A data collection method, apparatus, device, and storage medium

Abstract

This invention discloses a data collection method, apparatus, device, and storage medium, comprising: sending different data collection sub-tasks for the same data collection template to each reporting object according to data collection needs; receiving the data filling results of each reporting object for the matched data collection sub-tasks; summarizing the data filling results to obtain the completed data collection template, and displaying the completed data collection template to all task issuers. By automatically dispatching data collection sub-tasks to different reporting objects based on the identification of data collection needs, each reporting object can only fill in and view the data collection sub-tasks assigned to it. While filling in data online, the filling results of different reporting objects are isolated, ensuring data security. The data filling results are summarized and viewed on the task issuer's side, thereby achieving automatic data integration and summarization, improving the security and efficiency of the data collection process.

Description

Technical Field

[0001] This invention relates to the field of big data technology, and in particular to a data collection method, apparatus, device, and storage medium. Background Technology

[0002] In daily operations, there are numerous data collection needs, both scheduled and unplanned. These needs come from diverse sources, take various forms, cover a wide range of objects, and involve a broad scope of data. Different data collection plans often overlap and contain intersecting data. Furthermore, the timeliness, accuracy, and consistency requirements of these tasks are high, data verification is complex, and there are stringent data sensitivity requirements.

[0003] Currently, enterprises often use offline task templates to collect and manually summarize data in their data collection and management work and data processes. However, this data collection method not only increases labor costs but is also inefficient. On the other hand, online data collection methods pose the risk of data leakage and data security risks for data with high confidentiality requirements. Therefore, the existing data collection methods cannot meet the requirements of efficiency and security. Summary of the Invention

[0004] This invention provides a data collection method, apparatus, device, and storage medium to achieve secure and efficient data collection.

[0005] According to one aspect of the present invention, a data collection method is provided, comprising: receiving a data collection request sent by a task issuer, and sending different data collection sub-tasks for the same data collection template to each reporting object according to the data collection request, wherein the data collection request includes an identifier of the data collection template;

[0006] Receive the data entry results of each of the data entry objects for the matched data collection subtask, wherein each data entry object only has viewing permission for its own data entry results;

[0007] The data entry results are summarized to obtain the completed data collection template, and the completed data collection template is displayed to all the task issuers.

[0008] According to another aspect of the present invention, a data collection apparatus is provided, comprising: a data collection subtask sending module, configured to receive a data collection request sent by a task issuer, and send different data collection subtasks for the same data collection template to each reporting object according to the data collection request, wherein the data collection request includes an identifier of the data collection template;

[0009] The data entry result receiving module is used to receive the data entry results of each entry object for the matched data collection subtask, wherein each entry object only has viewing permission for its own data entry results;

[0010] The data display module is used to summarize the data entry results to obtain the completed data collection template, and then display the completed data collection template to all the task issuers.

[0011] According to another aspect of the present invention, a terminal device is provided, characterized in that the terminal device comprises:

[0012] One or more processors;

[0013] Storage device for storing one or more programs.

[0014] When the one or more programs are executed by the one or more processors, the one or more processors perform the method described in any embodiment of the present invention.

[0015] According to another aspect of the present invention, a storage medium for computer-executable instructions is provided, on which a computer program is stored, which, when executed by a processor, implements the method as described in any of the embodiments of the present invention.

[0016] The technical solution of this invention automatically dispatches data collection sub-tasks to different reporting objects by identifying data collection needs. Each reporting object can only fill in and view the data collection sub-tasks assigned to it. While filling in data online, the filling results of different reporting objects are isolated to ensure data security. The data filling results are summarized and viewed on the task issuer's side, thereby realizing automatic data integration and summarization, and improving the security and efficiency of the data collection process.

[0017] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a flowchart of a data collection method provided according to Embodiment 1 of the present invention;

[0020] Figure 2 This is a schematic diagram illustrating an application scenario of the data collection method provided in Embodiment 1 of the present invention;

[0021] Figure 3 This is a flowchart of a data collection method provided according to Embodiment 2 of the present invention;

[0022] Figure 4 This is a schematic diagram of the structure of a data collection device according to Embodiment 3 of the present invention;

[0023] Figure 5 This invention provides a structural block diagram of a terminal device. Detailed Implementation

[0024] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0025] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, apparatus, product, or terminal device that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or terminal devices.

