Dining report presentation method, apparatus, electronic device and computer readable medium

Abstract

This disclosure presents embodiments of a method, apparatus, electronic device, and computer-readable medium for displaying meal reports. One specific implementation of the method includes: in response to determining that a meal processing time has been reached, acquiring a meal dataset and employee attendance data; preprocessing the meal dataset and employee attendance data; automatically importing the preprocessed meal dataset and preprocessed attendance data into an associated file to generate at least one meal analysis data set; sending each meal analysis data set to a terminal used by the corresponding department; obtaining at least one meal data return message; and sending the generated visualized meal report to a target terminal for visualization. This implementation, without placing a significant data processing load on the processing end, utilizes a target meal analysis script to accurately and efficiently generate meal analysis data to obtain various aspects of meal information, enabling a comprehensive understanding of the meal situation through subsequently generated accurate visualized reports.

Description

Technical Field

[0001] Embodiments of this disclosure relate to the field of computer technology, and more specifically to methods, apparatus, electronic devices, and computer-readable media for displaying dining reports. Background Technology

[0002] Currently, with the development of information technology, enterprises are increasingly using computer systems to store and manage dining-related data. Although automation has improved, dining-related data still primarily relies on periodic data aggregation and manual comparison, limiting efficiency and accuracy. Furthermore, with a large number of employees, the processing end often faces a heavy workload for dining data processing, lacking sufficient resources for efficient processing, leading to issues such as processing delays, slow response times, and even system crashes.

[0003] The information disclosed in this background section is only intended to enhance the understanding of the background of the inventive concept, and therefore may contain information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0004] The summary portion of this disclosure is intended to provide a brief overview of the concepts, which will be described in detail in the detailed description portion. This summary portion is not intended to identify key or essential features of the claimed technical solutions, nor is it intended to limit the scope of the claimed technical solutions.

[0005] Some embodiments of this disclosure provide methods, apparatuses, electronic devices, and computer-readable media for displaying dining reports to address one or more of the technical problems mentioned in the background section above.

[0006] In a first aspect, some embodiments of this disclosure provide a method for displaying a meal report, comprising: in response to determining that a meal processing time has been reached, obtaining a meal dataset from a meal data terminal and obtaining employee attendance data for at least one employee from a user attendance terminal, wherein each meal dataset corresponds to a restaurant, and the meal data is the meal data of the at least one employee within a target time period; performing data preprocessing on the meal dataset and employee attendance data to generate a preprocessed meal dataset and preprocessed attendance data; automatically importing the preprocessed meal dataset and preprocessed attendance data into an associated file stored in a distributed file system corresponding to a target meal analysis script to generate at least one meal analysis data corresponding to at least one department, wherein the at least one department refers to the departments corresponding to the at least one employee, and the meal analysis data includes: employee information set, dinner usage records for each employee, overtime hours for each employee, meal value outflow information for each department, and dinner... Using comparison information between records and overtime hours, the comparison information includes: the number of times employees self-process their meals and the first meal value outflow information. The aforementioned distributed file system has at least one physical node for storing associated files, and the at least one physical node includes: a file metadata management node and at least one data processing node. Each meal analysis data in the aforementioned at least one meal analysis data is sent to the terminal used by the corresponding department for the department to review the meal data and process the meal value outflow. At least one meal data return information sent by the corresponding terminal of the aforementioned at least one department is obtained, wherein the meal data return information includes: meal data confirmation information. In response to determining that the aforementioned at least one meal data return information indicates that the meal analysis data is correct and that the meal value outflow has been completed, a visual meal report is generated for the aforementioned at least one department, the aforementioned at least one meal analysis data, and the aforementioned meal value outflow information. The aforementioned visual meal report is sent to the target terminal for visualization.

[0007] Secondly, some embodiments of this disclosure provide a meal report display device, comprising: a first acquisition unit configured to, in response to determining that a meal processing time has been reached, acquire a meal dataset from a meal data terminal and acquire employee attendance data for at least one employee from a user attendance terminal, wherein each meal data corresponds to a restaurant, and the meal data is the meal data of the at least one employee within a target time period; a processing unit configured to preprocess the meal dataset and employee attendance data to generate a preprocessed meal dataset and preprocessed attendance data; and an import unit configured to automatically import the preprocessed meal dataset and preprocessed attendance data into an associated file stored in a distributed file system corresponding to a target meal analysis script, generating at least one meal analysis data corresponding to at least one department, wherein the at least one department refers to the departments corresponding to the at least one employee, and the meal analysis data includes: employee information set, dinner usage records for each employee, overtime hours for each employee, meal value outflow information for each department, dinner usage records, and overtime hours. The comparison information between shifts includes: the number of times employees self-process their meals and the first meal value outflow information. The distributed file system has at least one physical node for storing associated files. The at least one physical node includes: a file metadata management node and at least one data processing node. A sending unit is configured to send each meal analysis data from the at least one meal analysis data to a terminal used by the corresponding department for departmental review and meal value outflow. A second acquisition unit is configured to acquire at least one meal data return information sent by the corresponding terminal of the at least one department. The meal data return information includes: meal data confirmation information. A generation unit is configured to generate a visualized meal report for the at least one department, the at least one meal analysis data, and the meal value outflow information in response to determining that the at least one meal data return information indicates that the meal analysis data is correct and that the meal value outflow has been completed. A display unit is configured to send the visualized meal report to a target terminal for visualization.

[0008] Thirdly, some embodiments of this disclosure provide an electronic device, including: one or more processors; and a storage device having one or more programs stored thereon, such that 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 implementation of the first aspect.

[0009] Fourthly, some embodiments of this disclosure provide a computer-readable medium having a computer program stored thereon, wherein the program, when executed by a processor, implements the method as described in any implementation of the first aspect.

