Data collection method, device, electronic device and medium combining RPA and AI

Abstract

The present disclosure proposes a data collection method, device, electronic device and medium combining RPA and AI. The method includes: using robot process automation RPA to obtain files to be processed, and using artificial intelligence AI to identify data to be reported from the files to be processed, wherein the data to be reported has corresponding data description information, and according to the data description information, the data to be reported is reported to a data collection platform. Since data collection is performed using robot process automation RPA and artificial intelligence AI, the efficiency and automation of data collection can be effectively improved, the accuracy and convenience of data reporting can be effectively improved, and the resource consumption of data collection can be reduced.

Description

Technical Field

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

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

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

[0004] Non-regulated enterprises are the abbreviation of enterprises below a certain scale, referring to legal entities whose annual main business income in the previous year was RMB 20 million or less. Relevant technologies usually use manual collection and reporting methods to collect data on non-regulated enterprises.

[0005] This method requires a large amount of resource consumption (such as human resources, time resources, etc.), has low data statistical efficiency, low degree of automation, and insufficient statistical accuracy and convenience. Summary of the invention

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

[0007] To this end, the purpose of the present disclosure is to propose a data collection method, device, electronic device and medium that combines RPA and AI, which can effectively improve the efficiency and automation of data collection, effectively improve the accuracy and convenience of data reporting, and reduce the resource consumption of data collection.

[0008] The data collection method combining RPA and AI proposed in the embodiment of the first aspect of the present disclosure includes: using robot process automation RPA to obtain files to be processed; using artificial intelligence AI to identify data to be reported from the files to be processed, wherein the data to be reported has corresponding data description information; and reporting the data to be reported to a data collection platform according to the data description information.

[0009] The data collection method combining RPA and AI proposed in the embodiment of the first aspect of the present disclosure adopts robot process automation RPA to obtain the file to be processed, and adopts artificial intelligence AI to identify the data to be reported from the file to be processed, wherein the data to be reported has corresponding data description information, and the data to be reported is reported to the data collection platform according to the data description information. Since data collection is performed by using robot process automation RPA and artificial intelligence AI, the efficiency and automation of data collection can be effectively improved, the accuracy and convenience of data reporting can be effectively improved, and the resource consumption of data collection can be reduced.

[0010] The data collection device combining RPA and AI proposed in the second aspect of the embodiment of the present disclosure includes: a first acquisition module, used to use robot process automation RPA to obtain files to be processed; an identification module, used to use artificial intelligence AI to identify data to be reported from the files to be processed, wherein the data to be reported has corresponding data description information; a reporting module, used to report the data to be reported to the data collection platform according to the data description information.

[0011] The data collection device combining RPA and AI proposed in the second aspect of the embodiment of the present disclosure obtains the file to be processed by using robot process automation RPA, and identifies the data to be reported from the file to be processed by using artificial intelligence AI, wherein the data to be reported has corresponding data description information. According to the data description information, the data to be reported is reported to the data collection platform. Since data collection is performed by using robot process automation RPA and artificial intelligence AI, the efficiency and automation of data collection can be effectively improved, the accuracy and convenience of data reporting can be effectively improved, and the resource consumption of data collection can be reduced.

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

[0013] The fourth aspect embodiment of the present disclosure proposes a computer-readable storage medium, in which computer execution instructions are stored. When a processor executes the computer execution instructions, the data collection method combining RPA and AI proposed in the first aspect embodiment of the present disclosure is implemented.

[0014] Additional aspects and advantages of the present disclosure will be given in part in the following description and in part will be obvious from the following description or learned through practice of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] The above and / or additional aspects and advantages of the present disclosure will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0016] Figure 1 It is a flowchart of a data collection method combining RPA and AI proposed in one embodiment of the present disclosure;

[0017] Figure 2 is a flowchart of a data collection method combining RPA and AI proposed in another embodiment of the present disclosure;

[0018] Figure 3 is a flowchart of a data collection method combining RPA and AI proposed in another embodiment of the present disclosure;

[0019] Figure 4 is a schematic diagram of a subject information list proposed in another embodiment of the present disclosure;

[0020] Figure 5 This is a schematic diagram of an information transmission address writing control interface proposed in another embodiment of the present disclosure;

[0021] Figure 6 is a schematic diagram of a prompt message writing control interface proposed in another embodiment of the present disclosure;

[0022] Figure 7 is a schematic diagram of a data collection platform selection interface proposed in another embodiment of the present disclosure;

[0023] Figure 8 is a schematic diagram of a statistical interface of a data collection platform proposed in another embodiment of the present disclosure;

[0024] Fig. 9 It is a structural diagram of a data collection device combining RPA and AI proposed in one embodiment of the present disclosure;

[0025] Fig.10 is a structural diagram of a data collection device combining RPA and AI proposed in another embodiment of the present disclosure;

[0026] Fig.11 A structural block diagram of an electronic device according to an embodiment of the present disclosure is shown. DETAILED DESCRIPTION

[0027] Embodiments of the present disclosure are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present disclosure, and are not to be construed as limitations of the present disclosure. On the contrary, the embodiments of the present disclosure include all changes, modifications, and equivalents that fall within the spirit and connotation of the appended claims.

[0028] In the description of the present disclosure, the term "plurality" refers to two or more.

[0029] In the description of this disclosure, the term "robotic process automation (RPA)" refers to the automatic execution of process tasks on a computer according to rules through robotic application software.

[0030] In the description of this disclosure, the term "artificial intelligence AI" refers to the discipline that studies how computers can simulate certain human thought processes and intelligent behaviors (such as learning, reasoning, thinking, planning, etc.), including both hardware-level and software-level technologies. Artificial intelligence hardware technologies generally include technologies such as sensors, dedicated artificial intelligence chips, cloud computing, distributed storage, and big data processing; artificial intelligence software technologies mainly include computer vision technology, speech recognition technology, natural language processing technology, as well as machine learning, deep learning, big data processing technology, knowledge graph technology, and other major directions.

[0031] In the description of the present disclosure, the term "file to be processed" refers to a file whose related data is to be reported and processed. The file to be processed in the embodiment of the present disclosure can be a file containing various types of enterprise data to be reported, collected and counted. The file to be processed can have multiple file types, such as a spreadsheet file, or a document file, etc., and there is no limitation on this.

