Data processing method, device, electronic device and storage medium combining RPA and AI

Abstract

The present disclosure proposes a data processing method, device, electronic device and storage medium combining RPA and AI, which are applied to natural language processing (NLP). The method includes: using a robotic process automation (RPA) method to receive a processing request, and the processing request includes: an identifier of the data to be processed in an entity framework; using an RPA method to obtain a data processing method according to the identifier; and using an RPA method in combination with artificial intelligence (AI) to process the data to be processed and related data according to the data processing method, wherein the data to be processed and the related data have an edge association relationship in the entity framework. When using artificial intelligence (AI) in combination with robotic process automation (RPA) for data processing, automatic association processing of data is realized, and the cost consumed in the data association processing process is effectively reduced. When the corresponding data processing method is determined based on the identifier of the data to be processed in the entity framework, the degree of automation of data association processing and the reliability of association processing can be effectively taken into account.

Description

Technical Field

[0001] The present disclosure relates to the field of computer technology and is applied to natural language processing (NLP), and in particular to a data processing method, device, electronic device and storage medium combining RPA (Robotic Process Automation) and AI (Artificial Intelligence). Background Art

[0002] Robotic Process Automation (RPA), referred to as Robotic Process Automation, uses specific "robot software" to simulate human operations on computers and automatically execute process tasks according to rules.

[0003] Artificial Intelligence (AI) is a technical science that studies and develops theories, methods, technologies and application systems for simulating, extending and expanding human intelligence.

[0004] In the related art, when processing the associated data of a business in the field of computer technology, it is usually necessary to manually define a data processing method and process each associated data based on manual intervention.

[0005] This method requires a lot of manpower costs and cannot guarantee the reliability of data processing results. Summary of the invention

[0006] The present disclosure aims to solve one of the technical problems in the related art at least to some extent.

[0007] To this end, the purpose of the present disclosure is to propose a data processing method, device, electronic device and storage medium that combines RPA and AI. When artificial intelligence AI is used in combination with robotic process automation RPA for data processing, automatic association processing of data can be realized, and the cost consumed in the data association processing process can be effectively reduced. When the corresponding data processing method is determined based on the identification of the data to be processed in the entity framework, the degree of automation of data association processing and the reliability of association processing can be effectively taken into account.

[0008] The data processing method combining RPA and AI proposed in the first aspect of the embodiment of the present disclosure is applied to natural language processing (Natural Language Processing, NLP), including: using a robotic process automation (RPA) method to receive a processing request, wherein the processing request includes: an identifier of the data to be processed in an entity framework; using the RPA method to obtain a data processing method according to the identifier; and using the RPA method in combination with artificial intelligence (AI) to process the data to be processed and related data according to the data processing method, wherein the data to be processed and the related data have an edge association relationship in the entity framework.

[0009] The data processing method combining RPA and AI proposed in the embodiment of the first aspect of the present disclosure adopts a robotic process automation (RPA) method to receive a processing request, adopts an RPA method to obtain a data processing method according to an identifier, and adopts an RPA method combined with artificial intelligence (AI) to process the data to be processed and related data according to the data processing method. When artificial intelligence (AI) is combined with robotic process automation (RPA) for data processing, automatic data association processing is achieved, effectively reducing the cost consumed in the data association processing process. When the corresponding data processing method is determined based on the identifier of the data to be processed in the entity framework, the degree of automation of data association processing and the reliability of association processing can be effectively taken into account.

[0010] The data processing device combining RPA and AI proposed in the second aspect of the embodiment of the present disclosure is applied to natural language processing (Natural Language Processing, NLP), including: a receiving module, used to receive a processing request using a robotic process automation (RPA) method, wherein the processing request includes: an identifier of the data to be processed in an entity framework; an acquisition module, used to obtain a data processing method according to the identifier using an RPA method; and a processing module, used to process the data to be processed and related data according to the data processing method using an RPA method combined with artificial intelligence (AI), wherein the data to be processed and the related data have an edge association relationship in the entity framework.

[0011] The data processing device combining RPA and AI proposed in the second aspect of the embodiment of the present disclosure receives a processing request by adopting a robotic process automation (RPA) method, obtains a data processing method according to an identifier by adopting an RPA method, and processes the data to be processed and related data according to the data processing method by adopting an RPA method combined with artificial intelligence (AI). When artificial intelligence (AI) is combined with robotic process automation (RPA) for data processing, automatic data association processing is realized, effectively reducing the cost consumed in the data association processing process. When the corresponding data processing method is determined based on the identifier of the data to be processed in the entity framework, the degree of automation of data association processing and the reliability of association processing can be effectively taken into account.

[0012] The electronic device proposed in the third aspect embodiment of the present disclosure includes: at least one processor and a memory; the memory stores computer execution instructions; at least one processor executes the computer execution instructions stored in the memory, so that the at least one processor executes the data processing method combining RPA and AI proposed in the first aspect embodiment of the present disclosure.

[0013] The electronic device proposed in the third aspect embodiment of the present disclosure receives a processing request by adopting a robotic process automation (RPA) method, obtains a data processing method according to an identifier by adopting the RPA method, and processes the data to be processed and the related data according to the data processing method by adopting the RPA method in combination with artificial intelligence (AI). When artificial intelligence (AI) is used in combination with robotic process automation (RPA) for data processing, automatic data association processing is realized, effectively reducing the cost consumed in the data association processing process. When the corresponding data processing method is determined based on the identifier of the data to be processed in the entity framework, the degree of automation of the data association processing and the reliability of the association processing can be effectively taken into account.

[0014] The computer-readable storage medium proposed in the fourth aspect embodiment of the present disclosure stores computer execution instructions. When the processor executes the computer execution instructions, the data processing method combining RPA and AI proposed in the first aspect embodiment of the present disclosure is implemented.