[0010] The above-described embodiments of this disclosure have the following beneficial effects: Through the meal report display method of some embodiments of this disclosure, meal analysis data can be accurately and efficiently generated using a target meal analysis script without placing too much data processing load on the processing end, thereby obtaining various aspects of meal information and enabling a precise visualization report to be generated subsequently to understand the meal situation. Specifically, relying on periodic data aggregation and manual comparison limits efficiency and accuracy. Furthermore, when dealing with a large number of employees, the processing end often experiences a heavy meal data processing load and lacks sufficient resources for efficient processing, leading to problems such as processing end lag, slow response speed, or even system crashes. Based on this, the meal report display method of some embodiments of this disclosure first, in response to determining that the meal processing time has arrived, obtains a meal dataset from a meal data terminal and employee attendance data for at least one employee from a user attendance terminal. Each meal dataset corresponds to a specific restaurant, and the meal data represents the meal data of the at least one employee within a target time period. Here, the meal data terminal and user attendance terminal enable effective data management of the corresponding business data, and the acquisition of the meal dataset and employee attendance data facilitates subsequent precise analysis of the meal situation. Then, the aforementioned meal dataset and employee attendance data are preprocessed to generate preprocessed meal datasets and preprocessed attendance data, transforming them into high-quality data for subsequent use and feature extraction. Next, the preprocessed meal datasets and preprocessed attendance data are automatically imported into the associated file based on a distributed file system corresponding to the target meal analysis script, generating at least one meal analysis data set for at least one department. The at least one department refers to the department corresponding to the at least one employee. The meal analysis data includes: employee information sets, dinner usage records for each employee, overtime hours for each employee, meal value outflow information for each department, and comparison information between dinner usage records and overtime hours. The comparison information includes: the number of times an employee self-processes their meal and the first meal value outflow information. The distributed file system has at least one physical node for storing the associated files, including a file metadata management node and at least one data processing node. Here, the meal analysis script enables accurate and efficient generation of meal analysis data for various business needs. A distributed file system can effectively solve the problem of insufficient resources for efficient processing of meal data when there are many employees, leading to processing delays, slow response times, or even system crashes. By coordinating the work of the file metadata management node and at least one data processing node, the workload of meal data analysis can be distributed, reducing the processing pressure on the processing end.Next, each of the at least one dining analysis data points is sent to the terminal used by the corresponding department for review and value disbursement. This allows departments to promptly understand the dining analysis data and execute value disbursement. Then, at least one dining data return message from the corresponding terminal of each department is obtained to receive feedback. This return message includes confirmation information. Further, in response to the confirmation that the at least one dining data return message indicates the dining analysis data is correct and the value disbursement has been completed, a visual dining report is generated for each department, the at least one dining analysis data point, and the value disbursement information. This report facilitates visualization and effectively displays key dining information for each department. Finally, the visual dining report is sent to the target terminal for visualization. In summary, by utilizing the target dining analysis script and the corresponding distributed file system, dining analysis data can be accurately and efficiently generated without placing excessive data processing load on the processing end. This allows for comprehensive dining information to be obtained, resulting in a precise visual report that provides a clear understanding of the dining situation. Attached Figure Description

[0011] The above and other features, advantages, and aspects of the embodiments of this disclosure will become more apparent from the accompanying drawings and the following detailed description. Throughout the drawings, the same or similar reference numerals denote the same or similar elements. It should be understood that the drawings are schematic, and elements are not necessarily drawn to scale.

[0012] Figure 1 This is a flowchart of some embodiments of the dining report display method according to this disclosure;

[0013] Figure 2 These are schematic diagrams illustrating the structure of some embodiments of the dining report display device according to this disclosure;

[0014] Figure 3 This is a schematic diagram of the structure of an electronic device suitable for implementing some embodiments of the present disclosure. Detailed Implementation

[0015] Embodiments of this disclosure will now be described in more detail with reference to the accompanying drawings. While some embodiments of this disclosure are shown in the drawings, it should be understood that this disclosure can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of this disclosure. It should be understood that the accompanying drawings and embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of protection of this disclosure.

[0016] It should also be noted that, for ease of description, only the parts relevant to the invention are shown in the accompanying drawings. Unless otherwise specified, the embodiments and features described in this disclosure can be combined with each other.

[0017] It should be noted that the concepts of "first" and "second" mentioned in this disclosure are used only to distinguish different devices, modules or units, and are not used to limit the order of functions performed by these devices, modules or units or their interdependencies.

[0018] It should be noted that the terms "a" and "a plurality of" used in this disclosure are illustrative rather than restrictive, and those skilled in the art should understand that, unless otherwise expressly indicated in the context, they should be understood as "one or more".

[0019] The names of messages or information exchanged between multiple devices in the embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of such messages or information.

[0020] This disclosure will now be described in detail with reference to the accompanying drawings and embodiments.

[0021] refer to Figure 1 The diagram illustrates a flow 100 of some embodiments of a dining report display method according to the present disclosure. This dining report display method includes the following steps:

[0022] Step 101: In response to determining that the meal processing time has been reached, obtain the meal dataset from the meal data terminal and obtain employee attendance data for at least one employee from the user attendance terminal.

[0023] In some embodiments, in response to determining that the meal processing time has been reached, the entity executing the above-described meal report display method (e.g., an electronic device) can obtain meal datasets from a meal data terminal and employee attendance data for at least one employee from a user attendance terminal via a wired or wireless connection. The meal processing time can be the time for analyzing and processing the meal data corresponding to each employee. In practice, the meal processing time can also be the time for meal reimbursement statistics. Meal reimbursement statistics can determine whether the meal situation of each employee complies with the company's catering reimbursement regulations. The meal processing time can be a time preset in the meal processing system. The meal processing system can be a processing system that performs various processing on the meal situation. For example, the meal processing time can be the 5th of each month. Various processing can include: meal data analysis, report generation, and meal data visualization. The meal data terminal can be a terminal that stores the meal data corresponding to each employee. The meal data terminal obtains the meal situation of each employee in each dining restaurant in real time. The meal data can be the employee's meal situation in the corresponding dining restaurant in the previous month. For example, the meal data can include: the meal situation of each employee in the dining restaurant in one month. For example, the dining processing system is bound to a set of restaurants including: Restaurant A, Restaurant B, and Restaurant C. The corresponding dining dataset can include dining data for Restaurant A, Restaurant B, and Restaurant C. The user attendance terminal can be a device that records the attendance of each employee in the previous month. The user attendance terminal records the attendance of each employee in real time every day. At least one employee can be the primary processing object for the current dining data analysis. Employee attendance data can be the actual attendance of each employee in the previous month. Each dining data point corresponds to a restaurant, and the dining data is the dining data of at least one employee within a target time period. For example, the target time period could be the previous month.

[0024] Step 102: Perform data preprocessing on the above-mentioned meal dataset and employee attendance data to generate preprocessed meal dataset and preprocessed attendance data.

