Statistical method, terminal device, and computer-readable storage medium

Abstract

The application discloses a statistical method, comprising the following steps: pre-encoding service areas corresponding to respective volunteer management departments to generate volunteer management department tables corresponding to respective service areas; when receiving a volunteer statistics instruction, obtaining a target service area of a volunteer area management department to be counted according to the volunteer management department table; obtaining volunteer information associated with a volunteer to be counted from a national volunteer table according to the target service area; performing data analysis on the obtained volunteer information; performing statistical analysis according to a statistical dimension in the volunteer statistics instruction, generating a corresponding analysis report according to a statistical analysis result, and displaying the analysis report on an information system so as to enable a user to manage all volunteers in a target service area under the user's jurisdiction, wherein the volunteer statistics instruction comprises the statistical dimension. The application also discloses a terminal device and a computer readable storage medium, and realizes automatic statistics and analysis of volunteers.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, and in particular to statistical methods, terminal devices, and computer-readable storage media. Background Technology

[0002] With the organization and implementation of various large-scale events, a large volunteer service team now exists throughout the country. Every year, a large number of enthusiastic volunteers join and continuously participate in various volunteer service activities both domestically and internationally. Volunteer service activities have always been an important part of social activities.

[0003] However, the lack of systematic and standardized methods for volunteer statistics and analysis currently hinders management departments in various regions from gaining a clear understanding of the service status and number of volunteers within their areas, thus impeding the implementation of volunteer service work. In other words, it is usually impossible to effectively display information on all volunteers within a given jurisdiction, and the information available to management departments cannot clearly reflect the participation of volunteers in volunteer service activities, making volunteer management difficult.

[0004] The above content is only used to help understand the technical solution of the present invention and does not represent an admission that the above content is prior art. Summary of the Invention

[0005] The main objective of this invention is to provide a statistical method, terminal device, and computer-readable storage medium, which aim to achieve the classification and statistics of volunteers to improve the management efficiency of volunteers.

[0006] To achieve the above objectives, the present invention provides a statistical method, the steps of which include:

[0007] Pre-code the service areas corresponding to each volunteer management department to generate a table of volunteer management departments corresponding to each service area;

[0008] Upon receiving a volunteer statistics instruction, the target service area of ​​the department to be counted is obtained from the volunteer management department table.

[0009] Based on the target service area, obtain the volunteer information associated with the volunteers to be counted from the national volunteer table, wherein the national volunteer table includes the volunteer information of all stored volunteers;

[0010] The obtained volunteer information is then parsed.

[0011] Statistical analysis is performed based on the statistical dimensions in the volunteer statistical instructions, and corresponding analysis reports are generated based on the statistical analysis results. The analysis reports are then displayed on the information system so that users can manage all volunteers within their designated target service area. The volunteer statistical instructions include statistical dimensions.

[0012] Optionally, statistical analysis is performed based on the statistical dimensions in the volunteer statistical instructions, and corresponding analysis reports are generated based on the statistical analysis results, including:

[0013] The characteristic indicators of the volunteers to be counted are determined based on the volunteer information and the statistical dimensions.

[0014] The feature indicators are used as input to a preset model, and the volunteer type corresponding to each volunteer to be counted is determined through the preset model.

[0015] Based on the distribution of volunteers corresponding to the volunteer types, statistical analysis is performed on the volunteers to be counted, and an analysis report is generated based on the statistical analysis results.

[0016] Optionally, the step of determining the characteristic indicators of the volunteers to be counted based on the volunteer information and the statistical dimensions includes:

[0017] Filter out the volunteer information corresponding to the statistical dimensions from the volunteer information;

[0018] The volunteer information corresponding to the statistical dimension is determined as the characteristic index of each volunteer to be counted.

[0019] Optionally, the step of using the feature indicators as input to a preset model and determining the volunteer type corresponding to each volunteer to be counted through the preset model includes:

[0020] Obtain the classification intervals corresponding to the statistical dimensions and the threshold ranges corresponding to each classification interval;

[0021] The feature indicators are compared with the threshold ranges corresponding to the classification intervals to determine the classification intervals corresponding to each feature indicator.

