CN114185935A

CN114185935A - Social security data processing method and device combining RPA and AI and storage medium

Info

Publication number: CN114185935A
Application number: CN202111289239.1A
Authority: CN
Inventors: 徐春峰; 汪冠春; 胡一川; 褚瑞; 李玮
Original assignee: Beijing Laiye Network Technology Co Ltd; Laiye Technology Beijing Co Ltd
Current assignee: Beijing Laiye Network Technology Co Ltd; Laiye Technology Beijing Co Ltd
Priority date: 2021-11-02
Filing date: 2021-11-02
Publication date: 2022-03-15

Abstract

The disclosure relates to a social security data processing method, device and storage medium combining RPA and AI. The method comprises the steps of acquiring a picture to be identified of transacted materials of a user under security by adopting a Robot Process Automation (RPA) technology; performing Optical Character Recognition (OCR) processing on the picture to be recognized based on an Artificial Intelligence (AI) technology to obtain text data; extracting the text data to obtain target data required by the social security management system; and inputting the target data to the social security management system through the RPA technology. The present disclosure can solve the problem in the related art that it is highly desirable to improve the processing efficiency of social security data.

Description

Social security data processing method and device combining RPA and AI and storage medium

Technical Field

The present disclosure relates to the field of computer technologies, and in particular, to a method and an apparatus for processing social security data in combination with an RPA and an AI, and a storage medium.

Background

Robot Process Automation (RPA) is a Process task that simulates human operations on a computer through specific robot software and automatically executes according to rules.

Artificial Intelligence (AI) is a technical science that studies and develops theories, methods, techniques and application systems for simulating, extending and expanding human Intelligence.

In the related technology, social security management personnel receive paper management data submitted by security participating users for managing social security business, need to manually refer to paper files to enter data in a social security management system, and have check index requirements during management, so that the pressure of workers is huge. Many business handling data are comparatively complicated, and data entry process not only consumes a large amount of efforts of handling personnel, also has high requirement to people's physical power, still can lead to effort tired often to take place the phenomenon of typing the mistake because of watching data for a long time. Therefore, how to improve the processing efficiency of social security data and reduce the workload of social security workers becomes a problem to be solved urgently.

Disclosure of Invention

Therefore, the present disclosure provides a social security data processing method, device, system, storage medium and computer device combining RPA and AI to at least solve the problem in the related art that it is highly desirable to improve the processing efficiency of social security data. The technical scheme of the disclosure is as follows:

according to a first aspect of the embodiments of the present disclosure, there is provided a social security data processing method combining RPA and AI, the method being applied to an RPA robot system, the method including:

acquiring a to-be-identified picture of transacted materials of a user under security by adopting a Robot Process Automation (RPA) technology;

performing Optical Character Recognition (OCR) processing on the picture to be recognized based on an Artificial Intelligence (AI) technology to obtain text data;

extracting the text data to obtain target data required by the social security management system;

and recording the target data into the social insurance management system through the RPA technology.

According to an embodiment of the disclosure, the extracting the text data to obtain target data required by the social security management system includes:

performing Natural Language Processing (NLP) on the text data based on an Artificial Intelligence (AI) technology to obtain a word segmentation result of the text data;

and extracting target data required by the social security management system from the text data based on a preset target data extraction rule and the word segmentation result.

According to one embodiment of the disclosure, the target data extraction rule is a rule set for extracting key field attribute values in a target form on the social security management system.

According to an embodiment of the disclosure, the entering of the target data onto the social security management system through the RPA technology includes:

simulating user operation to access a target operation page of the social security management system through the RPA technology;

filling the target data into a corresponding filling control in the target operation page;

and simulating a user click confirmation operation to enter the target data into a database of the social security management system.

According to an embodiment of the present disclosure, the filling the target data into the corresponding filling control in the target operation page includes:

determining the attribute of the target data;

identifying hypertext markup language (HTML) tags of key fields in the target operation page through an RPA technology;

matching the attribute of the target data with the HTML label;

and responding to the matching of the attribute of the target data and the HTML label, and filling the target data into a filling control corresponding to the matched HTML label.

According to an embodiment of the disclosure, simulating, by the RPA technology, a user operation to access a target operation page of the social security management system includes:

simulating, by the RPA technique, user operation to access a login page of the social security administration system;

obtaining pre-stored login information;

and filling the login information into a corresponding filling control in the login page so as to access the target operation page.

According to an embodiment of the present disclosure, the method further comprises:

acquiring a service handling result returned by the social security management system; the service transaction result is result information returned by the social security management system aiming at the transaction materials of the participating users when the target data is input into the social security management system;

and generating a report based on the account information of the insured user and the service transaction result, and providing the report to the social security management terminal.

According to a second aspect of the embodiments of the present disclosure, a social security data processing apparatus combining RPA and AI is applied to an RPA robot system, and the apparatus includes:

the acquisition module is used for acquiring the picture to be identified of the transacted material of the insured user by adopting a Robot Process Automation (RPA) technology;

the processing module is used for carrying out Optical Character Recognition (OCR) processing on the picture to be recognized based on an Artificial Intelligence (AI) technology to obtain text data;

the extraction module is used for extracting the text data to obtain target data required by the social security management system;

and the recording module is used for recording the target data to the social insurance management system through the RPA technology.

According to an embodiment of the present disclosure, the extraction module includes:

the processing submodule is used for carrying out Natural Language Processing (NLP) on the text data based on an Artificial Intelligence (AI) technology to obtain a word segmentation result of the text data;

and the extraction submodule is used for extracting target data required by the social security management system from the text data based on a preset target data extraction rule and the word segmentation result.