[0025] In some embodiments, the aforementioned executing entity may perform data preprocessing on the aforementioned meal dataset and employee attendance data to generate preprocessed meal dataset and preprocessed attendance data. This data preprocessing may include, but is not limited to, at least one of the following: time format processing, invalid or duplicate record removal processing, and department name adjustment processing.

[0026] Step 103: Automatically import the preprocessed meal dataset and the preprocessed attendance data into the associated file stored in the distributed file system corresponding to the target meal analysis script, generating at least one meal analysis data for at least one department.

[0027] In some embodiments, the executing entity can automatically import the preprocessed meal dataset and the preprocessed attendance data into the associated file corresponding to the target meal analysis script, generating at least one meal analysis data for at least one department. The target meal analysis script can be a pre-written script for comprehensive analysis of meal data and attendance data. The associated file can be a file bound to the target meal analysis script. After the dataset is imported into the onboarding associated file, the target meal analysis script will automatically start to generate the meal analysis data. There is a one-to-one correspondence between the departments in at least one department and the meal analysis data in at least one meal analysis dataset. At least one department can be the departments to which at least one employee belongs. For example, at least one department can include: algorithm department, data processing department, human resources department, administrative department, and legal department. The meal analysis data includes: employee information set, dinner usage records for each employee, overtime hours for each employee, meal value outflow information for each department, and comparison information between dinner usage records and overtime hours. The comparison information includes: the number of times an employee self-processes their meal and the first meal value outflow information. Employee information can represent the employee's identity. For example, employee information can be the employee's employee ID. The employee information set can refer to all employees within a department. Dinner usage records can be the employee's dinner dining history from the previous month. In practice, dinner usage records may include: dinner time, dinner restaurant, and dinner price. Overtime count can be the total number of overtime hours worked by an employee in the previous month. Meal value outflow information can be the value of meal value flowing out. In practice, for dinner reimbursement scenarios, the corresponding meal value outflow information can be the dinner expense payment value. Meal value outflow information can also be the total amount of dinner expenses payable by the entire department. Comparison information can be the comparison information obtained by comprehensively comparing dinner usage records and overtime counts. Number of self-processed meals can be the number of times meal expenses were paid independently. The first meal value outflow information can be the total amount of dinner expenses paid independently by employees. In practice, the target meal analysis script can be a pre-developed script for at least one analytical function required for the meal scenario. That is, the target meal analysis script supports meal analysis under multi-functional scenario requirements. For example, multi-functional scenario requirements may include: overtime count summary requirements, departmental meal value outflow information requirements, and comparison information generation requirements. The source files corresponding to the target dining analysis script support the layout and neural network model source files corresponding to the needs of multi-functional scenarios, in order to realize intelligent dining analysis. The aforementioned distributed file system has at least one physical node for storing associated files. This at least one physical node includes: a file metadata management node and at least one data processing node. The file metadata management node can be the master node among the at least one physical node.The file metadata management node can be used to manage file metadata and schedule the dining data processing workflow. The data processing node can be used to store scripts and set associated files. The processing terminal can be the terminal where the dining processing system resides.

[0028] In some optional implementations of certain embodiments, the aforementioned meal analysis data further includes: lunch usage records for each employee and secondary meal value outflow information for each employee. The lunch usage records may show the employee's lunch usage over the previous month. In practice, the lunch usage records may include: lunch time, lunch restaurant, and lunch price. The secondary meal value outflow information may be the total amount paid by the employee for lunch.

[0029] Optionally, the executing entity can automatically import the preprocessed meal dataset and the preprocessed attendance data into the associated file corresponding to the target meal analysis script. This allows the use of the lunch rule processing script included in the target meal analysis script to generate lunch usage records and second meal value outflow information for each employee. The lunch rule processing script indicates that lunch does not support determining the employee's meal value outflow when the employee dines at multiple restaurants simultaneously. Determining the employee's meal value outflow when dining at multiple restaurants simultaneously can involve determining the meal cost the employee should pay. In practice, the first lunch can be designated as a free lunch, and subsequent lunches can be designated as lunches the employee should pay for themselves.

[0030] In some optional implementations of certain embodiments, the comparison information corresponding to the target employee is generated through the following steps:

[0031] The first step is to respond to the situation where the number of overtime hours for the target employee is higher than or equal to the number of dinners in the corresponding dinner usage record, set the target value to the number of times meals are handled independently, and set the target value as the first meal value outflow information for the target employee. The target value can be a pre-set value, or it can be the value "0".

[0032] The second step is to subtract the number of overtime hours from the number of dinners consumed by the target employees, since the number of overtime hours is less than the number of dinners consumed.

[0033] The third step is to determine the number of times the meal was handled by the customer by the customer by subtracting the above values.

[0034] The fourth step involves determining the time information set representing the mismatch between overtime work and dinner usage, based on the aforementioned dinner usage records and the attendance data corresponding to the target employees in the preprocessed attendance data. This time information set can include the time when an employee ate dinner but did not work overtime.

[0035] As an example, the aforementioned implementing entity uses the method of matching overtime data with dinner data to characterize the time information set where overtime and dinner usage do not match.

[0036] Fifth, based on the above dinner usage records, determine the dinner value information set corresponding to the above time information set.

[0037] As an example, the aforementioned implementing entity can query the dinner cost value for each time period from the dinner usage record to obtain the dinner cost value set, which serves as the dinner value information set.

[0038] Step 6: Determine the value outflow object corresponding to each dinner value information in the aforementioned dinner value information set. The value outflow object can be one of the following: employee, department, or company. The value outflow object corresponding to each dinner value information is confirmed by the object confirmation information received through the value outflow object confirmation page after dinner. The value outflow object can represent the entity that pays for the dinner. When the value outflow object is an employee, it means the employee pays for the dinner themselves. When the value outflow object is a department, it means the department reimburses the dinner expenses. When the value outflow object is a company, it means the company reimburses the dinner expenses. The value outflow object confirmation page can be a confirmation page that determines who pays for the dinner that day.

[0039] Step 7: Take at least one dinner value information from the above dinner value information set whose corresponding value outflow object is an employee, as at least one first dinner value information. The first dinner value information can be the payment amount made by the employee themselves for dinner.

[0040] Step 8: Take at least one dinner value information from the above dinner value information set whose corresponding value outflow object is a department, as at least one second dinner value information. The first dinner value information can be the reimbursement amount for dinner reimbursement by the department.