[0022] The volunteer type corresponding to the preset classification interval is determined according to the correspondence between the classification interval and the volunteer type;

[0023] The volunteer type corresponding to the classification interval is determined as the volunteer type of the volunteers to be counted.

[0024] Optionally, the preset model includes a clustering model, and the step of using the feature index as input to the preset model to determine the volunteer type corresponding to each volunteer to be counted includes:

[0025] Determine the number of clusters corresponding to the statistical dimension;

[0026] The feature indicators are clustered according to the number of clusters to generate each target cluster;

[0027] The volunteer type is determined based on the target cluster to which the volunteers to be counted belong.

[0028] Optionally, the step of performing statistical analysis on the volunteers to be counted based on the volunteer distribution corresponding to the volunteer type, and generating an analysis report based on the statistical analysis results, includes:

[0029] The volunteers to be counted for each classification interval are determined based on the characteristic indicators contained in each classification interval.

[0030] The distribution of volunteers for each volunteer type is determined based on the volunteers to be counted for each category interval.

[0031] Based on the volunteer distribution, the number of volunteers corresponding to each volunteer type is obtained, and the statistical analysis results are determined based on the number of volunteers corresponding to each volunteer type.

[0032] The analysis report is generated based on the statistical analysis results.

[0033] Optionally, the step of performing statistical analysis on the volunteers to be counted based on the volunteer distribution corresponding to the volunteer type, and generating an analysis report based on the statistical analysis results, includes:

[0034] The number of volunteers to be counted for each volunteer type is determined based on the number of feature indicators contained in each target cluster, and the number of volunteers to be counted for each volunteer type is determined as the volunteer distribution.

[0035] The statistical analysis results are determined based on the number of volunteers to be counted for each volunteer type.

[0036] The analysis report is generated based on the statistical analysis results.

[0037] Optionally, the step of displaying the analysis report on the information system includes:

[0038] The analysis report is output in a preset display mode, which includes at least one of a list mode, a tree diagram mode, and a pie chart mode.

[0039] In addition, to achieve the above objectives, the present invention also provides a terminal device, the terminal device comprising: a memory, a processor, and a statistical program stored in the memory and executable on the processor, wherein the volunteer statistical program, when executed by the processor, implements the steps of the statistical method as described above.

[0040] In addition, to achieve the above objectives, the present invention also provides a computer-readable storage medium storing a statistical program, which, when executed by a processor, implements the steps of the statistical method as described above.

[0041] This invention proposes a statistical method, terminal device, and computer-readable storage medium. The method involves pre-coding the service areas of each volunteer management department to generate a table of volunteer management departments for each service area. Upon receiving a volunteer statistics instruction, the method retrieves the target service area of ​​the department to be counted from the volunteer management department table. Based on the target service area, it retrieves volunteer information associated with the volunteer to be counted from a national volunteer table, which includes all stored volunteer information. The method then parses the retrieved volunteer information. Statistical analysis is performed according to the statistical dimensions specified in the volunteer statistics instruction, and a corresponding analysis report is generated based on the analysis results. This analysis report is then displayed on the information system, enabling users to manage all volunteers within their designated target service area. The volunteer statistics instruction includes statistical dimensions.

[0042] The present invention has the following beneficial effects:

[0043] 1. This invention classifies and displays volunteer information (such as volunteer name, nationality, political affiliation, and volunteer service duration), making it easier for management departments to have a more intuitive and clear understanding of volunteer information within a region. It can also proactively provide different management operations for different types of volunteers, thus enabling precise management of different types of volunteers, assisting management departments in standardizing volunteer service work, and promoting the development of volunteer service.

