Recommended method, device and equipment of RPA component and readable storage medium

Abstract

The application provides a method, device and equipment for recommending RPA components, and a readable storage medium. When a user creates a component in an RPA interface, component information of a current component and a current business process are obtained. At least one historical business process with a similarity to the current business process greater than or equal to a first preset threshold is selected. Each corresponding component in the at least one historical business process is found according to the component information of the current component, and a next component corresponding to each corresponding component is determined. A probability value of each next component is calculated, and a next component with a probability value greater than or equal to a second preset threshold is selected to form a recommended component list. The method for recommending RPA components determines a to-be-recommended component according to a component relationship in a historical business process similar to a current business process, and selects a to-be-recommended component with a larger probability value as a final recommended component to form a recommended component list. The method can improve the relevance of recommended components and the accuracy of recommendations.

Description

Technical Field

[0001] This application relates to the field of RPA product technology, and more specifically to a recommended method, apparatus, device, and computer-readable storage medium for an RPA component. Background Technology

[0002] With the continuous development of internet and artificial intelligence technologies, automated office work has become a necessity for some enterprises. Automated office work refers to using standardized automated processes to automate simple, repetitive, low-value-added tasks, freeing up relevant personnel to perform more complex and valuable work. Robotic Process Automation (RPA) is a pre-configured software that simulates human operation to automatically execute processes. It can link multiple business systems and automatically connect a series of operational workflows for process reengineering without affecting the functionality and stability of existing IT systems. It is characterized by high efficiency, simplicity, intelligence, and flexibility, making it a crucial pathway for many enterprises to achieve intelligent transformation and upgrading.

[0003] While RPA offers many advantages, current RPA products contain a large number of components with varying functions and relationships. Mastering RPA requires understanding each component, which is clearly challenging. Most RPA products currently recommend components based on user actions, often relying on frequently used methods. This can lead to frequently used components consistently occupying prominent positions in recommendations, even though these components are often useless in most scenarios, resulting in inaccurate recommendations. Summary of the Invention

[0004] In view of this, embodiments of this application provide a recommended method, apparatus, device, and computer-readable storage medium for RPA components.

[0005] In a first aspect, embodiments of this application provide a method for recommending RPA components, the method comprising:

[0006] When a user creates a component in the RPA interface, obtain the component information and current business process of the current component;

[0007] Select at least one historical business process whose similarity to the current business process is greater than or equal to a first preset threshold.

[0008] Based on the component information of the current component, find each corresponding component in at least one of the historical business processes, and determine the next component corresponding to each corresponding component;

[0009] Calculate the probability value of each of the next components, and select the next component whose probability value is greater than or equal to a second preset threshold to form a recommended component list.

[0010] Secondly, embodiments of this application provide a recommendation apparatus for RPA components, the apparatus comprising:

[0011] The information acquisition module is used to obtain the component information and current business process of the current component when the user creates a component in the RPA interface;

[0012] The historical business process selection module is used to select at least one historical business process whose similarity to the current business process is greater than or equal to a first preset threshold.

[0013] The next component determination module is used to find each corresponding component in at least one of the historical business processes based on the component information of the current component, and determine the next component corresponding to each corresponding component.

[0014] The recommended component list forming module is used to calculate the probability value of each of the next components and select the next components whose probability values ​​are greater than or equal to a second preset threshold to form a recommended component list.

[0015] Thirdly, embodiments of this application provide a terminal device, including: a memory; one or more processors coupled to the memory; and one or more applications, wherein the one or more applications are stored in the memory and configured to be executed by the one or more processors, and the one or more applications are configured to perform the recommended method of the RPA components provided in the first aspect above.

[0016] Fourthly, embodiments of this application provide a computer-readable storage medium storing program code, which can be invoked by a processor to execute the recommended method of the RPA component provided in the first aspect.