[0041] Step nine: Take at least one dinner value information from the above dinner value information set whose corresponding value outflow object is the company, as at least one third dinner value information. The first dinner value information can be the reimbursement amount for dinner reimbursed by the company.

[0042] Step 10: Add the above-mentioned first dinner value information together to obtain the first sum value.

[0043] Step 11: Add the above-mentioned value information of at least one second dinner to obtain a second summed value.

[0044] Step 12: Add the above-mentioned value information of at least one third dinner to obtain the third sum value.

[0045] Step 13: The association information between the first summed value and the employee object, the association information between the second summed value and the department object, and the association information between the third summed value and the company object are determined as the first meal value outflow information corresponding to the target employee.

[0046] In some optional implementations of certain embodiments, the aforementioned executing entity can automatically import the preprocessed meal dataset and the preprocessed attendance data into the associated file stored in the distributed file system corresponding to the target meal analysis script, generating at least one meal analysis data corresponding to at least one department, including the following steps:

[0047] In the first step, in response to the determination that the number of employees corresponding to at least one of the above-mentioned employees is lower than the first value, the above-mentioned pre-processed meal dataset and the above-mentioned pre-processed attendance data are directly and automatically imported into the associated file in the above-mentioned file metadata management node corresponding to the target meal analysis script, so as to generate at least one meal analysis data corresponding to at least one department.

[0048] The second step, in response to determining that the number of employees corresponding to at least one of the aforementioned employees is higher than the first value, for each of the aforementioned at least one department, the following second generation step is performed using the aforementioned file metadata management node:

[0049] Sub-step 1: In response to determining that the number of employees corresponding to the aforementioned departments is higher than the second value, the employee information set corresponding to the aforementioned departments is grouped to obtain employee information groups. Each employee information group has a number of employees less than the second value, where the second value is less than the division value. The division value is the first value divided by the number of departments. The second value can be a pre-set value that is less than the first value. The first value can also be a pre-set value. When the number of employees is greater than the first value, it indicates that the company has a large number of employees. When the number of employees is greater than the second value, it indicates that the department has a large number of employees. Grouping is necessary to reduce the workload of the script in analyzing dining data.

[0050] As an example, the aforementioned executing entity can randomly group the employee information set corresponding to the aforementioned department based on the second value to obtain the employee information set.

[0051] Sub-step 2: In response to determining that the number of employees corresponding to the above-mentioned departments is less than or equal to the above-mentioned second value, the employee information set corresponding to the above-mentioned departments is determined as the employee information set.

[0052] The third step is to determine the number of groups corresponding to the employee information groups in the at least one employee information group set obtained.

[0053] The fourth step is to determine the group identifier corresponding to each employee information group in the at least one employee information group set mentioned above. The group identifier can represent the group identity corresponding to the employee information group.

[0054] Fifth step, set a predetermined number of associated files, wherein the predetermined number is the same as the number of groups.

[0055] Step 6: Using the file metadata management node mentioned above, set the filenames corresponding to the predetermined number of associated files, where the text name is the group identifier.

[0056] Step 7: Using the aforementioned file metadata management node, allocate a predetermined number of copies of the target dining analysis script to at least one of the aforementioned data processing nodes, with each data processing node having a corresponding copy.

[0057] Step 8: Using the aforementioned file metadata management node, bind the predetermined number of copies to the predetermined number of associated files.

[0058] Step 9: Using the aforementioned file metadata management node, the preprocessed meal dataset and the preprocessed attendance data are divided according to the grouping method corresponding to the at least one employee information set, to generate at least one meal data set and at least one attendance data set.

[0059] Step 10: Based on the above-mentioned at least one set of dining data, the above-mentioned at least one set of attendance data, the above-mentioned predetermined number of copies, and the above-mentioned predetermined number of associated files, use the above-mentioned file metadata management node to generate at least one set of dining analysis data corresponding to at least one department.

[0060] Optionally, the aforementioned executing entity may, based on the aforementioned at least one set of dining data, the aforementioned at least one set of attendance data, and the aforementioned predetermined number of copies and predetermined number of associated files, utilize the aforementioned file metadata management node to generate at least one set of dining analysis data corresponding to at least one department, including the following steps:

[0061] The first step is to use the file metadata management node to automatically import the meal data group and the attendance data group corresponding to the employee information group into the associated file named after the group identifier of the employee information group, so as to use the copy in the corresponding data processing node to generate the employee meal analysis data group.

[0062] The second step involves generating at least one set of employee meal analysis data based on the obtained dataset, using the departmental meal analysis scripts included in the aforementioned target meal analysis script. The departmental meal analysis script can be a script used to perform data analysis on the departmental meal data.

[0063] As one of the invention's key features, this invention addresses another technical problem: "When dealing with a large number of employees, the processing end often experiences a heavy workload for processing meal data, lacking sufficient resources for efficient processing, leading to issues such as lag, slow response times, and even system crashes." Based on this, this disclosure utilizes a file metadata management node and at least one data processing node to achieve employee allocation and the generation of at least one meal analysis data point for at least one department. This significantly improves the efficiency of meal analysis data generation and avoids high-load conditions.

[0064] In some optional implementations of certain embodiments, the target dining analysis script described above supports intelligent recommendations for dining locations and times using a recommendation model. The recommendation model can be a model that recommends dining locations and times. In practice, the recommendation model can make real-time recommendations during employee meal times. The recommendation model can be connected to a visualization page to allow employees to understand available dining locations and times.

[0065] Step 104: Send each of the above-mentioned at least one dining analysis data to the terminal used by the corresponding department so that the department can review the dining data and handle the outflow of dining value.

[0066] In some embodiments, the aforementioned executing entity may send each of the at least one meal analysis data points to a terminal used by the corresponding department for departmental review and meal value disbursement. The review of the meal data may involve the department's designated reviewer verifying the accuracy of the meal analysis data. In practice, for meal reimbursement scenarios, meal value disbursement may involve payment of meal expenses. Each department has a corresponding terminal. The accuracy of the meal analysis data is verified through the terminal.

[0067] Step 105: Obtain at least one dining data return message sent by the terminal corresponding to at least one of the above-mentioned departments.