According to one embodiment of the disclosure, the logging module comprises:

the access submodule is used for simulating user operation through the RPA technology to access a target operation page of the social insurance management system;

the first filling sub-module is used for filling the target data into the corresponding filling control in the target operation page;

and the entry sub-module is used for simulating a user click confirmation operation so as to enter the target data into the database of the social security handling system.

According to an embodiment of the present disclosure, the fill sub-module includes:

the determining submodule is used for determining the attribute of the target data;

the identification submodule is used for identifying a hypertext markup language (HTML) label of a key field in the target operation page through an RPA technology;

the matching submodule is used for matching the attribute of the target data with the HTML label;

and the second filling sub-module is used for filling the target data into a filling control corresponding to the matched HTML label in response to the matching of the attribute of the target data and the HTML label.

According to one embodiment of the present disclosure, the identification submodule includes:

the login submodule is used for simulating user operation to access a login page of the social insurance management system through the RPA technology;

the first acquisition submodule is used for acquiring pre-stored login information;

and the third filling sub-module is used for filling the login information into the corresponding filling control in the login page so as to access the target operation page.

According to an embodiment of the present disclosure, the apparatus further includes:

the second obtaining submodule is used for obtaining a service handling result returned by the social security handling system; the service transaction result is result information returned by the social security management system aiming at the transaction materials of the participating users when the target data is input into the social security management system;

and the generation sub-module is used for generating a report based on the account information of the insurance participating user and the service transaction result and providing the report to the social insurance management terminal.

According to a third aspect of the embodiments of the present disclosure, a storage medium whose instructions, when executed by a processor of a computer device, enable the computer device to perform the social security data processing method in combination with the RPA and the AI according to any one of the first aspects.

According to a fourth aspect of the embodiments of the present disclosure, a computer device includes a memory, a processor, and a computer program stored on the memory and executable on the processor, and the processor implements the social security data processing method combining the RPA and the AI according to the first aspect when executing the computer program.

According to a sixth aspect of the embodiments of the present disclosure, there is provided a storage medium having instructions that, when executed by a processor of a computer device, enable the computer device to execute the social security data processing method in combination with the RPA and the AI of the first aspect or the social security data processing method in combination with the RPA and the AI of the second aspect.

According to a seventh aspect of the embodiments of the present disclosure, there is provided a computer device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor implements the social security data processing method combining the RPA and the AI according to the first aspect when executing the computer program, or implements the social security data processing method combining the RPA and the AI according to the second aspect.

The technical scheme provided by the embodiment of the disclosure at least brings the following beneficial effects:

the method comprises the steps of acquiring a picture to be recognized of a transacted material of a user involved in security by adopting a robot flow automation (RPA) technology, carrying out Optical Character Recognition (OCR) processing on the picture to be recognized based on an Artificial Intelligence (AI) technology to obtain text data, extracting the text data, and obtaining target data required by a social security management system, so that the target data is input to the social security management system by the RPA technology, thereby not only avoiding the problem of error easily occurring in the manual input process, but also improving the input efficiency of the data; in addition, the method is based on an artificial intelligence AI technology, Natural Language Processing (NLP) is carried out on the text data to obtain word segmentation results of the text data, and target data required by the social security management system are extracted from the text data based on preset target data extraction rules and word segmentation results, so that the extracted target data can be accurately recorded on the social security management system according to actual requirements.

It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the disclosure and are not to be construed as limiting the disclosure.

Fig. 1 is a flowchart of a social security data processing method combining an RPA and an AI according to a first embodiment of the disclosure;

fig. 2 is a flowchart of a social security data processing method combining an RPA and an AI in the second embodiment of the disclosure;

FIG. 3 is a schematic diagram of a picture to be recognized in some embodiments of the present disclosure;

fig. 4 is a flowchart of a social security data processing method combining an RPA and an AI in the third embodiment of the disclosure;

fig. 5 is a flowchart of a social security data processing method combining an RPA and an AI in the fourth embodiment of the disclosure;

fig. 6 is a flowchart of a social security data processing method combining an RPA and an AI in the fifth embodiment of the disclosure;

fig. 7 is a flowchart of a social security data processing method combining an RPA and an AI in six embodiments of the disclosure;

FIG. 8 is a report diagram according to a sixth embodiment of the disclosure;

fig. 9 is a block diagram illustrating a social security data processing apparatus according to a seventh embodiment of the present disclosure;

fig. 10 is a block diagram of a computer device in an eighth embodiment of the disclosure.

Detailed Description

In order to make the technical solutions of the present disclosure better understood by those of ordinary skill in the art, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below with reference to the accompanying drawings.

It should be noted that the terms "first," "second," and the like in the description and claims of the present disclosure and in the above-described drawings are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the disclosure described herein are capable of operation in sequences other than those illustrated or otherwise described herein. The implementations described in the exemplary embodiments below are not intended to represent all implementations consistent with the present disclosure. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present disclosure, as detailed in the appended claims.

It should be noted that, in the technical solution of the present disclosure, the acquisition, storage, application, and the like of the personal information of the related user all conform to the regulations of the relevant laws and regulations, and do not violate the customs of the public order.