[0026] Example 1

[0027] Figure 1 This is a flowchart illustrating a data collection method provided in an embodiment of the present invention. This embodiment is applicable to online data collection. The method can be executed by a data collection device, which can be implemented in hardware and / or software, and can be integrated into a terminal device. Figure 1 As shown, the method includes:

[0028] Step S101: Receive the data collection request sent by the task issuer, and send different data collection sub-tasks for the same data collection template to each reporting object according to the data collection request.

[0029] Optionally, based on data collection needs, different data collection sub-tasks targeting the same data collection template can be sent to each reporting object, including: querying and obtaining the data collection template to be filled in based on the identifier of the data collection template, and uploading it as online based on the data collection template; generating data collection sub-tasks for the reporting object based on the reporting elements to be filled in; and sending the data collection sub-tasks to the matching reporting objects according to the collection frequency.

[0030] Among them, such as Figure 2 The diagram illustrates an application scenario for this implementation method. Online data collection primarily involves planned tasks, subtask assignment to designated objects, and task assigners revising content. This process also involves an online document permission isolation rule engine and an online collaborative big data similarity prediction analysis model. This implementation is merely illustrative and does not limit the specific operations involved in the application scenario. This implementation mainly addresses daily data collection needs. By automatically identifying data collection requirements and automatically assigning tasks to reporting objects, it supports online collaborative reporting with data isolation. This not only improves data aggregation efficiency but also reduces data permission security issues. Furthermore, for multiple tasks, a pre-configured similarity prediction analysis model further verifies the reported data and automatically pushes reminders, thereby better meeting the requirements of collection timeliness and security.

[0031] Specifically, this implementation receives data collection requests from the task issuer. These requests include information such as the data collection template identifier, the target audience, the required data elements, and the collection frequency. This is merely an example and does not limit the specific content of the data collection requests. Different formats of data collection templates, such as Excel or Word documents, are stored locally, each with a unique identifier. The implementation retrieves the required template based on these identifiers, parses the template, and uploads it to an online state. The online data collection template includes multiple fields (elements). Currently, each field does not contain a specific value; therefore, the specific value for each field must be collected and entered by the target audience.

[0032] It should be noted that in this embodiment, data collection sub-tasks are created according to data collection requirements. Specifically, basic task information is saved to a task information table, and linked to a template table through the identifier of the data collection template. The task information of the reporting objects that need to be filled in is saved to a reporting object task relationship table. This table records the correspondence between reporting objects and reporting elements, with each reporting object corresponding to a different task identifier, which is linked to the task information table. Therefore, in this embodiment, data collection sub-tasks for each reporting object are generated based on the information recorded in various tables, and these sub-tasks are sent to the matching reporting objects according to their collection frequency. For example, reporting object 1 receives data collection sub-task a and needs to fill in the data corresponding to element X1; reporting object 2 receives data collection sub-task b and needs to fill in the data corresponding to element X2. Of course, this embodiment is merely an example and does not limit the specific content of the reporting elements that each reporting object needs to fill in. Therefore, in this implementation, data collection subtasks will be created for the reporting objects according to the distribution frequency and data collection needs, and data permission isolation will be supported for different reporting objects. The reporting objects here can be enterprise departments, and different employees under the same reporting object can collaborate online to fill in the data.

[0033] Optionally, after querying and obtaining the data collection template to be filled in based on the identifier of the data collection template, the method further includes: checking whether the data collection template contains filling elements; if it is determined that there are no filling elements, then filling elements are added to the data collection template.

[0034] It should be noted that in this embodiment, after obtaining the data collection template based on the identifier, it checks whether the data collection template contains the reporting element specified by the task issuer. If it is determined that the reporting element does not exist, for example, if reporting object 1 is required to report element X1, but X1 is not in the data collection template, then reporting element X1 needs to be added to the data collection template to meet the data collection requirements proposed by the task issuer. Of course, this embodiment is only an example and does not limit the specific content of the reporting element that needs to be added.

[0035] Step S102: Receive the data entry results of each data entry object for the matched data collection subtask.

[0036] Optionally, the system receives the data entry results of each reporting object for the matched data collection sub-task, including: querying the historical reporting tasks for each reporting object and calculating the similarity results between the historical reporting tasks and the data collection sub-task; displaying the similarity results to the reporting object and receiving the data entry results determined by the reporting object based on the similarity results.

