A method, device and medium for multi-person collaborative data verification based on task flow

Abstract

This application discloses a multi-person collaborative data confirmation method, device, and medium based on task flow. The method includes: receiving raw data to be processed and determining the credibility of each data source; marking data fields to be confirmed in the raw data, publishing the data fields to be confirmed through tasks, and comparing and marking specified information in the raw data with specified information in the platform; receiving the data fields to be confirmed and collaborating the tasks corresponding to the data fields to be confirmed to other personnel to collaboratively confirm the data fields with specified marks; changing the confirmation status of the confirmed data, and summarizing the confirmed data with the confirmed status based on task submission trigger; sending the summarized confirmed data to the corresponding task publisher so that the task publisher can review the confirmed data and compare the differences between the raw data and the confirmed data.

Description

Technical Field

[0001] This application relates to the field of data processing technology, and in particular to a method, device and medium for multi-person collaborative data verification based on task flow. Background Technology

[0002] In today's society, with the rapid development of new-generation information technologies such as cloud computing, big data, and artificial intelligence, all industries are undergoing unprecedented changes. Especially in grassroots work, these new technologies not only bring potential improvements in work efficiency but also place new demands on the working methods of grassroots staff. As a bridge connecting the government and the people, the importance of grassroots work is self-evident, and data processing, as a crucial component of their daily work, is directly related to service quality and efficiency.

[0003] Traditionally, frontline staff face numerous challenges when processing large amounts of data and information. On the one hand, they need to ensure the authenticity and accuracy of every piece of data, which is the foundation for ensuring the effective implementation of policies and the quality of services. On the other hand, due to a lack of effective technical support, staff often find it difficult to quickly and accurately track the source and update time of data, leading to the need to adopt a full verification approach in practice. This is not only time-consuming and labor-intensive, but also greatly affects work efficiency. Summary of the Invention

[0004] This application provides a method, device, and medium for multi-person collaborative data confirmation based on task flow, in order to solve the above-mentioned technical problems.

[0005] On the one hand, embodiments of this application provide a method for multi-person collaborative data confirmation based on task flow, including:

[0006] Receive the raw data to be processed and determine the credibility of each data source; the credibility of the same data may differ depending on the data source.

[0007] Mark the data fields to be confirmed in the original data, publish the data fields to be confirmed in the form of a task, and compare and mark the specified information in the original data with the specified information in the platform;

[0008] Receive the data field to be confirmed, and coordinate the task corresponding to the data field to be confirmed to other personnel to conduct collaborative data confirmation on the data field with the specified mark;

[0009] Change the confirmation status of the confirmed data, and based on the task submission trigger, summarize the confirmed data with the confirmation status of "confirmed".

[0010] The aggregated confirmed data is sent to the corresponding task publisher so that the task publisher can review the confirmed data and compare the differences between the original data and the confirmed data.

[0011] In one implementation of this application, the process of receiving raw data to be processed and determining the credibility of each data source specifically includes:

[0012] Receive raw data to be processed uploaded by the task publisher, and record the data source and data update frequency corresponding to each data field in the raw data;

[0013] Set corresponding weight coefficients for data source and data update frequency, and determine the data source and data update frequency for each data source to determine the credibility of each data source;

[0014] Among them, the data source corresponding to the data authority is the most reliable data source among all the data sources, and the reliability is less than or equal to the unit length.

[0015] In one implementation of this application, a data field to be confirmed is marked in the original data, and the data field to be confirmed is published via a task, specifically including:

[0016] The task issuer marks the data fields to be confirmed in the original data and determines the confirmation status of the marked data fields; wherein, the confirmation status includes no confirmation required, confirmation required, and confirmed.

[0017] Identify the data fields in the original data whose confirmation status is "needs confirmation" and distribute them as tasks.

[0018] Determine whether the zoning information in the data field to be confirmed matches the zoning information of the recipient. If so, receive the corresponding data through the recipient.

[0019] The data with a confirmed status are aggregated, and the aggregated data with a confirmed status overwrites the corresponding original data.

[0020] In one implementation of this application, comparing and marking specified information in the original data with specified information in the platform specifically includes:

[0021] The number of data sources corresponding to basic information and business data in the original data is determined respectively, so as to determine the reliable data source corresponding to the basic information or business data based on the number of data sources;

[0022] Obtain basic information from a trusted data source for the basic information, and obtain business data from a trusted data source corresponding to the business data;

[0023] The update times corresponding to the basic information and business data in the original data are determined respectively, and based on the relationship between the corresponding update time and the preset validity period, it is determined whether the basic information or business data in the original data needs to be confirmed.