Based on the above problems, the present disclosure provides a social security data processing method, device, system, storage medium, and computer device that combine RPA (robot Process Automation) and AI (Artificial Intelligence), which can achieve obtaining a to-be-recognized picture of a transacted material of a participant by using a robot Process Automation RPA technology, performing Optical Character Recognition (OCR) on the to-be-recognized picture based on an Artificial Intelligence AI technology to obtain text data, extracting the text data, and obtaining target data required by a social security management system, thereby inputting the target data to the social security management system by using an RPA technology, not only avoiding a problem of error easily occurring in a manual input Process, but also improving data input efficiency.

It should be noted that, in the present disclosure, the social security data processing method combining the RPA and the AI may be configured in the social security data processing apparatus combining the RPA and the AI, the apparatus may be configured in the server, or may also be configured in the computer device, and the embodiment of the present application does not limit this.

The following first describes the related art terms to which this application relates:

the term "social insurance handling system" is a system used by a social insurance handling organization for handling social insurance-related services, and the social insurance handling organization is a functional organization for nations or society to perform administrative and institutional management on social insurance. And administrative management, namely determining the receiving and paying methods and using methods of social insurance funds through legislation, and supervising and checking the receiving and paying funds of lower institutions.

The term "social insurance management staff" refers to staff working in a social insurance management organization and responsible for conducting related social insurance services for the participating users through the social insurance management system.

The term "insured user" refers to a user who has an insurance contract with an insurer and has an obligation to pay premium according to the insurance contract, and the insured user needs to handle social insurance related business through a social insurance handling organization.

The term "transaction material" refers to the relevant material that needs to be submitted to the social insurance handling organization when the participating user transacts the social insurance related business through the social insurance handling organization.

Next, for the sake of easy understanding of the scheme, a social security data processing method combining RPA and AI applied to the RPA robot system will be described.

Example one

Fig. 1 is a flowchart of a social security data processing method combining an RPA and an AI in a first embodiment of the disclosure.

It should be noted that the social security data processing method combining the RPA and the AI in the embodiment of the present disclosure is applied to an RPA robot system, and the RPA robot system implements processing of the social security data. In addition, the social security data processing method combining the RPA and the AI in the embodiment of the present disclosure may be applied to a social security data processing apparatus combining the RPA and the AI in the embodiment of the present disclosure, and the apparatus may be configured in a computer device. As shown in fig. 1, the social security data processing method combining RPA and AI includes the following steps:

step 101, acquiring a to-be-identified picture of transacted materials of a user under security by using a Robot Process Automation (RPA) technology.

It can be understood that the social security service processing system needs to submit relevant social security service processing materials when the social security service processing system processes relevant social security services. The transacting material is usually paper material, and the paper material needs to be scanned by a scanning device so as to obtain a picture of the paper transacting material.

As a possible example, the picture to be identified of the office materials of the insured user can be obtained by the social security officer scanning the office materials of the insured user through the scanning device. Alternatively, the scanning device may be a high-speed scanner. The picture to be recognized is pre-stored in a folder of a specified path of the computer equipment, and the RPA robot acquires the picture to be recognized of the transacted material of the user according to the preset specified path.

102, performing Optical Character Recognition (OCR) processing on the picture to be recognized based on an Artificial Intelligence (AI) technology to obtain text data.

Optical Character Recognition (OCR) refers to a technology for recognizing Optical characters by image processing and pattern Recognition technologies, and specifically, to a technology for converting characters in a paper document into an image file of a black-and-white dot matrix in an Optical manner, and converting characters in the image into a text format by Recognition software for further editing and processing by Character processing software.

In the embodiment of the disclosure, after the picture to be recognized of the transaction material of the insured user is obtained, the picture to be recognized can be recognized by adopting an OCR recognition method based on an artificial intelligence AI technology, and characters in the picture to be recognized are converted into a text format, so that text data is obtained.

And 103, extracting the text data to obtain target data required by the social security handling system.

As a possible example, the RPA robot system extracts the text data according to the actual requirement, so as to obtain the target data required to be filled in by transacting related business in the social security management system.

And 104, recording the target data to the social insurance handling system through the RPA technology.

As one possible example, after filling the target data in the social security handling system, the RPA robot system may click on a relevant control such as a "confirm" control or a "submit" control, or a button, and submit the filled target data, thereby completing the entry of the target data on the social security handling system.

According to the social security data processing method combining the RPA and the AI, the picture to be recognized of the transacted material of the user participating in the security is obtained by adopting the robot flow automation RPA technology, the picture to be recognized is subjected to Optical Character Recognition (OCR) processing based on the artificial intelligence AI technology to obtain the text data, the text data is extracted to obtain the target data required by the social security management system, and therefore the target data is input to the social security management system through the RPA technology, the problem that errors are prone to occur in the manual input process is solved, and the input efficiency of the data is improved.

Example two

In order to ensure that extracted target data are accurately recorded into the social security management system according to actual requirements, optionally, Natural Language Processing (NLP) is performed on the text data based on an Artificial Intelligence (AI) technology to obtain word segmentation results of the text data, and the target data required by the social security management system are extracted from the text data based on preset target data extraction rules and word segmentation results. Fig. 2 is a flowchart of a social security data processing method combining an RPA and an AI in the second embodiment of the disclosure. It should be noted that the social security data processing method combining the RPA and the AI according to the embodiment of the present disclosure may be performed by an RPA robot system. In some embodiments of the disclosure, as shown in fig. 2, the social security data processing method combining RPA and AI includes:

step 201, a Robot Process Automation (RPA) technology is adopted to obtain a picture to be identified of transacted materials of a user to be insured.

