CN114880422A

CN114880422A - Interest point information processing method based on robot process automation and related device

Info

Publication number: CN114880422A
Application number: CN202210797366.0A
Authority: CN
Inventors: 黄际洲
Original assignee: Beijing Baidu Netcom Science and Technology Co Ltd
Current assignee: Beijing Baidu Netcom Science and Technology Co Ltd
Priority date: 2022-07-08
Filing date: 2022-07-08
Publication date: 2022-08-09
Anticipated expiration: 2042-07-08
Also published as: CN114880422B

Abstract

The disclosure provides a method and a related device for processing interest point information based on robot process automation, and relates to the technical fields of robot process automation, task flow generation and the like. The method comprises the following steps: receiving an operation instruction of a functional component, which is transmitted by a user under a visual configuration interface; determining each target function component related to the interest point task according to the operation instruction; assembling each target function component according to the operation time sequence of each operation instruction by the robot process automation technology to obtain a component structure diagram; and generating a target interest point task according to the component structure diagram. According to the method, the robot process automation technology is applied to the field of automatic processing of the point of interest information, various point of interest information processing tasks can be rapidly and automatically completed in a code-free mode, a more convenient solution is provided for users without code compiling capacity, and therefore the labor cost of the point of interest information processing tasks is reduced.

Description

Interest point information processing method based on robot process automation and related device

Technical Field

The present disclosure relates to the field of data processing technologies, and in particular, to the field of robot process automation, task flow generation, and the like, and in particular, to a method and an apparatus for processing information of a point of interest based on robot process automation, an electronic device, and a computer-readable storage medium.

Background

RPA, robot Process Automation, the main function is to interact the working information and the service through the robot to execute according to the designed Process. Therefore, if the interaction between the working information and the service is excessive, the complex processes can be efficiently solved through the RPA technology, and the labor cost is saved.

In the map field, there are a large number of processing tasks related to POIs (points of interest), and how to apply the RPA technology to the automatic generation of POIs is a problem to be solved urgently by those skilled in the art.

Disclosure of Invention

The embodiment of the disclosure provides a method and a device for processing interest point information based on robot process automation, an electronic device, a computer readable storage medium and a computer program product.

In a first aspect, an embodiment of the present disclosure provides a method for processing point of interest information based on robot process automation, including: receiving an operation instruction of a functional component, which is transmitted by a user under a visual configuration interface; determining target function components related to the interest point task according to the operation instruction, wherein each function component is obtained by packaging according to each independent step for completing the historical interest point task in advance and follows a uniform data processing specification; assembling each target function component according to the operation time sequence of each operation instruction by the robot process automation technology to obtain a component structure diagram; and generating a target interest point task according to the component structure diagram.

In a second aspect, an embodiment of the present disclosure provides a point of interest information processing apparatus based on robot process automation, including: the operation instruction receiving unit is configured to receive operation instructions of the functional components, which are transmitted by a user under the visual configuration interface; the target function component determining unit is configured to determine each target function component related to the interest point task according to the operation instruction, each function component is obtained by packaging according to each independent step for completing the historical interest point task in advance, and each function component follows a uniform data processing specification; the component assembling unit is configured to assemble each target functional component according to the operation time sequence of each operation instruction by the robot process automation technology to obtain a component structure diagram; and the target interest point information processing unit is configured to generate a target interest point task according to the component structure diagram.

In a third aspect, an embodiment of the present disclosure provides an electronic device, including: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor to cause the at least one processor to perform the method of point of interest information processing based on robotic process automation as described in any implementation manner of the first aspect when executed.

In a fourth aspect, the present disclosure provides a non-transitory computer-readable storage medium storing computer instructions for enabling a computer to implement a method for processing point of interest information based on robot process automation as described in any implementation manner of the first aspect.

In a fifth aspect, the present disclosure provides a computer program product including a computer program, which when executed by a processor is capable of implementing the steps of the method for processing point of interest information based on robotic process automation as described in any implementation manner of the first aspect.

According to the point of interest information processing scheme based on robot flow automation, the robot flow automation technology is applied to the field of point of interest information automatic processing, various point of interest information processing tasks can be rapidly and automatically completed in a code-free mode, a more convenient solution is provided for users without code compiling capacity, and therefore the labor cost of the point of interest information processing tasks is reduced.

It should be understood that the statements in this section do not necessarily identify key or critical features of the embodiments of the present disclosure, nor do they limit the scope of the present disclosure. Other features of the present disclosure will become apparent from the following description.