[0037] Optionally, receiving the data entry result determined by the similarity result of the object to be entered includes: when the similarity result meets the preset requirements, determining whether a data migration instruction has been received; if so, taking the historical data corresponding to the historical data entry task as the data entry result; otherwise, obtaining the manually entered data of the object to be entered and taking the manually entered data as the data entry result.

[0038] Specifically, in this embodiment, when each reporting object fills in data for the matched data collection sub-task, in order to avoid filling in a large amount of duplicate data, historical data collected in previous reporting tasks can be used. That is, if the same data has been collected in previous reporting tasks, it can be used directly without repeated collection, thereby avoiding a large amount of repetitive work. For example, if reporting object 1 receives data collection sub-task a, requiring reporting object 1 to fill in element X1, then the system will query the previous historical reporting tasks of reporting object 1, calculate the similarity results between the historical reporting tasks and the currently received data collection sub-task, and display the similarity results to the reporting object so that the reporting object can know whether similar data has been filled in before. The reporting object can determine whether to use manual filling or directly use historical data based on the displayed similarity results. For example, if the similarity result does not meet the preset requirements, it means that no data similar to the current task has been submitted before. In this case, manual collection and submission are used. If the similarity result meets the preset requirements, it means that data similar to the current task has been submitted before. In this case, the submitting object can decide whether to use historical data. When a data migration instruction is received from the submitting object, the historical data corresponding to the historical data submission task is directly used as the data submission result. However, if the submitting object feels that the historical data is outdated and needs the latest data, it can continue to use manual search and submission.

[0039] It should be noted that this implementation uses a big data similarity prediction and analysis model to obtain similarity results. This model utilizes big data technology to perform similarity analysis and prediction based on data domain relationships. In this big data similarity prediction and analysis, particularly for the accuracy of text numerical vector conversion and text semantic analysis, a self-attention mechanism framework is used to perform data similarity calculations and bias prediction analysis based on the similarity calculation results. Specifically, this implementation uses BERT for Chinese corpus processing, including word segmentation, part-of-speech tagging, named entity recognition, and stop word removal. Text-to-numerical vectorization involves word vectorization, sentence vectorization, and document vectorization. Word vectorization refers to word embedding, which uses a pre-trained Word2Vec model on a public corpus to map each word to a high-dimensional real-valued vector. These vectors have semantically related cosine similarities. Sentence vectorization refers to the self-attention mechanism generating sentence representations by performing self-attention calculations on each word in the sentence. To address the limitations of local or preceding contextual information in sequence data, the self-attention mechanism allows the model to observe all words in the input sequence and generate a context-aware representation for each word. Document vectorization refers to the document topic model generating a document representation by capturing the topic distribution within the document. Adding a hierarchical model, which extends Word2Vec through Doc2Vec, allows for the generation of a vector representation of the entire document. Finally, a weighted algorithm is used to weight the document topic model and the hierarchical model to generate the final document vectorization. Of course, this implementation is merely illustrative and does not limit the specific vector form used in the similarity prediction process.

[0040] Optionally, obtaining manually entered data for the object to be entered includes: identifying all users included under the object to be entered, and receiving collaborative entry instructions from all users; obtaining manually entered data based on the collaborative entry instructions.

[0041] In this implementation, different data entry objects only have viewing permissions for their own data entry results, while all users under the same data entry object can collaborate on data entry. This is specifically achieved through an online document permission isolation rule engine, which uses permission policy configuration, online collaboration touchpoints, and MQ message and token filtering mechanisms to solve the problem of data sharing and isolation in online collaboration. The specific working principle of the online document permission isolation rule engine is as follows: First, permission policy configuration, i.e., the system sets policy configuration to support customizable settings for data datasets, data regions, and data tables, allowing for read and write permissions for authorized objects (organizational structure, personnel, roles), and storing permission domains according to the combination of col and row; Second, before accessing an online document, the system reads the document's permission policy configuration requirements, performs regional block identification of templates and data example regions, decomposes the document, splits the step template domain, data domain, and identifier domain, and connects the permission domains for message processing; Third, the system sends MQ messages, retrieves existing channel information in Netty, obtains the current online user channel list based on the document ID, and excludes its own channel based on the document ID and the token passed from the front end; Fourth, the system sends MQ messages, polls the queue, and starts pushing messages to consumers. Once the consumer receives the message and successfully saves the file, it parses the current operation record content, generates information content relevant to the business, and performs incremental data persistence storage according to the online document ID, operator, coordinates, before modification, after modification, time, and original operation file path, completing the operation record persistence; Fifth, the system sends the operation content to other online channels of the current online document, receives the message, parses the data, renders the page, and completes the collaboration. Of course, this embodiment is only an example and does not limit the specific working principle of the online document permission isolation rule engine. As long as it can solve the problem of data sharing and isolation in online collaboration, it is within the protection scope of this application and is not limited in this embodiment.