[0032] In the description of the present disclosure, the term "data to be reported" refers to data related to enterprise operations to be reported to the data collection platform. The data to be reported can be directly identified from the data information involved in the file to be processed, or the data to be reported can be obtained by integrating the data information involved in the file to be processed, and the data to be reported can have corresponding data description information, without limitation.

[0033] In the description of this disclosure, the term "data description information" refers to data information that describes one or more relevant characteristics of the data to be reported. The data description information can be the data type, the enterprise to which the data belongs, the data name, the file type and name to which the data belongs, etc., and there is no limitation on this.

[0034] In the description of this disclosure, the term "data collection platform" refers to a platform used to collect, integrate, display, and back up data. The platform can be a cloud service platform, or it can be any other possible form of data collection system, etc., without limitation.

[0035] In the description of this disclosure, the term "data collection tag" refers to a data tag pre-set in the data collection platform for identifying various types of data description information. The data collection tag can be used to classify the data description information to facilitate the organization of the data to be reported.

[0036] In the description of this disclosure, the term "data collection area" refers to an area in a data collection platform used to store collected data. The data collection label is associated with the data collection area to classify, store, and record the saved data to be reported.

[0037] In the description of the present disclosure, the term "reminder setting instruction" refers to instruction information for reminding a corresponding subject based on reported data related to the operation of an enterprise.

[0038] In the description of the present disclosure, the term "data features to be reminded" refers to data features possessed by data related to enterprise operations.

[0039] In the description of the present disclosure, the term "subject to which the data feature to be reminded belongs" refers to the subject described by the data feature to be reminded. For example, if the data feature to be reminded is turnover, the subject to which the data feature to be reminded belongs may be the enterprise to which the turnover belongs.

[0040] In the description of this disclosure, the term "subject information" refers to the basic information corresponding to the subject to which the data feature to be reminded belongs. The subject information may include the basic information of the subject, including contact person, contact information, location information, etc., without limitation.

[0041] In the description of the present disclosure, the term "reporting status" refers to whether the subject reports the corresponding status. The reporting status can be "not reported", "reported" and other types, and there is no limitation on this.

[0042] In the description of the present disclosure, the term "subject information list" refers to a data list used to store subject information corresponding to unreported subjects.

[0043] In the description of the present disclosure, the term "information transmission platform" refers to a platform used to organize and transmit prompt information. Different information transmission platforms can be selected according to the type of prompt method, or multiple types of prompt methods can be integrated into the same information transmission platform. There is no limitation on this.

[0044] In the description of the present disclosure, the term “information transmission address writing control” refers to a control for writing an information transmission address.

[0045] In the description of the present disclosure, the term "subject-side electronic device" refers to the electronic device corresponding to the information transmission address. The subject-side electronic device can be, for example, a landline phone, a mobile phone, a computer, etc., without limitation.

[0046] In the description of the present disclosure, the term "information transmission address" refers to the transmission address corresponding to the electronic device on the subject side. A telephone number, an email address, and a real address can all be used as an information transmission address without limitation.

[0047] In the description of the present disclosure, the term "prompt message writing control" refers to a control used to compose and adjust a reporting prompt message.

[0048] In the description of this disclosure, the term "message transmission control" refers to a control used to transmit prompt messages to an information transmission address. The transmission methods include but are not limited to sending text messages, broadcasting voice calls, sending emails, etc., and there is no restriction on this.

[0049] Figure 1 It is a flowchart of a data collection method combining RPA and AI proposed in one embodiment of the present disclosure.

[0050] This embodiment takes the data collection method combining RPA and AI as an example configured as a data collection device combining RPA and AI. The data collection method combining RPA and AI in this embodiment can be configured in a data collection device combining RPA and AI. The data collection device combining RPA and AI can be set in a server, or can also be set in an electronic device. The embodiments of the present disclosure do not limit this.

[0051] This embodiment takes the data collection method combining RPA and AI as an example, which is configured in an electronic device, such as a smart phone, a tablet computer, a personal digital assistant, an e-book, and other hardware devices with various operating systems.

[0052] It should be noted that the execution subject of the embodiment of the present disclosure may be, for example, a central processing unit (CPU) in a server or electronic device in terms of hardware, or may be, for example, a related background service in a server or electronic device in terms of software, without limitation.

[0053] In addition, the "collection" in the embodiments of the present disclosure refers to the process of data collection that combines robotic process automation (RPA) and artificial intelligence (AI). That is to say, the data collection process is a fully automated data collection process, and the data collection process is also combined with artificial intelligence (AI) to achieve automated data collection in combination with methods in the field of natural language processing (NLP).

[0054] The present disclosure can be specifically applied to the field of natural language processing (NLP) of artificial intelligence AI, which is a field based on computer science, artificial intelligence, and linguistics that focuses on the interaction between computers and human (natural) language.

[0055] For example, in the embodiment of the present disclosure, based on the data collection process of full-process automation, the full-process automation can be implemented by using robotic process automation (RPA) to obtain files to be processed, using artificial intelligence (AI) to identify data to be reported from the files to be processed, and reporting the data to be reported to the data collection platform based on the data description information.

[0056] It should be noted that the collection and processing of relevant data information in the embodiments of the present disclosure are all carried out after authorization by relevant users, and the process complies with the provisions of relevant laws and regulations and does not violate public order and good customs.

[0057] like Figure 1 As shown, the data collection method combining RPA and AI includes:

[0058] S101: Use Robotic Process Automation (RPA) to obtain documents to be processed.

[0059] Among them, Robotic Process Automation (RPA) refers to the automatic execution of process tasks on computers according to rules through robot application software.

[0060] Among them, the file whose related data is to be reported and processed can be called a file to be processed. The file to be processed in the embodiment of the present disclosure can be a file containing various types of enterprise data to be reported, collected and counted. The file to be processed can have multiple file types, such as a table file, or a document file, etc., and there is no limitation on this.

[0061] That is to say, an application scenario in the embodiments of the present disclosure can be specifically, for example, using robotic process automation (RPA) to obtain a list of companies and related information in a region, using the acquired data information in the form of a file as a file to be processed, and then combining the data collection method of RPA and AI to automatically obtain the company information to be reported that meets the screening conditions from the data information involved in the file to be processed. Alternatively, the data collection method combining RPA and AI described in the embodiments of the present disclosure can also be applied to any other possible data collection scenarios, without limitation.