Drawings

Other features, objects and advantages of the disclosure will become more apparent upon reading of the following detailed description of non-limiting embodiments thereof, made with reference to the accompanying drawings in which:

FIG. 1 is an exemplary system architecture to which the present disclosure may be applied;

fig. 2 is a flowchart of a method for processing information of a point of interest based on robot process automation according to an embodiment of the present disclosure;

FIG. 3 is a schematic diagram illustrating functional components encapsulated according to individual steps for completing historical point of interest tasks, according to an embodiment of the present disclosure;

fig. 4 is a flowchart of a method for performing rationalization check processing on an assembly process according to an embodiment of the present disclosure;

FIG. 5 is a schematic diagram of a component structure of a point of interest task of an online medical detection mechanism according to an embodiment of the present disclosure;

fig. 6 is a schematic component structural diagram of a point of interest task for cell unblocking according to an embodiment of the present disclosure;

fig. 7 is a block diagram of a point of interest information processing apparatus based on robot process automation according to an embodiment of the present disclosure;

fig. 8 is a schematic structural diagram of an electronic device suitable for executing a point of interest information processing method based on robot process automation according to an embodiment of the present disclosure.

Detailed Description

Exemplary embodiments of the present disclosure are described below with reference to the accompanying drawings, in which various details of the embodiments of the disclosure are included to assist understanding, and which are to be considered as merely exemplary. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the present disclosure. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness. It should be noted that, in the present disclosure, the embodiments and features of the embodiments may be combined with each other without conflict.

In the technical scheme of the disclosure, the collection, storage, use, processing, transmission, provision, disclosure and other processing of the personal information of the related user are all in accordance with the regulations of related laws and regulations and do not violate the good customs of the public order.

Fig. 1 illustrates an exemplary system architecture 100 to which embodiments of a robot process automation-based point of interest information processing method, apparatus, electronic device, and computer-readable storage medium of the present disclosure may be applied.

As shown in fig. 1, the system architecture 100 may include

terminal devices

101, 102, 103, a network 104, and a server 105. The network 104 serves as a medium for providing communication links between the

terminal devices

101, 102, 103 and the server 105. Network 104 may include various connection types, such as wired, wireless communication links, or fiber optic cables, among others.

The user may use the

terminal devices

101, 102, 103 to interact with the server 105 via the network 104 to receive or send messages or the like. The

terminal devices

101, 102, 103 and the server 105 may be installed with various applications for implementing information communication between the two devices, such as a task creation application, a data analysis application, an instant messaging application, and the like.

The

terminal apparatuses

101, 102, 103 and the server 105 may be hardware or software. When the

terminal devices

101, 102, 103 are hardware, they may be various electronic devices with display screens, including but not limited to smart phones, tablet computers, laptop portable computers, desktop computers, and the like; when the

terminal devices

101, 102, and 103 are software, they may be installed in the electronic devices listed above, and they may be implemented as multiple software or software modules, or may be implemented as a single software or software module, and are not limited in this respect. When the server 105 is hardware, it may be implemented as a distributed server cluster composed of multiple servers, or may be implemented as a single server; when the server is software, the server may be implemented as a plurality of software or software modules, or may be implemented as a single software or software module, which is not limited herein.

The server 105 may provide various services through various built-in applications, taking a task creation class application that may provide a point of interest related task generation service as an example, the server 105 may implement the following effects when running the task creation class application: firstly, receiving operation instructions for functional components, which are transmitted by a user under a visual configuration interface presented on the

terminal equipment

101, 102 and 103, through the network 104; then, determining each target function component related to the interest point task according to the operation instruction, wherein each function component is obtained by packaging according to each independent step for completing the historical interest point task in advance, and each function component follows a uniform data processing specification; next, assembling each target function component according to the operation time sequence of each operation instruction by the robot flow automation technology to obtain a component structure diagram; and finally, generating a target interest point task according to the component structure diagram.

It should be noted that the operation instruction may be temporarily acquired from the

terminal apparatuses

101, 102, and 103 through the network 104, or may be stored locally in the server 105 in advance in various ways. Thus, when the server 105 detects that such data is already stored locally (e.g., a pending task remaining before starting processing), it may choose to retrieve such data directly from locally, in which case the exemplary system architecture 100 may also not include the

terminal devices

101, 102, 103 and the network 104.

The method for processing the point of interest information based on robot process automation provided in the subsequent embodiments of the present disclosure is generally performed by the server 105 having the task creation capability, and accordingly, the point of interest information processing apparatus based on robot process automation is also generally disposed in the server 105. However, it should be noted that when the

terminal devices

101, 102, and 103 also have the task creation capability that meets the requirement, the

terminal devices

101, 102, and 103 may also complete the above operations that are originally performed by the server 105 through the task creation application installed thereon, and then output the same result as the result of the server 105. Accordingly, the point-of-interest information processing device based on robot process automation may be provided in the

terminal apparatuses

101, 102, and 103. In such a case, the exemplary system architecture 100 may also not include the server 105 and the network 104.

It should be understood that the number of terminal devices, networks, and servers in fig. 1 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation.

Referring to fig. 2, fig. 2 is a flowchart of a method for processing point of interest information based on robot process automation according to an embodiment of the present disclosure, where the process 200 includes the following steps.

Step 201: and receiving an operation instruction of the functional component, which is transmitted by a user under the visual configuration interface.