[0024] The basic information and business data in the original data are compared with the basic information and business data in the corresponding trusted data source to determine whether the basic information and business data in the original data need to be confirmed, and are marked according to the confirmation status.

[0025] In one implementation of this application, the number of data sources corresponding to basic information and business data in the original data is determined respectively, so as to determine the trusted data source corresponding to the basic information or business data based on the number of data sources; obtaining basic information from the trusted data source of the basic information, and obtaining business data from the trusted data source corresponding to the business data, specifically includes:

[0026] Determine the number of data sources corresponding to the basic information and business data in the original data, and if the number of data sources corresponding to the basic information and the business data is one, directly obtain the basic information and the business data from the corresponding data sources;

[0027] If there are multiple data sources for both the basic information and the business data, then the corresponding credibility data sources for the basic information and the business data are determined from the multiple data sources, and the basic information and the business data are obtained from the corresponding credibility data sources.

[0028] The trusted data source is the data source with the highest credibility among the multiple data sources.

[0029] In one implementation of this application, the basic information and business data in the original data are compared with the basic information and business data in the corresponding trusted data source to determine whether the basic information and business data in the original data need to be confirmed, and a mark is made according to the confirmation status, specifically including:

[0030] Determine whether the basic information and business data in the original data match the basic information and business data in the corresponding trusted data source;

[0031] If so, then it is determined that the basic information and the business data do not require confirmation, and the basic information and the business data are marked with the corresponding color that indicates that no confirmation is required;

[0032] If not, then the basic information and the business data need to be confirmed, and the basic information and the business data are marked with the corresponding color that needs to be confirmed;

[0033] If the basic information and business data in the original data have no matching data in any data source, then the basic information and business data are marked with a specified color, so as to confirm the basic information and business data based on the specified color.

[0034] In one implementation of this application, the process involves receiving the data field to be confirmed and coordinating the task corresponding to the data field to be confirmed with other personnel to collaboratively confirm the data field with a specified marker. Specifically, this includes:

[0035] The grassroots staff receive the data confirmation task corresponding to the data field to be confirmed, and determine the other personnel corresponding to the data confirmation task to coordinate the data confirmation task to the other personnel in the corresponding department according to the zoning result corresponding to the data to be confirmed;

[0036] During data verification, a designated marker in the data verification task is identified, and a trusted data source corresponding to the marker color that does not require verification is determined; wherein the designated marker is used to represent the designated color and the marker color that needs to be verified.

[0037] The data to be confirmed by the specified mark is confirmed using the original data and the trusted data source. If the data in the original data and the trusted data source are both incorrect, the accurate data is manually entered.

[0038] Based on the accurate data entered, the data to be confirmed for the specified marker is confirmed to obtain the corresponding confirmation data.

[0039] In one implementation of this application, changing the confirmation status corresponding to the confirmed data specifically includes:

[0040] In the multi-user collaboration interface, change the task status corresponding to the confirmed data to "confirmed" and clear the marker color corresponding to the confirmed data;

[0041] If all the marker colors corresponding to the data to be confirmed in the original data are cleared, it is determined that the data in the original data has been confirmed, and the person who confirmed the data and the confirmation time are displayed.

[0042] On the other hand, embodiments of this application also provide a multi-person collaborative data confirmation device based on task flow, the device comprising:

[0043] At least one processor;

[0044] And, a memory communicatively connected to the at least one processor;

[0045] The memory stores instructions that can be executed by the at least one processor, which are then executed by the at least one processor to enable the at least one processor to perform a multi-person collaborative data confirmation method based on task flow as described above.

[0046] On the other hand, this application also provides a non-volatile computer storage medium storing computer-executable instructions, which, when executed, implement the multi-person collaborative data confirmation method based on task flow as described above.