[0015] The computer-readable storage medium proposed in the fourth aspect of the embodiment of the present disclosure receives a processing request by adopting a robotic process automation (RPA) method, obtains a data processing method according to an identifier by adopting the RPA method, and processes the data to be processed and the related data according to the data processing method by adopting the RPA method in combination with artificial intelligence (AI). When artificial intelligence (AI) is used in combination with robotic process automation (RPA) for data processing, automatic data association processing is realized, effectively reducing the cost consumed in the data association processing process. When the corresponding data processing method is determined based on the identifier of the data to be processed in the entity framework, the degree of automation of data association processing and the reliability of association processing can be effectively taken into account.

[0016] The above summary is for illustrative purposes only and is not intended to be limiting in any way. In addition to the illustrative aspects, embodiments and features described above, further aspects, embodiments and features of the present application will be readily apparent by reference to the accompanying drawings and the following detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The above and / or additional aspects and advantages of the present disclosure will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0018] Figure 1It is a flowchart of a data processing method combining RPA and AI proposed in one embodiment of the present disclosure;

[0019] Figure 2 is a flowchart of a data processing method combining RPA and AI proposed in another embodiment of the present disclosure;

[0020] Figure 3 is a flowchart of a data processing method combining RPA and AI proposed in another embodiment of the present disclosure;

[0021] Figure 4 is a structural diagram of a data processing device combining RPA and AI proposed in one embodiment of the present disclosure;

[0022] Figure 5 is a structural diagram of a data processing device combining RPA and AI proposed in another embodiment of the present disclosure;

[0023] Figure 6 A structural block diagram of an electronic device according to an embodiment of the present disclosure is shown. DETAILED DESCRIPTION

[0024] Embodiments of the present disclosure are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present disclosure, and are not to be construed as limitations of the present disclosure. On the contrary, the embodiments of the present disclosure include all changes, modifications, and equivalents that fall within the spirit and connotation of the appended claims.

[0025] Figure 1 It is a flowchart of a data processing method combining RPA and AI proposed in one embodiment of the present disclosure.

[0026] This embodiment takes the data processing method combining RPA and AI as an example configured in a data processing device combining RPA and AI. In this embodiment, the data processing method combining RPA and AI can be configured in a data processing device combining RPA and AI. The data processing device combining RPA and AI can be set in a server, or can also be set in an electronic device, and the embodiments of the present disclosure are not limited to this.

[0027] This embodiment takes the data processing method combining RPA and AI as an example, which is configured in an electronic device, such as a smart phone, a tablet computer, a personal digital assistant, an e-book, and other hardware devices with various operating systems.

[0028] It should be noted that the execution subject of the embodiment of the present disclosure may be, for example, a central processing unit (CPU) in a server or electronic device in terms of hardware, or may be, for example, a related background service in a server or electronic device in terms of software, without limitation.

[0029] In addition, the "processing" in the present disclosure refers to the process of data processing that combines robotic process automation (RPA) and artificial intelligence (AI). That is to say, the data processing process is a fully automated data processing process, and the data processing process is also combined with artificial intelligence (AI) to realize automated data processing in natural language processing (NLP).

[0030] The present disclosure can be specifically applied to Natural Language Processing (NLP) of artificial intelligence AI, which is a field of computer science, artificial intelligence, and linguistics that focuses on the interaction between computers and human (natural) language.

[0031] For example, the process of data processing based on the full-process automation in the present disclosure can realize the full-process automation execution of receiving processing requests using the robotic process automation (RPA) method, obtaining data processing methods based on identifiers using the RPA method, and processing the data to be processed and related data based on the data processing method using the RPA method combined with artificial intelligence (AI).

[0032] See also Figure 1 The data processing method that combines RPA and AI includes:

[0033] S101: Receive a processing request using a robotic process automation (RPA) method, wherein the processing request includes: an identifier of data to be processed in an entity framework.

[0034] Among them, processing refers to performing relevant processing operations on the data to be processed in the entity framework, such as deletion, updating, addition, etc., and there is no limitation on this. The processing request refers to the request received by the execution subject of the embodiment of the present disclosure, which can be used to trigger data association processing on the data to be processed in the entity framework. The processing request can be based on user configuration instructions to trigger relevant data association processing operations according to the user configuration instructions. Alternatively, a third-party control device can also be used to generate a processing request according to pre-configured operation instructions and send it to the execution subject of the embodiment of the present disclosure. Alternatively, any other possible method can be used to generate a processing request and transmit it to the execution subject of the embodiment of the present disclosure, and there is no limitation on this.

[0035] Optionally, in some embodiments, the entity framework may be an ent entity framework. Of course, the entity framework may also be any other possible entity framework involving business-related data association processing, and there is no limitation to this.

[0036] Among them, Entity Framework (EF) is an object-relational mapper (ORM), which is a tool that can be used to simplify the mapping between objects in software and tables and columns in relational databases. EF is an entity framework based on Go language, which is simple, powerful and scalable, allowing users to easily build and maintain applications with large data models.

[0037] The data to be processed refers to the data in the entity framework corresponding to the processing request. The data to be processed may be, for example, a data group, a data table, a field to be processed in a data table, etc. in the entity framework, and there is no limitation on this.

[0038] Among them, the identifier refers to the data in the processing request used to characterize the information related to the data to be processed in the entity framework. The identifier can be used to identify the data to be processed to assist in locating the data to be processed from the entity framework. The processing requirements of the data to be processed, the edge association relationship between the data to be processed and the associated data can also be determined based on the identifier. There is no restriction on this.