The step is intended to receive operation instructions for the pre-configured functional components, which are transmitted by a user under a visual configuration interface, by an executive body (such as the server 105 shown in fig. 1) of the point of interest information processing method based on robot process automation. The functional components are obtained by packaging according to independent steps for completing historical interest point tasks in advance, and the functional components follow a uniform data processing specification.

The visual configuration interface is a configuration interface provided for a user to perform visual operations on alternative functional components, and may be presented on a display screen of a terminal device (for example,

terminal devices

101, 102, and 103 shown in fig. 1), where an operation instruction performed on a functional component by the user under the visual configuration interface is to implement an implementation flow for implementing an assumed target point of interest task by conveniently drawing the operation instruction performed on the visual component, the operation instruction is generally expressed as various instructions capable of representing association and execution sequence relationships of the component, for example, an operation instruction performed on the functional component, such as a drag, a pull, a drag, and the like, and specifically, such an operation instruction may be expressed as a corresponding operation performed on a touch screen by the user or a corresponding operation performed on an external input device (for example, a mouse, a keyboard, and the like) by the user, and can also be expressed as a text conversion result of the operation instruction written by a code language or a Chinese language.

Specifically, the visualized configuration interface presented in front of the user may be an interface presented locally on the terminal device when an application installed on the terminal device runs, or an interface presented when the remote device runs and viewed through a screen projection or a remote control mode.

The historical interest point tasks are previously known interest point tasks, and may include previously self-initiated interest point tasks and previously self-initiated interest point tasks, and each historical interest point task generally includes at least one functional requirement, for example, verifying availability of target interest point attribute information, extracting information related to an interest point from a target webpage, and the like, so that by analyzing the functional requirements of a large number of historical interest point tasks, steps for completing the historical interest point tasks are disassembled and packaged to obtain individual functional components as much as possible, and for example, at least one of the following steps may be included: the system comprises an extraction component, a verification component, a chain finger component, a change monitoring component, a coordinate prediction component, a relation prediction component, a task assignment component and a quality inspection on-line component.

Meanwhile, in order to ensure that the functional components can be correctly identified with each other during subsequent assembly, the functional components need to be preset to follow a uniform data processing specification, such as data format, length, identification mode, compatibility, and the like.

Step 202: and determining each target functional component related to the interest point task according to the operation instruction.

On the basis of step 201, this step is intended to determine, by the execution subject, target functional components related to the point-of-interest task according to the operation instruction.

A Point of Interest, which is called Point of Interest in english, and is abbreviated as POI in english, in a geographic information system, a POI refers to a geographic object, such as a house, a shop, a mailbox, a bus station, and the like. The tasks related to the POI are various, such as searching for a geographic object of a target type, collecting attribute information of the geographic object in a certain live-action image, viewing status information and status change records of a certain geographic object, and the like, that is, all the tasks related to the POI belong to the POI-related tasks discussed in the disclosure.

Step 203: and assembling each target functional component according to the operation time sequence of each operation instruction by the robot process automation technology to obtain a component structure diagram.

On the basis of step 202, in this step, the execution main body assembles each target function component according to the operation time sequence of each operation instruction according to the robot process automation technology to obtain a component structure diagram describing an assembly result of each target function component.

The operation time sequence is determined and obtained based on the time sequence arrangement of a plurality of operation instructions, and a robot process automation technology (namely RPA technology) is specifically used during assembly, namely the RPA technology is applied to the automatic generation field of the interest point tasks, so that the convenience brought by the RPA technology can be utilized, and the problem of processing a large amount of interest point information which is provided by different users and is substantially the same but has different details is solved.

Specifically, the execution main body can automatically plan the execution flow and the input/output verification of each functional component according to the processing sequence of the functional components and the interdependence relationship between the functional components according to the robot flow automation technology to obtain a component structure diagram. The input and output verification is used for confirming whether the output of the previous functional component is the input which can be correctly identified and processed by the next functional component among the functional components with the precedence relationship in the execution sequence.

Step 204: and generating a target interest point task according to the component structure diagram.

On the basis of step 203, the target interest point task generated according to the component structure diagram in this step is assembled in order of operation timing sequence, that is, the target interest point task corresponding to the component structure diagram is actually a task flow with a fixed flow, and the task flow can quickly obtain a desired result by repeatedly executing the task flow.

According to the method for processing the information of the interest points based on the robot process automation, which is provided by the embodiment of the disclosure, the robot process automation technology is applied to the field of automatic processing of the information of the interest points, so that various information processing tasks of the interest points can be rapidly and automatically completed in a code-free mode, a more convenient solution is provided for users without code writing capability, and the labor cost of the information processing tasks of the interest points is reduced.

Further, after the target point of interest task is obtained in step 204, in order to enable the target point of interest task to actually take effect, the target point of interest task may be deployed to a preset location in a task flow manner, and after the task flow deployed at the preset location is successfully run, the user initiating the target point of interest task returns a corresponding prompt message to inform that the purpose of the user is completed. The preset positions may be: a certain network address, a certain network space, a certain server or a certain server cluster, etc. contain the position of the data to be processed specified by the user.