[0044] 2. This invention uses a self-developed algorithm to comprehensively display information on all volunteers within the corresponding area of ​​the management department. The displayed information can clearly and effectively reflect the service status of volunteers, making it easier for the management department to issue appropriate policies based on the classification of volunteers and to carry out appropriate management actions based on the relevant data of volunteers.

[0045] 3. After logging into the information system, the management department can accurately query the volunteer information of all volunteers in the jurisdiction under its management, which can fully reflect the volunteers' participation in volunteer service activities. Attached Figure Description

[0046] Figure 1 This is a schematic diagram of the terminal device structure of the hardware operating environment involved in the embodiments of the present invention;

[0047] Figure 2 This is a flowchart illustrating the first embodiment of the statistical method of the present invention;

[0048] Figure 3 Example diagram of a volunteer management department table;

[0049] Figure 4 This is a detailed flowchart of step S50 in the first embodiment of the statistical method of the present invention;

[0050] Figure 5 This is a detailed flowchart of step S52 in the first embodiment of the statistical method of the present invention;

[0051] Figure 6 This is a detailed flowchart of step S53 in the first embodiment of the statistical method of the present invention;

[0052] Figures 7a-7b This is a schematic diagram of the analysis report for the first embodiment of the statistical method of the present invention;

[0053] Figure 8 This is a detailed flowchart of step S52 in the second embodiment of the statistical method of the present invention;

[0054] Figure 9 This is a detailed flowchart of step S53 in the second embodiment of the statistical method of the present invention;

[0055] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0056] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0057] The main solution of this invention is as follows: First, pre-encode the service areas corresponding to each volunteer management department to generate a volunteer management department table for each service area. Second, upon receiving a volunteer statistics instruction, obtain the target service area of ​​the department to be counted based on the volunteer management department table. Third, obtain the volunteer information associated with the volunteer to be counted from the national volunteer table based on the target service area, wherein the national volunteer table includes the volunteer information of all stored volunteers. Fourth, parse the obtained volunteer information. Fifth, perform statistical analysis according to the statistical dimensions in the volunteer statistics instruction, generate a corresponding analysis report based on the statistical analysis results, and display the analysis report on the information system so that users can manage all volunteers within their managed target service area. The volunteer statistics instruction includes statistical dimensions.

[0058] like Figure 1 As shown, Figure 1 This is a schematic diagram of the terminal device structure of the hardware operating environment involved in the embodiments of the present invention.

[0059] The terminal device in this embodiment of the invention can be a PC, or a smartphone, tablet computer, portable computer, or other terminal device.

[0060] like Figure 1 As shown, the terminal device may include: a processor 1001, such as a CPU; a network interface 1004; a user interface 1003; a memory 1005; and a communication bus 1002. The communication bus 1002 is used to enable communication between these components. The user interface 1003 may include a display screen and an input unit such as a keyboard; optionally, the user interface 1003 may also include a standard wired interface or a wireless interface. The network interface 1004 may optionally include a standard wired interface or a wireless interface (such as a Wi-Fi interface). The memory 1005 may be a high-speed RAM or a stable memory, such as a disk storage device. Optionally, the memory 1005 may also be a storage device independent of the aforementioned processor 1001.

[0061] Those skilled in the art will understand that Figure 1 The terminal device structure shown does not constitute a limitation on the terminal device and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0062] like Figure 1 As shown, the memory 1005, which serves as a computer storage medium, may include an operating system, a network communication module, a user interface module, and a statistical program.

[0063] exist Figure 1In the terminal device shown, the network interface 1004 is mainly used to connect to the backend server and communicate with it; the user interface 1003 is mainly used to connect to the client (user terminal) and communicate with it; and the processor 1001 can be used to call the statistical program stored in the memory 1005 and perform the following operations:

[0064] Pre-code the service areas corresponding to each volunteer management department to generate a table of volunteer management departments corresponding to each service area;

[0065] Upon receiving a volunteer statistics instruction, the target service area of ​​the department to be counted is obtained from the volunteer management department table.