[0062] In the embodiment of the present disclosure, when using robotic process automation (RPA) to obtain files to be processed, a file collection interface can be pre-configured. In combination with the robotic process automation (RPA), the file collection interface can be used to scan the enterprise operation status-related files of various types of offline enterprises under the regulations according to the pre-set software operation process, and then the scanned electronic files that can be identified and read are used as files to be processed, without any restrictions.

[0063] In some other embodiments, a third-party data collection device may also be used, and a communication link between the execution subject of the embodiment of the present disclosure and the third-party data collection device may be established in advance. Based on the robotic process automation (RPA), files related to the operation status of various types of enterprises under the regulations collected by the third-party data collection device may be obtained, and then the collected electronic files that can be identified and read may be used as files to be processed. Alternatively, any other possible method based on robotic process automation (RPA) may be used to obtain files to be processed, and there is no limitation on this.

[0064] In the disclosed embodiments, the server may receive files to be processed uploaded by corporate users, and a specific folder may be set up to store the files to be processed. The specific folder may be checked to see whether there are files to be processed uploaded by corporate users. Alternatively, the files to be processed may be named in a specific format, and the server may receive the files, identify the file names, and determine and obtain the files to be processed. There are no restrictions on this.

[0065] S102: Using artificial intelligence AI to identify data to be reported from the files to be processed, wherein the data to be reported has corresponding data description information.

[0066] Among them, the data related to the enterprise operation to be reported to the data collection platform can be called data to be reported. The data to be reported can be directly identified from the data information involved in the file to be processed, or the data to be reported can be obtained by integrating the data information involved in the file to be processed, and the data to be reported can have corresponding data description information, and there is no restriction on this.

[0067] Among them, the data information that describes one or more relevant characteristics of the reported data can be called data description information. The data description information can be the data type, the enterprise to which the data belongs, the data name, the file type and name to which the data belongs, etc., and there is no limitation on this.

[0068] For example, if the data to be reported is enterprise operation data, the data description information may be the enterprise name, enterprise turnover, operation status of each department of the enterprise, etc.

[0069] In the embodiment of the present disclosure, artificial intelligence AI can be used to directly identify the data information involved in the file to be processed, or the data to be reported can be determined by integrating the data information involved in the file to be processed.

[0070] In the embodiments of the present disclosure, when artificial intelligence AI is used to identify the data to be reported from the files to be processed, the data to be reported can be identified from the files to be processed based on data analysis technology, or, a data recognition model can be constructed and trained through artificial intelligence AI, and the data to be reported can be identified from the files to be processed using the data recognition model, or, any other possible implementation method can be used to identify the data to be reported from the files to be processed, without limitation.

[0071] For example, the data description information corresponding to the data to be reported may include marking information for information identification. Image recognition technology and / or text recognition technology in artificial intelligence AI can be used in combination with the marking information to identify the data to be reported from the files to be processed. There is no limitation on this.

[0072] S103: Report the data to be reported to the data collection platform according to the data description information.

[0073] Among them, the data collection platform refers to a platform used to collect, integrate, display and back up data. The platform can be a cloud service platform, or it can be any other possible form of data collection system, etc., without limitation.

[0074] In the embodiments of the present disclosure, corresponding filtering conditions can be set to filter the data description information, and the data to be reported can be reported to the data collection platform based on the filtering results. Alternatively, the data to be reported can be classified according to the data description information, and the data to be reported can be reported to the data collection platform based on the classification results. There is no limitation on this.

[0075] Optionally, in some embodiments, a threshold value for the data description value can be set, the data description value corresponding to each type of data can be determined based on the data description information, the data that meets the threshold value can be screened as the data to be reported, and the data to be reported can be reported to the data collection platform without any restrictions.

[0076] For example, companies whose turnover does not exceed a certain amount and the corresponding company information can be set as data to be reported. Thus, a threshold value for filtering turnover can be set, such as not exceeding 20 million yuan, to filter out companies with a turnover below 20 million yuan, and report the company name and corresponding basic information as data to be reported to the data collection platform.

[0077] Optionally, in some other embodiments, a data classification method may be used to pre-set classification rules, process different data to be reported according to the classification rules, and report them to the data collection platform.

[0078] For example, enterprises can be divided into small and medium-sized enterprises, large enterprises, etc., and classified according to data description information such as turnover and number of employees, and the classified data can be reported to the data collection platform as data to be reported.

[0079] In the disclosed embodiment, for information security considerations, a verification code may be set for logging into the data collection platform. During the logging into the data collection platform, optical character recognition (OCR) technology may be used to automatically identify the verification code, thereby automating the login process.

[0080] In this embodiment, the files to be processed are obtained by using Robotic Process Automation (RPA), and Artificial Intelligence (AI) is used to identify the data to be reported from the files to be processed, wherein the data to be reported has corresponding data description information. According to the data description information, the data to be reported is reported to the data collection platform. Since data collection is performed using Robotic Process Automation (RPA) and Artificial Intelligence (AI), the efficiency and degree of automation of data collection can be effectively improved, the accuracy and convenience of data reporting can be effectively improved, and the resource consumption of data collection can be reduced.

[0081] Figure 2 It is a flowchart of a data collection method combining RPA and AI proposed in another embodiment of the present disclosure.

[0082] like Figure 2 As shown, the data collection method combining RPA and AI includes:

[0083] S201: Use Robotic Process Automation (RPA) to obtain the files to be processed.

[0084] S202: Using artificial intelligence AI to identify the data to be reported from the files to be processed, wherein the data to be reported has corresponding data description information.

[0085] The description of S201 - S202 can be specifically referred to the above embodiment, which will not be repeated here.

[0086] S203: Determine a data collection tag in the data collection platform according to the data description information, wherein the data collection tag corresponds to a data collection area.

[0087] Among them, a variety of data tags can be set in advance in the data collection platform to identify various types of data description information. The data tags can be called data collection tags. The data description information can be classified using data collection tags to facilitate the organization of data to be reported.

[0088] For example, the data collection label may be a company name label, a file type label, a file name label, etc., without limitation.

[0089] Among them, the area used to store data in the data collection platform can be called the data collection area, and the data collection label is matched with the data collection area to classify, store, and record the saved data to be reported.