[0017] The RPA component recommendation method, apparatus, device, and computationally readable storage medium provided in this application embodiment obtain the component information and current business process of the current component when a user creates a component in the RPA interface; then select at least one historical business process whose similarity to the current business process is greater than or equal to a first preset threshold; then find each corresponding component in the at least one historical business process according to the component information of the current component, and determine the next component corresponding to each corresponding component; calculate the probability value of each next component, and select the next component whose probability value is greater than or equal to a second preset threshold to form a recommended component list.

[0018] This RPA component recommendation method determines the components to be recommended based on the component relationships in historical business processes similar to the current business process (i.e., the contextual relationships in which components appear). Then, it selects the components with higher probability of occurrence as the final recommended components, thus forming a recommended component list. This method improves the relevance and accuracy of the recommended components. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of this application. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0020] Figure 1 A schematic diagram illustrating an application scenario for the recommended method of the RPA component provided in this application embodiment;

[0021] Figure 2 A flowchart illustrating a recommended method for an RPA component provided in one embodiment of this application;

[0022] Figure 3 A structural diagram of a recommended apparatus for an RPA component provided in one embodiment of this application;

[0023] Figure 4 This is a schematic diagram of the structure of a terminal device provided in one embodiment of this application;

[0024] Figure 5 This is a schematic diagram of the structure of a computer-readable storage medium provided in one embodiment of this application. Detailed Implementation

[0025] The technical solutions in the embodiments of this application will be clearly and completely described below. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments in this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0026] To provide a more detailed description of this application, the following description, in conjunction with the accompanying drawings, details a recommended method, apparatus, terminal device, and computer storage medium for an RPA component provided in this application.

[0027] Please refer to Figure 1 , Figure 1This diagram illustrates an application scenario of the RPA component recommendation method provided in this application embodiment. The application scenario includes a terminal device 100 provided in this application embodiment. The terminal device 100 can be various electronic devices with a display screen (such as structural diagrams 102, 104, 106, and 108), including but not limited to smartphones and computer devices. The computer device can be at least one of desktop computers, portable computers, laptop computers, tablet computers, etc. When a user operates the terminal device 100 and issues a recommended operation instruction for the RPA component, the terminal device 100 executes the RPA component recommendation method of this application. For details, please refer to the RPA component recommendation method embodiment.

[0028] Secondly, terminal device 100 can refer to one of a plurality of terminal devices; this embodiment uses terminal device 100 as an example only. Those skilled in the art will understand that the number of terminal devices can be more or less. For example, there may be only a few, or dozens or hundreds, or even more terminal devices. This application embodiment does not limit the number or type of terminal devices. Terminal device 100 can be used to execute a recommended method of an RPA component provided in this application embodiment.

[0029] In one optional implementation, the application scenario may include not only the terminal device 100 provided in this embodiment, but also a server, wherein a network is established between the server and the terminal device. The network serves as a medium for providing a communication link between the terminal device and the server. The network may include various connection types, such as wired or wireless communication links, or fiber optic cables, etc.

[0030] Optionally, the terminal device may include a component recommendation system capable of recommending RPA components. Further, the component recommendation system may include a component data cleaning system, a process information storage and retrieval system, and a component recommendation calculation system. The component data cleaning system is primarily used to obtain component information from the business process, de-identify and remove sensitive and useless information, retaining important component information such as component type, component operating software, coordinate information of the component's operating software, and component operation actions, and then storing this component information in the process information storage and retrieval system.

[0031] The process information storage and retrieval system can build a Lucene-based search service. This system includes a data storage model, primarily used to store historical business processes and component information. This historical business process and component information can be stored using a tree-structured data storage model, facilitating the later retrieval of corresponding components from at least one historical business process stored in the model, and determining the next component corresponding to each component.

[0032] The component recommendation calculation system is mainly used to calculate the similarity between the current business process and the historical business processes in order to ultimately determine the recommended component list.