[0066] Based on the target service area, obtain the volunteer information associated with the volunteers to be counted from the national volunteer table, wherein the national volunteer table includes the volunteer information of all stored volunteers;

[0067] The obtained volunteer information is then parsed.

[0068] Statistical analysis is performed based on the statistical dimensions in the volunteer statistical instructions, and corresponding analysis reports are generated based on the statistical analysis results. The analysis reports are then displayed on the information system so that users can manage all volunteers within their designated target service area. The volunteer statistical instructions include statistical dimensions.

[0069] The lack of systematic and standardized methods for collecting and analyzing volunteer data hinders management departments in various regions from gaining a clear understanding of the service status and number of volunteers within their areas, thus impeding the effective implementation of volunteer service work. In other words, it is typically impossible to effectively display information on all volunteers within a given jurisdiction, and the information available to management departments often fails to clearly reflect volunteer participation, hindering effective volunteer management. Therefore, this application innovatively collects and organizes regional codes corresponding to the areas of each management department. Based on these codes, a volunteer regional management table is generated for each service area. Each table records the volunteer information of several volunteers in each area, with each volunteer associated with a specific area. Volunteer data is then categorized using statistical dimensions to generate and display analytical reports. These reports allow management departments to develop different management approaches for various volunteer types, enabling accurate and appropriate management of different volunteer teams.

[0070] First Embodiment

[0071] Reference Figure 2The first embodiment of the statistical method of the present invention provides a method comprising the following steps:

[0072] Step S10: Pre-assign regional codes to the service areas corresponding to each volunteer management department to generate a table of volunteer management departments corresponding to each service area;

[0073] Step S20: Upon receiving the volunteer statistics instruction, obtain the target service area of ​​the volunteers to be counted based on the volunteer management department table;

[0074] Step S30: Obtain volunteer information associated with the volunteers to be counted from the national volunteer table according to the target service area, wherein the national volunteer table includes volunteer information of all stored volunteers;

[0075] Step S40: Perform data parsing on the obtained volunteer information;

[0076] Step S50: Perform statistical analysis according to the statistical dimensions in the volunteer statistical instruction, generate a corresponding analysis report based on the statistical analysis results, and display the analysis report on the information system so that users can manage all volunteers in the target service area under their jurisdiction. The volunteer statistical instruction includes statistical dimensions.

[0077] In this embodiment, the information system applied to the terminal device stores all volunteer information on a storage device on a remote server. The storage device includes, but is not limited to, a memory. The information system accesses the storage device through an interface protocol to query volunteer information. The volunteer information includes, but is not limited to, volunteer name, gender, date of birth, service area, ID number, service category, special skills, volunteer service duration, and real-name status. Different volunteers correspond to different service areas. To facilitate the management of volunteers in the service areas under the jurisdiction of the volunteer management department, this embodiment pre-codes the service areas corresponding to each volunteer management department to generate a volunteer management department table corresponding to each service area. Different service areas correspond to different area codes. One volunteer management department corresponds to at least one service area. The volunteer management department table includes the area code corresponding to the service area under the jurisdiction of the volunteer management department, and / or the volunteers in the service area under its jurisdiction, and / or the volunteer information of the volunteers in the service area under its jurisdiction. For example, a volunteer management department is the Beijing Municipal Management Department. The service area corresponding to the Beijing Municipal Management Department may include Dongcheng District, Xicheng District, Chaoyang District, Fengtai District, etc.

[0078] Optionally, before receiving the user's volunteer statistics instruction, the information system may also receive the user's login instruction, determine the volunteer management department to which the user belongs based on the login instruction, obtain the corresponding volunteer management department table based on the user's volunteer management department, and display the volunteer information of each service area and / or each volunteer based on the volunteer management department table, so as to facilitate the user to promptly query the volunteer information of all volunteers in the service areas under the jurisdiction of the volunteer management department, as per [reference]. Figure 3 , Figure 3 A sample diagram showing the volunteer management department table is provided.