[0090] In the disclosed embodiment, since the data to be reported has corresponding data description information, corresponding multiple data collection tags can be set according to the data description information, and the data collection tags can be made to correspond to the data collection areas.

[0091] In the disclosed embodiments, the name corresponding to the data collection label can be directly used as the name of the data collection area to achieve the correspondence between the data collection label and the data collection area. Alternatively, a multi-level data collection label can be set and used to classify, store, and record the data to be reported. While effectively improving the accuracy and convenience of data reporting, the classification, storage, and recording effects of the data to be reported are improved, so that data collection can be connected with the framework of the data collection platform, and the collected data can be adapted to the integrated framework in the data collection platform, thereby ensuring the automated collection effect of the data to be reported.

[0092] S204: Report the data to be reported to the data collection area.

[0093] In some embodiments, during the process of reporting the data to be reported to the data collection area, the data to be reported may be classified according to the data collection label, and the classified data to be reported may be reported to the corresponding data collection area.

[0094] In other embodiments, the data to be reported can be pre-classified and stored in multi-level folders according to the classification results. Corresponding folder names are set and used as data collection label names and data collection area names. After the data to be reported is reported to the data collection platform, the data collection platform identifies the folder name, configures the corresponding data collection area, and reports the data to be reported to the data collection area without any restrictions.

[0095] S205: Receive a reminder setting instruction, wherein the reminder setting instruction includes: characteristics of the data to be reminded.

[0096] It should be noted that, in the embodiment of the present disclosure, the execution order of the step “receiving a reminder setting instruction” and the execution order of the step “reporting the data to be reported to the data collection area” are not limited.

[0097] That is to say, the receiving reminder setting instruction can be triggered while the data to be reported is being reported to the data collection area, and there is no restriction on this.

[0098] Among them, the instruction information for reminding the corresponding subject based on the reported data related to the enterprise operation can be called the reminder setting instruction.

[0099] Among them, reminders are made based on data features of data related to enterprise operations, and the data features can be called data features to be reminded.

[0100] In the disclosed embodiment, the feature of the data to be reminded may be threshold information for filtering the data to be reported. The feature of the data to be reminded may be, for example, turnover, or may be the data format, data size, etc. of the data to be reported, and there is no limitation on this.

[0101] For example, if an enterprise whose annual turnover does not meet 20 million yuan needs to be reminded to report data, the instruction information used to initiate the reminder is the reminder setting instruction, and "annual turnover does not meet 20 million yuan" can be used as the data feature to be reminded.

[0102] In the embodiments of the present disclosure, the front end of the data acquisition platform can receive the data features to be reminded set by the user and send them to the back end, and the back end of the data acquisition platform can generate corresponding reminder setting instructions and perform corresponding reminder settings, wherein the front end of the data acquisition platform can be an interactive end that interacts with the user, such as an interactive interface, etc., and the back end can be a platform background for saving pre-processed data, thereby realizing the generation and reception of reminder setting instructions, and there is no restriction on this.

[0103] S206: Determine the subject information of the subject to which the data feature to be reminded belongs.

[0104] The subject to which the data feature to be reminded belongs is the subject described by the data feature to be reminded. For example, if the data feature to be reminded is turnover, the subject to which the turnover belongs may be the enterprise to which the turnover belongs.

[0105] Among them, the basic information corresponding to the subject to which the data feature to be reminded belongs can be called subject information. The subject information can include the basic information of the subject, including contact person, contact information, location information, etc., and there is no restriction on this.

[0106] In the disclosed embodiment, multiple subjects and subject information corresponding to the subjects may be pre-stored in the data collection platform, and after determining the subject to which the data feature to be reminded belongs, the subject information of the subject to which the data feature to be reminded belongs is determined. Alternatively, the subject and the subject information may be managed as data collection tags, and the subject and the subject information may be parsed from the data to be reported. After determining the subject to which the data feature to be reminded belongs, the corresponding subject information may be determined according to the data collection tag. Alternatively, any other possible implementation method may be used to determine the subject information of the subject to which the data feature to be reminded belongs, and there is no limitation to this.

[0107] S207: Based on the subject information, prompt the subject to report data in a timely manner.

[0108] In the disclosed embodiment, the prompting method of the subject can be parsed from the subject information to prompt the subject to report in time. Alternatively, an information prompting system can be set up to prompt the subject to report data in time according to the subject information. There is no limitation to this.

[0109] Optionally, in some embodiments, the reporting status of the subject is determined based on the subject information. If the reporting status indicates that the subject has not reported, the subject is prompted to report the data in a timely manner. Since the reporting status of the subject is determined in advance, the reported subjects can be accurately screened and the unreported subjects can be determined. The reporting situation of the subject can be accurately determined to prevent repeated reporting. At the same time, the resource occupation caused by repeated prompts can be effectively reduced, and the prompt efficiency can be effectively improved.

[0110] In other embodiments, when the reporting status indicates that the subject has been reported, the information related to the subject can be deleted from the subject information list, or the prompting step of the subject can be directly skipped, and there is no limitation on this.

[0111] The reporting status of the subject is the status corresponding to whether the subject has reported. The reporting status can be "not reported", "reported" and other types, and there is no restriction on this.

[0112] In the embodiments of the present disclosure, the reporting status of the subject is determined based on the subject information. A status identification identifier can be set and added to the subject information. The subject information is analyzed to determine the status identification identifier for identifying the reporting status of the subject. Alternatively, a corresponding status query tool can be set to query the reporting status of the subject. Alternatively, any other possible implementation method can be used to determine the reporting status of the subject, and there is no limitation on this.

[0113] In the disclosed embodiment, in order to prompt the subject to report the data in a timely manner, a variety of prompting methods such as SMS prompts, phone prompts, and email prompts can be used. The appropriate prompting method can be selected according to the prompting function of the data collection platform combined with the subject information, so that the selection of the prompting method has flexibility and applicability, and the prompting efficiency is effectively improved. In some application scenarios, the data collection platform can also obtain the data to be reported in advance, report the data to be reported to the data collection area, and then trigger the receipt of the reminder setting instruction, determine the subject information of the subject to which the data feature to be reminded belongs, screen the subject information, and prompt the subject to report the data in a timely manner according to the screening results. There is no restriction on this.