In the embodiment of the present disclosure, step 201 may be implemented by respectively adopting any one of the embodiments of the present disclosure, which is not limited by the embodiment of the present disclosure and is not described again.

Step 202, performing Optical Character Recognition (OCR) processing on the picture to be recognized based on an Artificial Intelligence (AI) technology to obtain text data.

In the embodiment of the present disclosure, step 202 may be implemented by any one of the embodiments of the present disclosure, which is not limited in this disclosure and is not described again.

And 203, performing Natural Language Processing (NLP) on the text data based on an Artificial Intelligence (AI) technology to obtain a word segmentation result of the text data.

Natural Language Processing (NLP) is to make a computer receive an input in a Natural Language form of a user, and perform a series of operations such as Processing and calculation internally through an algorithm defined by a human to simulate the understanding of the Natural Language by the human and return a result expected by the user. Natural language processing is an important direction in the fields of computer science and artificial intelligence.

As one possible implementation, the text data is segmented by natural language processing NLP, so that a string of recognized text data is divided into a plurality of independent words. For example, a string of text data identified in a table of transaction materials is segmented, and different words are separated by a separation symbol.

For example, as shown in fig. 3, by recognizing the table in the graph through OCR, text data of "the security-participating user basic information personal number 1234, name xxx, gender, male birth date 10 month 1 year 2010 to transfer the unit name AA technology limited responsibility company national identity number 123456a, the household address xx city xx area" may be obtained, and by performing segmentation on the text data through natural language processing NLP, the segmented segmentation result data is "the security-participating user basic information & personal number &1234& name & xxx & gender & male & birth date 10 month 1 year 2010 & transfer the unit name & AA technology limited responsibility company & national identity number 123456a & household address & xx city xx area".

And step 204, extracting target data required by the social security management system from the text data based on preset target data extraction rules and word segmentation results.

The target data extraction rule is a rule set for extracting key field attribute values in a target form on the social security management system.

As a possible implementation manner, the target data extraction rule can be preset according to the actual condition of the data in the transaction materials of the insured user. Different social security businesses correspond to different materials and different target data to be extracted, but for the same business, the business materials to be submitted are uniform, so that the same social security business corresponds to the same target data extraction rule. And aiming at the social security service needing to be handled currently, the RPA robot system extracts the data of the segmentation result according to a preset target data extraction rule, so that target data required by the social security management system is obtained.

It is understood that the target data may be attribute values of key fields in a target form for handling related business in the social security administration system. As an example of a possible implementation manner, the key field may be an attribute of the data to be filled, and the attribute value is the data to be filled in the target form, where the target data corresponds to the data in the transaction materials of the participating user.

For example, as shown in fig. 3, when the RPA robot system determines that gender information of the social security insurance user needs to be filled in a target form on the social security management system, the "gender" is a key field, and therefore a target data extraction rule needs to be preset, so as to extract an attribute value corresponding to the "gender" of the key field from the text data according to the target data extraction rule, that is, extract an attribute value with the "gender" in the text data. Therefore, the extracted attribute value is "male", the corresponding key field is "gender", and the target data "male" is filled in the position corresponding to the key field "gender" in the target form on the social security management system.

As a possible implementation manner, each key field attribute value in the target form on the social security handling system is extracted based on the target data, and the target data extraction rule may be a rule set for extracting the key field attribute value. For example, it may be set to extract an attribute value between two specified adjacent fields, or it may be set to extract an attribute value behind one specified key field.

For example, as shown in fig. 3, in order to extract the attribute value of the key field "personal number" in the target form, according to the actual position of the key field "personal number" in the picture to be identified, it is determined that the attribute value is located between the field "personal number" and the field "name", so that the attribute value between the extraction field "personal number" and the field "name" can be set in the target data extraction rule in advance, and the extracted attribute value in the text data is "1234"; for another example, in order to extract the attribute value of the key field "household address" in the target form, according to the actual position of the key field "household address" in the picture to be recognized, it is determined that the attribute value is located after the field "household address" and is the last attribute value in the picture to be recognized, so that the attribute value "xx city xx area" corresponding to the field "household address" in the text data is extracted.

And step 205, recording the target data to the social security management system through the RPA technology.

In the embodiment of the present disclosure, step 205 may be implemented by adopting any one of the embodiments of the present disclosure, and this is not limited in the embodiment of the present disclosure and is not described again.

According to the social security data processing method combining the RPA and the AI, based on the artificial intelligence AI technology, the natural language processing NLP is carried out on the text data to obtain the word segmentation result of the text data, and the target data required by the social security handling system is extracted from the text data based on the preset target data extraction rule and the word segmentation result, so that the extracted target data can be accurately recorded on the social security handling system according to actual requirements.

EXAMPLE III

In order to ensure the automatic uploading of the target data, optionally, through the RPA technology, a user operation is simulated to access a target operation page of the social security management system, the target data is filled in a corresponding filling control in the target operation page, and a user click confirmation operation is simulated to enter the target data into a database of the social security management system. Fig. 4 is a flowchart of a social security data processing method combining the RPA and the AI in the third embodiment of the disclosure. It should be noted that the social security data processing method combining the RPA and the AI according to the embodiment of the present disclosure may be performed by an RPA robot system. In some embodiments of the disclosure, as shown in fig. 4, the social security data processing method combining RPA and AI includes:

step 401, acquiring a to-be-identified picture of transacted materials of a user under security by using a Robot Process Automation (RPA) technology.

