing a target form template according to the form filling information and the form core information.
According to the form template generation method, firstly, a training input sample and a training output sample are constructed, and model training is carried out according to the training input sample and the training output sample, so that an information identification model is obtained. Then, carrying out information identification model test and updating: and obtaining a test sample of the information identification model, and constructing a test form template according to the test sample and the information identification model. And then optimizing an information identification model: and acquiring an evaluation value of the test form template, updating the information recognition model according to the evaluation value of the test form template, determining the importance degree of each training output sample through an information gain evaluation algorithm, determining an optimized output sample according to the importance degree, updating the information recognition model according to the optimized output sample of the training input sample, and finally constructing a final information recognition model.
In practical application, form filling information and form demand information of a target form template are acquired, and the form demand information is input into a pre-trained information identification model to obtain form core information output by the information identification model.
The embodiment of the application processes the acquired form filling information and form demand information, then can automatically generate the form template, and can clearly know which form to fill and how to fill the form when the form demand party fills the form template automatically generated, thereby reducing form dispatching errors, and outputting form core information through the importance degree of the information gain evaluation form core information, optimizing the information identification model, and ensuring that the output is more accurate, the identification speed is faster and the efficiency is higher.
It should be understood that, although the steps in the flowcharts related to the embodiments described above are sequentially shown as indicated by arrows, these steps are not necessarily sequentially performed in the order indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in the flowcharts described in the above embodiments may include a plurality of steps or a plurality of stages, which are not necessarily performed at the same time, but may be performed at different times, and the order of the steps or stages is not necessarily performed sequentially, but may be performed alternately or alternately with at least some of the other steps or stages.
Based on the same inventive concept, the embodiment of the application also provides a form template generating device for realizing the above related form template generating method. The implementation of the solution provided by the device is similar to the implementation described in the above method, so the specific limitation in the embodiments of the form template generating device or devices provided below may refer to the limitation of the form template generating method hereinabove, and will not be repeated herein.
In one embodiment, as shown in fig. 8, there is provided a form template generating apparatus including:
the information acquisition module 801 is configured to acquire form filling information and form requirement information of a target form template; the form requirement information includes the user's requirement content for the target form.
The information determining module 802 is configured to determine form core information according to the form requirement information.
The template construction module 803 is configured to construct a target form template according to the form filling information and the form core information.
In one embodiment, the information determining module 802 further includes:
the form core information processing method is used for inputting the form demand information into the pre-trained information recognition model to obtain the form core information output by the information recognition model.
In one embodiment, the form template generating device further includes:
the field item construction module is used for constructing a training input sample and a training output sample; the training input samples comprise sample requirement information, and the training output samples comprise field items for constructing a form template;
and the model training module is used for carrying out model training according to the training input sample and the training output sample to obtain an information identification model.
In one embodiment, the form template generating device further includes:
the test sample acquisition module is used for acquiring a test sample of the information identification model;
the test form template construction module is used for constructing a test form template according to the test sample and the information identification model;
and the model updating module is used for acquiring the evaluation value of the test form template and updating the information identification model according to the evaluation value of the test form template.
In one embodiment, a test form template building module includes:
the test result determining submodule is used for inputting the test sample into the information identification model to obtain a test result output by the information identification model;
and the form template construction submodule is used for constructing a test form template according to the test result.
In one embodiment, the form template generating device further includes:
the importance degree determining module is used for determining the importance degree of each training output sample through an information gain evaluation algorithm;
the sample optimizing module is used for determining an optimized output sample according to the importance degree;
and the model optimization module is used for updating the information identification model according to the optimized output sample of the training input sample.
The respective modules in the form template generating apparatus described above may be implemented in whole or in part by software, hardware, or a combination thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.
In one embodiment, a computer device is provided, which may be a terminal, and the internal structure thereof may be as shown in fig. 9. The computer device includes a processor, a memory, an input/output interface, a communication interface, a display unit, and an input means. The processor, the memory and the input/output interface are connected through a system bus, and the communication interface, the display unit and the input device are connected to the system bus through the input/output interface. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The input/output interface of the computer device is used to exchange information between the processor and the external device. The communication interface of the computer device is used for carrying out wired or wireless communication with an external terminal, and the wireless mode can be realized through WIFI, a mobile cellular network, NFC (near field communication) or other technologies. The computer program is executed by a processor to implement a form template generation method.