[0047] This application provides a method, device, and medium for multi-person collaborative data verification based on task flow, which has at least the following beneficial effects:

[0048] By determining the credibility of each data source and marking data fields to be confirmed, uncertainties and errors in the data can be effectively identified and addressed, thereby improving overall data quality. Publishing data fields to be confirmed as tasks and collaborating with other personnel for data confirmation promotes cooperation and communication among team members, improving data processing efficiency. Task submission triggers the aggregation of confirmed data, which is then sent to the task publisher for review, simplifying the data review process and making it more efficient and orderly. Comparing and marking specified information in the original data with specified information in the platform helps identify and resolve data inconsistencies, improving data consistency and accuracy. Comparing the differences between the original data and the confirmed data provides a clear understanding of data changes during processing, facilitating the tracking and analysis of data discrepancies. The entire data processing process, including data confirmation, status changes, data aggregation, and review, is traceable and transparent, enhancing the transparency and credibility of data processing. Attached Figure Description

[0049] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings:

[0050] Figure 1 A flowchart illustrating a multi-person collaborative data confirmation method based on task flow, provided in an embodiment of this application;

[0051] Figure 2 This is a schematic diagram of the internal structure of a multi-person collaborative data confirmation device based on task flow, provided in an embodiment of this application. Detailed Implementation

[0052] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below in conjunction with specific embodiments and corresponding drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0053] The technical solutions provided by the various embodiments of this application are described in detail below with reference to the accompanying drawings.

[0054] Figure 1 This is a flowchart illustrating a multi-person collaborative data confirmation method based on task flow, provided in an embodiment of this application.

[0055] The analysis method involved in the embodiments of this application can be implemented by a terminal device or a server, and this application does not impose any special limitations on it. For ease of understanding and description, the following embodiments are all described in detail using a server as an example.

[0056] It should be noted that the server can be a single device or a system composed of multiple devices, i.e., a distributed server. This application does not make any specific limitations on this.

[0057] like Figure 1 As shown in the embodiment of this application, a multi-person collaborative data confirmation method based on task flow is provided, including:

[0058] 101. Receive the raw data to be processed and determine the credibility of each data source; the credibility of different data sources for the same data is different.

[0059] Specifically, in one embodiment of this application, the server receives the raw data to be processed and determines the credibility of each data source, specifically including:

[0060] Receive raw data to be processed uploaded by the task publisher, and record the data source and data update frequency for each data field in the raw data;

[0061] Set corresponding weight coefficients for data sources and data update frequencies, and determine the data sources and data update frequencies corresponding to each data source in order to determine the credibility of each data source;

[0062] Among them, the data source corresponding to the data authority is the most reliable data source among all data sources, with a reliability less than or equal to the unit length.

[0063] In one embodiment, the credibility of each data source is set, and the credibility of the same data from different data sources cannot be the same. For example, if basic population information exists simultaneously in four data sources, then the data source shared by the responsible department is the most reliable data source for that data. The credibility of other data sources can be defined based on comprehensive indicators such as data origin and update frequency. The credibility value is represented by R. The maximum value of R is 1.

[0064] The task issuer prepares the original data that needs to be confirmed, which includes basic information and business information. Taking population data as an example, the information to be confirmed includes zoning information Q (q1, q2, q3, ..., qn), basic population information W (w1, w2, w3, ..., wn), and business information E (e1, e2, e3, ..., en).

[0065] In one embodiment, suppose the task poster uploads raw data about product sales, including data fields such as product name, sales volume, and sales date. The system records the data source and update frequency for each data field. For example, the product name comes from the product management department and is updated weekly; the sales volume comes from the sales department and is updated daily; and the sales date comes from the finance department and is updated monthly.

[0066] Assign corresponding weighting coefficients to data sources and data update frequencies. Assume the weighting coefficient for data sources is 0.6, and the weighting coefficient for data update frequency is 0.4. Calculate the reliability of each data source based on its weighting coefficients and corresponding data source and update frequency. For example, the reliability of the product management department's data source is 0.6 (data source weight) * 1 (department weight) + 0.4 (update frequency weight) * 0.5 (weekly update) = 0.8; the sales department's data source reliability is 0.6 + 0.4 (daily update) = 1; and the finance department's data source reliability is 0.6 + 0.4 * 0.25 (monthly update) = 0.7. In this example, the sales department's data source is the most reliable because its reliability is the highest, at 1.

[0067] 102. Mark the data fields to be confirmed in the original data, publish the data fields to be confirmed through the task, and compare and mark the specified information in the original data with the specified information in the platform.

[0068] Specifically, the server marks the data fields to be confirmed in the raw data, and publishes these data fields as tasks, including:

[0069] The task issuer marks the data fields to be confirmed in the original data and determines the confirmation status of the marked data fields; the confirmation status includes no confirmation required, confirmation required, and confirmed.

[0070] Identify the data fields in the original data whose confirmation status is "needs confirmation" so that these data fields with the confirmation status "needs confirmation" can be distributed as tasks.

[0071] Determine whether the zoning information in the data field to be confirmed matches the zoning information of the recipient. If so, receive the corresponding data through the recipient.