[0042] Step S103: Summarize the data entry results to obtain the completed data collection template, and display the completed data collection template to all task issuers.

[0043] Optionally, the results of each data entry can be summarized to obtain a completed data collection template, including: summarizing the results of each data entry in the online data collection template; and granting the task issuer permission to view all contents of the data collection template.

[0044] Specifically, in this embodiment, the data submission results of different submitters will be summarized, and the data summary will be carried out online. The task issuer can see all the content of the summarized data collection template and can view it in real time. However, the submitters can only see the data submission results they have entered. Therefore, the permissions assigned to the task issuer and the submitters are different in this embodiment.

[0045] In this implementation, various collection file templates such as Excel and Word are parsed to support different user objects issuing different collection sub-tasks for the same template. Sub-tasks can be issued to specified reporting objects based on different filling elements or topic paragraphs in the template, defining different permissions and approval process requirements for data filling and viewing. The system automatically creates filling tasks for reporting objects according to the issuance frequency and tasks, supports data permission isolation for different reporting objects, and allows different users of the same reporting object to collaborate online. The big data similarity prediction and analysis model performs data similarity verification on the filled data and prompts for tasks and filled data that require similarity reference. After reading and identifying the collection tasks, the big data similarity prediction and analysis model automatically captures historical data to provide data trend reporting warnings and push reminders.

[0046] The technical solution of this invention automatically dispatches data collection sub-tasks to different reporting objects by identifying data collection needs. Each reporting object can only fill in and view the data collection sub-tasks assigned to it. While filling in data online, the filling results of different reporting objects are isolated to ensure data security. The data filling results are then summarized and viewed on the task issuer's side, thereby realizing automatic data integration and summarization, and improving the security and efficiency of the data collection process.

[0047] Example 2

[0048] Figure 3 This is a flowchart of a data collection method provided by an embodiment of the present invention. Based on the above embodiments, this embodiment displays the completed data collection template to the task assignor, allowing the task assignor to view the summary content online and make corrections and edits. The submitting object can view the task assignor's revisions and revision records according to their permissions. For example... Figure 3 As shown, the method includes:

[0049] Step S201: Receive the data collection request sent by the task issuer, and send different data collection sub-tasks for the same data collection template to each reporting object according to the data collection request.

[0050] Optionally, based on data collection needs, different data collection sub-tasks targeting the same data collection template can be sent to each reporting object, including: querying and obtaining the data collection template to be filled in based on the identifier of the data collection template, and uploading it as online based on the data collection template; generating data collection sub-tasks for the reporting object based on the reporting elements to be filled in; and sending the data collection sub-tasks to the matching reporting objects according to the collection frequency.

[0051] Optionally, after querying and obtaining the data collection template to be filled in based on the identifier of the data collection template, the method further includes: checking whether the data collection template contains filling elements; if it is determined that there are no filling elements, then filling elements are added to the data collection template.

[0052] Step S202: Receive the data entry results of each data entry object for the matched data collection subtask.

[0053] Optionally, the system receives the data entry results of each reporting object for the matched data collection sub-task, including: querying the historical reporting tasks for each reporting object and calculating the similarity results between the historical reporting tasks and the data collection sub-task; displaying the similarity results to the reporting object and receiving the data entry results determined by the reporting object based on the similarity results.

[0054] Optionally, receiving the data entry result determined by the similarity result of the object to be entered includes: when the similarity result meets the preset requirements, determining whether a data migration instruction has been received; if so, taking the historical data corresponding to the historical data entry task as the data entry result; otherwise, obtaining the manually entered data of the object to be entered and taking the manually entered data as the data entry result.

[0055] Optionally, obtaining manually entered data for the object to be entered includes: identifying all users included under the object to be entered, and receiving collaborative entry instructions from all users; obtaining manually entered data based on the collaborative entry instructions.