[0039] That is to say, in the implementation of the present disclosure, the robotic process automation (RPA) method can be used to obtain the identification of the data to be processed in the ent entity framework, and then the data processing method is obtained based on the identification, and the data to be processed in the ent entity framework is processed according to the obtained data processing method, thereby helping to improve the data association processing effect of the ent entity framework.

[0040] In the embodiments of the present disclosure, a processing request receiving interface can be set in the execution body of the data processing method combining RPA and AI, and a processing request can be received via the processing request receiving interface, without any limitation.

[0041] S102: Using the RPA method to obtain a data processing method according to the identifier.

[0042] Among them, the data processing method refers to the pre-formulated processing method applicable to the data to be processed, which is obtained by the executing subject in the embodiment of the present disclosure according to the identification of the obtained data to be processed. The data processing method can be specifically, for example, deletion processing, addition processing, marking processing, supplementation processing, soft deletion processing, etc., and there is no limitation on this.

[0043] In the embodiment of the present disclosure, the RPA method is used to obtain the data processing method according to the identifier. The identifier can be input into a pre-trained learning model (the learning model can be obtained in advance based on an artificial intelligence training method) to obtain the data processing method corresponding to the identifier, and transmit it to the execution subject of the implementation of the present disclosure. Alternatively, it can be based on a configured relationship table, which can record the data processing method applicable to the identifier, and transmit the data processing method applicable to the identifier in the relationship table to the execution subject of the embodiment of the present disclosure. Alternatively, any other possible method can be used to obtain the corresponding data processing method, and there is no limitation to this.

[0044] Therefore, in the embodiment of the present disclosure, by adopting the RPA method to obtain the data processing method according to the identifier, the obtained data processing method can be effectively adapted to the actual application scenarios in the data processing process, and can effectively improve the efficiency of data association processing, and can effectively take into account the degree of automation of data association processing and the reliability of association processing.

[0045] S103: The RPA method is combined with artificial intelligence AI to process the data to be processed and the related data according to the data processing method, wherein the data to be processed and the related data have an edge association relationship in the entity framework.

[0046] Here, association refers to the association between the data to be processed and other data in the entity framework, and associated data may refer to data in the entity framework that is associated with the data to be processed. The associated data may specifically be, for example, a data group, a data table, a field to be processed in a data table, etc. that is associated with the data to be processed, and there is no limitation on this.

[0047] Among them, edge refers to multiple edges extending from the relevant characteristics of the data to be processed, and each edge can establish a corresponding association relationship with other data. The edge association relationship refers to the association relationship between the data to be processed and the related data. The edge association relationship can be specific, for example, one-to-many, many-to-one, one-to-one, many-to-many, etc., and there is no limitation on this.

[0048] The present disclosure is implemented by using the RPA method in combination with artificial intelligence AI. When processing the data to be processed and the related data according to the data processing method, the data to be processed and the related data can be spliced ​​and combined according to the edge association relationship to obtain the combined data, and then the combined data is processed by the data processing method. Alternatively, the data to be processed and the related data can be input into a pre-trained data processing model (the data processing model can be obtained in advance based on the artificial intelligence method), and the data processing is performed according to the data processing method, and the processing result is transmitted to the execution subject of the embodiment of the present disclosure. Alternatively, any other possible method can be used to process the data to be processed and the related data, without limitation.

[0049] Therefore, in the embodiments of the present disclosure, by adopting the RPA method in combination with artificial intelligence AI, the data to be processed and the related data are processed according to the data processing method, which can avoid repetitive processing operations in the process of processing related data. When processing the data to be processed, the related data is processed in an associative manner, thereby realizing automatic associative processing of data and effectively improving the cost consumed in the data association processing process.

[0050] In the implementation of the present disclosure, a processing request is received by adopting a robotic process automation (RPA) method, a data processing method is obtained according to an identifier by adopting an RPA method, and the data to be processed and related data are processed according to the data processing method by adopting an RPA method in combination with artificial intelligence (AI). When data processing is performed by using artificial intelligence (AI) in combination with robotic process automation (RPA), automatic data association processing is achieved, and the cost consumed in the data association processing process is effectively reduced. When the corresponding data processing method is determined based on the identifier of the data to be processed in the entity framework, the degree of automation of data association processing and the reliability of association processing can be effectively taken into account.

[0051] Figure 2 It is a flowchart of a data processing method combining RPA and AI proposed in another embodiment of the present disclosure.

[0052] See also Figure 2 The data processing method that combines RPA and AI includes:

[0053] S201: Receive a processing request using a robotic process automation (RPA) method, wherein the processing request includes: an identifier of data to be processed in an entity framework.

[0054] The description of S201 can be specifically referred to the above embodiment, which will not be repeated here.

[0055] S202: Using the RPA method to obtain the template content in the entity framework.

[0056] Among them, template refers to the result of fixing and standardizing the structural rules of a thing, which reflects the standardization of the structural form, and the template content, in the embodiment of the present disclosure, may refer to a reference template pre-configured in the entity framework for assisting data processing. The template content may specifically describe the possible associations between data, as well as the corresponding data processing methods, etc., without limitation.

[0057] Therefore, after the implementation of the present disclosure adopts the Robotic Process Automation (RPA) method to receive a processing request, the RPA method can be used to obtain the template content in the entity framework to trigger subsequent steps. The template content can be used as a reference template for determining the data processing method. When the data to be processed and the related data have an edge association relationship defined in the configuration file, the corresponding data processing method can be determined from the template content according to the identification of the data to be processed, which can effectively improve the intelligence and processing efficiency of the data processing process.

[0058] S203: Reading a target configuration file matching the identifier from the template content using an RPA method, wherein the target configuration file defines an edge association relationship between the data to be processed and the associated data.