It will be appreciated by persons skilled in the art that the architecture shown in fig. 9 is merely a block diagram of some of the architecture relevant to the present inventive arrangements and is not limiting as to the computer device to which the present inventive arrangements are applicable, and that a particular computer device may include more or fewer components than shown, or may combine some of the components, or have a different arrangement of components.
In one embodiment, a computer device is provided comprising a memory and a processor, the memory having stored therein a computer program, the processor when executing the computer program performing the steps of:
form filling information and form demand information of a target form template are obtained; the form requirement information comprises requirement content of a target form by a user;
determining form core information according to the form demand information;
and constructing a target form template according to the form filling information and the form core information.
In one embodiment, the processor when executing the computer program further performs the steps of:
in one embodiment, determining form core information from the form requirement information includes:
and inputting the form demand information into a pre-trained information recognition model to obtain form core information output by the information recognition model.
In one embodiment, the processor when executing the computer program further performs the steps of:
constructing a training input sample and a training output sample; the training input samples comprise sample requirement information, and the training output samples comprise field items for constructing a form template;
and performing model training according to the training input sample and the training output sample to obtain an information identification model.
In one embodiment, the processor when executing the computer program further performs the steps of:
obtaining a test sample of an information identification model;
constructing a test form template according to the test sample and the information identification model;
and acquiring an evaluation value of the test form template, and updating the information identification model according to the evaluation value of the test form template.
In one embodiment, the processor when executing the computer program further performs the steps of:
inputting the test sample into the information identification model to obtain a test result output by the information identification model;
and constructing a test form template according to the test result.
In one embodiment, the processor when executing the computer program further performs the steps of:
determining the importance degree of each training output sample through an information gain evaluation algorithm;
determining an optimized output sample according to the importance degree;
and updating the information identification model according to the optimized output sample of the training input sample.
In one embodiment, a computer readable storage medium is provided having a computer program stored thereon, which when executed by a processor, performs the steps of:
form filling information and form demand information of a target form template are obtained; the form requirement information comprises requirement content of a target form by a user;
determining form core information according to the form demand information;
and constructing a target form template according to the form filling information and the form core information.
In one embodiment, the computer program when executed by the processor further performs the steps of:
and inputting the form demand information into a pre-trained information recognition model to obtain form core information output by the information recognition model.
In one embodiment, the computer program when executed by the processor further performs the steps of:
constructing a training input sample and a training output sample; the training input samples comprise sample requirement information, and the training output samples comprise field items for constructing a form template;
and performing model training according to the training input sample and the training output sample to obtain an information identification model.
In one embodiment, the computer program when executed by the processor further performs the steps of:
obtaining a test sample of an information identification model;
constructing a test form template according to the test sample and the information identification model;
and acquiring an evaluation value of the test form template, and updating the information identification model according to the evaluation value of the test form template.
In one embodiment, the computer program when executed by the processor further performs the steps of:
inputting the test sample into the information identification model to obtain a test result output by the information identification model;
and constructing a test form template according to the test result.
In one embodiment, the computer program when executed by the processor further performs the steps of:
determining the importance degree of each training output sample through an information gain evaluation algorithm;
determining an optimized output sample according to the importance degree;
and updating the information identification model according to the optimized output sample of the training input sample.
In one embodiment, a computer program product is provided comprising a computer program which, when executed by a processor, performs the steps of:
form filling information and form demand information of a target form template are obtained; the form requirement information comprises requirement content of a target form by a user;
determining form core information according to the form demand information;
and constructing a target form template according to the form filling information and the form core information.
In one embodiment, the computer program when executed by the processor further performs the steps of:
and inputting the form demand information into a pre-trained information recognition model to obtain form core information output by the information recognition model.
In one embodiment, the computer program when executed by the processor further performs the steps of:
constructing a training input sample and a training output sample; the training input samples comprise sample requirement information, and the training output samples comprise field items for constructing a form template;
and performing model training according to the training input sample and the training output sample to obtain an information identification model.
In one embodiment, the computer program when executed by the processor further performs the steps of:
obtaining a test sample of an information identification model;
constructing a test form template according to the test sample and the information identification model;
and acquiring an evaluation value of the test form template, and updating the information identification model according to the evaluation value of the test form template.
In one embodiment, the computer program when executed by the processor further performs the steps of:
inputting the test sample into the information identification model to obtain a test result output by the information identification model;
and constructing a test form template according to the test result.
