CN116894637A

CN116894637A - Form processing method, form processing device, computer equipment and storage medium

Info

Publication number: CN116894637A
Application number: CN202310835758.6A
Authority: CN
Inventors: 张利平; 俞科峰; 仝建刚; 李嫚; 乔宏明
Original assignee: China Telecom Technology Innovation Center; China Telecom Corp Ltd
Current assignee: China Telecom Technology Innovation Center; China Telecom Corp Ltd
Priority date: 2023-07-07
Filing date: 2023-07-07
Publication date: 2023-10-17

Abstract

The application relates to a form processing method, a form processing device, computer equipment and a storage medium, wherein the method comprises the following steps: responding to a form editing instruction, and calling a robot flow automation model to extract a form to be processed; performing content identification processing on the to-be-processed form through the robot flow automatic model to obtain keyword information of the to-be-processed form; determining the category of the form to be processed according to the keyword information; determining an automatically executable identification result of the form to be processed according to the category of the form to be processed and the keyword information; and under the condition that the automatically executable identification result is that the form to be processed can be automatically executed, automatically collecting and editing the form to be processed. The method can improve the circulation efficiency of the forms.

Description

Form processing method, form processing device, computer equipment and storage medium

Technical Field

The present application relates to the field of computer technology, and in particular, to a form processing method, an apparatus, a computer device, a storage medium, and a computer program product.

Background

Collecting and editing refers to collecting information and editing information, and knowledge collection and editing of forms are often required according to service requirements in the field of service processing.

In the related art, the knowledge base editing system is processed by editing, putting on shelf, submitting and checking forms according to service requirements by editing staff, for example, after receiving the putting on shelf requirements for n games, the editing staff needs to manually search tree graph nodes according to a knowledge tree, and then edit and release latest messages one by one for the requirement forms of each game. Each form is dependent on the way that the editing staff manually extracts information and edits and circulates one by one, so that the circulation efficiency of the forms is low.

Disclosure of Invention

Based on this, it is necessary to provide a form processing method, apparatus, computer device, computer readable storage medium and computer program product for the technical problem that the flow efficiency of the above-mentioned forms is low.

In a first aspect, the present application provides a form processing method. The method comprises the following steps:

responding to a form editing instruction, and calling a robot flow automation model to extract a form to be processed;

performing content identification processing on the to-be-processed form through the robot flow automatic model to obtain keyword information of the to-be-processed form;

Determining the category of the form to be processed according to the keyword information;

determining an automatically executable identification result of the form to be processed according to the category of the form to be processed and the keyword information;

and under the condition that the automatically executable identification result is that the form to be processed can be automatically executed, automatically collecting and editing the form to be processed.

In one embodiment, the determining the category of the form to be processed according to the keyword information includes:

acquiring a preset form feature library, wherein the form feature library is used for storing mapping relations between form features and categories of a plurality of forms;

and inquiring the form feature library according to the keyword information of the form to be processed to obtain the category of the form to be processed.

In one embodiment, the determining the automatically executable identification result of the form to be processed according to the category of the form to be processed and the keyword information includes:

acquiring a preset knowledge model base; the knowledge model base comprises automatic execution conditions of forms of different categories;

determining a target automation execution condition corresponding to the form to be processed from the knowledge model base according to the category of the form to be processed;

And if the keyword information of the to-be-processed form accords with the target automatic execution condition, determining that the to-be-processed form can be automatically executed.

In one embodiment, the knowledge model base further comprises a plurality of typical form cases;

under the condition that the to-be-processed form can be automatically executed, automatically picking and editing the to-be-processed form, comprising the following steps:

under the condition that the to-be-processed form can be automatically executed, comparing the to-be-processed form with each typical form case in the knowledge model base to obtain the similarity between the to-be-processed form and each typical form case;

if the similarity between the to-be-processed form and any typical form case is greater than a threshold value, the to-be-processed form is subjected to the editing processing according to the editing processing flow corresponding to any typical form case.

In one embodiment, after determining the automatically executable recognition result of the form to be processed according to the category of the form to be processed and the keyword information, the method further includes:

determining a recording condition corresponding to the form to be processed according to the category under the condition that the automatically executable identification result is that the form to be processed cannot be automatically executed or the similarity between the form to be processed and each typical form case is not greater than a threshold value; the recording conditions comprise the service fields required by the recording and the field information requirements of the required service fields;

And if the current form content of the form to be processed accords with the form recording condition, automatically recording the form to be processed.

In one embodiment, the method further comprises:

if the current form content of the form to be processed does not accord with the corresponding recording condition, carrying out automatic information complement processing on the form to be processed;

and carrying out automatic recording processing on the completed form to be processed.