[0033] It should be understood that the number of terminal devices, networks, and servers is merely illustrative. Depending on implementation needs, any number of terminal devices, networks, and servers can be used. For example, a server can be a server cluster composed of multiple servers. The terminal devices interact with the server through the network to receive or send messages, etc. The server can be a server providing various services. The server can be used to execute the steps of the recommended method of an RPA component provided in this application embodiment. Furthermore, when executing the recommended method of an RPA component provided in this application embodiment, some steps can be executed on the terminal device and some steps can be executed on the server; this is not limited here.

[0034] Based on this, this application provides a recommended method for RPA components. Please refer to [link / reference]. Figure 2 , Figure 2 This paper illustrates a flowchart of a recommended method for an RPA component provided in an embodiment of this application, demonstrating how this method can be applied to... Figure 1 Taking a terminal device as an example, the explanation includes the following steps:

[0035] Step S110: When a user creates a component in the RPA interface, obtain the component information and current business process of the current component.

[0036] Among them, RPA (Robotic Process Automation) automates process execution by simulating human operation, which can quickly improve business efficiency, automate repetitive labor, and efficiently and easily connect different business systems, enabling industries such as finance, taxation, banking, human resources, information technology, insurance, customer service, telecommunications, and manufacturing to achieve automated and intelligent upgrades in their business processes.

[0037] The basic architecture of current RPA products includes a Studio, a Robot, and an Orchestrator. The Studio contains various functional components for development and debugging; a business process robot that can run automatically can be built through drag-and-drop functionality. The Studio also contains a Robot for debugging the robot during development. This Robot can be started manually or remotely controlled by the Orchestrator. The number of Studios purchased is usually adjusted based on the number of concurrent developers. When enterprises do not have a large demand for automated processes, they typically only purchase Studios and start the robot manually.

[0038] The controller (Orchestrator) is primarily used for unified management and scheduling of robots published by the designer (Studio). It is responsible for distributing tasks to various robots for execution. The executor (Robot) receives instructions and completes the automated tasks. The number of executors can be adjusted according to the amount of automated tasks.

[0039] Users can create components according to their needs. When a user creates or selects a component in the RPA interface, the system obtains the component's information and the current business process. This component information includes, but is not limited to, the component type, the software on which the component operates, the coordinates of the software operating on the component, and the component's action. For example, in RPA software, if a user uses the "Mouse Click" component to click the "Create" button in the "Email Client" application, then the component type is "Mouse Click," the software operated by the component is the email client, and the action performed by the component is "Click."

[0040] It should be noted that in addition to clicking, component operations can also include double-clicking, pressing and holding, and dragging, etc.

[0041] In addition, component information also includes other information, such as sensitive information and useless information. However, in practical applications, sensitive information and useless information can be preprocessed and deleted.

[0042] The current business process refers to the business process formed when the user selects the current component in the RPA interface.

[0043] Step S120: Select at least one historical business process whose similarity to the current business process is greater than or equal to a first preset threshold.

[0044] In one embodiment, in performing step S120, selecting at least one historical business process whose similarity to the current business process is greater than or equal to a first preset threshold includes: calculating the similarity between the current business process and each historical business process, and selecting each historical business process whose similarity is greater than or equal to the first preset threshold to form a related process array.

[0045] In this context, historical business processes refer to business processes built by users through RPA products within a past period. In this embodiment, historical business processes can be all business processes generated before the user creates a component in the RPA interface; or business processes generated within a certain period.

[0046] In this embodiment, the similarity between the current business process and each historical business process can be calculated first. Then, at least one historical business process with a similarity greater than or equal to a first preset threshold is selected. The selected historical business processes are grouped into a related process array, which can be denoted as processArr = [p1, p2, ..., pn]. Similarity refers to the degree of similarity between the current business process and the historical business processes. The higher the similarity, the higher the similarity between the current business process and the historical business process, and the greater the possibility that they belong to the same business process. Conversely, the lower the similarity between the current business process and the historical business process, the less likely that they belong to the same business process.

[0047] The first preset threshold is a pre-set value, which can be set according to actual needs.

[0048] Step S130: Based on the component information of the current component, find the corresponding components in at least one historical business process and determine the next component corresponding to each corresponding component.