In order to deepen understanding of how to obtain each functional component according to the individual steps for completing the historical interest point task, this embodiment also provides a specific implementation manner of obtaining a plurality of functional components through fig. 3, please refer to the schematic structural diagram shown in fig. 3.

Each functional component obtained by packaging according to each independent step for completing the historical interest point task comprises: the system comprises an extraction component, a verification component, a chain finger component, a change monitoring component, a coordinate prediction component, a relation prediction component, a task assignment component and a quality inspection on-line component.

The function of converting the unstructured data of the target source into the structured data can be packaged as an extraction component, for example, a section of unstructured text containing the content related to the interest point on the target webpage is converted into a structured text;

the function of checking the attribute information of the target interest point can be packaged as a checking component, and the checking mode can include: manual verification and smartphone verification, for example by means of a smartphone, whether the business hours recorded on the web page by the target point of interest are correct.

The function of determining the target point of interest number corresponding to the target unstructured data can be packaged as a chain finger component, for example, corresponding the Beijing XX sight to a preset number of PO 1-100.

The functionality of determining a change of state of a point of interest based on collected point of interest characteristic information may be encapsulated as a change monitoring component, e.g. to monitor whether a toll gate at an intersection has been moved (or normal, removed).

The function of determining the coordinates of the included interest points according to the picture or text information may be packaged as a coordinate prediction component, for example, determining the actual coordinates of a newly added interest point in the live-action picture, and the prediction method may include: monocular depth estimation, Geocoding (an encoding method based on spatial location technology that provides a way to convert geographic location information described as an address into geographic coordinates that can be used in a geographic information system).

The functionality Of determining the connection relationships Of different roads, the relationships between parent-child relationships and surfaces Of Interest (AOI, refers to regional-like geographical entities in map data) may be packaged as a relationship prediction component, e.g. determining whether road a is a secondary road to road B, whether road a and road B are two roads at different heights at the same location, respectively, etc.

Different interest point information acquisition or processing tasks can be assigned to corresponding functions of processing objects and packaged into task assignment components, assigned tasks can be flexibly formulated according to actual task requirements, such as a judging task, a point stamping task, a coordinate recording task and the like, and assigned processing objects can comprise pre-training models constructed manually and through a machine learning algorithm or a deep learning algorithm.

The functions of carrying out credibility secondary verification on the target information and bringing the information passing through the secondary verification on line can be packaged into a quality inspection on-line component, for example, a quality inspector specially carrying out quality inspection carries out manual secondary verification.

The functional components are enough to meet the functional requirements of most historical interest point tasks, but in addition to the functional components, the functional components may also include: the data specification component is used for standardizing the non-standard interest point names or the address names; the independent online component is used for deploying or pushing the information which is confirmed to be error-free through the quality inspection to a preset position; a visualization component for converting simple text information into a chart with a higher degree of visualization, and the like.

In order to better understand how to obtain the component structure diagrams for implementing different point-of-interest tasks, the embodiment is further illustrated by the following three specific examples.

Taking a target interest point task as an online medical detection mechanism as an example, a corresponding component structure diagram comprises the following information sources or functional components which are connected in sequence: target web page, extraction component, chain finger component, task assignment component, quality inspection on-line component, i.e. the formed component structure diagram will be expressed as: target web page → extraction component → chain finger component → task assignment component → quality check top line component. In order to achieve the task goal of the online medical detection mechanism, the general task flow is as follows: extracting information from a target webpage to obtain structured information containing a target interest point (namely a medical detection mechanism), then determining a POI number corresponding to the name of the medical detection mechanism through a chain finger assembly, then verifying whether the medical detection mechanism with the POI number has an online requirement, assigning a verification task to a verifier, finally performing secondary verification on a verification result of the verifier by a quality inspector, and online accessing the medical detection mechanism to a map or related applications after the secondary verification is passed, so that related users of the applications can search the medical detection mechanism.

Taking a target interest point task as an example for increasing interest points in a photo, a corresponding component structure diagram comprises the following information sources or functional components which are connected in sequence: the target picture, the extraction component, the coordinate prediction component, the change monitoring component, the task assignment component and the quality inspection on-line component, namely, the formed component structure diagram is shown as follows: target picture → extraction component → coordinate prediction component → change monitoring component → task assignment component → quality check line component. In order to complete the task of adding interest points to the photo, the general task flow is as follows: extracting the structural information containing each interest point from the target picture, predicting the coordinates of each interest point in the real world according to the structural information of each interest point, determining whether the state change exists in each interest point based on the same coordinates, assigning the comparison of state change to each processing object for confirmation, performing secondary verification on the confirmation result by a quality inspector, and updating the transformation condition of the interest points without problems after the secondary verification to the previous information base.