In one embodiment, the automatic information complement processing for the to-be-processed form includes:

acquiring service resource information required by the form to be processed based on the current form content of the form to be processed and a form recording condition corresponding to the form to be processed;

and carrying out automatic information complement processing on the form to be processed according to the service resource information.

In a second aspect, the application also provides a form processing device. The device comprises:

the model calling module is used for responding to the form editing instruction and calling the robot flow automation model to extract the form to be processed;

the form identification module is used for carrying out content identification processing on the form to be processed through the robot flow automation model to obtain keyword information of the form to be processed;

The category determining module is used for determining the category of the form to be processed according to the keyword information;

the result determining module is used for determining an automatically executable identification result of the form to be processed according to the category of the form to be processed and the keyword information;

and the automatic editing module is used for automatically editing the to-be-processed form under the condition that the automatically-executable identification result is that the to-be-processed form can be automatically executed.

In a third aspect, the present application also provides a computer device. The computer device comprises a memory storing a computer program and a processor which when executing the computer program performs the steps of:

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:

In a fifth aspect, the present application also provides a computer program product. The computer program product comprises a computer program which, when executed by a processor, implements the steps of:

The form processing method, the form processing device, the computer equipment, the storage medium and the computer program product call a robot flow automatic model to extract a form to be processed in response to a form editing instruction; performing content identification processing on the form to be processed through a robot flow automation model to obtain keyword information of the form to be processed; determining the category of the form to be processed according to the keyword information; determining an automatically executable identification result of the form to be processed according to the category of the form to be processed and the keyword information; and under the condition that the automatically executable identification result is that the form to be processed can be automatically executed, automatically picking and editing the form to be processed. According to the method, the intelligent recognition and classification of the forms are carried out by introducing the robot flow automation model, so that the automatic execution of the collecting and editing flow can be realized, the manpower resources can be released, and the circulation efficiency of the forms is improved.

Drawings

FIG. 1 is a schematic flow chart of a form processing method in the prior art;

FIG. 2 is a flow diagram of a form processing method in one embodiment;

FIG. 3 is a flow chart of steps for automatically performing determination of recognition results for forms in one embodiment;

FIG. 4 is a flow chart of a form processing method in another embodiment;

FIG. 5 is a schematic diagram of an RPA-based knowledge base automation mining system for implementing the form processing method of the present application, in one embodiment;

FIG. 6 is a schematic diagram of an implementation flow of an RPA-based knowledge base automation mining system in one embodiment;

FIG. 7 is a schematic flow diagram of keyword sorting and clustering and marking of forms in one embodiment;

FIG. 8 is a flow diagram of automated editing of forms in one embodiment;

FIG. 9 is a flow chart of an automatic form recording operation for a form in one embodiment;

FIG. 10 is a block diagram of the architecture of a form handling device in one embodiment;

FIG. 11 is an internal block 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.

Referring to fig. 1, which is a schematic diagram of a processing flow for processing forms in the prior art, as shown in fig. 1, a collecting and editing person can create a collecting and editing form through self-service contacts to record the form, and for newly added up or modified knowledge points, the collecting and editing person needs to manually sort keywords according to service requirements and recording contents issued by a service manager; synchronously pushing the sorted keywords to the corresponding knowledge tree nodes; for knowledge points to be put off or deleted, manual operation deadline expiration operation is required by a editing staff according to the requirements issued by a business manager; when the form complement information or the existing information recorded by the editing staff has ambiguity, the editing staff is required to manually correct, and the latest information can be released only by changing knowledge points after the correction is completed.

The processing method is dependent on the gatherer, but is easy to cause operation to be not standardized due to the knowledge background of the gatherer and the like, so that a plurality of forms are mapped incorrectly; meanwhile, when products related to certain nodes under a certain branch of the knowledge tree are off-line, personnel are required to be invested to conduct manual form sorting and corresponding operation, and efficiency is low.

Based on the problems, the application provides a technology of introducing robot process automation (Robotic Process Automation, RPA), and the keyword sorting and standard case automation hitching knowledge tree graph processing are carried out on the full-network full-quantity knowledge base collecting and editing form through RPA personification; aiming at the forms which cannot be automatically executed, standardized information and business resource checking results are supplemented to the greatest extent, the form processing efficiency is improved, manual intervention links are reduced, and batch processing of the forms is realized.

In one embodiment, as shown in fig. 2, a form processing method is provided, where the method is applied to a terminal to illustrate the method, it is understood that the method may also be applied to a server, and may also be applied to a system including the terminal and the server, and implemented through interaction between the terminal and the server. The terminal can be, but not limited to, various personal computers, notebook computers, smart phones, tablet computers, internet of things equipment and portable wearable equipment, and the internet of things equipment can be smart speakers, smart televisions, smart air conditioners, smart vehicle-mounted equipment and the like. The portable wearable device may be a smart watch, smart bracelet, headset, or the like. The server may be implemented as a stand-alone server or as a server cluster composed of a plurality of servers. In this embodiment, the method includes the steps of:

and step S210, in response to the form editing instruction, calling a robot flow automation model to extract the form to be processed.