[0049] Specifically, after selecting at least one historical business process, the corresponding components can be selected from each historical business process based on the component information of the current component. Then, the next component (i.e., the next component) of each corresponding component can be found. Since components and the connections between components constitute a business process, components and the connections between components can be found within the business process. The connection between components refers to the order in which the components are arranged, i.e., the hierarchical relationship between components. When a certain component is known, the next component of that component can be determined.

[0050] Step S140: Calculate the probability value of each next component, and select the next component whose probability value is greater than or equal to the second preset threshold to form a recommended component list.

[0051] To facilitate understanding, a detailed example is provided. Historical business processes and component information are typically stored using a tree-structured data storage model, as shown below:

[0052]

[0053] As can be seen from the above data storage structure, the corresponding component can be identified in the historical business process based on the component information, and then the next component can be identified based on the corresponding component. The specific process of the RPA component recommendation method is as follows: Based on the current component selected by the user, determine the component information and the current business process of the current component; where the component information of the current component includes componentId (i.e., component ID), componentAction (i.e., the operation action of the component), software (i.e., the operating software of the component), and softwareCoordinate (i.e., the coordinate information of the operating software); Based on the current business process, select historical business processes with a similarity greater than or equal to the first preset threshold to form a related process array processArr = [p1, p2, ..., pn]; and then in the related process array... The `processArr` function retrieves information where the componentId (component ID), componentAction (component's action), software (component's operating software), and softwareCoordinate (software's coordinates) match. This allows for the counting of each different `nextComponentId` (the next component), denoted as I = {I0, I1, I2, ..., In}, with a probability Pi = In / (I0 + I1 + I2 + ... + In). A second preset threshold N is set, and M recommended components with a probability greater than or equal to N are found to form a recommended component list. The query for the next component and its probability can be displayed using JSON data.

[0054] Since there can be multiple historical business processes, the next component selected in different historical business processes may be the same or different, and the same next component may appear once or multiple times. Therefore, the probability value of each next component can be calculated, and the next component with a probability value greater than or equal to a second preset threshold can be selected to form a recommended component list.

[0055] The second preset threshold is a pre-set value, usually a percentage value, which can be set according to actual needs.

[0056] The RPA component recommendation method provided in this application involves obtaining the component information and current business process of the current component when a user creates a component in the RPA interface; then selecting at least one historical business process whose similarity to the current business process is greater than or equal to a first preset threshold; finding each corresponding component in the at least one historical business process based on the component information of the current component, and determining the next component corresponding to each corresponding component; calculating the probability value of each next component, and selecting the next component whose probability value is greater than or equal to a second preset threshold to form a recommended component list.

[0057] This RPA component recommendation method determines the components to be recommended based on the component relationships in historical business processes similar to the current business process (i.e., the contextual relationships in which components appear). Then, it selects the components with higher probability of occurrence as the final recommended components, thus forming a recommended component list. This method improves the relevance and accuracy of the recommended components.

[0058] Furthermore, a specific implementation method for calculating the similarity between the current business process and each historical business process is given and described as follows:

[0059] In one embodiment, calculating the similarity between the current business process and each historical business process includes: calculating the similarity between the operating software of the current business process and the operating software of each historical business process, denoted as the operating software similarity; and / or: calculating the similarity between the operating components of the current business process and the operating components of each historical business process, denoted as the operating component similarity.

[0060] Specifically, whether two business processes are similar can be determined based on their operating software and / or operating components. Therefore, in this embodiment, calculating the similarity between the current business process and each historical business process mainly involves calculating the similarity between the operating software of the current business process and the operating software of each historical business process, denoted as the operating software similarity, and / or calculating the similarity between the operating components of the current business process and the operating components of each historical business process.

[0061] Furthermore, an implementation method for calculating the similarity of operating software is provided, which will be described in detail below.