[0056] Step S203: Summarize the data entry results to obtain the completed data collection template, and display the completed data collection template to all task issuers.

[0057] Optionally, the results of each data entry can be summarized to obtain a completed data collection template, including: summarizing the results of each data entry in the online data collection template; and granting the task issuer permission to view all contents of the data collection template.

[0058] Step S204: When a revision instruction is received from the task issuer for the completed data collection template, the data collection template is updated according to the revision instruction.

[0059] Specifically, this implementation allows task issuers to view and edit the summarized content online. Task issuers can not only view the entire content of the completed data collection template, but also revise the displayed template as needed. When a revision instruction is received from the task issuer, the data collection template is updated according to the revision method indicated in the instruction. For example, the revision instruction may involve deleting or changing data in the data collection template. Of course, this implementation is merely illustrative and does not limit the specific modifications to the data collection template.

[0060] Step S205: Determine the target element that has been updated in the data collection template, and the target reporting object corresponding to the target element.

[0061] Specifically, this implementation also supports the isolated viewing of revisions and revision records of the data entry content by the task assigner, based on user permissions. By monitoring the data collection template in real time to identify updated target elements, and since the data entry elements corresponding to each user have been defined in the previously assigned collection sub-tasks (i.e., different users have different viewing permissions for different elements in the data collection template—configured during sub-task assignment), the target user corresponding to the target element can be determined based on the configuration information from the previous task assignment.

[0062] Step S206: Generate an update message for the target element and send the update message to the target data entry object.

[0063] In this embodiment, when the target data entry object is determined, an update message is generated for the target element and sent to the target data entry object. For example, the update message may be displayed as a pop-up window on the page corresponding to the target data entry object, or the update message may be played as a voice broadcast on the client side of the target data entry object. Of course, this embodiment is only an example and does not limit the specific display method of the update message on the target data entry object side.

[0064] The technical solution of this invention automatically dispatches data collection sub-tasks to different reporting objects by identifying data collection needs. Each reporting object can only fill in and view the data collection sub-tasks assigned to it. While filling in data online, the filling results of different reporting objects are isolated to ensure data security. The data filling results are then summarized and viewed on the task issuer's side, thereby realizing automatic data integration and summarization, and improving the security and efficiency of the data collection process.

[0065] Example 3

[0066] Figure 4 This is a schematic diagram of a data collection device provided in an embodiment of the present invention. Figure 4 As shown, the device includes: a data collection subtask sending module 310, a data filling result receiving module 320, and a data display module 330.

[0067] The data collection subtask sending module 310 is used to receive the data collection request sent by the task issuer, and send different data collection subtasks for the same data collection template to each reporting object according to the data collection request. The data collection request includes the identifier of the data collection template.

[0068] The data entry result receiving module 320 is used to receive the data entry results of each entry object for the matched data collection subtask. Each entry object only has viewing permission for its own data entry results.

[0069] The data display module 330 is used to summarize the data entry results, obtain the completed data collection template, and display the completed data collection template to all task issuers.

[0070] Optionally, the data collection requirements may also include the reporting objects, the reporting elements that the reporting objects need to fill in, and the collection frequency;

[0071] The data collection subtask sending module is used to query and obtain the data collection template to be filled in based on the identifier of the data collection template, and upload it as online based on the data collection template;

[0072] Generate a data collection subtask for the reporting object based on the reporting elements required for the reporting object;

[0073] Send the data collection subtasks to the matching reporting objects according to the collection frequency.

[0074] Optionally, the device also includes a template completion module for checking whether the data collection template contains filling elements;

[0075] If it is determined that there is no element to fill in, then the element will be added to the data collection template.

[0076] Optionally, a data entry result receiving module is used to query historical entry tasks for each entry object and calculate the similarity results between historical entry tasks and data collection subtasks.

[0077] The similarity results are displayed to the reporting subjects, and the data reporting results determined by the reporting subjects based on the similarity results are received.

[0078] Optionally, a data entry result receiving module is used to determine whether a data migration instruction has been received when the similarity result meets the preset requirements. If so, the historical data corresponding to the historical entry task is used as the data entry result.

[0079] Otherwise, retrieve the manually entered data of the data entry object and use the manually entered data as the data entry result.