In the embodiment of the present disclosure, step 401 may be implemented by using any one of the embodiments of the present disclosure, which is not limited in this disclosure and is not described again.

And 402, performing Optical Character Recognition (OCR) processing on the picture to be recognized based on an Artificial Intelligence (AI) technology to obtain text data.

In the embodiment of the present disclosure, step 402 may be implemented by any one of the embodiments of the present disclosure, which is not limited in this disclosure and is not described again.

Step 403, extracting the text data to obtain target data required by the social security management system.

In the embodiment of the present disclosure, step 403 may be implemented by any one of the embodiments of the present disclosure, which is not limited in this disclosure and is not described again.

In step 404, user operation is simulated through the RPA technology to access a target operation page of the social security management system.

As an example of a possible implementation manner, by using the RPA technology, a preset access address of the social security management system is obtained, a target operation page may be determined according to the type of the service to be handled, and the social security management system is accessed according to the access address and enters the target operation page.

And step 405, filling the target data into the corresponding filling control in the target operation page.

The filling control may be a control used for filling target data in the target operation page.

As an example of a possible implementation manner, each information to be filled in the target operation page is provided with a filling control, a filling control corresponding to the target data is found, and the target data is filled in the corresponding filling control.

In step 406, a user click confirmation operation is simulated to enter the target data into the database of the social security handling system.

As an example of one possible implementation, after filling the target data in the social security handling system, the RPA robot system may click on a relevant control such as a "ok" control or a "submit" control, or a button, and submit the filled target data, so as to enter the target data into the database of the social security handling system.

According to the social security data processing method combining the RPA and the AI, through the RPA technology, user operation is simulated to access a target operation page of the social security management system, target data are filled in a corresponding filling control in the target operation page, and a user click confirmation operation is simulated to record the target data into a database of the social security management system, so that automatic uploading of the target data is achieved, and the recording efficiency is effectively improved.

Example four

In order to ensure that the target data are accurately filled in the corresponding positions of the target operation page, optionally, the attribute of the target data is determined, a hypertext markup language (HTML) tag of a key field in the target operation page is identified through an RPA technology, the attribute of the target data is matched with the HTML tag, and the target data are filled in a filling control corresponding to the matched HTML tag in response to the matching of the attribute of the target data and the HTML tag. Fig. 5 is a flowchart of a social security data processing method combining the RPA and the AI in the fourth embodiment of the disclosure. It should be noted that the social security data processing method combining the RPA and the AI according to the embodiment of the present disclosure may be performed by an RPA robot system. In some embodiments of the disclosure, as shown in fig. 5, the social security data processing method combining RPA and AI includes:

step 501, acquiring a to-be-identified picture of transacted materials of a user under security by using a Robot Process Automation (RPA) technology.

In the embodiment of the present disclosure, step 501 may be implemented by any one of the embodiments of the present disclosure, which is not limited in this disclosure and is not described again.

Step 502, performing Optical Character Recognition (OCR) processing on the picture to be recognized based on an Artificial Intelligence (AI) technology to obtain text data.

In the embodiment of the present disclosure, step 502 may be implemented by any one of the embodiments of the present disclosure, which is not limited in this disclosure and is not described again.

Step 503, extracting the text data to obtain the target data required by the social security management system.

In the embodiment of the present disclosure, step 503 may be implemented by any one of the embodiments of the present disclosure, and the embodiments of the present disclosure do not limit this, and are not described again.

And step 504, simulating user operation through the RPA technology to access a target operation page of the social security management system.

In the embodiment of the present disclosure, step 504 may be implemented by any one of the embodiments of the present disclosure, and this is not limited in the embodiment of the present disclosure and is not described again.

And step 505, determining the attribute of the target data.

As an example of one possible implementation manner, the RPA robot may extract the text data according to a preset target data extraction rule, and the target data extraction rule may be a rule set for extracting each key field attribute value in the target form on the social security handling system. The key field can be the attribute of the data to be filled, the attribute value is the data to be filled in the target form, and the target data corresponds to the data in the transaction materials of the participating and ensuring users. Therefore, the attribute of the target data can be determined according to the target data extraction rule corresponding to the target data.

For example, as shown in fig. 3, if the attribute value between the field "name" and the field "gender" is extracted, the extracted attribute value is "xxx", the attribute value is the target data, and the attribute corresponding to the target data is the name.

Step 506, through the RPA technology, the HTML tag of the key field in the target operation page is identified.

It should be noted that, the sequence of execution of step 505 and step 506 is not distinguished.

The hypertext Markup Language (HTML for short) is a Markup Language, and includes a series of tags. The document formats on the network can be unified through the tags, so that the scattered internet resources are connected into a logic whole.

As a positive example, the RPA robot identifies HTML tags of key fields in the target operation page, and finds HTML tags corresponding to the key fields.

And step 507, matching the attribute of the target data with the HTML label.

For example, if the attribute of the target data is NAME, and the RPA robot recognizes that the HTML tag is "NAME" in the target operation page, the attribute of the target data is matched with the HTML tag.

And step 508, responding to the matching of the attribute of the target data and the HTML label, and filling the target data in a filling control corresponding to the matched HTML label.

For example, the HTML tag is "NAME", the attribute corresponding to the HTML tag is NAME, and the attribute of the target data is NAME, so that the attribute of the target data can be matched with the HTML tag, and the RPA robot fills the attribute value "xxx" corresponding to the attribute to the filling control corresponding to the HTML tag "NAME".