[0059] In the embodiment of the present disclosure, the edge association relationship between the data to be processed and the associated data can be pre-defined, and then the edge association relationship between the data to be processed and the associated data can be written into the target configuration file. The target configuration file can also be marked according to the identifier of the data to be processed, indicating that the target configuration file matching the identifier defines the edge association relationship related to the data to be processed to which the identifier belongs.

[0060] The above-mentioned configuration file can be a pre-configured file used to define the edge association relationship between the data to be processed and the related data, and the target configuration file refers to a configuration file that matches the identifier (i.e., defines the edge association relationship related to the data to be processed to which the identifier belongs) among multiple pre-configured configuration files.

[0061] For example, in the ent entity framework, the disclosed embodiment can define the relationship between multiple data tables through the edges in the database schema, and save the defined edge relationship as a configuration file in the template content, and then generate and save the corresponding data processing method in the template content according to the relationship. Therefore, in the actual data processing process, the target configuration file can be determined according to the identification of the data to be processed, and the corresponding data processing method can be called.

[0062] The embodiment of the present disclosure adopts an RPA method to read a target configuration file that matches the identifier from the template content. For example, the identifier and the template content can be input into a pre-trained learning model (the learning model can be obtained in advance based on an artificial intelligence method) to determine the target configuration file that matches the identifier, and transmit the target configuration file to the execution subject of the embodiment of the present disclosure. Alternatively, an engineering method can be used to analyze the matching information between multiple configuration files in the template and the identifier, and the target configuration file is determined based on the matching information. Alternatively, any other possible method can be used to determine the target configuration file, and there is no limitation on this.

[0063] Optionally, in some embodiments, the RPA method is used to read the target configuration file that matches the identifier from the template content. The RPA method can be used to determine the target data type of the data to be processed to which the identifier belongs, wherein the target data type corresponds to the target pattern in the entity framework, and then the RPA method is used to use the configuration file under the target pattern in the template content as the target configuration file, wherein the target configuration file defines the edge association relationship between the data to be processed and the related data based on the target pattern. Therefore, when the target pattern in the entity framework is determined based on the target data type of the data to be processed, and then the target configuration file is determined according to the target pattern, the efficiency of using the RPA method to read the target configuration file that matches the identifier from the template content is greatly improved, and at the same time, the accuracy of the representation of the edge association relationship between the data to be processed and the related data by the relevant information in the obtained target configuration file can be ensured.

[0064] Among them, the data type may refer to the "roles" configured for the two sets of data in the edge association relationship when the two sets of data have an edge association relationship, and the target data type refers to the "role" configured for the data to be processed in the edge association relationship with the associated data during this data processing process.

[0065] For example, in the ent entity framework, a user entity can be configured with multiple pet entities, while a Pet entity can only be configured with one User entity. Therefore, when defining edge relationships, the Pet edge is a one-to-many relationship, and the User edge is a many-to-one relationship. During data processing, the target data type can be determined based on the edge relationship. The target data type can be a User type, a Pet type, etc., without restriction.

[0066] Among them, the schema can be pre-configured in the entity framework and is used to store the above configuration files according to the data type of the data to be processed. It can be understood that there can be multiple schemas in the entity framework, and there may be data associations between multiple schemas.

[0067] For example, in the ent entity framework, when the data type of the data to be processed is the User type, during the data association processing, the corresponding mode of the data to be processed in the entity framework is the User mode. In the User mode, the edge.To statement can be used to establish the connection between the data to be processed (User entity) and the associated data (Pet entity); when the data type of the data to be processed is the Pet type, during the data association processing, the corresponding mode of the data to be processed in the entity framework is the Pet mode. In the Pet mode, there is only a reverse reference to the data to be processed (Pet entity), which can be declared using the edge.From statement and / or the Ref (comparison of columns and indexes, indicating the connection matching conditions between multiple tables, that is, which columns or constants are used to find the value on the index column) method, where the Ref method describes which edge of the User mode is referenced by the data to be processed in the Pet mode. Because there can be multiple references from one mode to another, in this processing process, the unique constraint method can be used to control the cardinality of the edge / relationship.

[0068] S204: Using the RPA method to obtain a data processing method that matches the edge association relationship, wherein the matching data processing method is pre-constructed based on the edge association relationship.

[0069] It is understandable that during the data processing process, the data processing requirements corresponding to different edge associations may be different. Therefore, different data processing methods are determined according to the edge associations to perform data processing, thereby effectively improving the rationality of the obtained data processing method.

[0070] That is to say, after the embodiment of the present disclosure adopts the Robotic Process Automation (RPA) method to receive the processing request, the RPA method can be used to obtain the template content in the entity framework, and the RPA method can be used to read the target configuration file that matches the identifier from the template content, wherein the target configuration file defines the edge association relationship between the data to be processed and the related data, and the RPA method is used to obtain the data processing method that matches the edge association relationship, wherein the matching data processing method is pre-constructed according to the edge association relationship. Therefore, when the data processing method is constructed based on the edge association relationship between the data to be processed and the related data, the applicability of the obtained data processing method to the data to be processed and the related data can be effectively improved. Moreover, the data processing method is constructed based on the edge association relationship, so it can also be effectively adapted to the actual application scenarios in the data processing process, thereby improving the practicality and flexibility of the data processing method combining RPA and AI.

[0071] S205: Adopting the RPA method in combination with artificial intelligence AI, according to the data processing method, the data to be processed and the associated data are processed, wherein there is an edge association relationship in the entity framework between the data to be processed and the associated data.

[0072] The description of S205 can be specifically referred to the above embodiment, which will not be repeated here.