In one embodiment, the computer program when executed by the processor further performs the steps of:
determining the importance degree of each training output sample through an information gain evaluation algorithm;
determining an optimized output sample according to the importance degree;
and updating the information identification model according to the optimized output sample of the training input sample.
It should be noted that, the user information (including but not limited to user equipment information, user personal information, etc.) and the data (including but not limited to data for analysis, stored data, presented data, etc.) related to the present application are information and data authorized by the user or sufficiently authorized by each party, and the collection, use and processing of the related data need to comply with the related laws and regulations and standards of the related country and region.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, database, or other medium used in embodiments provided herein may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical Memory, high density embedded nonvolatile Memory, resistive random access Memory (ReRAM), magnetic random access Memory (Magnetoresistive Random Access Memory, MRAM), ferroelectric Memory (Ferroelectric Random Access Memory, FRAM), phase change Memory (Phase Change Memory, PCM), graphene Memory, and the like. Volatile memory can include random access memory (Random Access Memory, RAM) or external cache memory, and the like. By way of illustration, and not limitation, RAM can be in the form of a variety of forms, such as static random access memory (Static Random Access Memory, SRAM) or dynamic random access memory (Dynamic Random Access Memory, DRAM), and the like. The databases referred to in the embodiments provided herein may include at least one of a relational database and a non-relational database. The non-relational database may include, but is not limited to, a blockchain-based distributed database, and the like. The processor referred to in the embodiments provided in the present application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic unit, a data processing logic unit based on quantum computing, or the like, but is not limited thereto.
The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The foregoing examples illustrate only a few embodiments of the application and are described in detail herein without thereby limiting the scope of the application. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the application, which are all within the scope of the application. Accordingly, the scope of the application should be assessed as that of the appended claims.
Claims (10)
1. A form template generation method, the method comprising:
form filling information and form demand information of a target form template are obtained; the form requirement information comprises requirement content of a user on the target form;
determining form core information according to the form demand information;
and constructing the target form template according to the form filling information and the form core information.
2. The method of claim 1, wherein said determining form core information from said form requirement information comprises:
and inputting the form demand information into a pre-trained information identification model to obtain the form core information output by the information identification model.
3. The method according to claim 2, wherein the method further comprises:
constructing a training input sample and a training output sample; the training input samples comprise sample requirement information, and the training output samples comprise field items for constructing a form template;
and performing model training according to the training input sample and the training output sample to obtain the information identification model.
4. A method according to claim 3, characterized in that the method further comprises:
obtaining a test sample of the information identification model;
constructing a test form template according to the test sample and the information identification model;
and acquiring the evaluation value of the test form template, and updating the information identification model according to the evaluation value of the test form template.
5. The method of claim 4, wherein said constructing a test form template from said test sample and said information recognition model comprises:
inputting the test sample into the information identification model to obtain a test result output by the information identification model;
and constructing the test form template according to the test result.
6. A method according to claim 3, characterized in that the method further comprises:
determining the importance degree of each training output sample through an information gain evaluation algorithm;
determining an optimized output sample according to the importance degree;
updating the information recognition model according to the optimized output samples of the training input samples.
7. A form template generating apparatus, the apparatus comprising:
the information acquisition module is used for acquiring form filling information and form demand information of the target form template; the form requirement information comprises requirement content of a user on the target form;
the information determining module is used for determining form core information according to the form demand information;
and the template construction module is used for constructing the target form template by the form filling information and the form core information.
8. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any of claims 1 to 6 when the computer program is executed.
9. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 6.
10. A computer program product comprising a computer program, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 6.
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|---|---|---|---|
| CN202310675459.0A CN116911270A (en) | 2023-06-07 | 2023-06-07 | Form template generation method, apparatus, device, storage medium and program product |
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| Application Number | Priority Date | Filing Date | Title |
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| CN202310675459.0A CN116911270A (en) | 2023-06-07 | 2023-06-07 | Form template generation method, apparatus, device, storage medium and program product |
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| CN116911270A true CN116911270A (en) | 2023-10-20 |
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| CN202310675459.0A Pending CN116911270A (en) | 2023-06-07 | 2023-06-07 | Form template generation method, apparatus, device, storage medium and program product |
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| Country | Link |
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| CN (1) | CN116911270A (en) |
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