[0062] In one embodiment, calculating the similarity between the operating software of the current business process and the operating software of each historical business process includes: forming operating software arrays by combining the operating software of the current business process and the operating software of each historical business process; identifying the same operating software elements in the operating software array of the current business process and the operating software array of each historical business process to form corresponding new software arrays; and calculating the similarity between the operating software of the current business process and the operating software of each historical business process based on each new software array.

[0063] Specifically, we can first perform mathematical abstraction on each historical business process and the current business process, that is, array the operating software of each historical business process and the current business process respectively. To facilitate understanding, a detailed embodiment is given, which uses the current business process and a historical business process as examples. Assume that the current business process A contains n operating software and the historical business process B contains m operating software. Then the operating software array of the current business process A is S1 = [a1, a2, ..., an], and the operating software array of the historical business process B is S2 = [b1, b2, ..., bm]. Then, by iteratively comparing the two arrays, we obtain the elements that are the same in the two arrays, forming a new software array S3 = [c1, c2, ..., cn]. Then, the similarity of the operating software between the current business process A and the historical business process B (i.e., the similarity of the operating software) Si = S3.length / Min(S1.length, S2.length)T.

[0064] It should be noted that the method for calculating the phase velocity of the operating software of the current business process and the historical business process is the same as the method for calculating the similarity Si of the operating software of the current business process A and the historical business process B. When there are several historical business processes, calculate as many as possible and obtain the corresponding similarity. This will not be elaborated further here.

[0065] Next, an implementation method for calculating the similarity of operational components is given, described in detail below:

[0066] In one embodiment, calculating the similarity between the operation components of the current business process and the operation components of each historical business process includes: forming operation component arrays by combining the operation components of the current business process and the operation components of each historical business process; identifying the same operation component elements in the operation component arrays of the current business process and each historical business process to form corresponding new component arrays; and calculating the similarity between the operation components of the current business process and the operation components of each historical business process based on each new component array.

[0067] Specifically, regarding the processing of operation components and the processing type of operation software, the operation components of each historical business process and the current business process are first arrayed. To facilitate understanding, a detailed implementation example is provided, using the current business process and a historical business process as examples. Assume that the current business process A includes h component types, resulting in an operation component list T1 = [a1, a2, ..., ah], and the historical business process B includes g components, resulting in operation component categories T2 = [b1, b2, ..., bg]. By iteratively comparing the two arrays, an array of elements T3 = [c1, c2, ..., cn] with the same elements is obtained. Then, the similarity (i.e., operation component similarity) Sk between the operation components of the current business process A and the historical business process B is Sk = T3.length / Min(T1.length, T2.length).

[0068] It should be noted that the calculation method for the similarity between the operation components of the current business process and the historical business process is the same as the calculation method for the similarity Sk between the operation components of the current business process A and the historical business process B. When there are several historical business processes, calculate the similarity for each one and obtain the corresponding similarity. This will not be elaborated further here.

[0069] In one embodiment, in performing step S120, selecting each historical business process whose similarity is greater than or equal to a first preset threshold includes: selecting each historical business process whose operating software similarity is greater than or equal to a first preset software threshold and whose operating component similarity is greater than or equal to a first preset component threshold; wherein, the first preset threshold includes a first preset software threshold and a first preset component threshold.

[0070] Specifically, when the similarity between the operating software of the current business process and the operating software of a certain historical business process (i.e., the similarity of operating software) is greater than or equal to the first preset software threshold, it indicates that the operating software of the current business process is similar to that of the historical business process.

[0071] When the similarity (i.e., the similarity of operation components) between the operation components of the current business process and the operation components of a certain historical business process is greater than or equal to a first preset component threshold, it indicates that the operation components of the current business process are similar to those of the historical business process. In this embodiment, when the operation software and operation components of the current business process are similar to those of a certain historical business process, it indicates that the current business process is similar to that historical business process.

[0072] To facilitate understanding, a detailed embodiment is provided. Assume the similarity (i.e., software similarity) Si between the current business process A and the historical business process B, and the similarity (i.e., component similarity) Sk between the current business process A and the historical business process B. Let P1 be a first preset software threshold and P2 be a first preset component threshold. When Si ≥ P1 and Sk ≥ P2, it indicates that the current business process A is similar to the historical business process B. Therefore, the historical business process B can be selected to form a related process array.