[0073] In the disclosed embodiment, a robotic process automation (RPA) method is used to receive a processing request, an RPA method is used to obtain template content in an entity framework, an RPA method is used to read a target configuration file that matches an identifier from the template content, wherein an edge association relationship between the data to be processed and the associated data is defined in the target configuration file, an RPA method is used to obtain a data processing method that matches the edge association relationship, wherein the matched data processing method is pre-constructed based on the edge association relationship, an RPA method is used in combination with artificial intelligence (AI), and according to the data processing method, the data to be processed and the associated data are processed, wherein there is an edge association relationship in the entity framework between the data to be processed and the associated data. When the edge association relationship between the data to be processed and the associated data is defined based on the edge association relationship between the data to be processed and the associated data, The data processing method based on edge association relationship construction can effectively improve the applicability of the obtained data processing method for the data to be processed and the related data. The data processing method is constructed based on the edge association relationship, so it can also be effectively adapted to the actual application scenarios in the data processing process, thereby improving the practicality and flexibility of the data processing method combining RPA and AI. When the target mode in the entity framework is determined based on the target data type of the data to be processed, and then the target configuration file is determined according to the target mode, the efficiency of using the RPA method to read the target configuration file that matches the identifier from the template content is greatly improved, and at the same time, the accuracy of the representation of the edge association relationship between the data to be processed and the related data in the obtained target configuration file can be ensured.

[0074] Figure 3 It is a flowchart of a data processing method combining RPA and AI proposed in another embodiment of the present disclosure.

[0075] See also Figure 3 The data processing method that combines RPA and AI includes:

[0076] S301: Receive a processing request using a robotic process automation (RPA) method, wherein the processing request includes: an identifier of data to be processed in an entity framework.

[0077] The description of S301 can be specifically referred to the above embodiment, which will not be repeated here.

[0078] S302: Determine the edge association relationship between the data to be processed and the associated data using the RPA method, and define the edge association relationship using the target configuration file in the template content of the entity framework.

[0079] It is understandable that there are many possibilities for the edge association relationship between the data to be processed and the associated data, so there may not be a target configuration file matching the identifier in the template content in the entity framework. Therefore, after receiving the processing request using the Robotic Process Automation (RPA) method, the disclosed embodiment can use the RPA method to determine the edge association relationship between the data to be processed and the associated data, and use the target configuration file in the template content of the entity framework to define the edge association relationship, thereby supplementing the template content, ensuring that the template content is suitable for specific application scenarios, triggering subsequent steps, and determining the data processing method according to the processing request and the template content.

[0080] For example, in the ent entity framework, you can use the edge.From statement and edge.To statement to maintain the edge relationship between the tables. When adding a new edge relationship in User mode, you can use the edge.To statement to configure the new edge relationship in the Schema corresponding to the data to be processed, so that the edge relationship can be called in the subsequent data processing process and the corresponding modification statement can be generated.

[0081] S303: The RPA method is combined with artificial intelligence AI to generate a first processing method corresponding to the data to be processed, wherein, in response to a processing request, the first processing method can be called to process the data to be processed.

[0082] Among them, the first processing method refers to a data processing method suitable for the data to be processed that is generated by combining the RPA method with artificial intelligence AI.

[0083] Optionally, in some embodiments, the first processing method may be a soft deletion processing method. Of course, it may also be any other possible processing method applicable to the embodiments of the present disclosure, such as update processing, query processing, etc., without limitation.

[0084] Among them, soft deletion means that the data in the database is not deleted. The data can be restored, but the data after the soft deletion process is blocked in the user's "view".

[0085] It is understandable that the data itself may have actual value or potential value. When users delete data by directly deleting the data and then discover the potential value of the data, they may not be able to retrieve the deleted data, causing losses to the users. Soft deletion can solve this problem well.

[0086] S304: The RPA method is combined with artificial intelligence AI to generate a second processing method corresponding to the associated data according to the edge association relationship, wherein the second processing method is used to link the associated data when the first processing method is called.

[0087] Among them, the second processing method refers to a data processing method suitable for associated data generated by combining the RPA method with artificial intelligence AI based on edge correlation relationships.

[0088] It can be understood that in the data processing process, the first processing object of data processing is the data to be processed, the second processing object is the related data, and the processing of the related data depends on the edge association relationship. Therefore, when the RPA method is combined with artificial intelligence AI to generate a second processing method corresponding to the related data according to the edge association relationship, the applicability of the second processing method for the related data can be effectively improved. When the first processing method is called, the second processing method is called in conjunction with the related data, which can effectively improve the overall efficiency of data processing.

[0089] Optionally, in some embodiments, the second processing method may be a soft deletion processing method. Of course, it may also be any other possible processing method applicable to the embodiments of the present disclosure, without limitation. Therefore, when the first processing method and the second processing method are soft deletion processing methods, it can meet the user's needs for data deletion processing while avoiding performance problems that may be caused by frequent data deletion operations. It can also restore deleted data according to user configuration instructions to avoid losses caused by the inability to retrieve deleted data, effectively improving the robustness of the data processing method that combines RPA and AI.

[0090] Therefore, in the embodiment of the present disclosure, when there is no target configuration file matching the identifier in the template content of the entity framework, the RPA method can be used to determine the edge association relationship between the data to be processed and the related data, and the target configuration file in the template content of the entity framework can be used to define the edge association relationship, and then the RPA method combined with artificial intelligence AI can be used to generate a first processing method corresponding to the data to be processed, and the RPA method combined with artificial intelligence AI can be used to generate a second processing method corresponding to the related data according to the edge association relationship. Therefore, the RPA method is used to determine the edge association relationship between the data to be processed and the related data, and the target configuration file in the template content of the entity framework can be used to define the edge association relationship, which can ensure that the target configuration file matches the identifier of the data to be processed during the data processing process. The obtained edge association relationship and the corresponding first processing method and second processing method can continuously improve and expand the template content in the entity framework, and can be used to call and process related data with the same edge association relationship, which can effectively improve the applicability and scalability of the data processing method combining RPA and AI.

