CN115082766B

CN115082766B - RPA service scene recognition method, system, device and storage medium

Info

Publication number: CN115082766B
Application number: CN202210874025.9A
Authority: CN
Inventors: 廖万里; 金卓; 江斌超; 周雄雄
Original assignee: Zhuhai Kingsware Information Technology Co Ltd
Current assignee: Zhuhai Kingsware Information Technology Co Ltd
Priority date: 2022-07-25
Filing date: 2022-07-25
Publication date: 2022-11-25
Anticipated expiration: 2042-07-25
Also published as: CN115082766A

Abstract

The invention discloses a method, a system, a device and a storage medium for identifying an RPA service scene, wherein the method for identifying the RPA service scene identifies an object to be identified by adopting an identification method of a selectable preset identification method and a user-defined identification method to obtain a standard template, searches a target value by adopting a search method of the selectable preset search method and the user-defined search method and processes the target value by adopting a processing method of the selectable preset processing method and the user-defined processing method to obtain a result value, so that the RPA technology can adapt to the identification under multiple scenes, different methods can be selected according to different scenes to optimize the identification rate, the RPA script does not need to be modified, the decoupling of a service flow and a bottom script is realized, the service requirement can be responded quickly, and the convenience and the service processing efficiency are improved. The invention can be widely applied to the technical field of data processing.

Description

RPA service scene recognition method, system, device and storage medium

Technical Field

The present application relates to the field of data processing technologies, and in particular, to a method, a system, an apparatus, and a storage medium for identifying an RPA service scenario.

Background

With the development of software Process Automation (RPA) in various industries, more and more scenes need to be combined with Optical Character Recognition (OCR) technology. Since each enterprise provides different OCR capabilities, it is costly to develop similar scenarios via RPA. Moreover, if the recognition rate needs to be optimized, the RPA script needs to be modified, and meanwhile, the RPA script needs to be modified when the processing rule of the file to be recognized or the target data changes, so that the service flow is complicated, and inconvenience is brought to RPA developers and service personnel.

Disclosure of Invention

The present invention aims to solve at least to some extent one of the technical problems existing in the prior art.

Therefore, an object of the embodiments of the present invention is to provide a method, a system, a device, and a storage medium for identifying an RPA service scenario, so as to improve convenience of identification in the RPA service scenario.

In order to achieve the technical purpose, the technical scheme adopted by the embodiment of the invention comprises the following steps:

in one aspect, an embodiment of the present invention provides a method for identifying an RPA service scenario, including the following steps:

generating a template file to be identified according to an object to be identified;

converting unstructured data in the object to be recognized into structured data according to a recognition method in the template file to be recognized to generate a standard template, wherein the recognition method comprises a preset recognition method and a custom recognition method, the preset recognition method is a preset recognition method, and the custom recognition method is a custom set recognition method;

searching a target value by adopting a searching method in the template file to be identified according to the standard template, wherein the searching method comprises a preset searching method and a custom searching method, the preset searching method is a preset searching method, and the custom searching method is a custom searching method;

processing the target value according to a processing method in the template file to be recognized to generate a result value, wherein the processing method comprises a preset processing method and a user-defined processing method, the preset processing method is a preset processing method, and the user-defined processing method is a user-defined processing method;

and writing the result value into the template file to be identified to generate a result file.

According to the RPA service scene recognition method, the standard template is obtained by recognizing the object to be recognized by adopting the recognition method of the selectable preset recognition method and the user-defined recognition method, the target value is searched by adopting the search method of the selectable preset search method and the user-defined search method, and the target value is processed by adopting the processing method of the selectable preset processing method and the user-defined processing method to obtain the result value, so that the RPA technology can adapt to recognition under multiple scenes, different methods can be selected according to different scenes to optimize the recognition rate, the RPA script does not need to be modified, the decoupling of the service flow and the bottom layer script is realized, the user requirement can be responded quickly, and the convenience and the service processing efficiency are improved.