Taking the target interest point as an example of the removal of the sealed control area, the corresponding component structure diagram comprises the following information sources or functional components which are connected in sequence: the target information source, the extraction component, the chain finger component, the task assignment component, the change monitoring component and the quality check on-line component, namely, the formed corresponding component structure diagram is shown as follows: target information source → extraction component → chain finger component → task assignment component → change monitoring component → quality check top line component. Namely, the task target of releasing the sealed control area is completed, and the general task flow is as follows: extracting structured information containing target interest points (namely all cells in a sealed control state before) from a target information source (such as a local government open network, an authoritative video public number and a news website), then determining POI numbers corresponding to the names of all the cells, then assigning the judgment work of the POI numbers to all processing objects for processing, next, carrying out change detection on the state information of all the POI numbers after judgment and re-processing (namely whether a release condition is met), finally, verifying a change detection result by a quality inspector, and releasing the cells meeting the release condition after verification to a preset platform.

On the basis of any embodiment, in order to better assist a user to create a correct component structure diagram with higher efficiency, the reasonability of splicing operation can be determined according to the association relationship among the target function components, and when the unreasonable splicing operation is determined, the next-level alternative function component having the association relationship with the previous-level target function component is presented.

The association relationship may refer to a dependency relationship of different functional components on an execution timing sequence, for example, the chain finger component needs to perform coordinate prediction by the coordinate prediction component before change monitoring, on the basis that the extraction component obtains the structural information of the interest point. Therefore, in this embodiment, after the user selects the upper-level target function component, all reasonable lower-level candidate function components are presented by means of the association relationship, so as to prevent the user from mistakenly selecting a wrong function component without the association relationship as a lower-level function component.

An implementation that includes, but is not limited to, may refer to the flowchart shown in fig. 4.

Step 401: and determining the rationality of the assembling operation according to the incidence relation among the target functional components.

Step 402: and in response to receiving the description information of the target interest point task previously transmitted by the user and determining that unreasonable splicing operation exists, removing partial alternative functional components which are not matched with the description information from all the next-level alternative functional components to obtain recommended alternative functional components.

The description information can be used for determining the task processing type of the target point-of-interest task, so that each functional component associated with the task processing type can be determined based on the task processing type.

Step 403: and presenting the recommended alternative functional components of the next level which have an association relation with the target functional components of the previous level.

That is, when determining the rationality of the splicing operation, the embodiment also combines description information (for example, store contact verification, intersection traffic light change, and the like) of a target point of interest task, which may be introduced by a user in advance, that is, the task purpose of the user is substantially known through the description information, and further, based on the correlation between the task purpose and the functional component, a more accurate next-level functional component is recommended for the user to narrow the selection range.

In addition, the description information can be used for reasonably detecting the reasonability and reasonably recommending the next-stage functional component, and can also be used for recommending a proper functional component which is selected by the first operation at the beginning of the dragging operation attempted by the user and generating a component structure diagram matched with the description information in a whole process guiding manner.

In order to better understand the implementation scheme provided by the present disclosure, the present disclosure also combines two specific point of interest tasks, and more fully illustrates the assembly result of the functional components through fig. 5 and fig. 6, respectively, where fig. 5 illustrates the assembly result of the functional components for implementing the task of the online medical detection mechanism (where GC in the GC coordinate is an abbreviation of Geocoding); fig. 6 shows the assembly result of the functional components for implementing the task of releasing the sealed control area.

With further reference to fig. 7, as an implementation of the methods shown in the above-mentioned figures, the present disclosure provides an embodiment of a point of interest information processing apparatus based on robot process automation, which corresponds to the method embodiment shown in fig. 2, and which may be applied in various electronic devices.

As shown in fig. 7, the point of interest information processing apparatus 700 based on robot process automation according to the present embodiment may include: an operation instruction receiving unit 701, a target function component determining unit 702, a component assembling unit 703 and a target interest point information processing unit 704. The operation instruction receiving unit 701 is configured to receive an operation instruction of a functional component, which is input by a user under a visual configuration interface; a target function component determination unit 702 configured to determine, according to the operation instruction, target function components related to the point of interest task, where each function component is obtained by being packaged in advance according to each independent step for completing the historical point of interest task, and each function component follows a uniform data processing specification; the component assembling unit 703 is configured to assemble each target functional component according to the operation timing sequence of each operation instruction according to the robot process automation technology to obtain a component structure diagram; and a target interest point information processing unit 704 configured to generate a target interest point task according to the component structure diagram.

In the present embodiment, the point-of-interest information processing apparatus 700 based on robot process automation: the specific processing and the technical effects of the operation instruction receiving unit 701, the target function component determining unit 702, the component assembling unit 703 and the target interest point information processing unit 704 can refer to the related descriptions of step 201 and step 204 in the corresponding embodiment of fig. 2, which are not described herein again.

In some optional implementation manners of this embodiment, the point of interest information processing apparatus 700 based on robot process automation may further include:

and the task deployment unit is configured to deploy the target interest point task to a preset position in a task flow mode.

And the prompt information returning unit is configured to return prompt information in response to the successful operation of the task flow deployed at the preset position.