[0072] The data with a confirmed status is aggregated, and the aggregated data with a confirmed status overwrites the corresponding original data.

[0073] In one embodiment, the task issuer needs to mark the data fields that require confirmation. After the data fields are marked, the system automatically records the confirmation status C of the corresponding data. When C=0, no confirmation is required; when C=1, confirmation is required. Once the staff confirms the data, the confirmation status C=2.

[0074] A snapshot of the original data is saved and cannot be modified. Simultaneously, a pending confirmation data set is generated from the original data and distributed as a task. Confirmed data is then aggregated and overwritten with the original data. The system compares the district information Q in the pending confirmation information with the recipient's district information Q1. If Q = Q1, the corresponding data is received. This method ensures that the recipient only receives data from their own district.

[0075] In one embodiment, suppose a task publisher uploads raw data on sales performance across various regions of the country, including data fields such as region, sales amount, and sales date. The task publisher marks the sales amount data fields for some regions in the raw data as pending confirmation because this data may be questionable or require further verification. The system determines the confirmation status corresponding to the marked pending confirmation data fields. In this example, the confirmation status of the marked data fields is set to "requires confirmation".

[0076] The system identifies data fields in the original data that are in a "need confirmation" status and distributes them as tasks. Each task includes the data field to be confirmed, along with relevant contextual information, so that the recipient can better understand the task and make the confirmation.

[0077] When distributing tasks, the system considers whether the region information in the data field to be confirmed matches the recipient's region information. For example, if the data field to be confirmed is about sales in the Beijing area, the system will distribute the task to a recipient whose region is Beijing. After receiving the task, the recipient can view the data field to be confirmed and confirm it based on their own knowledge and experience.

[0078] Once the recipient has completed the data verification task, the system will update the verification status to "Verified". The system then aggregates the data with a "Verified" status and generates a new dataset. This new dataset overwrites the unverified portions of the original data, thus updating the entire dataset and ensuring its accuracy. Finally, the system can provide the updated dataset to the task issuer or other relevant personnel for further analysis or use.

[0079] In one embodiment of this application, the server compares and marks specified information in the original data with specified information in the platform, specifically including:

[0080] Determine the number of data sources corresponding to basic information and business data in the original data respectively, so as to determine the reliable data source corresponding to the basic information or business data based on the number of data sources;

[0081] Basic information is obtained from trusted data sources for basic information, and business data is obtained from trusted data sources corresponding to business data.

[0082] Determine the update time corresponding to the basic information and business data in the original data respectively, and determine whether the basic information or business data in the original data needs to be confirmed based on the relationship between the corresponding update time and the preset validity period.

[0083] The basic information and business data in the original data are compared with the basic information and business data in the corresponding trusted data source to determine whether the basic information and business data in the original data need to be confirmed, and are marked according to the confirmation status.

[0084] In one embodiment, suppose there is an e-commerce platform that needs to regularly update its product information, including basic product information (such as name, category, brand, etc.) and business data (such as sales volume, reviews, inventory, etc.). To ensure data accuracy, the platform employs a data verification system.

[0085] The platform first counted the number of data sources corresponding to basic information and business data. For example, product names might come from multiple data sources such as suppliers, product editing departments, and user feedback; while sales data mainly comes from the sales department and the order system. Based on the number of data sources, the platform determined the reliable data sources corresponding to the basic information and business data. For example, for product names, the data sources provided by suppliers were the most numerous and considered the most accurate, thus being selected as reliable data sources; for sales data, the data sources from the sales department were considered reliable.

[0086] After identifying a reliable data source, the platform retrieves basic product information, such as name, category, and brand, from the supplier's data source. Simultaneously, the platform also obtains business data about the products, such as sales volume, reviews, and inventory, from the sales department's data source.

[0087] The platform records the update times of basic information and business data in trusted data sources. For example, the supplier last updated the product name last Wednesday, and the sales department last updated sales figures today. The platform sets a preset validity period, such as 7 days. Data updated within this validity period is considered accurate and requires no verification; however, data updated after the validity period may require verification. Based on this rule, the platform determines which basic information and business data need verification. For example, if a product name was updated more than 7 days ago, then the name needs to be verified to ensure its accuracy.

[0088] The platform compares the basic information and business data in the raw data with the data in the corresponding trusted data sources. For example, it compares whether the product names in the raw data match the names in the supplier data source; it compares whether the sales volume in the raw data matches the sales volume in the sales department data source. Based on the comparison results, the platform marks the basic information and business data in the raw data with a confirmation status. For example, if the product names match, it is marked as "No confirmation required"; if the sales volume does not match, it is marked as "Confirmation required".