[0068] In some embodiments, the aforementioned executing entity may obtain at least one dining data return message sent by the terminal corresponding to at least one department. The dining data return message may represent feedback from the department regarding the dining analysis data. There is a one-to-one correspondence between the dining data return message and the department in at least one of the at least one departments. The dining data return message includes: dining data confirmation information. The dining data confirmation information may indicate whether the corresponding dining analysis data is normal and error-free. In addition, if the dining data confirmation information indicates that there is a problem with the dining analysis data, the dining data return message may also include: problematic data, a description corresponding to the problematic data, and supporting documents for the problematic data. The problematic data may be dining data that the department believes is erroneous. The description corresponding to the problematic data may be a detailed description of the problem. The supporting documents for the problematic data may be relevant supporting materials proving the existence of the problem.

[0069] Step 106: In response to determining that the dining data returned by at least one of the above-mentioned dining data is correct and that the dining value outflow has been completed, a visual dining report is generated for the at least one department, the at least one dining analysis data, and the dining value outflow information.

[0070] In some embodiments, in response to determining that the at least one dining data return information indicates that the dining analysis data is correct and that the dining value outflow has been completed, the executing entity can generate a visual dining report for the at least one department, the at least one dining analysis data, and the dining value outflow information. The visual dining report can be a report in image format displaying the dining situation for each department. The dining value outflow information can indicate whether the department has completed payment for the dining expenses. That is, the dining value outflow information can be one of the following: "01" or "00". When the dining value outflow information is "00", it indicates that the department has completed payment for each dining expense. When the dining value outflow information is "01", it indicates that the department has not completed payment for each dining expense.

[0071] As an example, the aforementioned implementing entity can fill in at least one department, at least one dining analysis data, and the dining value outflow information into the initial visualized dining report to obtain the visualized dining report.

[0072] In some optional implementations of certain embodiments, the aforementioned implementing entity can generate a visualized dining report for at least one department, at least one dining analysis data point, and the dining value outflow information, including the following steps:

[0073] First, for each of the at least one of the above departments, perform the following first generation step:

[0074] Sub-step 1: Determine the dining analysis data corresponding to the above departments as the target dining analysis data.

[0075] Sub-step 2: Based on the target meal analysis data mentioned above, generate the per capita meal data and departmental meal value information for the aforementioned departments. The per capita meal data can be the average meal cost per employee within the department. In practice, this data may include: per capita lunch cost and per capita dinner cost. The departmental meal value information can be the total meal cost for all employees within the department. In practice, this information may include:

[0076] As an example, firstly, the total lunch and dinner costs for each department are determined from the target meal analysis data mentioned above, serving as the department's meal value information. Then, the total lunch and dinner costs are divided by the number of employees in the department to obtain the per capita meal data.

[0077] Sub-step 3 involves determining the historical departmental dining value information sequence for the aforementioned departments within a specific historical time period. This historical time period can be any period preceding the target time period. For example, the current date is December 5th, and the target time period is November. The corresponding historical time period could be from January to October.

[0078] Sub-step 4: Add the above-mentioned departmental dining value information to the above-mentioned historical departmental dining value information sequence to obtain the departmental dining value information sequence.

[0079] Sub-step 5: Based on the aforementioned departmental dining value information sequence, use the dining value information prediction model to determine the future dining value information sequence within the target future time period. The dining value information prediction model can be a neural network model that predicts dining value information within a future time period. For example, the target future time period can be a future time period following the target time period. In practice, the dining value information prediction model can be a regression model or a temporal neural network model (e.g., a recurrent neural network model).

[0080] Sub-step 6 generates first meal value description information for the aforementioned departmental meal value information sequence and second meal value description information for the aforementioned future meal value information sequence. The first meal value description information can be a description of departmental meal expenses within the target time period and historical time periods. The first meal value description information can characterize the level of departmental meal expenses. For example, the first meal value description information could be "Department A had relatively high expenses in the historical and target time periods." The second meal value description information can be a description of departmental meal expenses in the future time period. For example, the first meal value description information could be "Department A will have relatively high expenses in the future time period."

[0081] As an example, the aforementioned implementing entity can use a question-and-answer model to generate a first dining value description for the aforementioned department's dining value information sequence and a second dining value description for the aforementioned future dining value information sequence.

[0082] Sub-step 7: Based on the above per capita meal data, the above departmental meal value information, the above first meal value description information, and the above second meal value description information, generate a departmental meal report for the above departments. The departmental meal report can be a report summarizing and analyzing the meal situation of a department.

[0083] The second step is to determine the dining location distribution information and dining value distribution information based on at least one of the aforementioned dining analysis data. The dining location distribution information can be the distribution of locations where at least one employee ate. Specifically, this information can represent the dining distribution of at least one employee across various restaurants. The dining value distribution information can be the distribution of the cost of meals eaten by at least one employee. This information can represent the number of employees dining within each cost range.

[0084] The third step is to generate a visual dining report from the obtained dining reports of at least one department, the above-mentioned dining location distribution information, and the above-mentioned dining value distribution information.

[0085] As an example, the aforementioned implementing entity can fill in at least one department's dining report, the aforementioned dining location distribution information, and the aforementioned dining value distribution information into the initial visualized dining report to obtain the visualized dining report.

[0086] Step 107: Send the above-mentioned visualized dining report to the target terminal for visualization display.

[0087] In some embodiments, the aforementioned executing entity may send the visualized dining report to a target terminal for visualization. The target terminal may be the terminal used by the superior entity corresponding to each department.