In addition, the method for identifying an RPA service scenario according to the above embodiment of the present invention may further have the following additional technical features:

further, in the RPA service scene identification method according to the embodiment of the present invention, the template file to be identified is generated by manual filling or automatically generated.

Further, in an embodiment of the present invention, before the converting the unstructured data in the object to be recognized into the structured data according to the recognition method in the template file to be recognized, and generating a standard template, the method for recognizing an RPA service scene further includes:

and analyzing the template file to be identified.

Further, in the RPA service scene recognition method according to the embodiment of the present invention, the preset recognition method includes OCR recognition, python recognition, and RPA chinese component recognition;

converting unstructured data in the object to be identified into structured data according to the identification method in the template file to be identified to generate a standard template, wherein the standard template comprises at least one of the following data:

converting unstructured data in the object to be recognized into structured data by adopting OCR recognition, and generating the standard template;

adopting Python identification to convert unstructured data in the object to be identified into structured data, and generating the standard template;

adopting RPA Chinese component identification to convert unstructured data in the object to be identified into structured data, and generating the standard template;

and converting the unstructured data in the object to be recognized into structured data by adopting the custom recognition method to generate the standard template.

Further, in one embodiment of the present invention, the preset search method includes a full word search method and a fuzzy search method;

according to the standard template, searching for a target value by adopting a searching method in the template file to be identified comprises at least one of the following steps:

searching the target value by adopting a whole word searching method according to the standard template;

searching the target value by adopting a fuzzy search method according to the standard template;

and searching the target value by adopting the custom searching method according to the standard template.

Further, in an embodiment of the present invention, the preset processing method includes space removal, date conversion, decimal point conversion;

the target value is processed according to the processing method in the template file to be identified, and a result value is generated, wherein the result value comprises at least one of the following:

removing spaces from the target value to generate the result value;

performing date conversion on the target value to generate the result value;

carrying out decimal point conversion on the target value to generate the result value;

and processing the target value by adopting the user-defined processing method to generate the result value, wherein the user-defined processing method comprises the step of not processing the target value.

Further, in an embodiment of the present invention, after the writing the result value into the template file to be identified and generating a result file, the RPA service scene identification method further includes:

and performing log recording according to the result file.

On the other hand, an embodiment of the present invention provides an RPA service scene identification system, including:

the generating module is used for generating a template file to be identified according to the object to be identified;

the identification module is used for converting unstructured data in the object to be identified into structured data according to an identification method in the template file to be identified to generate a standard template, wherein the identification method comprises a preset identification method and a custom identification method, the preset identification method is a preset identification method, and the custom identification method is a custom set identification method;

the searching module is used for searching the target value by adopting a searching method in the template file to be identified according to the standard template, wherein the searching method comprises a preset searching method and a custom searching method, the preset searching method is a preset searching method, and the custom searching method is a custom searching method;

the processing module is used for processing the target value according to a processing method in the template file to be identified to generate a result value, wherein the processing method comprises a preset processing method and a custom processing method, the preset processing method is a preset processing method, and the custom processing method is a custom set processing method;

and the value writing module is used for writing the result value into the template file to be identified to generate a result file.

On the other hand, an embodiment of the present invention provides an apparatus for identifying an RPA service scenario, including:

at least one processor;

at least one memory for storing at least one program;

when the at least one program is executed by the at least one processor, the at least one program causes the at least one processor to implement the RPA service scene recognition method.

In another aspect, an embodiment of the present invention provides a storage medium, in which a processor-executable program is stored, where the processor-executable program is used to implement the RPA service scene identification method when executed by a processor.

Advantages and benefits of the present invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the present application:

according to the embodiment of the invention, the identification method adopting the selectable preset identification method and the user-defined identification method is adopted to identify the object to be identified to obtain the standard template, the search method adopting the selectable preset search method and the user-defined search method is adopted to search the target value, and the processing method adopting the selectable preset processing method and the user-defined processing method is adopted to process the target value to obtain the result value, so that the RPA technology can adapt to the identification under multiple scenes, different methods can be selected according to different scenes to optimize the identification rate, the RPA script does not need to be modified, the decoupling of the service process and the bottom script is realized, the user requirement can be quickly responded, and the convenience and the service processing efficiency are improved.