[0114] In this embodiment, since robotic process automation RPA and artificial intelligence AI are used for data collection, the efficiency and automation of data collection can be effectively improved, the accuracy and convenience of data reporting can be effectively improved, and the resource consumption of data collection can be reduced. Since the data collection labels in the data collection platform are determined according to the data description information, various types of data in the data collection platform can be labeled, and the data to be reported can be effectively classified. Since the data to be reported is reported to the data collection area, the data sorting effect can be improved, making data collection more organized and enhancing the convenience of data collection. By receiving the reminder setting instruction, the subject of the subject to which the data feature to be reminded belongs is determined Information, based on the subject information, prompts the subject to report the data in time. Since the subject information is determined and the subject is prompted to report the data in time, the prompting of the subject can be more convenient and effective, and resource consumption can be effectively reduced. Using the data collection platform to determine the subject to be reported can effectively reduce the misreporting and omissions caused by human factors, effectively improve the accuracy of subject determination, and enhance the degree of automation of data collection and subject prompts. Since the reporting status of the subject is determined in advance, the reported subjects can be accurately screened and the unreported subjects can be determined. The reporting status of the subject can be accurately determined to prevent repeated reporting, while effectively reducing the resource occupation caused by repeated prompts and effectively improving the prompt efficiency.

[0115] Figure 3 It is a flowchart of a data collection method combining RPA and AI proposed in another embodiment of the present disclosure.

[0116] like Figure 3 As shown, the data collection method combining RPA and AI includes:

[0117] S301: Use Robotic Process Automation (RPA) to obtain the files to be processed.

[0118] S302: Artificial intelligence AI is used to identify the data to be reported from the files to be processed, wherein the data to be reported has corresponding data description information.

[0119] S303: Report the data to be reported to the data collection platform according to the data description information.

[0120] S304: Receive a reminder setting instruction, wherein the reminder setting instruction includes: characteristics of data to be reminded.

[0121] S305: Determine the subject information of the subject to which the data feature to be reminded belongs.

[0122] The description of S301 - S305 can be specifically referred to the above embodiment, which will not be repeated here.

[0123] S306: Determine the reporting status of the subject according to the subject information.

[0124] In the disclosed embodiment, the reporting status of the subject is determined based on the subject information. The reporting status of the subject can be saved in the data collection platform and updated in real time. After determining the subject information, the data collection platform queries the reporting status of the subject to which the subject information belongs. Alternatively, the information corresponding to the reporting status can be saved in the subject information. The reporting status of the subject can be determined based on the data information related to the reporting status of the subject in the parsed subject information. There is no restriction on this.

[0125] For example, the subject information corresponding to the reported subject includes information corresponding to the reporting status, such as turnover, etc. If the subject has been reported, the subject information includes the turnover content. If the subject has not been reported, the subject information does not include the turnover content. Therefore, the reporting status of the subject is determined based on whether the subject information contains the turnover content.

[0126] For example, corresponding reporting status information may also be set in the main information, such as "reporting status: reported", and then the main information is parsed to determine the corresponding reporting status.

[0127] S307: If the reporting status indicates that the subject has not reported, a subject information list is generated according to the subject information.

[0128] The subject information list is a data list used to store the subject information of unreported subjects.

[0129] For example, Figure 4 As shown, Figure 4 This is a schematic diagram of a subject information list proposed in another embodiment of the present disclosure. In the collection direct management folder, a subject information table for storing subject information, a reporting data processing table for storing data to be reported, and an information summary execution table for processing and summarizing subject information are added. If the reporting status indicates that the subject has not been reported, the corresponding subject information can be added to the subject information table to facilitate subsequent reading of the subject information in the subject information table and prompt the subject to which it belongs.

[0130] In the disclosed embodiments, the subject information may be arranged in a format such as a table or a document to prompt the subject to report the data in a timely manner. Alternatively, a subject information processing system may be built to process the subject information and prompt the subject to report the data in a timely manner. Alternatively, data processing may be used to filter the subject information corresponding to the subject to be reported from the subject information and prompt the subject to report the data in a timely manner. There is no limitation on this.

[0131] S308: In response to confirmation of the subject information in the subject information list, start the information transmission platform.

[0132] Among them, the information transmission platform is a platform for organizing and transmitting prompt information. Different information transmission platforms can be selected according to the type of prompt method, or multiple types of prompt methods can be integrated into the same information transmission platform. There is no restriction on this.

[0133] In the disclosed embodiment, the information transmission platform may include various controls such as an information transmission address writing control, a prompt message writing control, and a message transmission control.

[0134] Among them, the information transmission address writing control is a control used to write the information transmission address. The information transmission address is the transmission address corresponding to the electronic device on the subject side. Telephone numbers, email addresses and real addresses can all be used as information transmission addresses, and there is no restriction on this.

[0135] Among them, the prompt message writing control is a control used to write prompt messages. A prompt message template can be generated in advance, and the main body information is brought into the prompt message generated in the message template. There is no restriction on this.

[0136] Among them, the message transmission control is a control used to transmit prompt messages to the information transmission address. The transmission methods include but are not limited to sending text messages, broadcasting voice calls, sending emails, etc., and there is no restriction on this.

[0137] In the disclosed embodiment, after determining the subject information list corresponding to the unreported subject, the information transmission platform can be triggered to start, and the information transmission platform can be used to transmit a prompt message to the unreported subject listed in the subject information list.

[0138] In the embodiment of the present disclosure, after confirming the subject information list, the data collection platform can generate a start instruction and send the start instruction to the information transmission platform. In response to the start instruction, the information transmission platform is automatically started, and there is no limitation on this.

[0139] In some embodiments, for information security considerations, a startup verification method can be set during the process of starting the information transmission platform, such as verifying an account password or verifying a QR code, etc. At this time, optical character recognition (OCR) technology can be used to automatically identify the verification code or verify the QR code, etc., so that the login process can be automated.

[0140] S309: Acquire the information transmission address of the electronic device on the subject side according to the subject information.

[0141] Among them, the main-side electronic device is the electronic device corresponding to the information transmission address.

[0142] In the embodiment of the present disclosure, the electronic device on the subject side may be an electronic device corresponding to the information transmission address saved in the subject information. If the information transmission address contained in the subject information is a telephone number, then the electronic device on the subject side is the corresponding telephone or mobile phone. If the information transmission address contained in the subject information is an email address number, then the electronic device on the subject side is the corresponding email address, etc. There is no limitation on this.