[0088] The above-described embodiments of this disclosure have the following beneficial effects: Through the meal report display method of some embodiments of this disclosure, meal analysis data can be accurately and efficiently generated using a target meal analysis script without placing too much data processing load on the processing end, thereby obtaining various aspects of meal information and enabling a precise visualization report to be generated subsequently to understand the meal situation. Specifically, relying on periodic data aggregation and manual comparison limits efficiency and accuracy. Furthermore, when dealing with a large number of employees, the processing end often experiences a heavy meal data processing load and lacks sufficient resources for efficient processing, leading to problems such as processing end lag, slow response speed, or even system crashes. Based on this, the meal report display method of some embodiments of this disclosure first, in response to determining that the meal processing time has arrived, obtains a meal dataset from a meal data terminal and employee attendance data for at least one employee from a user attendance terminal. Each meal dataset corresponds to a specific restaurant, and the meal data represents the meal data of the at least one employee within a target time period. Here, the meal data terminal and user attendance terminal enable effective data management of the corresponding business data, and the acquisition of the meal dataset and employee attendance data facilitates subsequent precise analysis of the meal situation. Then, the aforementioned meal dataset and employee attendance data are preprocessed to generate preprocessed meal datasets and preprocessed attendance data, transforming them into high-quality data for subsequent use and feature extraction. Next, the preprocessed meal datasets and preprocessed attendance data are automatically imported into the associated file based on a distributed file system corresponding to the target meal analysis script, generating at least one meal analysis data set for at least one department. The at least one department refers to the department corresponding to the at least one employee. The meal analysis data includes: employee information sets, dinner usage records for each employee, overtime hours for each employee, meal value outflow information for each department, and comparison information between dinner usage records and overtime hours. The comparison information includes: the number of times an employee self-processes their meal and the first meal value outflow information. The distributed file system has at least one physical node for storing the associated files, including a file metadata management node and at least one data processing node. Here, the meal analysis script enables accurate and efficient generation of meal analysis data for various business needs. A distributed file system can effectively solve the problem of insufficient resources for efficient processing of meal data when there are many employees, leading to processing delays, slow response times, or even system crashes. By coordinating the work of the file metadata management node and at least one data processing node, the workload of meal data analysis can be distributed, reducing the processing pressure on the processing end.Next, each of the at least one dining analysis data points is sent to the terminal used by the corresponding department for review and value disbursement. This allows departments to promptly understand the dining analysis data and execute value disbursement. Then, at least one dining data return message from the corresponding terminal of each department is obtained to receive feedback. This return message includes confirmation information. Further, in response to the confirmation that the at least one dining data return message indicates the dining analysis data is correct and the value disbursement has been completed, a visual dining report is generated for each department, the at least one dining analysis data point, and the value disbursement information. This report facilitates visualization and effectively displays key dining information for each department. Finally, the visual dining report is sent to the target terminal for visualization. In summary, by utilizing the target dining analysis script and the corresponding distributed file system, dining analysis data can be accurately and efficiently generated without placing excessive data processing load on the processing end. This allows for comprehensive dining information to be obtained, resulting in a precise visual report that provides a clear understanding of the dining situation.

[0089] Further reference Figure 2 As an implementation of the methods shown in the above figures, this disclosure provides some embodiments of a dining report display device, which are similar to... Figure 1 Corresponding to the method embodiments shown, this dining report display device can be specifically applied to various electronic devices.

[0090] like Figure 2As shown, a dining report display device 200 includes: a first acquisition unit 201, a processing unit 202, an import unit 203, a sending unit 204, a second acquisition unit 205, a generation unit 206, and a display unit 207. The first acquisition unit 201 is configured to, in response to determining that the meal processing time has been reached, acquire a meal dataset from a meal data terminal and employee attendance data for at least one employee from a user attendance terminal. Each meal dataset corresponds to a specific restaurant, and the meal data represents the meal data of the at least one employee within a target time period. The processing unit 202 is configured to preprocess the meal dataset and employee attendance data to generate a preprocessed meal dataset and preprocessed attendance data. The import unit 203 is configured to automatically import the preprocessed meal dataset and preprocessed attendance data into an associated file stored in a distributed file system corresponding to the target meal analysis script, generating at least one meal analysis dataset for at least one department. The at least one department refers to the departments corresponding to the at least one employee. The meal analysis data includes: employee information sets, dinner usage records for each employee, overtime hours for each employee, meal value outflow information for each department, and comparison information between dinner usage records and overtime hours. The information includes: the number of times employees handle their own meals and the first meal value outflow information. The distributed file system has at least one physical node for storing associated files. The at least one physical node includes: a file metadata management node and at least one data processing node. The sending unit 204 is configured to send each of the at least one meal analysis data to the terminal used by the corresponding department for the department to review the meal data and process the meal value outflow. The second acquisition unit 205 is configured to acquire at least one meal data return information sent by the terminal corresponding to the at least one department. The meal data return information includes: meal data confirmation information. The generation unit 206 is configured to generate a visualized meal report for the at least one department, the at least one meal analysis data, and the meal value outflow information in response to the determination that the at least one meal data return information indicates that the meal analysis data is correct and that the meal value outflow has been completed. The display unit 207 is configured to send the visualized meal report to the target terminal for visualization.

[0091] It is understandable that the units recorded in the dining report display device 200 are related to the reference. Figure 1 The steps in the described method correspond to each other. Therefore, the operations, features, and beneficial effects described above for the method also apply to the dining report display device 200 and the units contained therein, and will not be repeated here.

[0092] The following is for reference. Figure 3It shows a schematic diagram of the structure of an electronic device (e.g., an electronic device) 300 suitable for implementing some embodiments of the present disclosure. Figure 3 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of the embodiments of this disclosure.

[0093] like Figure 3 As shown, the electronic device 300 may include a processing unit (e.g., a central processing unit, a graphics processing unit, etc.) 301, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 302 or a program loaded from a storage device 308 into a random access memory (RAM) 303. The RAM 303 also stores various programs and data required for the operation of the electronic device 300. The processing unit 301, ROM 302, and RAM 303 are interconnected via a bus 304. An input / output (I / O) interface 305 is also connected to the bus 304.

[0094] Typically, the following devices can be connected to I / O interface 305: input devices 306 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 307 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 308 including, for example, magnetic tapes, hard disks, etc.; and communication devices 309. Communication device 309 allows electronic device 300 to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 3 An electronic device 300 with various devices is shown; however, it should be understood that it is not required to implement or possess all of the devices shown. More or fewer devices may be implemented or possessed alternatively. Figure 3 Each box shown can represent a device or multiple devices as needed.

[0095] In particular, according to some embodiments of this disclosure, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, some embodiments of this disclosure include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication device 309, or installed from storage device 308, or installed from ROM 302. When the computer program is executed by processing device 301, it performs the functions defined in the methods of some embodiments of this disclosure.

[0096] It should be noted that, in some embodiments of this disclosure, the computer-readable medium described above may be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In some embodiments of this disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In some embodiments of this disclosure, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium can be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wires, optical fibers, RF (radio frequency), etc., or any suitable combination thereof.

[0097] In some implementations, clients and servers can communicate using any currently known or future-developed network protocol such as HTTP (Hypertext Transfer Protocol) and can interconnect with digital data communication (e.g., communication networks) of any form or medium. Examples of communication networks include local area networks (“LANs”), wide area networks (“WANs”), the Internet (e.g., the Internet of Things), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future-developed networks.