The robot process automation model in the application adopts a robot process automation technology (RPA technology), and the RPA is a business process automation technology, and the technology adopts a virtual software robot, also called a digital robot or a robot, to execute time-consuming manual work or task, and is mainly used for processing repeatability and modularization work.

In the specific implementation, after the collecting and editing personnel receive the collecting and editing requirement, the collecting and editing personnel can trigger a self-service list recording channel to store the total quantity of the forms to be processed in a form buffer medium in a converging mode, and after the terminal receives a form collecting and editing instruction, the robot process automation model can be started to extract the forms to be processed from the form buffer medium to perform automatic circulation processing on the forms to be processed. The number of the forms to be processed can be one or a plurality of forms.

And step S220, carrying out content identification processing on the form to be processed through a robot flow automation model to obtain the keyword information of the form to be processed.

Wherein the keyword information can be understood as words capable of characterizing the information content of the form to be processed.

In the specific implementation, the contents in the form to be processed can be identified through a robot flow automation model by combining an artificial intelligence technology, and the keyword information of each field in the form is extracted.

In the step, the keyword information of the form to be processed is extracted, so that the form to be processed can be classified according to the keyword information.

Step S230, determining the category of the form to be processed according to the keyword information.

The types of the forms to be processed can be classified into product types, fault types, complaints and the like according to scenes, can be classified into types of addition, deletion, modification and the like according to business requirements, and can be classified according to other dimensions, and the application is not particularly limited.

In a specific implementation, a form feature library can be preset to store form features of different types, and after keyword information of a form to be processed is obtained, the form feature library can be queried through the keyword information to obtain the type of the form to be processed.

Further, in one embodiment, when there are multiple forms to be processed, after determining the category of each form to be processed, clustering may be performed on each form to be processed according to the category, specifically, the forms to be processed with the same category are used as a cluster to form a data warehouse. And then distributing the forms to be processed in each cluster to different processing terminals according to the category of each cluster, and collecting and editing the received forms to be processed by each processing terminal, thereby improving the processing efficiency of the forms to be processed.

Step S240, determining an automatically executable identification result of the form to be processed according to the category of the form to be processed and the keyword information.

It can be understood that, because the forms may have a problem that the information is wrong, conflicts with the historical form content or is ambiguous, in this case, the form content needs to be further checked, so that not all forms can be subjected to automatic editing operation, and before the automatic editing processing is performed on the forms to be processed, whether the forms to be processed can be automatically performed or not needs to be judged, specifically, the automatically executable identification result of the forms to be processed is determined according to the category and keyword information of the forms to be processed.

In a specific implementation, different types of forms can correspond to different automatic execution conditions, so that the target automatic execution conditions corresponding to the forms to be processed can be determined according to the types of the forms to be processed, and further, whether the forms to be processed meet the target automatic execution conditions or not is judged according to key word information of the forms to be processed, and an automatically executable identification result of the forms to be processed is obtained.

Step S250, under the condition that the automatically executable identification result is that the form to be processed can be automatically executed, automatic picking and editing processing is carried out on the form to be processed.

In the specific implementation, if the form to be processed meets the corresponding target automation execution condition, the form to be processed can be determined to be automatically executed, and in this case, automatic editing processing can be performed on the form to be processed.

In the form processing method, a robot flow automatic model is called to extract a form to be processed in response to a form collecting and editing instruction; performing content identification processing on the form to be processed through a robot flow automation model to obtain keyword information of the form to be processed; determining the category of the form to be processed according to the keyword information; determining an automatically executable identification result of the form to be processed according to the category of the form to be processed and the keyword information; and under the condition that the automatically executable identification result is that the form to be processed can be automatically executed, automatically picking and editing the form to be processed. According to the method, the intelligent recognition and classification of the forms are carried out by introducing the robot flow automation model, so that the automatic execution of the collecting and editing flow can be realized, the manpower resources can be released, and the circulation efficiency of the forms is improved.

In an exemplary embodiment, determining the category of the form to be processed according to the keyword information in step S230 includes: acquiring a preset form feature library, wherein the form feature library is used for storing mapping relations between form features and categories of a plurality of forms; and according to the keyword information of the form to be processed, inquiring a form feature library to obtain the category of the form to be processed.