[0080] Optionally, the data entry result receiving module is also used to determine all users included under the entry object and to receive collaborative entry instructions from all users;

[0081] Retrieve manually entered data based on collaborative data entry instructions.

[0082] Optional, the data display module is used to summarize the results of each data entry in the online data collection template;

[0083] Enable the task issuer to view all content of the data collection template.

[0084] Optionally, the device also includes a template revision module, which updates the data collection template according to the revision instruction when it receives a revision instruction from the task issuer for the completed data collection template;

[0085] Identify the target elements that have been updated in the data collection template, and the target reporting objects corresponding to those target elements;

[0086] Generate an update message for the target element and send the update message to the target data entry object.

[0087] The data collection device provided in this embodiment of the invention can execute a data collection method provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of executing the method.

[0088] Example 4

[0089] Figure 5 A schematic diagram of a terminal device 10 that can be used to implement embodiments of the present invention is shown. The terminal device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The terminal device can also represent various forms of mobile devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0090] The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the invention described and / or claimed herein.

[0091] like Figure 5 As shown, the terminal device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer programs stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 can also store various programs and data required for the operation of the terminal device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0092] Multiple components in terminal device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows terminal device 10 to exchange information / data with other terminal devices through computer networks such as the Internet and / or various telecommunications networks.

[0093] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as data collection methods.

[0094] In some embodiments, the data collection method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on terminal device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the data collection method described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to perform the data collection method by any other suitable means (e.g., by means of firmware).

[0095] Various embodiments of the apparatuses and techniques described above herein can be implemented in digital electronic circuit devices, integrated circuit devices, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), device-on-a-chip (SoCs), complex programmable logic terminal devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable device including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage device, at least one input device, and at least one output device, and transmitting data and instructions to the storage device, the at least one input device, and the at least one output device.

[0096] Computer programs used to implement the data collection method of the present invention can be written in any combination of one or more programming languages. These computer programs can be provided to the processor of a general-purpose computer, a special-purpose computer, or other non-stop data migration device, such that when executed by the processor, the functions / operations specified in the flowcharts and / or block diagrams are implemented. The computer programs can be executed entirely on the machine, partially on the machine, or as a standalone software package, partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0097] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution apparatus, device, or terminal device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage terminal devices, magnetic storage terminal devices, or any suitable combination thereof.

[0098] To provide interaction with a user, the apparatus and techniques described herein can be implemented on a terminal device having: a display device (e.g., a touchscreen) for displaying information to the user; and buttons through which the user can provide input to the terminal device. Other types of apparatus can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or haptic feedback); and input from the user can be received in any form (including voice input, speech input, or haptic input).

[0099] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0100] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A data collection method, characterized in that, The method includes: Receive data collection requests sent by the task issuer, and send different data collection sub-tasks for the same data collection template to each reporting object according to the data collection requests, wherein the data collection requests include the identifier of the data collection template; The system receives data entry results from each of the aforementioned data entry objects for the matched data collection subtask. Each data entry object only has viewing permissions for its own data entry results, implemented through an online document permission isolation rule engine. The working principle of the online document permission isolation rule engine is as follows: First, permission policy configuration is performed, and permission domains are stored according to row and column combinations. Second, before accessing an online document, the system reads the document's permission policy configuration requirements, performs regional segmentation, identifies templates and data example regions, decomposes the document, and connects permission domains for message processing. Third, the system sends MQ messages, retrieves existing channel information in Netty, obtains the current online user channel list based on the document ID, and excludes its own channel based on the document ID and the token passed from the front end. Fourth, the system sends MQ messages, polls the queue, and starts pushing messages to consumers. Upon receiving the message and successfully saving the file, the consumer parses the current operation record content, generates information content relevant to the business, and performs incremental data persistence storage according to the online document ID, operator, coordinates, before modification, after modification, time, and original operation file path. Fifth, the system sends operation content to other online channels of the current online document, receives the message, parses the data, renders the page, and completes the collaboration. The data entry results are summarized to obtain the completed data collection template, and the completed data collection template is displayed to all the task issuers. The data collection requirements also include the reporting objects, the reporting elements that the reporting objects need to fill in, and the collection frequency; the step of sending different data collection sub-tasks for the same data collection template to each reporting object according to the data collection requirements includes: The data collection template to be filled in is retrieved by querying the identifier of the data collection template, and then uploaded as online based on the data collection template. Generate the data collection subtask for the object to be filled in based on the filling elements required for the object to be filled in; The data collection subtask is sent to the matching reporting object according to the collection frequency; After obtaining the data collection template to be filled in by querying based on the identifier of the data collection template, the method further includes: checking whether the data collection template contains the filling element; If it is determined that the required data entry element does not exist, then the required data entry element will be added to the data collection template.