[0091] For example, a soft delete operation is performed in the ent entity framework. The disclosed embodiment can loop through the node data in the graph database (Graph) in the ent entity framework in the template content, and define the implementation method of the soft delete in the loop body according to the specific application scenario. The UpdateName statement is used as the update generator, and the data to be processed can be set to a modified state. Then, the associated data of the data to be processed is obtained through the loop edge. Through all the IDs of the queried associated entities, the corresponding modification statements are generated according to the edge association relationship defined in the target configuration file. Thus, the associated deletion operation is implemented through the edge association relationship.

[0092] S305: Using the RPA method to obtain the template content in the entity framework.

[0093] S306: Using an RPA method, read a target configuration file that matches the identifier from the template content, wherein the target configuration file defines an edge association relationship between the data to be processed and the associated data.

[0094] S307: Using the RPA method to obtain a data processing method that matches the edge association relationship, wherein the matching data processing method is pre-constructed based on the edge association relationship.

[0095] The description of S305 to S307 can be specifically referred to the above embodiment, which will not be repeated here.

[0096] S308: Adopting the RPA method in combination with artificial intelligence AI, according to the data processing method, the data to be processed and the related data are processed, wherein there is an edge association relationship in the entity framework between the data to be processed and the related data.

[0097] It can be understood that in the embodiment of the present disclosure, after the first processing method and the second processing method are obtained, the first processing method and the second processing method are applicable to this data processing process.

[0098] Therefore, in some embodiments, the RPA method is combined with artificial intelligence AI. According to the data processing method, processing the data to be processed and the related data can be that when the RPA method responds to the processing request, the first processing method is called to jointly process the data to be processed by artificial intelligence AI. When the first processing method is called, the RPA method is used to call the second processing method, and the related data is processed by artificial intelligence AI. In this way, the logical delay caused by obtaining the data processing method again can be avoided, and the data processing efficiency can be effectively improved. The first processing method responds to the processing request, which can effectively improve the timeliness and rationality of executing data processing. When the first processing method is called, the RPA method is used to call the second processing method, and the related data is processed by artificial intelligence AI. It can replace the user to perform corresponding data processing operations on the related data, which can effectively improve the portability of data processing.

[0099] In the embodiment of the present disclosure, when there is no target configuration file matching the identifier in the template content of the entity framework, the RPA method is used to determine the edge association relationship between the data to be processed and the associated data, and then the RPA method is used in combination with artificial intelligence AI to generate a first processing method corresponding to the data to be processed, and the RPA method is used in combination with artificial intelligence AI to generate a second processing method corresponding to the associated data based on the edge association relationship, which are used for subsequent processing of the data to be processed and the associated data, respectively. Therefore, the RPA method is used to determine the edge association relationship between the data to be processed and the associated data, and the target configuration file in the template content of the entity framework is used to define the edge association relationship, which can ensure that the target configuration file matches the identifier of the data to be processed during the data processing process. The obtained edge association relationship and the corresponding first processing method and second processing method can continuously improve the template content in the entity framework, and can be used to call and process associated data with the same edge association relationship, which can effectively improve the applicability and scalability of the data processing method combining RPA and AI. When the RPA method is used to respond to the processing request, the first processing method is called to jointly process the data to be processed by artificial intelligence AI. When the first processing method is called, the RPA method is used to call the second processing method and jointly process the related data by artificial intelligence AI. This can avoid the logical delay caused by re-acquiring the data processing method, and can effectively improve the data processing efficiency. The first processing method responds to the processing request, which can effectively improve the timeliness and rationality of executing data processing. When the first processing method is called, the RPA method is used to call the second processing method in linkage, and jointly process the related data by artificial intelligence AI. This can replace the user to perform the corresponding data processing operation on the related data, and can effectively improve the portability of data processing. When the first processing method and the second processing method are soft deletion processing methods, while meeting the user's demand for data deletion processing, it can avoid the performance problems that may be caused by frequent data deletion operations. It can also restore the deleted data according to the user configuration instructions to avoid losses caused by the inability to retrieve the deleted data, and effectively improve the robustness of the data processing method combining RPA and AI.

[0100] Figure 4 It is a structural diagram of a data processing device combining RPA and AI proposed in one embodiment of the present disclosure.

[0101] See also Figure 4 The data processing device 400 combining RPA and AI includes:

[0102] The receiving module 401 is used to receive a processing request using a robotic process automation (RPA) method, wherein the processing request includes: an identifier of the data to be processed in the entity framework;

[0103] An acquisition module 402 is used to acquire a data processing method according to the identifier using an RPA method; and

[0104] The processing module 403 is used to process the data to be processed and the related data according to the data processing method by using the RPA method in combination with artificial intelligence AI, wherein the data to be processed and the related data have an edge association relationship in the entity framework.

[0105] Optionally, in some embodiments, see Figure 5 , Figure 5 4 is a schematic diagram of a data processing device combining RPA and AI proposed in another embodiment of the present disclosure, wherein the acquisition module 402 includes:

[0106] The first acquisition submodule 4021 is used to acquire the template content in the entity framework using the RPA method;

[0107] The second acquisition submodule 4022 is used to read a target configuration file matching the identifier from the template content using an RPA method, wherein the target configuration file defines an edge association relationship between the data to be processed and the associated data;

[0108] The third acquisition submodule 4023 is used to adopt the RPA method to acquire the data processing method that matches the edge association relationship, wherein the matching data processing method is pre-constructed according to the edge association relationship.