[0098] The aforementioned computer-readable medium may be included in the aforementioned electronic device; or it may exist independently and not assembled into the electronic device. The aforementioned computer-readable medium carries one or more programs that, when executed by the electronic device, cause the electronic device to: in response to determining that a meal processing time has been reached, acquire a meal dataset from a meal data terminal and acquire employee attendance data for at least one employee from a user attendance terminal, wherein each meal dataset corresponds to a specific restaurant, and the meal data is the meal data of the at least one employee within a target time period; perform data preprocessing on the aforementioned meal dataset and employee attendance data to generate a preprocessed meal dataset and preprocessed attendance data; automatically import the aforementioned preprocessed meal dataset and preprocessed attendance data into an associated file stored in a distributed file system corresponding to the target meal analysis script, generating at least one meal analysis data corresponding to at least one department, wherein the at least one department refers to the departments corresponding to the at least one employee, and the meal analysis data includes: employee information sets, dinner usage records for each employee, overtime hours for each employee, and meal records for each department. The comparison information between value outflow information, dinner usage records, and overtime hours includes: the number of times employees self-process their meals and the first meal value outflow information. The aforementioned distributed file system has at least one physical node for storing associated files. The at least one physical node includes: a file metadata management node and at least one data processing node. Each meal analysis data in the at least one meal analysis data is sent to the terminal used by the corresponding department for the department to review the meal data and process the meal value outflow. At least one meal data return information sent by the corresponding terminal of the at least one department is obtained, wherein the meal data return information includes: meal data confirmation information. In response to determining that the at least one meal data return information indicates that the meal analysis data is correct and that the meal value outflow has been completed, a visual meal report is generated for the at least one department, the at least one meal analysis data, and the meal value outflow information. The visual meal report is sent to the target terminal for visualization.

[0099] Computer program code for performing operations of some embodiments of this disclosure can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0100] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0101] The units described in some embodiments of this disclosure can be implemented in software or hardware. The described units can also be housed in a processor; for example, a processor can be described as including a first acquisition unit, a processing unit, an import unit, a sending unit, a second acquisition unit, a generation unit, and a display unit. The names of these units do not necessarily limit the specific unit; for example, the display unit can also be described as "a unit that sends the aforementioned visualized dining report to a target terminal for visual display."

[0102] The functions described above in this document can be performed, at least in part, by one or more hardware logic components. For example, exemplary types of hardware logic components that can be used, without limitation, include: Field Programmable Gate Arrays (FPGAs), Application-Specific Integrated Circuits (ASICs), Application Standard Products (ASSPs), System-on-Chip (SoCs), Complex Programmable Logic Devices (CPLDs), and so on.

[0103] The above description is merely a selection of preferred embodiments of this disclosure and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of the invention involved in the embodiments of this disclosure is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the above-described inventive concept. For example, technical solutions formed by substituting the above-described features with (but not limited to) technical features with similar functions disclosed in the embodiments of this disclosure.

Claims

1. A method for displaying a dining report, comprising: In response to determining that the meal processing time has been reached, a meal dataset is obtained from the meal data terminal, and employee attendance data for at least one employee is obtained from the user attendance terminal, wherein each meal dataset corresponds to a restaurant, and the meal dataset is the meal data of the at least one employee within the target time period. The meal dataset and employee attendance data are preprocessed to generate preprocessed meal dataset and preprocessed attendance data; The preprocessed meal dataset and the preprocessed attendance data are automatically imported into the associated file stored in the distributed file system corresponding to the target meal analysis script, generating at least one meal analysis data for at least one department. The at least one department refers to the departments corresponding to the at least one employee. The meal analysis data includes: employee information set, dinner usage records for each employee, overtime hours for each employee, meal value outflow information for each department, and comparison information between dinner usage records and overtime hours. The comparison information includes: the number of times the employee handles meals independently and the first meal value outflow information. The distributed file system has at least one physical node for storing associated files. The at least one physical node includes: a file metadata management node and at least one data processing node. Each of the at least one dining analysis data points is sent to the terminal used by the corresponding department for the department to review the dining data and manage the outflow of dining value. Obtain at least one dining data return message sent by the terminal corresponding to the at least one department, wherein the dining data return message includes: dining data confirmation information; In response to determining that the at least one dining data return information characterizes the dining analysis data as correct and that the dining value outflow has been completed, a visual dining report is generated for the at least one department, the at least one dining analysis data, and the dining value outflow information. The visualized dining report is sent to the target terminal for visualization.

2. The method according to claim 1, wherein, The meal analysis data also includes: lunch usage records for each employee and information on the outflow of secondary meal value for each employee; and The step of automatically importing the preprocessed meal dataset and the preprocessed attendance data into the associated file stored in the distributed file system corresponding to the target meal analysis script, and generating at least one meal analysis data for at least one department, includes: The preprocessed meal dataset and the preprocessed attendance data are automatically imported into the associated file corresponding to the target meal analysis script. The lunch rule processing script included in the target meal analysis script is used to generate lunch usage records and second meal value outflow information for each employee. The lunch rule processing script indicates that lunch does not support determining the meal value outflow for employees when they dine at multiple restaurants at the same time.

3. The method according to claim 1, wherein, The comparison information corresponding to the target employees is generated through the following steps: In response to the target employee’s overtime count being higher than or equal to the number of dinners in the corresponding dinner usage record, the target value is set as the number of times the employee handles their own meals and the target value is set as the first meal value outflow information for the target employee. In response to the fact that the number of overtime hours for the target employee is less than the number of dinners consumed, the number of dinners consumed is subtracted from the number of overtime hours to obtain the subtraction value; The difference is used to determine the number of times a meal was handled independently. Based on the dinner usage records and the attendance data corresponding to the target employees in the pre-processed attendance data, determine the time information set that represents the mismatch between overtime and dinner usage; Based on the dinner usage records, determine the dinner value information set corresponding to the time information set; The value outflow object corresponding to each dinner value information in the dinner value information set is determined. The value outflow object is one of the following: employee object, department object, company object. The value outflow object corresponding to the dinner value information is confirmed by the object confirmation information received through the value outflow object confirmation page after dinner. At least one dinner value information whose corresponding value outflow object is an employee object is taken as at least one first dinner value information; At least one dinner value information whose corresponding value outflow object is a department object in the dinner value information set shall be regarded as at least one second dinner value information; At least one dinner value information whose corresponding value outflow object is a company object is taken as at least one third meal value information; The value information of at least one first dinner is added together to obtain a first sum value; The value information of at least one second dinner is added together to obtain a second summed value; The at least one third dinner value information is added together to obtain a third sum value; The association information between the first summed value and the employee object, the association information between the second summed value and the department object, and the association information between the third summed value and the company object are determined as the first meal value outflow information corresponding to the target employee.