[0089] In one embodiment of this application, the server determines the number of data sources corresponding to basic information and business data in the original data, respectively, so as to determine the trusted data source corresponding to the basic information or business data based on the number of data sources; obtaining basic information from the trusted data source of basic information and obtaining business data from the trusted data source corresponding to business data specifically includes:

[0090] Determine the number of data sources corresponding to basic information and business data in the original data, and if there is only one data source corresponding to both basic information and business data, directly obtain the basic information and business data from the corresponding data source.

[0091] If there are multiple data sources for both basic information and business data, then the corresponding credibility data sources for basic information and business data are determined from the multiple data sources, and the basic information and business data are obtained from the corresponding credibility data sources.

[0092] Among these, the trusted data source is the data source with the highest credibility among multiple data sources.

[0093] In one embodiment, suppose a financial services platform needs to integrate its customers' basic information and transaction data. To ensure the accuracy and reliability of the data, the platform employs a data integration system that acquires data based on the quantity and credibility of the data sources.

[0094] Regarding the customer's basic information (such as name, ID number, contact information, etc.), the platform found that this data came from only one data source, namely the information the customer filled in during registration. Since there was only one data source for the basic information, the platform directly obtained the customer's basic information from this data source without needing to conduct further credibility assessment.

[0095] For customer transaction data (such as transaction amount, transaction time, and counterparty), the platform found that this data comes from multiple data sources, including customer self-service transaction systems, bank-connected systems, and third-party payment systems. In this situation, the platform needs to determine which data source is reliable. By evaluating factors such as the historical accuracy, update frequency, and authority of each data source, the platform determined that the bank-connected system is the reliable data source for transaction data because its data accuracy and update frequency are relatively high. After determining the reliable data source, the platform retrieved the customer's transaction data from the bank-connected system.

[0096] The platform integrates the acquired basic information and business data to form a complete customer data profile. This data is used in multiple business scenarios such as customer analysis, risk assessment, and transaction monitoring, providing strong support for the operation of the financial service platform.

[0097] In one embodiment of this application, the server compares the basic information and business data in the original data with the basic information and business data in the corresponding trusted data source to determine whether the basic information and business data in the original data need to be confirmed, and marks them according to the confirmation status, specifically including:

[0098] Determine whether the basic information and business data in the original data match the basic information and business data in the corresponding trusted data source;

[0099] If so, then determine that the basic information and business data do not require confirmation, and mark the basic information and business data with the corresponding color that does not require confirmation;

[0100] If not, then determine that the basic information and business data need to be confirmed, and mark the basic information and business data with the corresponding color that needs to be confirmed;

[0101] If no matching data is found for the basic information and business data in the original data from any of the data sources, the basic information and business data will be marked with a specified color to confirm the data based on the specified color.

[0102] In one embodiment, data comparison is performed by comparing the basic information B in the original data with the basic information B1 in the platform, and comparing the business data Y with Y1 in the business system interface connected to the platform, and the comparison results are marked.

[0103] Verify the data source of B1. If B1 has only one data source, retrieve the data directly from that source. If B1 exists in multiple data sources, select the data source with the highest reliability R. Verify the update time of B1. Each field has a last update time D and an expiration period V. Let the current time be D0. Determine the relationship between D0-D and V. If D0-D≥V, mark it as orange; if D0-D<V, mark it as green. Green indicates no confirmation is needed, and orange indicates confirmation is required. Compare the basic information B in the original data with the data value of basic information B1 in the reliable data source. If B=B1, mark it as green; if B≠B1, mark it as red. Green indicates no confirmation is needed, and red indicates confirmation is required.

[0104] Verify the data source of Y1. If Y1 has only one data source, retrieve the data directly from that source. If Y1 exists in multiple data sources, select the data source with the highest reliability R. Verify the update time of Y1. Each field has a last update time D and an expiration period V. Let the current time be D0. Determine the relationship between D0-D and V. If D0-D≥V, mark it as orange; if D0-D<V, mark it as green. Green indicates no confirmation required, and orange indicates confirmation required. Compare the business data Y with the data value of Y1 in the business system interface. If Y=Y1, mark it as green; if Y≠Y1, mark it as red. Green indicates no confirmation required, and red indicates confirmation required.