In some optional implementations of this embodiment, each functional component obtained by encapsulating according to each independent step for completing the historical point of interest task at least includes at least one of the following:

the system comprises an extraction component, a verification component, a chain finger component, a change monitoring component, a coordinate prediction component, a relation prediction component, a task assignment component and a quality inspection on-line component.

and the extraction component packaging unit is configured to convert the unstructured data of the target source into the function of the structured data and package the function of the structured data into the extraction component.

the verification component packaging unit is configured to package the function of verifying the attribute information of the target interest point into a verification component; wherein, the mode of carrying out the verification includes: and checking the smart phone.

and the chain finger component packaging unit is configured to package the function of determining the target interest point number corresponding to the target interest point name into a chain finger component.

and the change monitoring component packaging unit is configured to package a function of determining the state change of the interest point according to the collected interest point characteristic information into the change monitoring component.

In some optional implementations of the present embodiment, the point of interest information processing apparatus 700 based on robot flow automation may further include:

and a coordinate prediction component packaging unit configured to package a function of determining the coordinates of the included interest points from the picture or text information as a coordinate prediction component.

and the relation prediction component packaging unit is configured to package the function of determining the connection relation, the parent-child relation and the relation between the interest surfaces of different roads into the relation prediction component.

and the task allocation component packaging unit is configured to allocate different interest point information acquisition or processing tasks to the corresponding functions of the processing objects and package the different interest point information acquisition or processing tasks into the task allocation component.

and the quality inspection online component packaging unit is configured to package the functions of secondarily checking the credibility of the target information and online the information passing the secondary checking into the quality inspection online component.

In some optional implementations of this embodiment, in response to the target point of interest task being an online medical detection mechanism, the corresponding component structure diagram includes the following sequentially connected information sources or functional components:

target web page, extraction component, chain finger component, task assignment component and quality check on-line component.

In some optional implementation manners of this embodiment, in response to the target interest point task adding an interest point to the real-time photo, the corresponding component structure diagram includes the following sequentially connected information sources or functional components:

the system comprises a target picture, an extraction component, a coordinate prediction component, a change monitoring component, a task assignment component and a quality check online component.

In some optional implementation manners of this embodiment, in response to that the target point of interest task is a sealed control area release, the corresponding component structure diagram includes the following sequentially connected information sources or functional components:

target information source, extraction component, chain finger component, task assignment component, change monitoring component and quality check on-line component.

the rationality determining unit is configured to determine the rationality of the splicing operation according to the incidence relation among the target functional components;

and the alternative functional component presenting unit is configured to present a next-level alternative functional component which is associated with the previous-level target functional component in response to determining that the unreasonable splicing operation exists.

and the recommended alternative functional component determining unit is configured to remove part of alternative functional components which are not matched with the description information from all next-level alternative functional components in response to receiving the description information of the target interest point task, which is transmitted by the user in advance, so as to obtain recommended alternative functional components.

Correspondingly, the alternative functional component presenting unit is further configured to.

And presenting the recommended alternative functional components of the next level which have an association relation with the target functional components of the previous level.

The embodiment exists as an embodiment of a device corresponding to the method embodiment, and the point of interest information processing device based on robot flow automation provided by the embodiment applies a robot flow automation technology to the field of point of interest information automatic processing, so that various point of interest information processing tasks can be quickly and automatically completed in a code-free manner, a more convenient solution is provided for users without code compiling capability, and the labor cost of the point of interest information processing tasks is reduced.

According to an embodiment of the present disclosure, the present disclosure also provides an electronic device including: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executable by the at least one processor to enable the at least one processor to implement the point of interest information processing method based on robot process automation as described in any of the above embodiments.

According to an embodiment of the present disclosure, there is also provided a readable storage medium storing computer instructions for enabling a computer to implement the method for processing point of interest information based on robot process automation described in any of the above embodiments when executed.

According to an embodiment of the present disclosure, there is also provided a computer program product, which when executed by a processor, is capable of implementing the steps of the point of interest information processing method based on robot process automation described in any of the above embodiments.

FIG. 8 illustrates a schematic block diagram of an example electronic device 800 that can be used to implement embodiments of the present disclosure. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be examples only, and are not meant to limit implementations of the disclosure described and/or claimed herein.

As shown in fig. 8, the apparatus 800 includes a computing unit 801 that can perform various appropriate actions and processes according to a computer program stored in a Read Only Memory (ROM) 802 or a computer program loaded from a storage unit 808 into a Random Access Memory (RAM) 803. In the RAM 803, various programs and data required for the operation of the device 800 can also be stored. The calculation unit 801, the ROM 802, and the RAM 803 are connected to each other by a bus 804. An input/output (I/O) interface 805 is also connected to bus 804.