[0109] Optionally, in some embodiments, the second acquisition submodule 4022 is specifically used to:

[0110] Determine a target data type of the data to be processed to which the identifier belongs by using an RPA method, wherein the target data type corresponds to a target schema in an entity framework;

[0111] The RPA method is adopted to use the configuration file under the target mode in the template content as the target configuration file, wherein the target configuration file defines the edge association relationship between the to-be-processed data and the associated data based on the target mode.

[0112] Optionally, in some embodiments, the acquisition module 402 further includes:

[0113] A determination submodule 4024 is used to determine the edge association relationship between the data to be processed and the associated data using the RPA method;

[0114] A first generating submodule 4025 is used to generate a first processing method corresponding to the data to be processed by using the RPA method in combination with artificial intelligence AI, wherein the first processing method can be called to process the data to be processed in response to the processing request;

[0115] The second generation submodule 4026 is used to generate a second processing method corresponding to the associated data based on the edge association relationship by adopting the RPA method in combination with artificial intelligence AI, wherein the second processing method is used to link the associated data when the first processing method is called.

[0116] Optionally, in some embodiments, the processing module 403 is specifically configured to:

[0117] When the RPA method is used to respond to the processing request, the first processing method is called to jointly process the data to be processed with the artificial intelligence AI;

[0118] When the first processing method is called, the RPA method is used to call the second processing method, and artificial intelligence AI is used to process related data.

[0119] Optionally, in some embodiments, the first processing method is a soft deletion processing method, and the second processing method is a soft deletion processing method.

[0120] Optionally, in some embodiments, the entity framework is the ent entity framework.

[0121] The functions of each module in the data processing device combining RPA and AI in the embodiments of the present disclosure can be found in the corresponding description in the above-mentioned data processing method combining RPA and AI, and will not be repeated here.

[0122] In the implementation of the present disclosure, a processing request is received by adopting a robotic process automation (RPA) method, a data processing method is obtained according to an identifier by adopting an RPA method, and the data to be processed and related data are processed according to the data processing method by adopting an RPA method in combination with artificial intelligence (AI). When data processing is performed by using artificial intelligence (AI) in combination with robotic process automation (RPA), automatic related processing of data is realized, and the cost consumed in the data processing process is effectively reduced. When the corresponding data processing method is determined based on the identifier of the data to be processed in the entity framework, the degree of automation of data related processing and the reliability of related processing can be effectively taken into account.

[0123] Figure 6 FIG. 1 is a block diagram showing a structure of an electronic device according to an embodiment of the present disclosure. Figure 6 As shown, the electronic device includes: a memory 610 and a processor 620, wherein the memory 610 stores a computer program that can be run on the processor 620. When the processor 620 executes the computer program, the data processing method combining RPA and AI in the above embodiment is implemented. The number of the memory 610 and the processor 620 can be one or more.

[0124] The electronic device also includes:

[0125] The communication interface 630 is used to communicate with external devices and perform data exchange transmission.

[0126] If the memory 610, the processor 620 and the communication interface 630 are implemented independently, the memory 610, the processor 620 and the communication interface 630 can be connected to each other through a bus and communicate with each other. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 6 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0127] Optionally, in a specific implementation, if the memory 610, the processor 620 and the communication interface 630 are integrated on a chip, the memory 610, the processor 620 and the communication interface 630 can communicate with each other through an internal interface.

[0128] An embodiment of the present disclosure provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements a data processing method combining RPA and AI provided in an embodiment of the present disclosure.

[0129] An embodiment of the present disclosure also provides a chip, which includes a processor for calling and executing instructions stored in the memory from the memory, so that a communication device equipped with the chip executes the data processing method combining RPA and AI provided by an embodiment of the present disclosure.

[0130] The embodiments of the present disclosure also provide a chip, including: an input interface, an output interface, a processor and a memory. The input interface, the output interface, the processor and the memory are connected through an internal connection path. The processor is used to execute the code in the memory. When the code is executed, the processor is used to execute the data processing method combining RPA and AI provided in the disclosed embodiments.

[0131] It should be understood that the processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor, etc. It is worth noting that the processor may be a processor supporting the advanced RISC machines (ARM) architecture.

[0132] Further, optionally, the above-mentioned memory may include a read-only memory and a random access memory, and may also include a non-volatile random access memory. The memory may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memories. Among them, the non-volatile memory may include a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory may include a random access memory (RAM), which is used as an external cache. By way of example but not limitation, many forms of RAM are available. For example, static RAM (SRAM), dynamic random access memory (DRAM), synchronous DRAM (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM) and direct rambus RAM (DR RAM).

[0133] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function according to the present disclosure is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium.

[0134] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present disclosure. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, unless they are contradictory.

[0135] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of the features. In the description of the present disclosure, the meaning of "plurality" is two or more, unless otherwise clearly and specifically defined.

[0136] Any process or method description described in the flowchart or otherwise herein can be understood to represent a module, segment or portion of code including one or more executable instructions for implementing the steps of a specific logical function or process. And the scope of the preferred embodiments of the present disclosure includes other implementations, in which the functions may not be performed in the order shown or discussed, including in a substantially simultaneous manner or in a reverse order according to the functions involved.

[0137] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, which can be embodied in any computer-readable medium for use by an instruction execution system, apparatus or device (such as a computer-based system, a system including a processor or other system that can fetch instructions from an instruction execution system, apparatus or device and execute instructions), or used in combination with these instruction execution systems, apparatuses or devices.

[0138] It should be understood that the various parts of the present disclosure may be implemented with hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods may be implemented with software or firmware stored in a memory and executed by a suitable instruction execution system. All or part of the steps of the above embodiment method may be completed by instructing the relevant hardware through a program, which may be stored in a computer-readable storage medium, and when the program is executed, includes one or a combination of the steps of the method embodiment.