In specific implementation, for each form category, a plurality of sample forms belonging to the category after history processing can be obtained, feature extraction is carried out on the sample forms, a plurality of form features of the forms under the category are obtained, a mapping relation between each form feature and the category of the forms is further established, and the plurality of form features and the corresponding category of each form are stored in a form feature library, so that the form feature library is obtained. Further, after the keyword information of the form to be processed is obtained, the keyword information can represent the characteristics of the form to be processed, so that a preset form characteristic library can be queried according to the keyword information, and the category of the form to be processed is obtained based on the mapping relation in the form characteristic library.

More specifically, the to-be-processed form and each form feature of each category can be respectively matched, a target category with the largest number of the form features matched with the to-be-processed form is determined according to the matching result, and the target category is used as the category of the to-be-processed form.

In this embodiment, the form feature library is preset to store the form features of the forms of different types, so that after the keyword information of the form to be processed is determined, the form feature library can be directly queried to determine the type of the form to be processed, thereby improving the determination efficiency of the type of the form to be processed.

In an exemplary embodiment, as shown in fig. 3, determining an automatically executable recognition result of the form to be processed according to the category and the keyword information of the form to be processed in step S240 includes:

step S241, a preset knowledge model base is obtained; the knowledge model base comprises automatic execution conditions of forms of different categories;

step S242, determining the target automation execution condition corresponding to the form to be processed from the knowledge model base according to the category of the form to be processed;

step S243, if the keyword information of the form to be processed accords with the target automatic execution condition, determining that the form to be processed can be automatically executed.

In a specific implementation, the automatic execution conditions may include whether the automatic execution conditions have execution logic, whether the automatic execution conditions are typical cases, whether the automatic execution requirements are met, and the like, and since the execution logic, the execution requirements, and the like of the forms of different categories are different, the corresponding automatic execution conditions need to be set for the forms of different categories, respectively, and a mapping relationship between the different categories and the corresponding automatic execution conditions may be established, and the mapping relationship is stored in the knowledge model library. Further, after the category of the to-be-processed form is determined, an automatic execution condition corresponding to the to-be-processed form can be found in the knowledge model, the automatic execution condition is determined from a knowledge model library and is used as a target automatic execution condition, then whether the to-be-processed form accords with the target automatic execution condition is judged based on the keyword information of the to-be-processed form, if so, the to-be-processed form can be automatically executed, and otherwise, the to-be-processed form cannot be automatically executed is judged. After the automatically executable identification result of the to-be-processed form is obtained, the to-be-processed form can be labeled according to the automatically executable identification result, and the to-be-processed form with the label is stored in a form cache medium.

In this embodiment, the knowledge model base is preset to store the automation execution conditions of the forms of different types, so that after the type and keyword information of the forms to be processed are determined, the knowledge model base can be directly queried to determine the automation executable recognition result of the forms to be processed, thereby improving the recognition efficiency of the automation executable recognition result of the forms to be processed, and facilitating the execution of different processing strategies according to the automation executable recognition result.

In an exemplary embodiment, the knowledge model base further includes a number of typical form cases;

in the step S250, under the condition that the form to be processed can be automatically executed, the step of automatically collecting and editing the form to be processed specifically includes: under the condition that the to-be-processed form can be automatically executed, comparing the to-be-processed form with each typical form case in the knowledge model base to obtain the similarity between the to-be-processed form and each typical form case; if the similarity between the to-be-processed form and any typical form case is greater than a threshold value, the to-be-processed form is subjected to the editing processing according to the editing processing flow corresponding to any typical form case.

In a specific implementation, the preset knowledge model library includes a plurality of typical form cases in addition to the automatic execution conditions of the forms of different types, under the condition that the to-be-processed forms are judged to be automatically executable, the to-be-processed forms can be compared with each typical form case in the knowledge model library through a robot flow automation model to obtain the similarity between the to-be-processed forms and each typical form case, and when the similarity between each typical form case and the to-be-processed form case is greater than a threshold value, the to-be-processed forms can be collected and compiled according to the collecting and compiling process corresponding to the typical form case. Otherwise, if the similarity between the to-be-processed form and each typical form case is not greater than the threshold value, performing automatic form recording processing on the to-be-processed form.

In one embodiment, if there are multiple typical form cases with similarity greater than the threshold value in each typical form case, the typical form cases with the similarity greater than the threshold value may be sorted according to the value of the similarity, and the picking and editing processing is performed on the to-be-processed form according to the picking and editing processing flow corresponding to the typical form case with the maximum similarity.

In this embodiment, under the condition that the to-be-processed forms can be automatically executed, comparing the to-be-processed forms with each typical form case in the knowledge model base, and according to the comparison result, performing the editing processing on the to-be-processed forms according to the editing processing flow corresponding to the typical form case with the similarity between the to-be-processed forms being greater than the threshold value, so that the to-be-processed forms can be rapidly checked, and the processing efficiency of the to-be-processed forms is improved. If the similarity between the to-be-processed form and each typical form case is not greater than the threshold value, automatic information is complemented through the robot flow automatic model, and then automatic recording processing is carried out, so that most processing flows can be automatically processed by the robot flow automatic model, manual intervention is reduced, and the form flow efficiency is improved.