[0073] The above method can select historical business processes that are highly similar to the current business process. In other words, the selected historical business processes are more accurate, and the recommended components determined based on the selected historical business processes will be more accurate.

[0074] In one embodiment, the method for recommending RPA components further includes: when no next component with a probability value greater than or equal to a second preset threshold is selected, forming a list of recommended components based on preset components.

[0075] Specifically, in cases where there are indeed historical business processes, it is either impossible to select a historical business process that is highly similar to the current business process, or the number of next components in a highly similar historical business process is small, making it impossible to select a next component with a high probability of occurrence. In such cases, it is impossible to determine recommended components based on historical business processes, but recommendations can be made based on the recommended components corresponding to the system's preset components.

[0076] The above method can quickly provide recommended components when it is impossible to determine recommended components based on historical business processes, thereby improving the convenience of user operation.

[0077] Furthermore, the method for recommending RPA components also includes displaying the recommended component list on the RPA product interface after it is generated, so as to facilitate users in using the relevant components.

[0078] It should be understood that, although Figure 2 The steps in the flowchart are shown sequentially as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order in which these steps are executed; they can be performed in other orders. Figure 2 At least some of the steps in the process may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but may be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but may be executed in turn or alternately with other steps or at least some of the sub-steps or stages of other steps.

[0079] The embodiments disclosed in this application describe in detail a method for recommending RPA components. The method disclosed in this application can be implemented using various types of devices. Therefore, this application also discloses an apparatus for recommending RPA components corresponding to the above method. Specific embodiments are given below for detailed description.

[0080] Please see Figure 3 This application discloses a recommended apparatus for an RPA component, which mainly includes:

[0081] The information acquisition module 310 is used to acquire the component information and current business process of the current component when the user creates a component in the RPA interface.

[0082] The historical business process selection module 320 is used to select at least one historical business process whose similarity to the current business process is greater than or equal to a first preset threshold.

[0083] The next component determination module 330 is used to find each corresponding component in at least one historical business process based on the component information of the current component, and determine the next component corresponding to each corresponding component.

[0084] The recommended component list forming module 340 is used to calculate the probability value of each next component and select the next component whose probability value is greater than or equal to a second preset threshold to form a recommended component list.

[0085] In one embodiment, the next component determination module 330 is used to calculate the similarity between the current business process and each historical business process, and select each historical business process whose similarity is greater than or equal to a first pre-threshold to form a related process array.

[0086] In one embodiment, the next component determination module 330 is used to calculate the similarity between the operating software of the current business process and the operating software of each historical business process, denoted as the operating software similarity; and / or: calculate the similarity between the operating component of the current business process and the operating component of each historical business process, denoted as the operating component similarity.

[0087] In one embodiment, the historical business process selection module 320 is used to select each historical business process whose operating software similarity is greater than or equal to a first preset software threshold and whose operating component similarity is greater than or equal to a first preset component threshold; wherein, the first preset threshold includes a first preset software threshold and a first preset component threshold.

[0088] In one embodiment, the next component determination module 330 is used to form operation software arrays by combining the operation software of the current business process and the operation software of each historical business process; to find the same operation software elements in the operation software array of the current business process and the operation software array of each historical business process, so as to form new software arrays accordingly; and to calculate the similarity between the operation software of the current business process and the operation software of each historical business process based on each new software array.

[0089] In one embodiment, the next component determination module 330 is used to form operation component arrays by combining the operation components of the current business process and the operation components of each historical business process; to find the same operation component elements in the operation component array of the current business process and the operation component array of each historical business process, so as to form new component arrays accordingly; and to calculate the similarity between the operation components of the current business process and the operation components of each historical business process based on each new component array.