[0143] In the disclosed embodiment, the subject information can be parsed to directly determine the information transmission address of the electronic device on the subject side, or the subject information list can be retrieved to determine the information transmission address of the electronic device on the subject side from the subject information list, without limitation.

[0144] S310: Write the information transmission address into the information transmission address write control.

[0145] Among them, the information transmission address write control is a control used to receive and save the written information transmission address. The information transmission address is the transmission address corresponding to the electronic device on the subject side. Telephone numbers, email addresses and real addresses can all be used as information transmission addresses, and there is no restriction on this.

[0146] In the embodiment of the present disclosure, the information transmission address is written into the information transmission address write control, the information transmission address can be corresponded to the identifier of the electronic device on the main side, a document file, or a file format such as a table file is generated, and the file is written into the information transmission address write control according to the form of the document or table, or the information transmission address can be directly determined and written into the information transmission address write control, and there is no limitation on this.

[0147] For example, Figure 5 As shown, Figure 5It is a schematic diagram of the information transmission address writing control interface proposed in another embodiment of the present disclosure. The information transmission address writing control is automatically opened, and the search bar is located. The information transmission address can be automatically identified and written in the search bar. Click the icon at the back to confirm the transmission of prompt information to the information transmission address. Alternatively, the subject identification identifier (such as a company name, etc.) can be written, and the subject identification identifier can be determined to determine the corresponding information transmission address (such as a mobile phone number or an email address, etc.).

[0148] S311: Generate a reporting prompt message based on the subject information.

[0149] For the description of S311, please refer to the above embodiment, which will not be repeated here.

[0150] S312: Write the reporting prompt message into the prompt message writing control.

[0151] Among them, the prompt message writing control is a control used to write and adjust the reporting prompt message. The prompt message template can be pre-generated to bring the main information into the prompt message generated in the message template, and there is no restriction on this.

[0152] In the disclosed embodiment, a fixed-format reporting prompt message can be used and directly written into the prompt message writing control. Alternatively, the reporting prompt message can be templated and the relevant information can be automatically filled in the template to complete the compilation of the reporting prompt message, and the compiled reporting prompt message can be written into the prompt message writing control. There is no limitation on this.

[0153] For example, Figure 6 As shown, Figure 6 This is a schematic diagram of a prompt message writing control interface proposed in another embodiment of the present disclosure. The reporting prompt message is automatically entered in the dialog box. The confirmation and transmission of the reporting prompt message can be completed by clicking the "Send" button, and the reporting prompt message can be transmitted to the information transmission platform.

[0154] S313: Transmit the reporting prompt message to the electronic device of the subject via the information transmission platform.

[0155] In the embodiment of the present disclosure, a control can be used to receive a reporting prompt message, and the reporting prompt message can be transmitted to the electronic device on the subject side via the information transmission platform. Alternatively, a message transmission system or a message transmission application can be set up and connected to the information transmission platform. When it is detected that a reporting prompt message needs to be transmitted, the reporting prompt message can be transmitted to the electronic device on the subject side via the information transmission platform. There is no restriction on this.

[0156] Optionally, in response to triggering the message transmission control, the report prompt message is transmitted to the electronic device on the subject side via the information transmission platform. Since the report prompt message is transmitted to the electronic device on the subject side via the information transmission platform using the message transmission control, the report prompt message can be automatically transmitted, thereby improving the message transmission efficiency. The setting of the message transmission control facilitates the management and transmission of the report prompt message, thereby improving the flexibility of information transmission.

[0157] Among them, the message transmission control is a control used to transmit the reporting prompt message.

[0158] In the disclosed embodiment, the message transmission control can query the status of the reporting prompt message in real time. When a reporting prompt message transmission is detected, the reporting prompt message and the information transmission address are received, and the reporting prompt message is transmitted to the electronic device on the subject side corresponding to the information transmission address. Alternatively, the information transmission platform can generate instruction information that needs to be reported and send the instruction information to the message transmission control. The message transmission control responds to the instruction information, determines the reporting prompt message to be transmitted and the corresponding information transmission address, and transmits the reporting prompt message to the electronic device on the subject side via the information transmission platform. There is no restriction on this.

[0159] In this embodiment, since data collection is performed using Robotic Process Automation (RPA) and Artificial Intelligence (AI), the efficiency and automation of data collection can be effectively improved, the accuracy and convenience of data reporting can be effectively improved, and the resource consumption of data collection can be reduced. Since the subject information is determined and the subject is prompted to report the data in a timely manner, the subject does not need to be manually determined, which effectively reduces the consumption of human resources and time costs. The subject to be reported is determined by the platform, which can effectively reduce the misreporting and omission caused by human factors, and effectively improve the accuracy of subject determination. Since the reporting status of the subject is determined in advance, the reported subjects can be screened and the unreported subjects can be determined, which can effectively prevent duplicate reporting, improve the accuracy of subject prompts, and effectively reduce the resource occupation caused by duplicate prompts, and improve data collection efficiency. Since the subject information list is used to arrange multiple subject information to be reported, the orderliness of subject information reporting can be effectively improved. The subject information list can also arrange unreported subjects and subject information, which is convenient for managing subject information and enhancing information management. Management efficiency is improved, and the occurrence of repeated reporting or missed reporting is effectively prevented. Since the information transmission platform is used, the reporting prompt message is transmitted to the electronic device on the subject side via the information transmission platform, and the reporting prompt message can be sorted and transmitted, thereby improving the efficiency of information transmission and enhancing the effect of information transmission. It is ensured that the reporting prompt message can be stably and quickly automatically transmitted to the electronic device on the subject side. Since the information transmission address writing control is used, the information transmission address can be received and sorted, which is convenient for the management of the information transmission address, and the convenience of information transmission address management is effectively improved. Since the prompt message writing control is used, the reporting prompt message can be flexibly edited, and the reporting prompt message can be personalized according to the subject information, effectively improving the diversity and flexibility of data transmission. Since the message transmission control is used to transmit the reporting prompt message to the electronic device on the subject side via the information transmission platform, the reporting prompt message can be automatically transmitted, and the message transmission efficiency is improved. The setting of the message transmission control facilitates the management and transmission of the reporting prompt message, and improves the flexibility of information transmission.