In an exemplary embodiment, after determining the automatically executable recognition result of the form to be processed according to the category and the keyword information of the form to be processed in step S240, the method further includes: under the condition that the automatically executable identification result is that the form to be processed can not be automatically executed, or the similarity between the form to be processed and each typical form case is not more than a threshold value, determining a form recording condition corresponding to the form to be processed according to the category; the recording conditions comprise the service fields required by the recording and the field information requirements of the required service fields; and if the current form content of the form to be processed accords with the form recording condition, automatically recording the form to be processed.

In the specific implementation, if the automatically executable identification result of the to-be-processed form is determined to be non-automatically executable according to the category and keyword information of the to-be-processed form, or the similarity between the to-be-processed form and each typical form case is not greater than a threshold value, which indicates that the to-be-processed form has a problem, the to-be-processed form can be automatically recorded in order to improve the form processing efficiency. However, the automatic form is also provided with some limited form records, not every form can execute the automatic form records, so after the form to be processed is determined to be incapable of being automatically executed, the form record condition corresponding to the form to be processed can be further determined, whether the form to be processed accords with the corresponding form record condition is judged, and if so, the automatic form record processing can be carried out on the form to be processed.

More specifically, the forms of different types correspond to different recording conditions, so that the recording conditions corresponding to the forms to be processed can be determined according to the types of the forms to be processed obtained in advance, and the recording conditions can include the service fields required by the forms and the field information requirements of the required service fields. And then matching the content of the current form of the to-be-processed form with the service field required by the form of the category to which the to-be-processed form belongs and the field information requirement of the required service field, judging whether the content of the current form of the to-be-processed form meets the form recording condition, if the content of the current form of the to-be-processed form lacks the field information of certain service fields or the field information of certain service fields does not meet the corresponding field information requirement, determining that the content of the current form of the to-be-processed form does not meet the form recording condition, otherwise, if the content of the current form of the to-be-processed form comprises the service field required by the form of the category to which the to-be-processed form belongs and the field information also meets the corresponding field information requirement, determining that the content of the current form of the to-be-processed form meets the form recording condition, and carrying out automatic form recording processing on the to-be-processed form through the robot flow automation model.

Further, in an exemplary embodiment, the form processing method further includes: if the current form content of the form to be processed does not accord with the corresponding recording condition, carrying out automatic information complement processing on the form to be processed; and carrying out automatic recording processing on the completed form to be processed.

Wherein the information completion may include information modification and information population.

In the specific implementation, if the content of the current form of the to-be-processed form does not meet the corresponding recording condition, which indicates that the content of the current form of the to-be-processed form lacks field information of certain service fields, or the field information of certain service fields does not meet the corresponding field information requirement, automatic information complement processing can be performed on the to-be-processed form through a robot flow automation model to obtain a completed to-be-processed form meeting the recording condition, and then automatic recording processing is performed on the completed to-be-processed form.

In this embodiment, for a form to be processed that cannot be automatically executed, whether the form to be processed meets the form recording condition is firstly determined, if yes, the form to be processed is automatically processed through the robot flow automation model, if not, automatic information complement processing is performed through the robot flow automation model, so that the form to be processed meets the form recording condition, and then automatic form recording processing is performed, therefore, most of processing flows can be automatically processed by the robot flow automation model, manual intervention is reduced, and form transfer efficiency is improved.

In an exemplary embodiment, performing automated information-completion processing on a form to be processed includes: acquiring service resource information required by a form to be processed based on the current form content of the form to be processed and the form recording condition corresponding to the form to be processed; and carrying out automatic information complement processing on the form to be processed according to the service resource information.

In specific implementation, information complementation is performed on a form to be processed, the content and the complementation reference or basis of the current form of the form to be processed are required to be determined, in this embodiment, a record condition corresponding to the form to be processed is used as the complementation reference, based on the content of the current form of the form to be processed and the record condition corresponding to the form to be processed, a field in which the content of the current form and the record condition are inconsistent can be determined, then required service resource information is acquired from a resource providing system, and in particular, the field information of the inconsistent field can be acquired, and then the acquired field information of the inconsistent field is supplemented to the form to be processed, so that the completed form to be processed is obtained.

In this embodiment, based on the current form content of the form to be processed and the recording condition corresponding to the form to be processed, the service resource information required by the form to be processed is obtained from the resource providing system, and according to the service resource information, the automatic information complement processing is performed on the form to be processed.