Drawings

In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following description is made on the drawings of the embodiments of the present application or the related technical solutions in the prior art, and it should be understood that the drawings in the following description are only for convenience and clarity of describing some embodiments in the technical solutions of the present application, and it is obvious for those skilled in the art that other drawings can be obtained according to these drawings without creative efforts.

Fig. 1 is a schematic flow chart of a specific embodiment of an RPA service scene identification method according to the present invention;

fig. 2 is a schematic diagram of a template file to be identified in an embodiment of an RPA service scene identification system according to the present invention;

FIG. 3 is a schematic diagram of an RPA script according to an embodiment of the RPA service scene recognition system of the present invention

Fig. 4 is a schematic structural diagram of an embodiment of an RPA service scene recognition system according to the present invention;

fig. 5 is a schematic structural diagram of an embodiment of an RPA service scene recognition apparatus according to the present invention.

Detailed Description

Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the accompanying drawings are illustrative and are only for the purpose of explaining the present application and are not to be construed as limiting the present application. The step numbers in the following embodiments are provided only for convenience of illustration, the order between the steps is not limited at all, and the execution order of each step in the embodiments can be adapted according to the understanding of those skilled in the art.

The terms "first," "second," "third," and "fourth," etc. in the description and claims of the invention and in the accompanying drawings are used for distinguishing between different objects and not for describing a particular order. Furthermore, the terms "include" and "have," as well as any variations thereof, are intended to cover a non-exclusive inclusion. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those steps or elements but may alternatively include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.

Reference in the specification to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the invention. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein may be combined with other embodiments.

As RPA advances across industries, more and more scenes need to be incorporated into OCR technology. Since each enterprise provides different OCR capabilities, it is costly to develop similar scenarios via RPA. Moreover, if the recognition rate needs to be optimized, the RPA script needs to be modified, and meanwhile, the RPA script needs to be modified when the processing rule of the file to be recognized or the target data changes, so that the service flow is complicated, and much inconvenience is brought to service personnel. The invention provides an RPA service scene recognition method, a system, a device and a storage medium, wherein a standard template is obtained by recognizing an object to be recognized by adopting a recognition method of a selectable preset recognition method and a user-defined recognition method, a target value is searched by adopting a search method of a selectable preset search method and a user-defined search method, and a result value is obtained by processing the target value by adopting a processing method of a selectable preset processing method and a user-defined processing method, so that the RPA technology can adapt to recognition under multiple scenes, different methods can be selected according to different scenes to optimize the recognition rate, the RPA script does not need to be modified, the decoupling of a service flow and a bottom script is realized, the user requirement can be responded quickly, and the convenience and the service processing efficiency are improved.

An RPA service scene recognition method, system, apparatus, and storage medium according to an embodiment of the present invention will be described in detail below with reference to the accompanying drawings, and first, an RPA service scene recognition method according to an embodiment of the present invention will be described with reference to the accompanying drawings.

Referring to fig. 1, an embodiment of the present invention provides an RPA service scene identification method, which may be applied to a terminal, a server, software running in the terminal or the server, or the like. The terminal may be, but is not limited to, a tablet computer, a notebook computer, a desktop computer, and the like. The server may be an independent physical server, a server cluster or a distributed system formed by a plurality of physical servers, or a cloud server providing basic cloud computing services such as a cloud service, a cloud database, cloud computing, a cloud function, cloud storage, a network service, cloud communication, middleware service, a domain name service, a security service, a Content Delivery Network (CDN), a big data and artificial intelligence platform, and the like. The RPA service scene recognition method in the embodiment of the invention mainly comprises the following steps:

s101, generating a template file to be identified according to an object to be identified;

in the embodiment of the present invention, the object to be identified is obtained according to the requirement of the user, which specifically includes:

and responding to the user requirement, and generating the object to be recognized.