[0160] In summary, if Figure 7 As shown, Figure 7This is a schematic diagram of the data collection platform selection interface proposed in another embodiment of the present disclosure. After reporting the reporting prompt message to the information transmission platform, the information transmission platform can call the selection interface to facilitate the user to use appropriate conditions to filter the subject information to be prompted. The selection interface can be used as a schematic diagram of a web page interface, or it can also be used as a schematic diagram of an application program interface. In the selection interface, the condition type selection box can be used as a filter box for related conditions, such as revenue value, output value, etc., without restriction. The time range selection box can set the time filter range, which can conveniently select the appropriate object for the time range. The subject type selection box can set a variety of subject types for more accurate search and statistics. The custom selection box can customize the filter conditions to meet the diversity and flexibility of filtering.

[0161] In summary, if Figure 8 As shown, Figure 8 is a schematic diagram of a statistical interface of a data collection platform proposed in another embodiment of the present disclosure, comprising Figure 7 The multiple subjects selected in the interface can generate a list of subjects to be prompted, and the statistical interface can be used as an interface for statistically displaying the subject information to be prompted, wherein the subject name box is used to list the subjects to be prompted, and the report element box can list the relevant data information of the subject, such as the subject type, etc. The corresponding indicators and filtering conditions can be set in the indicator box and the filter condition box for further filtering, and a variety of mathematical operators can be added in the operator box to facilitate the calculation of data information such as indicators and filtering conditions. After processing, a list of subject information that can be exported is obtained, and an export key can be set for export. The exported subject information list can be automatically combined with the information transmission platform to transmit prompt information to the subjects in the list.

[0162] Fig. 9 It is a structural diagram of a data collection device combining RPA and AI proposed in one embodiment of the present disclosure.

[0163] like Fig. 9 As shown, the data collection device 90 combining RPA and AI includes:

[0164] A first acquisition module 901 is used to acquire a file to be processed by using Robotic Process Automation (RPA);

[0165] An identification module 902 is used to identify the data to be reported from the to-be-processed file using artificial intelligence AI, wherein the data to be reported has corresponding data description information;

[0166] The reporting module 903 is used to report the data to be reported to the data collection platform according to the data description information.

[0167] In some embodiments of the present disclosure, Fig.10 As shown, Fig.10 90 is a schematic diagram of a data collection device combining RPA and AI proposed in another embodiment of the present disclosure, wherein the reporting module 903 is specifically used for:

[0168] Determine the data collection label in the data collection platform according to the data description information, wherein the data collection label corresponds to the data collection area;

[0169] According to the data collection label, the data to be reported is reported to the data collection area.

[0170] In some embodiments of the present disclosure, Fig.10 As shown, the device also includes:

[0171] The receiving module 904 is used to receive a reminder setting instruction, wherein the reminder setting instruction includes: characteristics of the data to be reminded;

[0172] A determination module 905 is used to determine the subject information of the subject to which the data feature to be reminded belongs;

[0173] The prompt module 906 is used to prompt the subject to report data in time according to the subject information.

[0174] In some embodiments of the present disclosure, Fig.10 As shown, the prompt module 906 is specifically used for:

[0175] Determine the reporting status of the subject according to the subject information;

[0176] When the reporting status indicates that the subject has not reported, the subject is prompted to report the data in time.

[0177] In some embodiments of the present disclosure, Fig.10 As shown, the prompt module 906 is specifically used for:

[0178] When the reporting status indicates that the subject has not reported, a subject information list is generated according to the subject information;

[0179] In response to confirmation of the subject information in the subject information list, the subject is prompted to report data in a timely manner.

[0180] In some embodiments of the present disclosure, Fig.10 As shown, the prompt module 906 is specifically used for:

[0181] In response to confirmation of the subject information in the subject information list, starting the information transmission platform;

[0182] Generate a reporting prompt message based on the subject information;

[0183] The reporting prompt message is transmitted to the electronic device of the subject via the information transmission platform.

[0184] In some embodiments of the present disclosure, Fig.10 As shown, the information transmission platform includes: an information transmission address writing control;

[0185] The device further comprises:

[0186] The second acquisition module 907 is used to acquire the information transmission address of the subject-side electronic device according to the subject information after starting the information transmission platform in response to the confirmation of the subject information in the subject information list;

[0187] The first writing module 908 is used to write the information transmission address into the information transmission address writing control.

[0188] In some embodiments of the present disclosure, Fig.10 As shown, the information transmission platform includes: a prompt message writing control;

[0189] The device further comprises:

[0190] The second writing module 909 is used to write the reporting prompt message into the prompt message writing control after generating the reporting prompt message according to the subject information.

[0191] In some embodiments of the present disclosure, Fig.10 As shown, the information transmission platform includes: a message transmission control;

[0192] The prompt module 906 is specifically used for:

[0193] In response to triggering the message transmission control, the reporting prompt message is transmitted to the electronic device on the subject side via the information transmission platform.

[0194] With the above Figures 1 to 8 Corresponding to the data collection method combining RPA and AI provided in the embodiment, the present disclosure also provides a data collection device combining RPA and AI. Figures 1 to 8 The data collection method combining RPA and AI provided in the embodiment corresponds to each other, so the implementation method of the data collection method combining RPA and AI is also applicable to the data collection device combining RPA and AI provided in the embodiment of the present disclosure, and will not be described in detail in the embodiment of the present disclosure.

[0195] The functions of each module in each device in the embodiments of the present disclosure can be found in the corresponding description in the above method, and will not be repeated here.

[0196] In this embodiment, the files to be processed are obtained by using Robotic Process Automation (RPA), and Artificial Intelligence (AI) is used to identify the data to be reported from the files to be processed, wherein the data to be reported has corresponding data description information. According to the data description information, the data to be reported is reported to the data collection platform. Since data collection is performed using Robotic Process Automation (RPA) and Artificial Intelligence (AI), the efficiency and degree of automation of data collection can be effectively improved, the accuracy and convenience of data reporting can be effectively improved, and the resource consumption of data collection can be reduced.