2. The method according to claim 1, characterized in that, The receiving of data entry results from each of the data entry objects for the matched data collection subtask includes: For each reporting object, query the historical reporting tasks and calculate the similarity results between the historical reporting tasks and the data collection sub-tasks; The similarity results are displayed to the data entry object, and the data entry results determined by the data entry object based on the similarity results are received.

3. The method according to claim 2, characterized in that, Receiving the data entry result determined by the data entry object based on the similarity result includes: When the similarity result meets the preset requirements, it is determined whether a data migration instruction has been received. If so, the historical data corresponding to the historical data entry task is used as the data entry result. Otherwise, obtain the manually entered data of the object to be filled in, and use the manually entered data as the data filling result.

4. The method according to claim 3, characterized in that The process of obtaining the manually entered data of the object includes: Identify all users included under the reported object and receive collaborative reporting instructions from all users; The manually entered data is obtained according to the collaborative data entry instruction.

5. The method according to claim 1, characterized in that, The step of summarizing the data entry results to obtain the completed data collection template includes: The results of each data entry are summarized in the online data collection template. Grant the task issuer permission to view all contents of the data collection template.

6. The method according to claim 1, characterized in that, After displaying the completed data collection template to the task issuer, the process further includes: When a revision instruction is received from the task issuer regarding the completed data collection template, the data collection template is updated according to the revision instruction; Identify the target element that has been updated in the data collection template, and the target reporting object corresponding to the target element; An update message is generated for the target element, and the update message is sent to the target data entry object.

7. A data collection device, characterized in that, include: The data collection subtask sending module is used to receive the data collection request sent by the task issuer, and send different data collection subtasks for the same data collection template to each reporting object according to the data collection request, wherein the data collection request includes the identifier of the data collection template; The data entry result receiving module is used to receive the data entry results of each entry object for the matched data collection subtask. Each entry object only has viewing permissions for its own data entry results, and this is implemented through an online document permission isolation rule engine. The working principle of the online document permission isolation rule engine is as follows: First, permission policy configuration is performed, and permission domains are stored according to a row and column combination method; second, before accessing the online document, the permission policy configuration requirements of the document are read, and the document is divided into regions, templates and data example regions are identified, the document is decomposed, and permission domains are connected for message processing; third, MQ messages are sent and nett is obtained. The system retrieves the existing channel information in y, obtains the list of currently online user channels based on the document ID, and excludes its own channel based on the document ID and the token passed from the front end. Fourth, it sends MQ messages and polls the queue to start pushing messages to consumers. Once a consumer receives a message and successfully saves the file, it parses the current operation record, generates information relevant to the business, and performs incremental data persistence based on the online document ID, operator, coordinates, before modification, after modification, time, and original operation file path. Fifth, it sends the operation content to other online channels of the current online document, receives the message, parses the data, renders the page, and completes the collaboration. The data display module is used to summarize the data entry results to obtain the completed data collection template, and display the completed data collection template to all the task issuers. The data collection requirements also include the reporting object, the reporting elements to be filled in by the reporting object, and the collection frequency; the data collection subtask sending module is used to query and obtain the data collection template to be filled in according to the identifier of the data collection template, and upload it as online according to the data collection template. Generate the data collection subtask for the object to be filled in based on the filling elements required for the object to be filled in; The data collection subtask is sent to the matching reporting object according to the collection frequency; The device also includes a template filling module for checking whether the data collection template contains the filling element; If it is determined that the required data entry element does not exist, then the required data entry element will be added to the data collection template.

8. A terminal device, characterized in that, The terminal device includes: One or more processors; Storage device for storing one or more programs. When the one or more programs are executed by the one or more processors, the one or more processors implement the method as described in any one of claims 1-6.

9. A storage medium for computer-executable instructions, wherein a computer program is stored thereon, characterized in that, When the program is executed by the processor, it implements the method as described in any one of claims 1-6.

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