Referring to fig. 4, a flowchart of a form processing method according to another exemplary embodiment of the present application is provided, and in this embodiment, the method includes the following steps:

step S401, responding to a form editing instruction, and calling a robot flow automatic model to extract a form to be processed;

step S402, carrying out content identification processing on a form to be processed through a robot flow automation model to obtain keyword information of the form to be processed;

step S403, inquiring a preset form feature library according to the keyword information of the form to be processed to obtain the category of the form to be processed;

step S404, determining a target automation execution condition corresponding to the form to be processed from a preset knowledge model base according to the category of the form to be processed;

step S405, determining an automatically executable result of the form to be processed according to the keyword information of the form to be processed;

step S406, if the to-be-processed form can be automatically executed, comparing the to-be-processed form with each typical form case in the knowledge model base to obtain the similarity between the to-be-processed form and each typical form case;

step S407, judging whether target typical form cases with similarity larger than a threshold value with the to-be-processed forms exist in the typical form cases or not;

Step S408, if yes, carrying out mining and editing processing on the form to be processed according to the mining and editing processing flow corresponding to the target typical form case; if not, carrying out automatic recording processing on the form to be processed;

step S409, if the form to be processed can not be automatically executed, determining the recording condition corresponding to the form to be processed according to the category;

step S410, judging whether the current form content of the form to be processed accords with the form recording condition;

and S411, if yes, performing automatic recording processing on the form to be processed.

And step S412, if not, carrying out automatic information complement processing on the to-be-processed form, and carrying out automatic recording processing on the complemented to-be-processed form.

According to the form processing method, the intelligent recognition and classification of the forms are carried out by introducing the robot flow automation model, so that the automatic execution of the collecting and editing flow can be realized, the manpower resources can be released, and the circulation efficiency of the forms is improved.

In one embodiment, to facilitate understanding of embodiments of the application by those skilled in the art, a specific example will be described below in conjunction with the accompanying drawings.

Referring to fig. 5, there is provided a schematic structural diagram of an RPA-based knowledge base automation mining system for implementing a form processing method of the present application, including: the system comprises RPA computer equipment, a configuration module, a feature library, a knowledge template library, a strategy center and an automatic execution module. The application adds PRA computer equipment to the existing collecting and editing processing flow to realize the anthropomorphic sorting and standardized processing execution of the keywords of the full-network full-volume collecting and editing form. Wherein:

The RPA computer equipment is a core module of personification operation, can automatically sort the keywords of the acquired and compiled form through example characteristic information such as a form characteristic library, a knowledge model library and the like, and can mark whether the form to be processed can be automatically executed or not by combining the knowledge model library and a product deadline identification result.

The RPA computer equipment uses an automatic execution module to rapidly process the to-be-processed form with the similarity of more than 90% with the typical form cases in the knowledge model base based on the knowledge model base and the strategy center, and outputs the latest message column; and for the to-be-processed forms with the similarity lower than 90%, executing automatic recording processing based on the editing processing strategy, and recording the processing result and publishing the processing result to the latest message column of the first page of the knowledge base.

The RPA computer equipment uses an automatic execution module to match the recording conditions of service field information, service check information and the like required by a corresponding form system based on a policy center, automatically records the corresponding form to be processed, and returns to the original manual processing flow.

And an automatic execution module: the RPA is mainly used for executing the functions of collecting and editing knowledge points, sorting keywords, automatic form processing, intelligent recording and the like;

form feature library: the method is used for storing the characteristics of the mining and editing form, the characteristics of the knowledge type, the characteristics of the scene phenomenon and the like and providing keyword sorting and scene type support.

Knowledge model base: the system is used for storing automatic execution conditions and typical form case information of automatic forms of different types, supporting automatic scene service and form picking and editing processing.

Policy center: the method is used for storing the collection and editing form processing strategy, the client automatic return visit strategy and the information complement strategy, and supporting the automatic processing capability.

Referring to fig. 6, a schematic diagram of an execution flow of an RPA-based knowledge base automation editing system is shown, including the following steps:

(1) after receiving the mining and editing requirements, the mining and editing personnel automatically trigger automatic mining and editing operation, take over the mining and editing operation by the RPA robot, extract keywords of the forms, classify the forms by combining a form feature library, and store the forms in a clustering way.

(2) The PRA robot recognizes whether the form can be automatically executed according to the category, the keyword and the knowledge model base of the form, and caches the preliminary judgment result to the form cache medium.

(3) For forms that are not automatically executable, the RPA robot will perform an automatic form recording operation.

(4) For automatically executable forms, the RPA robot further compares the form with each typical form case in the knowledge model to determine whether a target typical form case with similarity to the form greater than a threshold exists.

(5) If the form exists, the RPA robot automatically collects and compiles the form according to the collecting and editing processing flow of the target typical form case. The method can be combined with a policy center to perform operations including service information checking and resource information checking, and perform service automation online and offline processing and the like.