As an example of one possible implementation, there may be a plurality of target data. The RPA robot determines the attribute of each target data, identifies the HTML (hypertext markup language) tag of each key field in the target operation page through an RPA technology, matches the attributes of the target data with the HTML tags, and fills the target data into the filling control corresponding to the matched HTML tag in response to the matching of the attributes of the target data with the HTML tags.

In step 509, the user click confirmation operation is simulated to enter the target data into the database of the social security handling system.

In the embodiment of the present disclosure, step 509 may be implemented by any one of the embodiments of the present disclosure, which is not limited in this disclosure and is not described again.

According to the social security data processing method combining the RPA and the AI, the attribute of the target data is determined, the HTML tag of the key field in the target operation page is identified through the RPA technology, the attribute of the target data is matched with the HTML tag, the target data is filled in the filling control corresponding to the matched HTML tag in response to the matching of the attribute of the target data and the HTML tag, and therefore the target data is matched with the corresponding filling control in the target operation page, and the target data is accurately filled in the corresponding position of the target operation page.

EXAMPLE five

Optionally, through an RPA technique, user operation is simulated to access a login page of the social security management system, pre-stored login information is obtained, and the login information is filled in a corresponding filling control in the login page. Fig. 6 is a flowchart of a social security data processing method combining the RPA and the AI in the fifth embodiment of the disclosure. It should be noted that the social security data processing method combining the RPA and the AI according to the embodiment of the present disclosure may be performed by an RPA robot system. In some embodiments of the disclosure, as shown in fig. 6, the social security data processing method combining RPA and AI includes:

step 601, acquiring the picture to be identified of the transacted material of the user under security by adopting a Robot Process Automation (RPA) technology.

In the embodiment of the present disclosure, step 601 may be implemented by adopting any one of the embodiments of the present disclosure, which is not limited in the embodiment of the present disclosure and is not described again.

Step 602, performing Optical Character Recognition (OCR) processing on the picture to be recognized based on an Artificial Intelligence (AI) technology to obtain text data.

In the embodiment of the present disclosure, step 602 may be implemented by any one of the embodiments of the present disclosure, which is not limited in this disclosure and is not described again.

Step 603, extracting the text data to obtain target data required by the social security handling system.

In the embodiment of the present disclosure, step 603 may be implemented by any one of the embodiments of the present disclosure, which is not limited in the embodiment of the present disclosure and is not described again.

Step 604, simulating user operation to access the login page of the social security management system through the RPA technology.

As an example of one possible implementation, the access path of the login page of the social security handling system may be stored in advance on the computer device, and the RPA robot acquires the access path of the login page of the social security handling system and accesses the login page of the social security handling system according to the access path.

Step 605, pre-stored login information is obtained.

As an example of one possible implementation, login information for logging in the social security administration system may be stored in advance on the computer device, and the RPA robot acquires the login information. The login information may include at least one or more of the following items 1) -2): 1) logging in a user name; 2) and (6) logging in a password.

It should be noted that step 604 and step 605 do not distinguish the execution order.

And 606, filling the login information into the corresponding filling control in the login page to access the target operation page.

The filling control may be a control for filling in login information in a login page. As an example of one possible implementation manner, after the RPA robot fills the login information in the corresponding filling control in the login page, the RPA robot may click a relevant control such as a "confirm" control or a "submit" control, or a button, and then, in response to the social security administration system confirming that the login information is correct, complete the login operation, thereby accessing the target operation page.

And step 607, filling the target data into the corresponding filling control in the target operation page.

In the embodiment of the present disclosure, step 607 may be implemented by any one of the embodiments of the present disclosure, which is not limited in this disclosure and is not described again.

Step 608, simulating a user click confirmation operation to enter the target data into a database of the social security handling system.

In the embodiment of the present disclosure, step 608 may be implemented by any one of the embodiments of the present disclosure, and the embodiment of the present disclosure does not limit this and is not described again.

According to the social security data processing method combining the RPA and the AI, through the RPA technology, user operation is simulated to access the login page of the social security management system, pre-stored login information is obtained, the login information is filled in the corresponding filling control in the login page, and login operation is completed, so that automatic access can be performed on a target operation page, and further automation of social security data processing can be further achieved.

EXAMPLE six

In order to ensure that social security management staff can check and analyze the relevant conditions of the social security management staff to the social security management staff according to the report, optionally, the service transaction results returned by the social security management system are obtained through the RPA robot, the report is generated based on the account information and the service transaction results of the social security management staff, and the report is provided for the social security management terminal. Fig. 7 is a flowchart of a social security data processing method combining the RPA and the AI in the sixth embodiment of the disclosure. It should be noted that the social security data processing method combining the RPA and the AI according to the embodiment of the present disclosure may be performed by an RPA robot system. In some embodiments of the disclosure, as shown in fig. 7, the social security data processing method combining RPA and AI includes:

and 701, acquiring a to-be-identified picture of transacted materials of a user under security by adopting a Robot Process Automation (RPA) technology.

In the embodiment of the present disclosure, step 701 may be implemented by using any one of the embodiments of the present disclosure, which is not limited in this disclosure and is not described again.

And 702, performing Optical Character Recognition (OCR) processing on the picture to be recognized based on an Artificial Intelligence (AI) technology to obtain text data.

In the embodiment of the present disclosure, step 702 may be implemented by any one of the embodiments of the present disclosure, which is not limited in this disclosure and is not described again.