[0105] If some data in the original data does not have matching data in any of the data sources, it is marked in purple, and purple indicates that data confirmation is required. The data is compared using a round-robin method, with the priority of each color being purple > red > orange > green. That is, if a piece of data has been compared multiple times and the results include multiple colors, it will be displayed in the color with the highest priority. Data that does not require confirmation is marked in gray.

[0106] 103. Receive the data field to be confirmed and coordinate the task corresponding to the data field to be confirmed to other personnel to conduct collaborative data confirmation on the data field with the specified mark.

[0107] Specifically, in one embodiment of this application, the server receives a data field to be confirmed and coordinates the task corresponding to the data field to be confirmed with other personnel to perform collaborative data confirmation on the data field with a specified mark, specifically including:

[0108] The data confirmation task is received by the grassroots staff and the data confirmation task is coordinated with other personnel in the corresponding departments according to the zoning results of the data to be confirmed.

[0109] When performing data verification, the specified markers in the data verification task are identified, and the trusted data sources corresponding to the marker colors that do not require verification are determined; the specified markers are used to represent the specified colors and the corresponding marker colors that need to be verified.

[0110] The system verifies the data to be verified by using the original data and the trusted data source. If the data in both the original data and the trusted data source is incorrect, the accurate data is manually entered.

[0111] Based on the accurate data entered, confirm the data to be confirmed for the specified markers to obtain the corresponding confirmation data.

[0112] In one embodiment, when a frontline worker receives a data confirmation task, they can delegate the task to other personnel for joint data confirmation. During task collaboration, data is no longer distributed by region, meaning the entire collaborative data can be viewed.

[0113] When verifying data, frontline staff only need to confirm the data marked in purple, red, and orange. The system will also display the color-coded trusted data sources, along with the specific data and update time. Staff can verify the data from both the original data and the trusted data sources and then select the accurate data. If, after verification, both the original data and the trusted data sources are inaccurate, staff can manually enter the accurate data.

[0114] 104. Change the confirmation status of the confirmed data, and based on the task submission trigger, summarize the confirmed data with the confirmation status of "confirmed".

[0115] Specifically, in one embodiment of this application, the server changes the confirmation status corresponding to the confirmed data, which specifically includes:

[0116] In the multi-user collaboration interface, change the task status corresponding to the confirmed data to "confirmed" and clear the marker color corresponding to the confirmed data;

[0117] Once all the marker colors for the data to be confirmed in the original data are cleared, the confirmation of the data in the original data is confirmed, and the person who confirmed the data and the confirmation time are displayed.

[0118] In one embodiment, suppose an e-commerce platform needs to regularly update its product information, including basic product information (such as name, category, brand, etc.) and business data (such as inventory, price, sales volume, etc.). To ensure data accuracy, the platform employs a multi-person collaborative data verification system.

[0119] The platform provides a collaborative interface for updating product information, allowing employees from different departments to participate in data verification. Once an employee has completed the verification of a piece of data, they can change the task status to "Confirmed" on the collaborative interface. Simultaneously, the system will automatically clear the marker color for the confirmed data to indicate that the verification process has been completed.

[0120] When all the marker colors corresponding to the data awaiting confirmation in the original data are cleared, the system determines that the data confirmation process for this batch of original data has been completed. At this point, the system will display the confirmer and the confirmation time for the confirmed data to track the data update history and confirmation responsibility.

[0121] Suppose an e-commerce platform launches a batch of new products. The product information department enters the basic information and business data of these new products into the system and marks them as pending confirmation. Subsequently, employees from the product review department, price management department, and inventory management department log into a multi-person collaborative interface to confirm the data they are responsible for. Each time a department completes data confirmation, they change the task status to "Confirmed" on the collaborative interface and clear the corresponding marker color. Once all pending confirmation data has had its marker color cleared, the system notifies that the product information update task is complete and displays the person who confirmed each piece of confirmed data and the confirmation time.

[0122] 105. Send the summarized confirmed data to the corresponding task publisher so that the task publisher can review the confirmed data and compare the differences between the original data and the confirmed data.

[0123] When a staff member submits a task, the confirmed data will be automatically aggregated to the task publisher. In collaborative tasks involving multiple people, once one person submits the task, it is considered submitted. Data in a submitted task cannot be confirmed again.

[0124] Once the task publisher receives the confirmed data, they can review it. Data that fails the review can be marked as pending confirmation and rejected. After rejection, the task will be returned to the original task publisher via the same route. If rejection is not required, the task publisher can use the data comparison function to compare the differences between the original data snapshot and the confirmed data. This concludes the data confirmation process.