4. The method according to claim 1, wherein, The generation of a visualized dining report for the at least one department, the at least one dining analysis data, and the dining value outflow information includes: For each of the at least one department, perform the following first generation step: Determine the dining analysis data corresponding to the aforementioned department as the target dining analysis data; Based on the target dining analysis data, generate the per capita dining data and departmental dining value information for the department; Determine the historical departmental dining value information sequence for the aforementioned department within a historical time period; The departmental meal value information is added to the historical departmental meal value information sequence to obtain the departmental meal value information sequence; Based on the dining value information sequence of the aforementioned departments, the future dining value information sequence within the target future time period is determined using a dining value information prediction model. Generate a first dining value description information for the dining value information sequence of the department and a second dining value description information for the future dining value information sequence; Based on the average meal per person, the departmental meal value information, the first meal value description information, and the second meal value description information, a departmental meal report is generated for the department: Based on the at least one dining analysis data, determine the dining location distribution information and dining value distribution information; A visual dining report is generated from the obtained dining reports of at least one department, the distribution information of the dining locations, and the distribution information of the dining value.

5. The method according to claim 1, wherein, The step of automatically importing the preprocessed meal dataset and the preprocessed attendance data into the associated file stored in the distributed file system corresponding to the target meal analysis script, and generating at least one meal analysis data for at least one department, includes: In response to determining that the number of employees corresponding to the at least one employee is lower than a first value, the preprocessed meal dataset and the preprocessed attendance data are automatically imported directly into the associated file in the file metadata management node corresponding to the target meal analysis script, generating at least one meal analysis data for at least one department. In response to determining that the number of employees corresponding to the at least one employee is higher than the first value, for each of the at least one department, the following second generation step is performed using the file metadata management node: In response to determining that the number of employees corresponding to the department is higher than the second value, the employee information set corresponding to the department is grouped into employee information groups, wherein the number of employees corresponding to each employee information group is less than the second value, wherein the second value is less than the division value, and the division value is the first value divided by the number of departments. In response to determining that the number of employees corresponding to the department is less than or equal to the second value, the employee information set corresponding to the department is determined as an employee information group set; Determine the number of groups corresponding to the employee information groups in at least one obtained employee information group set; Determine the group identifier corresponding to each employee information group in the at least one employee information group set; Set a predetermined number of associated files, wherein the predetermined number is the same as the number of groups; Using the file metadata management node, set the filenames corresponding to the predetermined number of associated files, wherein the text name is the group identifier; Using the file metadata management node, a predetermined number of copies of the target dining analysis script are allocated to the at least one data processing node, with each data processing node having a corresponding copy; Using the file metadata management node, the predetermined number of copies are bound to the predetermined number of associated files; Using the file metadata management node, the preprocessed meal dataset and the preprocessed attendance data are divided according to the grouping method corresponding to the at least one employee information set, so as to generate at least one meal data set and at least one attendance data set; based on the at least one meal data set, the at least one attendance data set, the predetermined number of copies, and the predetermined number of associated files, the file metadata management node is used to generate at least one meal analysis data set corresponding to at least one department.

6. The method according to claim 5, wherein, The step of generating at least one set of dining analysis data for at least one department, based on the at least one set of dining data, the at least one set of attendance data, the predetermined number of copies, and the predetermined number of associated files, using the file metadata management node, includes: For each employee information group in the at least one employee information group set, the corresponding meal data group and the corresponding attendance data group of the employee information group are automatically imported into an associated file named with the group identifier of the employee information group using the file metadata management node, so as to generate an employee meal analysis data group using the copy in the corresponding data processing node. Based on the obtained at least one set of employee meal analysis data, at least one set of meal analysis data corresponding to at least one department is generated using the department meal analysis script included in the target meal analysis script.

7. The method according to claim 1, wherein, The target dining analysis script supports intelligent recommendations for dining locations and times using recommendation models.

8. A dining report display device, comprising: The first acquisition unit is configured to acquire a meal dataset from a meal data terminal and acquire employee attendance data for at least one employee from a user attendance terminal in response to determining that the meal processing time has been reached. Each meal dataset corresponds to a restaurant, and the meal dataset is the meal data of the at least one employee within a target time period. The processing unit is configured to preprocess the dining dataset and employee attendance data to generate a preprocessed dining dataset and preprocessed attendance data. The import unit is configured to automatically import the preprocessed meal dataset and the preprocessed attendance data into the associated file stored in the distributed file system corresponding to the target meal analysis script, generating at least one meal analysis data corresponding to at least one department. The at least one department refers to the departments corresponding to the at least one employee. The meal analysis data includes: employee information set, dinner usage records for each employee, overtime hours for each employee, meal value outflow information for each department, and comparison information between dinner usage records and overtime hours. The comparison information includes: the number of times the employee self-processes meals and the first meal value outflow information. The distributed file system has at least one physical node for storing the associated file. The at least one physical node includes: a file metadata management node and at least one data processing node. The sending unit is configured to send each of the at least one dining analysis data to a terminal used by the corresponding department, so that the department can review the dining data and handle the outflow of dining value; The second acquisition unit is configured to acquire at least one dining data return information sent by the terminal corresponding to the at least one department, wherein the dining data return information includes: dining data confirmation information; The generation unit is configured to generate a visual dining report for the at least one department, the at least one dining analysis data, and the dining value outflow information in response to determining that the dining analysis data is correct and that the dining value outflow has been completed, based on the determination that the at least one dining data return information characterization is correct and the determination that the dining value outflow has been completed. The display unit is configured to send the visualized dining report to the target terminal for visualization.

9. An electronic device, comprising: One or more processors; Storage device, on which one or more programs are stored, 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 1-7.

10. A computer-readable medium having a computer program stored thereon, wherein, When the program is executed by the processor, it implements the method as described in any one of claims 1-7.

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