[0197] Fig.11 FIG. 1 is a block diagram showing a structure of an electronic device according to an embodiment of the present disclosure. Fig.11 As shown, the electronic device 110 includes: a memory 1110 and a processor 1120, and the memory 1110 stores a computer program that can be run on the processor 1120. When the processor 1120 executes the computer program, the data collection method combining RPA and AI in the above embodiment is implemented. The number of the memory 1110 and the processor 1120 can be one or more.

[0198] The electronic device 110 further includes:

[0199] The communication interface 1130 is used to communicate with external devices and perform data exchange transmission.

[0200] If the memory 1110, the processor 1120 and the communication interface 1130 are implemented independently, the memory 1110, the processor 1120 and the communication interface 1130 can be connected to each other through a bus and communicate with each other. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Fig.11 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0201] Optionally, in a specific implementation, if the memory 1110, the processor 1120 and the communication interface 1130 are integrated on a chip, the memory 1110, the processor 1120 and the communication interface 1130 can communicate with each other through an internal interface.

[0202] An embodiment of the present disclosure provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the data collection method combining RPA and AI provided in an embodiment of the present disclosure.

[0203] An embodiment of the present disclosure also provides a chip, which includes a processor for calling and executing instructions stored in the memory from the memory, so that a communication device equipped with the chip executes the data collection method combining RPA and AI provided by an embodiment of the present disclosure.

[0204] The embodiment of the present disclosure also provides a chip, including: an input interface, an output interface, a processor and a memory. The input interface, the output interface, the processor and the memory are connected through an internal connection path. The processor is used to execute the code in the memory. When the code is executed, the processor is used to execute the data collection method combining RPA and AI provided in the embodiment of the application.

[0205] It should be understood that the processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc. It is worth noting that the processor may be a processor supporting the Advanced RISC Machines (ARM) architecture.

[0206] Further, optionally, the above-mentioned memory may include a read-only memory and a random access memory, and may also include a non-volatile random access memory. The memory may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memories. Among them, the non-volatile memory may include a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory may include a random access memory (RAM), which is used as an external cache. By way of example but not limitation, many forms of RAM are available. For example, static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM) and direct memory bus random access memory (DR RAM).

[0207] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function according to the present disclosure is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium.

[0208] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present disclosure. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, unless they are contradictory.

[0209] It should be noted that, in the description of the present disclosure, the terms "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or implying relative importance. In addition, in the description of the present disclosure, unless otherwise specified, the meaning of "plurality" is two or more.

[0210] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, segment or portion of code that includes one or more executable instructions for implementing the steps of a specific logical function or process, and the scope of the preferred embodiments of the present disclosure includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in the reverse order depending on the functions involved, which should be understood by those skilled in the art to which the embodiments of the present disclosure belong.

[0211] It should be understood that the various parts of the present disclosure can be implemented in hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0212] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

[0213] In addition, each functional unit in each embodiment of the present disclosure may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0214] The storage medium mentioned above can be a read-only memory, a magnetic disk or an optical disk, etc.

[0215] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present disclosure. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0216] Although the embodiments of the present disclosure have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations of the present disclosure. A person skilled in the art may change, modify, replace and vary the above embodiments within the scope of the present disclosure.

Claims

1. A data collection method combining RPA and AI, characterized in that: include: Use Robotic Process Automation (RPA) to obtain documents to be processed; Using artificial intelligence AI to identify the data to be reported from the file to be processed, wherein the data to be reported has corresponding data description information; According to the data description information, the data to be reported is reported to the data collection platform; The method further comprises: Receiving a reminder setting instruction, wherein the reminder setting instruction includes: characteristics of data to be reminded; Determine the subject information of the subject to which the data feature to be reminded belongs, the subject information includes contact person, contact information, and location information; Determine the reporting status of the subject according to the subject information; If the reporting status indicates that the subject has not reported, generating a subject information list according to the subject information; In response to confirmation of the subject information in the subject information list, starting an information transmission platform; Generate a reporting prompt message according to the subject information; The reporting prompt message is transmitted to the electronic device on the subject side via the information transmission platform.

2. The method according to claim 1, characterized in that The step of reporting the data to be reported to the data collection platform according to the data description information includes: Determine a data collection tag in the data collection platform according to the data description information, wherein the data collection tag corresponds to a data collection area; According to the data collection tag, the data to be reported is reported to the data collection area.

3. The method according to claim 1, characterized in that The information transmission platform includes: an information transmission address writing control; Wherein, after the information transmission platform is started in response to the confirmation of the subject information in the subject information list, the method further includes: According to the subject information, obtaining the information transmission address of the electronic device on the subject side; The information transmission address is written into the information transmission address write control.

4. The method according to claim 1, characterized in that The information transmission platform includes: a prompt message writing control; Wherein, after generating the reporting prompt message according to the subject information, the method further includes: The reporting prompt message is written into the prompt message writing control.

5. The method according to claim 1, characterized in that The information transmission platform includes: a message transmission control; The step of transmitting the reporting prompt message to the electronic device on the subject side via the information transmission platform includes: In response to triggering the message transmission control, the reporting prompt message is transmitted to the electronic device on the subject side via the information transmission platform.

6. A data collection device combining RPA and AI, characterized in that: include: A first acquisition module is used to acquire the to-be-processed file by using Robotic Process Automation (RPA); An identification module, used for identifying the data to be reported from the to-be-processed file using artificial intelligence AI, wherein the data to be reported has corresponding data description information; A reporting module, used for reporting the data to be reported to a data collection platform according to the data description information; The device is also used for: Receiving a reminder setting instruction, wherein the reminder setting instruction includes: characteristics of data to be reminded; Determine the subject information of the subject to which the data feature to be reminded belongs, the subject information includes contact person, contact information, and location information; Determine the reporting status of the subject according to the subject information; If the reporting status indicates that the subject has not reported, generating a subject information list according to the subject information; In response to confirmation of the subject information in the subject information list, starting an information transmission platform; Generate a reporting prompt message according to the subject information; The reporting prompt message is transmitted to the electronic device on the subject side via the information transmission platform.

7. An electronic device, characterized in that: include: at least one processor and memory; The memory stores computer-executable instructions; The at least one processor executes the computer-executable instructions stored in the memory, so that the at least one processor executes the data collection method combining RPA and AI as described in any one of claims 1-5.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions. When the processor executes the computer-executable instructions, the data collection method combining RPA and AI as described in any one of claims 1 to 5 is implemented.

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