[0125] The above are embodiments of the method proposed in this application. Based on the same inventive concept, embodiments of this application also provide a multi-person collaborative data confirmation device based on task flow, the structure of which is as follows: Figure 2 As shown.

[0126] Figure 2 This is a schematic diagram of the internal structure of a multi-user collaborative data confirmation device based on task flow, provided as an embodiment of this application. Figure 2 As shown, the device includes:

[0127] At least one processor;

[0128] And, a memory that is communicatively connected to at least one processor;

[0129] The memory stores instructions that can be executed by at least one processor, and the instructions, when executed by at least one processor, enable at least one processor to:

[0130] Receive the raw data to be processed and determine the credibility of each data source; the credibility of the same data may differ depending on the data source.

[0131] Mark the data fields to be confirmed in the raw data, publish the data fields to be confirmed through the task, and compare and mark the specified information in the raw data with the specified information in the platform;

[0132] Receive data fields to be confirmed and coordinate the tasks corresponding to the data fields to be confirmed to other personnel to conduct collaborative data confirmation on data fields with specified tags;

[0133] Change the confirmation status of the confirmed data, and based on the task submission trigger, summarize the confirmed data with the confirmation status of "confirmed".

[0134] The aggregated and confirmed data will be sent to the corresponding task publisher so that the task publisher can review the confirmed data and compare the differences between the original data and the confirmed data.

[0135] This application also provides a non-volatile computer storage medium storing computer-executable instructions, which, when executed, can:

[0136] Receive the raw data to be processed and determine the credibility of each data source; the credibility of the same data may differ depending on the data source.

[0137] Mark the data fields to be confirmed in the raw data, publish the data fields to be confirmed through the task, and compare and mark the specified information in the raw data with the specified information in the platform;

[0138] Receive data fields to be confirmed and coordinate the tasks corresponding to the data fields to be confirmed to other personnel to conduct collaborative data confirmation on data fields with specified tags;

[0139] Change the confirmation status of the confirmed data, and based on the task submission trigger, summarize the confirmed data with the confirmation status of "confirmed".

[0140] The aggregated and confirmed data will be sent to the corresponding task publisher so that the task publisher can review the confirmed data and compare the differences between the original data and the confirmed data.

[0141] The various embodiments in this application are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the device and medium embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the description of the method embodiments.

[0142] The foregoing has described specific embodiments of this application. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in a different order than that shown in the embodiments and may still achieve the desired results. Furthermore, the processes depicted in the drawings do not necessarily require the specific or sequential order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0143] The devices and media provided in this application are one-to-one with the methods. Therefore, the devices and media also have similar beneficial technical effects as their corresponding methods. Since the beneficial technical effects of the methods have been described in detail above, the beneficial technical effects of the devices and media will not be repeated here.

[0144] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0145] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0146] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0147] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0148] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0149] Memory may include non-persistent storage in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0150] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0151] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0152] The above description is merely an embodiment of this application and is not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

Claims

1. A multi-person collaborative data confirmation method based on task flow, characterized in that, The method includes: Receive the raw data to be processed and determine the credibility of each data source; the credibility of the same data may differ depending on the data source. Mark the data fields to be confirmed in the original data, publish the data fields to be confirmed in the form of a task, and compare and mark the specified information in the original data with the specified information in the platform; Receive the data field to be confirmed, and coordinate the task corresponding to the data field to be confirmed to other personnel to conduct collaborative data confirmation on the data field with the specified mark; Change the confirmation status of the confirmed data, and based on the task submission trigger, summarize the confirmed data with the confirmation status of "confirmed". The aggregated confirmed data is sent to the corresponding task publisher so that the task publisher can review the confirmed data and compare the differences between the original data and the confirmed data. Receive the raw data to be processed and determine the credibility of each data source, specifically including: Receive raw data to be processed uploaded by the task publisher, and record the data source and data update frequency corresponding to each data field in the raw data; Set corresponding weight coefficients for data source and data update frequency, and determine the data source and data update frequency for each data source to determine the credibility of each data source; Among them, the data source corresponding to the data authority is the most reliable data source among all the data sources, and the reliability is less than or equal to the unit length. Marking fields to be confirmed in the original data, and publishing these fields via a task, specifically includes: The task issuer marks the data fields to be confirmed in the original data and determines the confirmation status of the marked data fields; wherein, the confirmation status includes no confirmation required, confirmation required, and confirmed. Identify the data fields in the original data whose confirmation status is "needs confirmation" and distribute them as tasks. Determine whether the zoning information in the data field to be confirmed matches the zoning information of the recipient. If so, receive the corresponding data through the recipient. The data with a confirmed status are aggregated, and the aggregated data with a confirmed status is used to overwrite the corresponding original data. Receiving the data field to be confirmed and coordinating the task corresponding to the data field to be confirmed with other personnel to perform collaborative data confirmation on data fields with specified tags, specifically including: The grassroots staff receive the data confirmation task corresponding to the data field to be confirmed, and determine the other personnel corresponding to the data confirmation task to coordinate the data confirmation task to the other personnel in the corresponding department according to the zoning result corresponding to the data to be confirmed; During data verification, a designated marker in the data verification task is identified, and a trusted data source corresponding to the marker color that does not require verification is determined; wherein the designated marker is used to represent the designated color and the marker color that needs to be verified. The data to be confirmed by the specified mark is confirmed using the original data and the trusted data source. If the data in the original data and the trusted data source are both incorrect, the accurate data is manually entered. Based on the accurate data entered, the data to be confirmed for the specified marker is confirmed to obtain the corresponding confirmation data.