(6) And after the form processing is finished, the form is released to the latest message column.

(7) If not, the RPA robot will execute the automatic recording operation as in step (3).

Specifically, the step of the RPA robot performing the automatic recording operation includes:

(8) and comparing the recording conditions corresponding to the form according to the current existing content of the form.

(9) If the existing content does not meet the recording condition, the RPA robot can acquire service resource information through the corresponding support system based on the strategy center to automatically complement the form information.

And (3) the RPA robot performs automatic recording after completing the related field information, informs corresponding form processing personnel to process, and returns the form to the existing manual processing flow.

Referring to fig. 7, a schematic flow chart of keyword sorting and clustering on a form according to an embodiment includes the following steps:

(1) the collecting and editing personnel collect the total amount of to-be-processed requirements in a total amount of form caching media (readable storage media) by triggering a self-service form recording channel;

(2) the RPA robot module starts to intervene in the keyword sorting and form clustering work.

(3) The RPA robot uses an automated execution module to extract the form content and keywords for each field of the form based on AI capabilities.

(4) The RPA robot uses an automatic execution module to classify the forms based on the characteristic information recorded by the form characteristic library.

(5) The RPA robot clusters the sorted work orders based on the classification result to form a data warehouse.

(6) The RPA robot uses an automatic execution module to match with a knowledge model base based on a classification result and keywords, and judges whether the form has the characteristic of being capable of being automatically executed or not, and the method comprises the following steps: whether execution logic is present, whether typical cases are present, whether automated execution requirements are met.

(7) And forming an automatically executable label according to a judging result of whether the automatically executable feature is provided, and marking each form.

(8) And storing the form with the label into a form cache medium.

Referring to fig. 8, a schematic flow chart of automatic editing of a form according to an embodiment includes the following steps:

(1) the RPA robot extracts the form to be processed from the form cache medium.

(2) Form processing flow, processing logic and processing method of corresponding characteristics of the matching strategy center are performed according to the category and the keywords of the form.

(3) The form capable of being automatically executed starts an automatic execution flow; forms that are not automatically executable are then streamed to an automatic form recording process (see FIG. 9); the automatic execution flow comprises the following steps:

(4) and (3) comparing the to-be-processed form with a knowledge model base by the RPA robot, if the to-be-processed form can be matched with a typical form case with the similarity larger than a threshold value, rapidly generating a result, executing the steps (7) and (8), putting the form on the shelf, and broadcasting the form to the latest message column.

(5) If the typical form case with the similarity larger than the threshold cannot be matched, the RPA robot acquires resource information, service information and information required by service acceptance through a related support system according to the form processing logic and the processing method, and executes a form recording processing flow shown in fig. 9.

(6) After the form is checked, calling interface capability to inform a business manager of the checked result.

(7) The RPA hangs the handling forms to the corresponding nodes of the knowledge tree and performs archiving, and meanwhile, related information of the form caching media is deleted.

Referring to fig. 9, a schematic flow chart of an automatic recording operation for a form that cannot be automatically executed according to an embodiment includes the following steps:

(1) the RPA robot acquires the task of the form to be processed from the form buffer medium, and executes the process on the form which can not be automatically executed.

(2) And according to the form keyword sorting result, acquiring service fields required by the corresponding types of form records from a production and sales system/form system/dimension system and the like.

(3) The RPA robot executes intelligent recording, including filling in information such as form basic information, form content, early-stage resource auditing, business auditing and the like.

(4) And the policy center provides related information support such as an algorithm, a resource address, a network resource pool and the like according to the automatic recording demand.

(5) And the RPA robot performs resource auditing or business condition auditing according to the required business field and the required resource address, and records the checking content.

(6) When the service support system cannot supplement the related resource information, third-party network resources are acquired through the network, for example: and (5) carrying out information completion and standardization processing on various games of IPTV and the like.

(7) When the information cannot be completed through the service system and the web crawler, the necessary service information is acquired by interacting with the service manager through calling the AI capability.

(8) The RPA robot performs automatic recording on the corresponding form system and deletes the form cache information.

The form processing method provided by the application has the following advantages: (1) By introducing RPA computer equipment, the work of service collecting and editing personnel can be effectively analyzed, and the automation processing of most flow machines is realized. (2) Keyword mapping relations can be automatically extracted through supplementing intelligent technology and standardized cases. (3) And realizing the batch operation of the business under the leaf nodes through the standardized processing flow of the forms.

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 processing device for realizing the above-mentioned related form processing method. The implementation of the solution provided by the apparatus is similar to that described in the above method, so the specific limitation in the embodiments of the form processing apparatus provided below may be referred to as the limitation of the form processing method hereinabove, and will not be repeated herein.