Optionally, the user requirement is a requirement document, and the embodiment of the present invention obtains a file path according to the requirement document to obtain an object to be identified, such as a pdf to be identified, a picture, a fax, and other files.

In the embodiment of the invention, the template file to be identified is generated by manual filling or automatically generated.

Fig. 2 shows a template file to be recognized according to an embodiment of the present invention.

S102, converting unstructured data in an object to be identified into structured data according to an identification method in a template file to be identified, and generating a standard template;

in the embodiment of the present invention, before step S102, a parsing step of the template file to be identified is further included.

In the embodiment of the invention, the identification method comprises a preset identification method and a user-defined identification method, wherein the preset identification method is a preset identification method, and the user-defined identification method is a user-defined identification method.

Optionally, the preset recognition method includes OCR recognition, python recognition, RPA chinese component recognition.

Specifically, step S102 includes at least one of:

1) Converting unstructured data in an object to be recognized into structured data by adopting OCR recognition to generate a standard template;

2) Adopting Python identification to convert unstructured data in an object to be identified into structured data and generating a standard template;

3) Adopting RPA Chinese component identification to convert unstructured data in an object to be identified into structured data and generating a standard template;

4) And converting unstructured data in the object to be recognized into structured data by adopting a custom recognition method to generate a standard template.

Optionally, the standard template is excel.

S103, searching a target value by adopting a searching method in a template file to be identified according to the standard template;

in the embodiment of the invention, the searching method comprises a preset searching method and a custom searching method, wherein the preset searching method is a preset searching method, and the custom searching method is a custom searching method.

Optionally, the preset search method includes a full word search method and a fuzzy search method.

Specifically, step S103 includes at least one of:

1) Searching a target value by adopting a full-word searching method according to a standard template;

2) Searching a target value by adopting a fuzzy search method according to a standard template;

3) And searching the target value by adopting a custom searching method according to the standard template.

Alternatively, the target values are the displacement relationship, the offset amount, and the search pattern, as shown in fig. 2.

S104, processing the target value according to the processing method in the template file to be identified to generate a result value;

in an embodiment of the present invention, the processing method includes a preset processing method and a custom processing method, where the preset processing method is a preset processing method, the custom processing method is a custom set processing method, and the custom processing method includes not processing the target value.

Optionally, the preset processing method includes de-spacing, date conversion, decimal point conversion, as shown in fig. 2.

Specifically, step S104 includes at least one of:

1) Removing spaces from the target value to generate a result value;

2) Date conversion is carried out on the target value to generate a result value;

3) Carrying out decimal point conversion on the target value to generate a result value;

4) And processing the target value by a user-defined processing method to generate a result value.

And S105, writing the result value into the template file to be identified to generate a result file.

Specifically, after the result file is generated, log recording is performed according to the result file.

FIG. 3 illustrates an RPA script of an embodiment of the present invention. The RPA service scene recognition method of the embodiment of the invention adopts the design concept of convention greater than configuration, thereby reducing a large number of configuration codes.

The RPA service scene identification method described in connection with steps S101-S105 can be seen in that, in the present invention, a standard template is obtained by identifying an object to be identified by using an identification method that selects a preset identification method and a custom identification method, a search target value is obtained by using a search method that selects a preset search method and a custom search method, and a result value is obtained by processing the target value by using a processing method that selects a preset processing method and a custom processing method, so that the RPA technology can adapt to identification under multiple scenes, and different methods can be selected according to different scenes to optimize the identification rate without modifying RPA scripts, thereby decoupling the service flow and the underlying scripts, rapidly responding to user requirements, and improving convenience and service processing efficiency.

Next, an RPA service scene recognition system proposed according to an embodiment of the present application is described with reference to the drawings.

Fig. 4 is a schematic structural diagram of an RPA service scene recognition system according to an embodiment of the present application.