2. The method for multi-person collaborative data confirmation based on task flow according to claim 1, characterized in that, The data comparison and labeling are performed between specified information in the original data and specified information in the platform, specifically including: The number of data sources corresponding to basic information and business data in the original data is determined respectively, so as to determine the reliable data source corresponding to the basic information or business data based on the number of data sources; Obtain basic information from a trusted data source for the basic information, and obtain business data from a trusted data source corresponding to the business data; The update times corresponding to the basic information and business data in the original data are determined respectively, and based on the relationship between the corresponding update time and the preset validity period, it is determined whether the basic information or business data in the original data needs to be confirmed. The basic information and business data in the original data are compared with the basic information and business data in the corresponding trusted data source to determine whether the basic information and business data in the original data need to be confirmed, and are marked according to the confirmation status.

3. The method for multi-person collaborative data confirmation based on task flow according to claim 2, characterized in that, The number of data sources corresponding to basic information and business data in the original data is determined respectively, so as to determine the reliable data source corresponding to the basic information or business data based on the number of data sources; Obtaining basic information from a trusted data source for the basic information, and obtaining business data from a trusted data source corresponding to the business data, specifically includes: Determine the number of data sources corresponding to the basic information and business data in the original data, and if the number of data sources corresponding to the basic information and the business data is one, directly obtain the basic information and the business data from the corresponding data sources; If there are multiple data sources for both the basic information and the business data, then the corresponding credibility data sources for the basic information and the business data are determined from the multiple data sources, and the basic information and the business data are obtained from the corresponding credibility data sources. The trusted data source is the data source with the highest credibility among the multiple data sources.

4. The method for multi-person collaborative data confirmation based on task flow according to claim 2, characterized in that, The basic information and business data in the original data are compared with the basic information and business data in the corresponding trusted data source to determine whether the basic information and business data in the original data need to be confirmed, and are marked according to the confirmation status, specifically including: Determine whether the basic information and business data in the original data match the basic information and business data in the corresponding trusted data source; If so, then it is determined that the basic information and the business data do not require confirmation, and the basic information and the business data are marked with the corresponding color that indicates that no confirmation is required; If not, then the basic information and the business data need to be confirmed, and the basic information and the business data are marked with the corresponding color that needs to be confirmed; If the basic information and business data in the original data have no matching data in any data source, then the basic information and business data are marked with a specified color, so as to confirm the basic information and business data based on the specified color.

5. The method for multi-person collaborative data confirmation based on task flow according to claim 1, characterized in that, Changes to the confirmation status of confirmed data include: In the multi-user collaboration interface, change the task status corresponding to the confirmed data to "confirmed" and clear the marker color corresponding to the confirmed data; If all the marker colors corresponding to the data to be confirmed in the original data are cleared, it is determined that the data in the original data has been confirmed, and the person who confirmed the data and the confirmation time are displayed.

6. A multi-user collaborative data confirmation device based on task flow, characterized in that, The device includes: At least one processor; And, a memory communicatively connected to the at least one processor; The memory stores instructions that can be executed by the at least one processor, which are executed by the at least one processor to enable the at least one processor to perform a multi-person collaborative data confirmation method based on task flow as described in any one of claims 1-5.

7. A non-volatile computer storage medium storing computer-executable instructions, characterized in that, When the computer-executable instructions are executed, a multi-person collaborative data confirmation method based on task flow as described in any one of claims 1-5 is implemented.

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