[0139] In addition, each functional unit in each embodiment of the present disclosure may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the above-mentioned integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium. The storage medium may be a read-only memory, a disk or an optical disk, etc.

[0140] The above is only a specific implementation of the present disclosure, but the protection scope of the present disclosure is not limited thereto. Any technician familiar with the technical field can easily think of various changes or substitutions within the technical scope disclosed in the present disclosure, which should be included in the protection scope of the present disclosure. Therefore, the protection scope of the present disclosure should be based on the protection scope of the claims.

Claims

1. A data processing method combining RPA and AI, characterized in that: Applied to natural language processing (NLP), including: A processing request is received using a robotic process automation (RPA) method, wherein the processing request includes: an identification of data to be processed in an entity framework; Acquire a data processing method according to the identifier using the RPA method; and The RPA method is combined with artificial intelligence AI to process the data to be processed and the associated data according to the data processing method, wherein the data to be processed and the associated data have an edge association relationship in the entity framework; Wherein, the adopting the RPA method to obtain the data processing method according to the identifier includes: The RPA method is used to obtain the template content in the entity framework; The RPA method is used to read a target configuration file matching the identifier from the template content, wherein the target configuration file defines the edge association relationship between the data to be processed and the associated data; The RPA method is used to obtain the data processing method that matches the edge association relationship, wherein the matching data processing method is pre-constructed based on the edge association relationship.

2. The method according to claim 1, characterized in that The adopting the RPA method to read a target configuration file matching the identifier from the template content, wherein the target configuration file defines the edge association relationship between the to-be-processed data and the associated data, includes: Determine a target data type of the data to be processed to which the identifier belongs using the RPA method, wherein the target data type corresponds to a target schema in the entity framework; The RPA method is adopted to use the configuration file under the target mode in the template content as the target configuration file, wherein the target configuration file defines the edge association relationship between the to-be-processed data and the associated data based on the target mode.

3. The method according to claim 1, characterized in that Before the RPA method is used to obtain the template content in the entity framework, the method further includes: Determine the edge association relationship between the data to be processed and the associated data using the RPA method, and define the edge association relationship using a target configuration file in the template content of the entity framework; The RPA method is combined with artificial intelligence AI to generate a first processing method corresponding to the data to be processed, wherein, in response to the processing request, the first processing method can be called to process the data to be processed; The RPA method is combined with artificial intelligence AI to generate a second processing method corresponding to the associated data according to the edge association relationship, wherein the second processing method is used to link the associated data when the first processing method is called.

4. The method according to claim 3, characterized in that The RPA method is combined with artificial intelligence AI to process the data to be processed and the associated data according to the data processing method, including: When the RPA method is used to respond to the processing request, the first processing method is called to jointly process the data to be processed with the artificial intelligence AI; When the first processing method is called, the second processing method is called by the RPA method, and the associated data is processed in conjunction with the artificial intelligence AI.

5. The method according to claim 3 or 4, characterized in that The first processing method is a soft deletion processing method, and the second processing method is the soft deletion processing method.

6. The method according to any one of claims 1 to 4, characterized in that: The entity framework is ent entity framework.

7. A data processing device combining RPA and AI, characterized in that: Applied to natural language processing (NLP), including: A receiving module, configured to receive a processing request using a robotic process automation (RPA) method, wherein the processing request includes: an identifier of data to be processed in an entity framework; an acquisition module, configured to acquire a data processing method according to the identifier using the RPA method; and A processing module, used to process the data to be processed and the associated data by using the RPA method in combination with artificial intelligence AI according to the data processing method, wherein the data to be processed and the associated data have an edge association relationship in the entity framework; Wherein, the acquisition module includes: A first acquisition submodule is used to acquire the template content in the entity framework using the RPA method; A second acquisition submodule is configured to read a target configuration file matching the identifier from the template content using the RPA method, wherein the target configuration file defines the edge association relationship between the data to be processed and the associated data; The third acquisition submodule is used to adopt the RPA method to acquire the data processing method that matches the edge association relationship, wherein the matching data processing method is pre-constructed according to the edge association relationship.

8. The device according to claim 7, characterized in that The second acquisition submodule is specifically used for: Determine a target data type of the data to be processed to which the identifier belongs using the RPA method, wherein the target data type corresponds to a target schema in the entity framework; The RPA method is adopted to use the configuration file under the target mode in the template content as the target configuration file, wherein the target configuration file defines the edge association relationship between the to-be-processed data and the associated data based on the target mode.

9. The device according to claim 7, characterized in that The acquisition module further includes: A determination submodule, configured to determine an edge association relationship between the to-be-processed data and the associated data by using the RPA method; A first generating submodule, configured to generate a first processing method corresponding to the data to be processed by adopting the RPA method in combination with artificial intelligence AI, wherein the first processing method can be called to process the data to be processed in response to the processing request; The second generation submodule is used to adopt the RPA method in combination with artificial intelligence AI to generate a second processing method corresponding to the associated data according to the edge association relationship, wherein the second processing method is used to link the associated data when the first processing method is called.

10. The device according to claim 9, characterized in that The processing module is specifically used for: When the RPA method is used to respond to the processing request, the first processing method is called to jointly process the data to be processed with the artificial intelligence AI; When the first processing method is called, the second processing method is called by the RPA method, and the associated data is processed in conjunction with the artificial intelligence AI.

11. An electronic device, characterized in that: include: at least one processor and memory; The memory stores computer-executable instructions; The at least one processor executes the computer-executable instructions stored in the memory, so that the at least one processor executes the data processing method combining RPA and AI as described in any one of claims 1 to 6.

12. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions. When the processor executes the computer-executable instructions, the data processing method combining RPA and AI as described in any one of claims 1 to 6 is implemented.

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