A number of components in the device 800 are connected to the I/O interface 805, including: an input unit 806, such as a keyboard, a mouse, or the like; an output unit 807 such as various types of displays, speakers, and the like; a storage unit 808, such as a magnetic disk, optical disk, or the like; and a communication unit 809 such as a network card, modem, wireless communication transceiver, etc. The communication unit 809 allows the device 800 to exchange information/data with other devices via a computer network such as the internet and/or various telecommunication networks.

Computing unit 801 may be a variety of general and/or special purpose processing components with processing and computing capabilities. Some examples of the computing unit 801 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various dedicated Artificial Intelligence (AI) computing chips, various computing units running machine learning model algorithms, a Digital Signal Processor (DSP), and any suitable processor, controller, microcontroller, and the like. The calculation unit 801 executes the respective methods and processes described above, such as a point of interest information processing method based on robot process automation. For example, in some embodiments, the point-of-interest information processing method based on robotic process automation may be implemented as a computer software program tangibly embodied in a machine-readable medium, such as the storage unit 808. In some embodiments, part or all of the computer program can be loaded and/or installed onto device 800 via ROM 802 and/or communications unit 809. When loaded into RAM 803 and executed by the computing unit 801, may perform one or more steps of the point of interest information processing method based on robotic flow automation described above. Alternatively, in other embodiments, the computing unit 801 may be configured to perform the point of interest information processing method based on robotic process automation by any other suitable means (e.g., by means of firmware).

Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuitry, Field Programmable Gate Arrays (FPGAs), Application Specific Integrated Circuits (ASICs), Application Specific Standard Products (ASSPs), system on a chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, receiving data and instructions from, and transmitting data and instructions to, a storage system, at least one input device, and at least one output device.

Program code for implementing the methods of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the program codes, when executed by the processor or controller, cause the functions/operations specified in the flowchart and/or block diagram to be performed. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package partly on the machine and partly on a remote machine or entirely on the remote machine or server.

In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which a user can provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic, speech, or tactile input.

The systems and techniques described here can be implemented in a computing system that includes a back-end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), Wide Area Networks (WANs), and the Internet.

The computer system may include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The Server may be a cloud Server, which is also called a cloud computing Server or a cloud host, and is a host product in a cloud computing service system, so as to solve the defects of high management difficulty and weak service extensibility in the conventional physical host and Virtual Private Server (VPS) service.

According to the technical scheme of the embodiment of the disclosure, the robot process automation technology is applied to the field of automatic processing of the point of interest information, so that various point of interest information processing tasks can be rapidly and automatically completed in a code-free mode, a more convenient solution is provided for users without code compiling capability, and the labor cost of the point of interest information processing tasks is reduced.

It should be understood that various forms of the flows shown above may be used, with steps reordered, added, or deleted. For example, the steps described in the present disclosure may be executed in parallel, sequentially, or in different orders, as long as the desired results of the technical solutions disclosed in the present disclosure can be achieved, and the present disclosure is not limited herein.

The above detailed description should not be construed as limiting the scope of the disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may be made in accordance with design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present disclosure should be included in the scope of protection of the present disclosure.

Claims

1. A point of interest information processing method based on robot process automation comprises the following steps:

receiving an operation instruction of a functional component, which is transmitted by a user under a visual configuration interface;

determining each target function component related to the interest point task according to the operation instruction; each functional component is obtained by packaging according to each independent step for completing historical interest point tasks in advance, and each functional component follows a uniform data processing specification;

assembling each target function component according to the operation time sequence of each operation instruction by a robot process automation technology to obtain a component structure diagram;

and generating a target interest point task according to the component structure diagram.

2. The method of claim 1, further comprising:

deploying the target interest point task to a preset position in a task flow mode;

and responding to the successful operation of the task flow deployed at the preset position, and returning prompt information.

3. The method of claim 1, wherein the functional components encapsulated according to the individual steps for completing the historical point of interest task include at least one of:

4. The method of claim 3, further comprising:

and converting the unstructured data of the target source into structured data, and packaging the structured data into the extraction component.

5. The method of claim 3, further comprising:

the attribute information of the target interest points is verified and packaged into the verification component; wherein, the mode of carrying out the verification includes: and checking the smart phone.

6. The method of claim 3, further comprising:

and packaging the function of determining the target interest point number corresponding to the target interest point name into the chain finger component.

7. The method of claim 3, further comprising:

and determining the state change function of the interest points according to the collected interest point characteristic information, and packaging the function as the change monitoring component.

8. The method of claim 3, further comprising:

and packaging the function of determining the coordinates of the contained interest points according to the picture or text information into the coordinate prediction component.

9. The method of claim 3, further comprising:

and packaging the function of determining the relation among the connection relation, the parent-child relation and the interest surface of different roads into the relation prediction component.

10. The method of claim 3, further comprising:

and allocating different interest point information acquisition or processing tasks to the functions of corresponding processing objects, and packaging the functions into the task allocation component.

11. The method of claim 3, further comprising:

and performing secondary credibility verification on the target information and performing online function on the information passing the secondary verification to package the information into the quality inspection online component.