[0090] In one embodiment, the RPA component recommendation device further includes a component recommendation module, which is used to form a recommended component list based on preset components when no next component with a probability value greater than or equal to a second preset threshold is selected.

[0091] For specific limitations on the recommended apparatus for RPA components, please refer to the method limitations above, which will not be repeated here. Each module in the above apparatus can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in hardware or independently of the processor in the terminal device, or stored in software in the memory of the terminal device, so that the processor can call and execute the operations corresponding to each module.

[0092] Please refer to Figure 4 , Figure 4 This illustration shows a structural block diagram of a terminal device provided in an embodiment of this application. The terminal device 40 may be a computer device. The terminal device 40 in this application may include one or more of the following components: a processor 42, a memory 44, and one or more application programs, wherein the one or more application programs may be stored in the memory 44 and configured to be executed by the one or more processors 42, and the one or more application programs are configured to perform the methods described in the recommended method embodiments of the RPA components described above.

[0093] Processor 42 may include one or more processing cores. Processor 42 connects to various parts within the terminal device 40 using various interfaces and lines, and performs various functions and processes data of the terminal device 40 by running or executing instructions, programs, code sets, or instruction sets stored in memory 44, and by calling data stored in memory 44. Optionally, processor 42 may be implemented using at least one hardware form of Digital Signal Processing (DSP), Field-Programmable Gate Array (FPGA), or Programmable Logic Array (PLA). Processor 42 may integrate one or a combination of several of the following: Central Processing Unit (CPU), Graphics Processing Unit (GPU), and modem. The CPU primarily handles the operating system, user interface, and applications; the GPU is responsible for rendering and drawing the displayed content; and the modem handles wireless communication. It is understood that the modem may also not be integrated into processor 42 and may be implemented separately using a communication chip.

[0094] The memory 44 may include random access memory (RAM) or read-only memory (ROM). The memory 44 can be used to store instructions, programs, code, code sets, or instruction sets. The memory 44 may include a program storage area and a data storage area. The program storage area may store instructions for implementing an operating system, instructions for implementing at least one function (such as touch functionality, sound playback functionality, image playback functionality, etc.), and instructions for implementing the various method embodiments described below. The data storage area may also store data created by the terminal device 40 during use.

[0095] Those skilled in the art will understand that Figure 4 The structure shown is merely a block diagram of a portion of the structure related to the solution of this application and does not constitute a limitation on the terminal device to which the solution of this application is applied. A specific terminal device may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0096] In summary, the terminal device provided in this application embodiment is used to implement the recommended method of the corresponding RPA component in the foregoing method embodiment, and has the beneficial effects of the corresponding method embodiment, which will not be repeated here.

[0097] Please see Figure 5This diagram illustrates a structural block diagram of a computer-readable storage medium provided in an embodiment of this application. The computer-readable storage medium 50 stores program code that can be invoked by a processor to execute the methods described in the recommended method embodiments of the RPA components described above.

[0098] The computer-readable storage medium 50 may be an electronic memory such as flash memory, EEPROM (Electrically Erasable Programmable Read-Only Memory), EPROM, hard disk, or ROM. Optionally, the computer-readable storage medium 50 includes a non-transitory computer-readable storage medium. The computer-readable storage medium 50 has storage space for program code 52 that performs any of the method steps described above. This program code can be read from or written to one or more computer program products. The program code 52 may be compressed, for example, in a suitable form.