And 703, extracting the text data to obtain target data required by the social security handling system.

In the embodiment of the present disclosure, step 703 may be implemented by any one of the embodiments of the present disclosure, which is not limited in this embodiment of the present disclosure and is not described again.

Step 704, the target data is recorded into the social security management system through the RPA technology.

In the embodiments of the present disclosure, step 704 may be implemented by any one of the embodiments of the present disclosure, and the embodiments of the present disclosure do not limit this, and are not described again.

Step 705, a business transaction result returned by the social security management system is obtained.

In the embodiment of the disclosure, the service transaction result is result information returned by the social security management system for the transaction materials of the participating users when the target data is input into the social security management system.

As an example of one possible implementation manner, when the RPA robot enters the target data into the social security management system, the social security management system may return result information for the transaction materials of the participating users, and the RPA robot may obtain the result information. Optionally, the result information may be related prompt information given by the social security management system according to the entered information of the insurance-participating user, for example, a prompt "fee refund is required"; the result information may also be information that the social security management system feeds back the entry state of the target data, for example, prompting "entry success", or prompting "entry failure".

And step 706, generating a report based on the account information and the service transaction result of the insurance participating user, and providing the report to the social insurance management terminal.

As an example of one possible implementation manner, the RPA robot generates a report based on account information and a service transaction result of a participating user, and provides the report to the social security management terminal, so that social security management staff can conveniently check and analyze the service transaction condition. Optionally, the report may include one or more of the following 1) -3): 1) a participating user name;

2) a social security number; 3) the state is transacted. Wherein, the transaction status may be the transaction result.

As an example of a possible implementation manner, as shown in fig. 8, the RPA robot system may enter the service transaction information of multiple insured users, and therefore, the report may include account information of one or more insured users and service transaction result information corresponding to the insured users.

For example, after the RPA robot system completes the entry of the business transaction information of the insured user AA, the insured user BB and the insured user CC, a report is generated, and the report includes the social security number and the business transaction status corresponding to the three insured users. The RPA robot acquires the feedback information and generates the feedback information into a report if the feedback information given by the social security management system is 'refund required' according to the relevant target data of the AA of the insurance-participating user recorded into the social security management system; according to the related target data of the BB of the social security participating user, which is input into the social security management system, the social security management system confirms that the input operation is completed, and if the given feedback information is input successfully, the RPA robot acquires the feedback information and generates the feedback information into a report; and according to the relevant target data of the CC of the social security participation user, which is input into the social security management system, the social security management system confirms that the input operation is not completed, namely the input operation is identified, the feedback information is input failure, the RPA robot acquires the feedback information and generates the feedback information into a report.

According to the RPA and AI combined social security data processing method, the RPA robot is used for obtaining the business transaction results returned by the social security management system, a report is generated based on the account information and the business transaction results of the insurance participating users, and the report is provided for the social security management terminal, so that the social security management staff can check and analyze the relevant conditions of the insurance participating users according to the report.

EXAMPLE seven

In order to achieve the above embodiments, the present disclosure proposes a social security data processing apparatus that combines RPA and AI.

Fig. 9 is a block diagram of a social security data processing apparatus that combines an RPA and an AI in the seventh embodiment of the present disclosure. The device is applied to the RPA robot system. As shown in fig. 9, the apparatus includes:

an obtaining module 901, configured to obtain a to-be-identified picture of a transacted material of a participant through a Robot Process Automation (RPA) technology;

the processing module 902 is configured to perform Optical Character Recognition (OCR) processing on the picture to be recognized based on an Artificial Intelligence (AI) technology to obtain text data;

an extraction module 903, configured to extract text data to obtain target data required by the social security management system;

and an entry module 904, configured to enter the target data into the social security handling system through the RPA technology.

According to one embodiment of the present disclosure, the extraction module 903 comprises:

and the extraction submodule is used for extracting target data required by the social security management system from the text data based on a preset target data extraction rule and a word segmentation result.

As an example of one possible implementation: the target data extraction rule is a rule set for extracting key field attribute values in a target form on the social security management system.

As an example of one possible implementation: the logging module 904 includes:

the access submodule is used for simulating user operation through an RPA technology to access a target operation page of the social security management system;

and the entry sub-module is used for simulating the click confirmation operation of the user so as to enter the target data into the database of the social security handling system.

As an example of one possible implementation: filling out a sub-module, comprising:

the identification submodule is used for identifying the HTML (hypertext markup language) tags of the key fields in the target operation page through an RPA (remote procedure access) technology;

and the second filling sub-module is used for filling the target data into the filling control corresponding to the matched HTML label in response to the fact that the attribute of the target data is matched with the HTML label.

As an example of one possible implementation: the identification submodule comprises:

the login submodule is used for simulating user operation to access a login page of the social security management system through an RPA technology;

As an example of one possible implementation: the social security data processing apparatus combining the RPA and the AI further includes:

the second acquisition submodule is used for acquiring a service handling result returned by the social security handling system; the service handling result is result information returned by the social security management system aiming at handling materials of the insurance participating users when the target data is input into the social security management system;

and the generation submodule is used for generating a report based on the account information and the service handling result of the insurance participating user and providing the report to the social insurance handling terminal.