In one embodiment, as shown in fig. 10, there is provided a form processing apparatus including: a model calling module 1001, a form identifying module 1002, a category determining module 1003, a result determining module 1004, and an automatic editing module 1005, wherein:

the model calling module 1001 is configured to call the robot flow automation model to extract a form to be processed in response to the form editing instruction;

the form identification module 1002 is configured to perform content identification processing on a form to be processed through a robot flow automation model, so as to obtain keyword information of the form to be processed;

a category determining module 1003, configured to determine a category of the form to be processed according to the keyword information;

the result determining module 1004 is configured to determine an automatically executable recognition result of the form to be processed according to the category and keyword information of the form to be processed;

The automatic editing module 1005 is configured to automatically edit the form to be processed when the automatically executable identification result is that the form to be processed can be automatically executed.

In one embodiment, the category determining module 1003 is further configured to obtain a preset form feature library, where the form feature library is used to store mapping relationships between form features and categories of a plurality of forms; and according to the keyword information of the form to be processed, inquiring a form feature library to obtain the category of the form to be processed.

In one embodiment, the result determining module 1004 is further configured to obtain a preset knowledge model base; the knowledge model base comprises automatic execution conditions of forms of different categories; determining a target automation execution condition corresponding to the form to be processed from a knowledge model base according to the category of the form to be processed; and if the keyword information of the form to be processed accords with the target automatic execution condition, determining that the form to be processed can be automatically executed.

In one embodiment, the knowledge model base further comprises a plurality of typical form cases; the automatic collecting and editing module 1005 is further configured to compare the to-be-processed form with each typical form case in the knowledge model base to obtain a similarity between the to-be-processed form and each typical form case under the condition that the to-be-processed form can be automatically executed; if the similarity between the to-be-processed form and any typical form case is greater than a threshold value, the to-be-processed form is subjected to the editing processing according to the editing processing flow corresponding to any typical form case.

In one embodiment, the form processing device further includes an automatic form recording module, configured to determine a form recording condition corresponding to the form to be processed according to the category when the automatically executable identification result indicates that the form to be processed cannot be automatically executed, or when the similarity between the form to be processed and each typical form case is not greater than a threshold; the recording conditions comprise the service fields required by the recording and the field information requirements of the required service fields; and if the current form content of the form to be processed accords with the form recording condition, automatically recording the form to be processed.

In one embodiment, the automatic form recording module is further configured to perform automatic information completion processing on the form to be processed if the current form content of the form to be processed does not conform to the corresponding form recording condition; and carrying out automatic recording processing on the completed form to be processed.

In one embodiment, the automatic form recording module is further configured to obtain service resource information required by the form to be processed based on the current form content of the form to be processed and a form recording condition corresponding to the form to be processed; and carrying out automatic information complement processing on the form to be processed according to the service resource information.

The various modules in the form handling device described above may be implemented in whole or in part in software, hardware, and combinations 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. 11. The computer device includes a processor, a memory, a communication interface, a display screen, and an input device connected by a system bus. 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 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 handling method. The display screen of the computer equipment can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment can be a touch layer covered on the display screen, can also be keys, a track ball or a touch pad arranged on the shell of the computer equipment, and can also be an external keyboard, a touch pad or a mouse and the like.

It will be appreciated by those skilled in the art that the structure shown in FIG. 11 is merely a block diagram of some of the structures associated with the present inventive arrangements and is not limiting of the computer device to which the present inventive arrangements may be applied, 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 an embodiment, there is also provided a computer device comprising a memory and a processor, the memory having stored therein a computer program, the processor implementing the steps of the method embodiments described above when the computer program is executed.

In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored which, when executed by a processor, carries out the steps of the method embodiments described above.

In an embodiment, a computer program product is provided, comprising a computer program which, when executed by a processor, implements the steps of the method embodiments described above.

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

1. A form processing method, the method comprising:

2. The method of claim 1, wherein determining the category of the form to be processed based on the keyword information comprises:

3. The method according to claim 1, wherein determining an automatically executable recognition result of the form to be processed according to the category of the form to be processed and the keyword information comprises:

4. The method of claim 3, wherein the knowledge model base further comprises a plurality of typical form cases;

5. The method according to claim 1 or 4, wherein after determining the automatically executable recognition result of the form to be processed according to the category of the form to be processed and the keyword information, further comprising:

6. The method of claim 5, wherein the method further comprises:

7. The method of claim 6, wherein the automated information-completion processing of the pending forms comprises:

8. A form handling device, the device comprising:

9. 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 form handling method of any of claims 1 to 7 when the computer program is executed.

10. 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 form handling method of any of claims 1 to 7.

11. 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 form handling method of any of claims 1 to 7.