[0099] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0100] The above description of the disclosed embodiments enables those skilled in the art to make or use this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for recommending RPA components, characterized in that, The method includes: When a user creates a component in the RPA interface, obtain the component information and current business process of the current component; Select at least one historical business process whose similarity to the current business process is greater than or equal to a first preset threshold. Based on the component information of the current component, find each corresponding component in at least one of the historical business processes, and determine the next component corresponding to each corresponding component; Calculate the probability value of each of the next components, and select the next components whose probability values ​​are greater than or equal to a second preset threshold to form a recommended component list. The probability value of the next component is determined based on the number of times the relevant process array appears in the historical business process. The step of selecting at least one historical business process whose similarity to the current business process is greater than or equal to a first preset threshold includes: Calculate the similarity between the current business process and each of the historical business processes, and select each of the historical business processes whose similarity is greater than or equal to a first pre-threshold to form a related process array; The calculation of the similarity between the current business process and each of the historical business processes includes: Calculate the similarity between the operating software of the current business process and the operating software of each of the historical business processes, and record it as the operating software similarity. And / or: Calculate the similarity between the operation components of the current business process and the operation components of each of the historical business processes, and record it as the operation component similarity. The calculation of the similarity between the operation components of the current business process and the operation components of each of the historical business processes includes: The operation components of the current business process and the operation components of each of the historical business processes are respectively formed into operation component arrays; Find the same operation component elements in the operation component array of the current business process and the operation component array of each historical business process, and form new component arrays accordingly. Calculate the similarity between the operation components of the current business process and the operation components of each of the historical business processes based on each of the new component arrays. When no next component with a probability value greater than or equal to the second preset threshold is selected, a recommended component list is formed based on preset components.

2. The method according to claim 1, characterized in that, Selecting each of the historical business processes whose similarity is greater than or equal to a first pre-threshold includes: Each of the historical business processes whose similarity to the operating software is greater than or equal to a first preset software threshold and whose similarity to the operating components is greater than or equal to a first preset component threshold is selected. The first preset threshold includes a first preset software threshold and a first preset component threshold.

3. The method according to claim 1, characterized in that, The calculation of the similarity between the operating software of the current business process and the operating software of each of the historical business processes includes: The operating software for the current business process and the operating software for each of the historical business processes are respectively formed into operating software arrays; Find the same operation software elements in the operation software array of the current business process and the operation software array of each historical business process, and form corresponding new software arrays; The similarity between the operating software of the current business process and the operating software of each of the historical business processes is calculated based on each of the new software arrays.

4. A device for recommending RPA components, characterized in that, The device includes: The information acquisition module is used to obtain the component information and current business process of the current component when the user creates a component in the RPA interface; The historical business process selection module is used to select at least one historical business process whose similarity to the current business process is greater than or equal to a first preset threshold. The next component determination module is used to find each corresponding component in at least one of the historical business processes based on the component information of the current component, and determine the next component corresponding to each corresponding component. The recommended component list forming module is used to calculate the probability value of each of the next components and select the next components whose probability values ​​are greater than or equal to a second preset threshold to form a recommended component list. The probability value of the next component is determined based on the number of times the related process array appears in the historical business process. The step of selecting at least one historical business process whose similarity to the current business process is greater than or equal to a first preset threshold includes: Calculate the similarity between the current business process and each of the historical business processes, and select each of the historical business processes whose similarity is greater than or equal to a first pre-threshold to form a related process array; The calculation of the similarity between the current business process and each of the historical business processes includes: Calculate the similarity between the operating software of the current business process and the operating software of each of the historical business processes, and record it as the operating software similarity. And / or: Calculate the similarity between the operation components of the current business process and the operation components of each of the historical business processes, and record it as the operation component similarity. The calculation of the similarity between the operation components of the current business process and the operation components of each of the historical business processes includes: The operation components of the current business process and the operation components of each of the historical business processes are respectively formed into operation component arrays; Find the same operation component elements in the operation component array of the current business process and the operation component array of each historical business process, and form new component arrays accordingly. Calculate the similarity between the operation components of the current business process and the operation components of each of the historical business processes based on each of the new component arrays. When no next component with a probability value greater than or equal to the second preset threshold is selected, a recommended component list is formed based on preset components.

5. A terminal device, characterized in that, include: Memory; One or more processors are coupled to the memory; One or more applications, wherein the one or more applications are stored in memory and configured to be executed by one or more processors, and the one or more applications are configured to perform the method as described in any one of claims 1-3.

6. A computer-readable storage medium, characterized in that, The computer-readable storage medium contains program code that can be invoked by a processor to execute the method as described in any one of claims 1-3.

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