According to the social security data processing device combining the RPA and the AI, the picture to be recognized of the transacted material of the user participating in the security is obtained, the picture to be recognized is subjected to Optical Character Recognition (OCR) processing based on an artificial intelligence AI technology to obtain text data, the text data is extracted to obtain target data required by the social security management system, and therefore the target data is input to the social security management system through the RPA technology, the problem that errors are prone to occur in the manual input process is solved, and the input efficiency of the data is improved; in addition, the method is based on an artificial intelligence AI technology, Natural Language Processing (NLP) is carried out on the text data to obtain word segmentation results of the text data, and target data required by the social security management system are extracted from the text data based on preset target data extraction rules and word segmentation results, so that the extracted target data can be accurately recorded on the social security management system according to actual requirements.

Example eight

Fig. 10 is a block diagram of a computer device in an eighth embodiment of the disclosure. As shown in fig. 10, the computer apparatus 1000 may include:

a memory 1010 and a processor 1020, a bus 1030 connecting the various components (including the memory 1010 and the processor 1020), the memory 1010 storing instructions executable by the processor 1020; the processor 1020 is configured to execute instructions to implement the social security data processing method combining RPA and AI of the embodiment of the present disclosure.

Bus 1030 represents one or more of any of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, and a processor or local bus using any of a variety of bus architectures. By way of example, such architectures include, but are not limited to, Industry Standard Architecture (ISA) bus, micro-channel architecture (MAC) bus, enhanced ISA bus, Video Electronics Standards Association (VESA) local bus, and Peripheral Component Interconnect (PCI) bus.

Computer device 1000 typically includes a variety of electronic device readable media. Such media may be any available media that is accessible by computer device 1000 and includes both volatile and nonvolatile media, removable and non-removable media. Memory 1010 may also include computer system readable media in the form of volatile memory, such as Random Access Memory (RAM)1040 and/or cache memory 1050. The computer device 1000 may further include other removable/non-removable, volatile/nonvolatile computer system storage media. By way of example only, storage system 1060 may be used to read from and write to non-removable, nonvolatile magnetic media (not shown in FIG. 10, commonly referred to as a "hard disk drive"). Although not shown in FIG. 10, a magnetic disk drive for reading from and writing to a removable, nonvolatile magnetic disk (e.g., a "floppy disk") and an optical disk drive for reading from or writing to a removable, nonvolatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In such cases, each drive may be connected to bus 1030 by one or more data media interfaces. Memory 1010 may include at least one program product having a set (e.g., at least one) of program modules that are configured to carry out the functions of embodiments of the disclosure.

Program/utility 1080 having a set (at least one) of program modules 1070 may be stored, for example, in memory 1010, such program modules 1070 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each of which examples or some combination thereof may comprise an implementation of a network environment. Program modules 1070 generally perform the functions and/or methods of the embodiments described in this disclosure.

The computer device 1000 may also communicate with one or more external devices 1090 (e.g., keyboard, pointing device, display 1091, etc.), with one or more devices that enable a user to interact with the computer device 1000, and/or with any devices (e.g., network card, modem, etc.) that enable the computer device 1000 to communicate with one or more other computing devices. Such communication may occur through an input/output (I/O) interface 1092. Also, computer device 1000 may communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network such as the internet) through network adapter 1093. As shown, the network adapter 1093 communicates with the other modules of the computer device 1000 via the bus 1030. It should be understood that although not shown in the figures, other hardware and/or software modules may be used in conjunction with the computer device 1000, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, among others.

The processor 1020 executes various functional applications and data processing by executing programs stored in the memory 1010.

It should be noted that, for the implementation process and the technical principle of the computer of the present embodiment, reference is made to the foregoing explanation of the social security data processing method combining the RPA and the AI according to the embodiment of the present disclosure, and details are not described here again.

In order to implement the above embodiments, the present disclosure also provides a storage medium.

Wherein the instructions in the storage medium, when executed by a processor of a computer device, enable the computer device to perform the social security data processing method as before in conjunction with the RPA and AI.

To implement the above embodiments, the present disclosure also provides a computer program product. The computer program product comprises a computer program which, when executed by a processor of a computer device, implements the social security data processing method as before in conjunction with RPA and AI.

Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This disclosure is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.

It will be understood that the present disclosure is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims

1. A social security data processing method combining RPA and AI, which is applied to an RPA robot system, the method comprising:

2. The method as claimed in claim 1, wherein the extracting the text data to obtain target data required by the social security management system comprises:

3. The method as claimed in claim 2, wherein the target data extraction rule is a rule set for extracting key field attribute values in a target form on the social security management system.

4. The method as claimed in claim 1, wherein said entering said target data into said social security management system by said RPA technique comprises:

5. The method of claim 4, wherein the filling the target data into the corresponding filling control in the target operation page comprises:

determining the attribute of the target data;

matching the attribute of the target data with the HTML label;

6. The method of claim 4, wherein simulating, by the RPA technique, user operations to access a target operations page of the social security management system comprises:

obtaining pre-stored login information;

7. The method of claim 1, further comprising:

8. A social security data processing apparatus combining RPA and AI, the apparatus being applied to an RPA robot system, the apparatus comprising:

9. The apparatus of claim 8, wherein the extraction module comprises:

10. The apparatus according to claim 8, wherein the logging module comprises:

11. The apparatus of claim 10, wherein the first fill submodule comprises:

12. The apparatus of claim 11, wherein the identification submodule comprises:

13. A storage medium in which instructions, when executed by a processor of a computer device, enable the computer device to perform the social security data processing method in combination with RPA and AI of any one of claims 1 to 7.

14. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the social security data processing method in combination with RPA and AI of any one of claims 1 to 7 when executing the computer program.