The system specifically comprises:

the generating module 401 is configured to generate a template file to be identified according to an object to be identified;

an identification module 402, configured to convert unstructured data in the object to be identified into structured data according to an identification method in the template file to be identified, and generate a standard template, where the identification method includes a preset identification method and a custom identification method, the preset identification method is a preset identification method, and the custom identification method is a custom set identification method;

a searching module 403, configured to search for a target value by using a searching method in the template file to be identified according to the standard template, where the searching method includes a preset searching method and a customized searching method, the preset searching method is a preset searching method, and the customized searching method is a customized searching method;

a processing module 404, configured to process the target value according to a processing method in the template file to be identified, so as to generate a result value, where the processing method includes a preset processing method and a custom processing method, the preset processing method is a preset processing method, and the custom processing method is a custom set processing method;

and a value writing module 405, configured to write the result value into the template file to be identified, so as to generate a result file.

The embodiment of the invention adopts the design concept of spring Boot, and realizes a highly expandable and customizable RPA service scene recognition system through modular design.

It can be seen that the contents in the foregoing method embodiments are all applicable to this system embodiment, the functions specifically implemented by this system embodiment are the same as those in the foregoing method embodiment, and the advantageous effects achieved by this system embodiment are also the same as those achieved by the foregoing method embodiment.

Referring to fig. 5, an embodiment of the present application provides an RPA service scene recognition apparatus, including:

at least one processor 501;

at least one memory 502 for storing at least one program;

when the at least one program is executed by the at least one processor 501, the at least one processor 501 is enabled to implement the RPA service scene recognition method described in steps S101-S105.

Similarly, the contents of the method embodiments are all applicable to the apparatus embodiments, the functions specifically implemented by the apparatus embodiments are the same as the method embodiments, and the beneficial effects achieved by the apparatus embodiments are also the same as the beneficial effects achieved by the method embodiments.

In alternative embodiments, the functions/acts noted in the block diagrams may occur out of the order noted in the operational illustrations. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality/acts involved. Furthermore, the embodiments presented and described in the flowcharts of the present application are provided by way of example in order to provide a more thorough understanding of the technology. The disclosed methods are not limited to the operations and logic flows presented herein. Alternative embodiments are contemplated in which the order of various operations is changed and in which sub-operations described as part of larger operations are performed independently.

Furthermore, although the present application is described in the context of functional modules, it should be understood that, unless otherwise stated to the contrary, one or more of the functions and/or features may be integrated in a single physical device and/or software module, or one or more functions and/or features may be implemented in separate physical devices or software modules. It will also be appreciated that a detailed discussion regarding the actual implementation of each module is not necessary for an understanding of the present application. Rather, the actual implementation of the various functional modules in the apparatus disclosed herein will be understood within the ordinary skill of an engineer, given the nature, function, and internal relationship of the modules. Accordingly, those skilled in the art can, using ordinary skill, practice the present application as set forth in the claims without undue experimentation. It is also to be understood that the specific concepts disclosed are merely illustrative of and not intended to limit the scope of the application, which is to be determined by the appended claims along with their full scope of equivalents.

The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the present application, which are essential or part of the technical solutions contributing to the prior art, may be embodied in the form of a software product, which is stored in a storage medium and includes several programs for enabling a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the methods described in the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.

The logic and/or steps represented in the flowcharts or otherwise described herein, such as an ordered listing of executable programs that can be considered to implement logical functions, can be embodied in any computer-readable medium for use by or in connection with a program execution system, apparatus, or device (such as a computer-based system, processor-containing system, or other system that can fetch the programs from the program execution system, apparatus, or device and execute the programs). For the purposes of this description, a "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the program execution system, apparatus, or device.

More specific examples (a non-exhaustive list) of the computer-readable medium would include the following: an electrical connection (electronic device) having one or more wires, a portable computer diskette (magnetic device), a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium could even be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, via for instance optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner if necessary, and then stored in a computer memory.

It should be understood that portions of the present application may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, various steps or methods may be implemented in software or firmware stored in a memory and executed by a suitable program execution system. For example, if implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.