12. The method of any of claims 3-11, wherein in response to the target point of interest task being an online medical detection facility, the corresponding component structure diagram includes the following sequentially connected information sources or functional components:

target webpage, the extraction component, the chain finger component, the task assignment component and the quality check online component.

13. The method according to any one of claims 3 to 11, wherein in response to the target point of interest task adding a point of interest to the captured photograph, the corresponding component structure diagram comprises the following sequentially connected information sources or functional components:

a target picture, the extraction component, the coordinate prediction component, the change monitoring component, the task assignment component, and the quality check on-line component.

14. The method according to any one of claims 3-11, wherein in response to the target point of interest task being a containment zone release, the corresponding component structure diagram comprises the following sequentially connected information sources or functional components:

a target information source, the extraction component, the chain finger component, the task assignment component, the change monitoring component, and the quality check on-line component.

15. The method of claim 1, further comprising:

determining the rationality of the assembling operation according to the incidence relation among the target functional components;

and in response to determining that unreasonable splicing operation exists, presenting the next-level alternative functional component which has the incidence relation with the previous-level target functional component.

16. The method of claim 15, further comprising:

in response to receiving description information of a target interest point task, which is transmitted by a user in advance, extracting partial alternative functional components which are not matched with the description information from all next-level alternative functional components to obtain recommended alternative functional components;

correspondingly, the presenting of the next-level alternative functional component having the association relation with the previous-level target functional component includes:

and presenting the recommended alternative functional component of the next level with the incidence relation with the target functional component of the previous level.

17. An interest point information processing apparatus based on robot process automation, comprising:

the operation instruction receiving unit is configured to receive operation instructions of the functional components, which are transmitted by a user under the visual configuration interface;

the target function component determining unit is configured to determine each target function component related to the interest point task according to the operation instruction; each functional component is obtained by packaging according to each independent step for completing historical interest point tasks in advance, and each functional component follows a uniform data processing specification;

the component assembling unit is configured to assemble each target function component according to the operation time sequence of each operation instruction by the robot process automation technology to obtain a component structure chart;

and the target interest point information processing unit is configured to generate a target interest point task according to the component structure diagram.

18. The apparatus of claim 17, further comprising:

the task deployment unit is configured to deploy the target interest point task to a preset position in a task flow mode;

19. The apparatus of claim 17, wherein the functional components encapsulated from the individual steps for completing the historical point of interest task include at least one of:

20. The apparatus of claim 19, further comprising:

21. The apparatus of claim 19, further comprising:

a verification component packaging unit configured to package a function of verifying attribute information of a target point of interest as the verification component; wherein, the mode of carrying out the verification includes: and checking the smart phone.

22. The apparatus of claim 19, further comprising:

and the chain finger component packaging unit is configured to package a function of determining a target interest point number corresponding to the target interest point name as the chain finger component.

23. The apparatus of claim 19, further comprising:

and the change monitoring component packaging unit is configured to package a function of determining the state change of the interest point according to the collected interest point characteristic information as the change monitoring component.

24. The apparatus of claim 19, further comprising:

a coordinate prediction component packaging unit configured to package a function of determining coordinates of included points of interest from picture or text information as the coordinate prediction component.

25. The apparatus of claim 19, further comprising:

a relation prediction component packaging unit configured to package a function of determining a relation between connection relations, parent-child relations, and interest planes of different roads as the relation prediction component.

26. The apparatus of claim 19, further comprising:

and the task dispatching component packaging unit is configured to dispatch different interest point information acquisition or processing tasks to the functions of corresponding processing objects and package the tasks into the task dispatching component.

27. The apparatus of claim 19, further comprising:

28. The apparatus of any of claims 19-27, wherein in response to the target point of interest task being an online medical detection facility, the corresponding component structure diagram comprises the following sequentially connected information sources or functional components:

29. The method of any of claims 19-27, wherein in response to the target point of interest task adding a point of interest to the captured photograph, the corresponding component structure diagram comprises the following sequentially connected information sources or functional components:

30. The apparatus according to any of claims 19-27, wherein in response to the target point of interest task being a containment zone release, the corresponding component structure diagram comprises the following sequentially connected information sources or functional components:

31. The apparatus of claim 17, further comprising:

the rationality determining unit is configured to determine the rationality of the splicing operation according to the incidence relation among the target function components;

and the alternative functional component presenting unit is configured to present the next-level alternative functional component with the incidence relation with the previous-level target functional component in response to the fact that the unreasonable splicing operation is determined to exist.

32. The apparatus of claim 31, further comprising:

the recommended alternative functional component determining unit is configured to respond to the received description information of the target interest point task, which is transmitted by the user in advance, remove partial alternative functional components which are not matched with the description information from all the next-level alternative functional components, and obtain recommended alternative functional components;

correspondingly, the alternative functional component presenting unit is further configured to:

33. An electronic device, comprising:

at least one processor; and

a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,

the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-16.

34. A non-transitory computer readable storage medium having stored thereon computer instructions for causing the computer to perform the method of any one of claims 1-16.