In the foregoing description of the specification, reference to the description of "one embodiment/example," "another embodiment/example," or "certain embodiments/examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the application. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

While embodiments of the present application have been shown and described, it will be understood by those of ordinary skill in the art that: numerous changes, modifications, substitutions and alterations can be made to the embodiments without departing from the principles and spirit of the application, the scope of which is defined by the claims and their equivalents.

While the present application has been described with reference to the preferred embodiments, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined by the appended claims.

Claims

1. A method for identifying RPA service scene is characterized by comprising the following steps:

generating a template file to be identified according to an object to be identified; the object to be identified comprises pdf, picture and fax;

converting unstructured data in the object to be identified into structured data according to an identification method in the template file to be identified to generate a standard template, wherein the identification method comprises a preset identification method and a custom identification method, the preset identification method is a preset identification method, and the custom identification method is a custom set identification method; wherein the standard template is an excel format template;

searching a target value by adopting a searching method in the template file to be identified according to the standard template, wherein the searching method comprises a preset searching method and a custom searching method, the preset searching method is a preset searching method, and the custom searching method is a custom searching method; the target value comprises a displacement relation, an offset and a search mode;

processing the target value according to a processing method in the template file to be recognized to generate a result value, wherein the processing method comprises a preset processing method and a user-defined processing method, the preset processing method is a preset processing method, and the user-defined processing method is a user-defined processing method; the preset processing method comprises space removal, date conversion and decimal point conversion;

writing the result value into the template file to be identified to generate a result file;

the preset recognition method comprises OCR recognition, python recognition and RPA Chinese component recognition;

converting unstructured data in the object to be recognized into structured data by adopting Python recognition to generate the standard template;

2. The method as claimed in claim 1, wherein the template file to be identified is generated by manual filling or automatically generated.

3. The RPA service scene recognition method according to claim 1, wherein before the unstructured data in the object to be recognized is converted into structured data according to the recognition method in the template file to be recognized, and a standard template is generated, the method further comprises:

and analyzing the template file to be identified.

4. The RPA service scene recognition method according to claim 1, wherein the preset search method comprises a full word search and a fuzzy search;

searching the target value by adopting full word search according to the standard template;

searching the target value by fuzzy search according to the standard template;

5. The method according to claim 1, wherein the processing the target value according to the processing method in the template file to be identified to generate a result value comprises at least one of the following:

removing spaces from the target value to generate the result value;

performing date conversion on the target value to generate the result value;

6. The RPA service scene recognition method according to claim 1, wherein after said writing the result value into the standard template to generate a result file, the method further comprises:

and performing log recording according to the result file.

7. An RPA service scene recognition system, comprising:

the generating module is used for generating a template file to be identified according to the object to be identified; the object to be identified comprises pdf, picture and fax;

the identification module is used for converting unstructured data in the object to be identified into structured data according to an identification method in the template file to be identified to generate a standard template, wherein the identification method comprises a preset identification method and a custom identification method, the preset identification method is a preset identification method, and the custom identification method is a custom set identification method; wherein the standard template is an excel format template;

the processing module is used for processing the target value according to a processing method in the template file to be identified to generate a result value, wherein the processing method comprises a preset processing method and a custom processing method, the preset processing method is a preset processing method, and the custom processing method is a custom set processing method; the target value comprises a displacement relation, an offset and a search mode; the preset processing method comprises space removal, date conversion and decimal point conversion;

the value writing module is used for writing the result value into the template file to be identified to generate a result file;

converting unstructured data in the object to be recognized into structured data according to the recognition method in the template file to be recognized, and generating a standard template, wherein the standard template comprises at least one of the following data:

8. An apparatus for identifying RPA service scenario, comprising:

at least one processor;

at least one memory for storing at least one program;

when executed by the at least one processor, the at least one program causes the at least one processor to implement a method for RPA traffic scene recognition according to any of claims 1-6.

9. A storage medium having stored therein a processor-executable program, wherein the processor-executable program, when executed by a processor, is configured to implement an RPA service scene recognition method according to any one of claims 1 to 6.