[0079] Optionally, after the information system receives the volunteer statistics instruction, it determines the management department to be counted based on the volunteer statistics instruction. After determining the management department to be counted, it determines the volunteer management department corresponding to the management department to be counted based on the stored table of various volunteer management departments. It then determines the target service area of ​​the management department to be counted based on the volunteer management department corresponding to the management department to be counted. The target service area is the service area to which the volunteers to be counted belong.

[0080] Optionally, after obtaining the target service area, the system retrieves volunteer information associated with the volunteers to be counted from the national volunteer table based on the target service area. The national volunteer table includes all stored volunteer information, and the service area to which the volunteers to be counted belong is the target service area. Specifically, the national volunteer table summarizes the volunteer information of all volunteers and is stored on a storage device on a remote server. The storage device includes, but is not limited to, a memory. The information system accesses the storage device through an interface protocol to obtain the national volunteer table, and then filters out the volunteers to be counted based on the national volunteer table, whereby the service area in the volunteer information is consistent with the target service area.

[0081] Optionally, the national volunteer table can also be stored in an Elasticsearch search engine. Each volunteer's information in the national volunteer table is used to generate a corresponding index, and both the index and the volunteer information are stored in the Elasticsearch search engine. When it is necessary to filter out volunteers who meet the filtering criteria, the target index corresponding to the filtering criteria is determined from the various indexes stored in the Elasticsearch search engine. The volunteer to be counted and the volunteer information associated with the volunteer to be counted are then determined based on the target index. Based on this embodiment, using the Elasticsearch search engine to store volunteer information improves the efficiency of obtaining the volunteer information associated with the volunteer to be counted during actual statistics, thereby improving statistical efficiency.

[0082] Optionally, after obtaining the volunteer information associated with the volunteer to be counted, the obtained volunteer information is parsed. Optionally, the volunteer information is stored in the form of fields, for example: when the gender is female, field 1; when the gender is male, field 2; when the service area is Dongcheng District, Beijing, field AA; when the service area is Chaoyang District, Beijing, field BB. Based on this, after obtaining the fields corresponding to the volunteer information, the fields corresponding to the volunteer information are parsed to determine the semantics of each field, and complete volunteer information is generated according to the semantics.

[0083] Optionally, after parsing the obtained volunteer information, refer to... Figure 4 The steps for statistical analysis based on the statistical dimensions in the volunteer statistical instructions include:

[0084] Step S51: Determine the characteristic indicators of the volunteers to be counted based on the volunteer information and the statistical dimensions;

[0085] Step S52: Use the feature indicators as input to the preset model, and determine the volunteer type corresponding to each volunteer to be counted through the preset model;

[0086] Step S53: Based on the volunteer distribution corresponding to the volunteer type, perform statistical analysis on the volunteers to be counted, and generate an analysis report based on the statistical analysis results.

[0087] Optionally, the characteristic indicators of the volunteers to be counted are determined based on the volunteer information and the volunteer statistical instructions. The characteristic indicators are determined based on the volunteer information. The volunteer statistical instructions also include statistical dimensions. Specifically, the statistical dimensions corresponding to the volunteer statistical instructions are obtained; the volunteer information corresponding to the statistical dimensions is filtered from the volunteer information, and the volunteer information corresponding to the statistical dimensions is determined as the characteristic indicators of each volunteer to be counted. The volunteer statistical instructions include statistical dimensions, which include, but are not limited to, service area dimension, age dimension, service category dimension, characteristic skill dimension, gender dimension, and service duration dimension. Optionally, the statistical dimension can be one of the service area dimension, age dimension, service category dimension, characteristic skill dimension, gender dimension, and service duration dimension, or it can be a combination of the area dimension, age dimension, service category dimension, characteristic skill dimension, gender dimension, and service duration dimension, for example, a combination of the area dimension and the age dimension.

[0088] Optionally, after determining the statistical dimension, volunteer information corresponding to the statistical dimension is filtered from the volunteer information, and the volunteer information corresponding to the statistical dimension is determined as the feature index of each volunteer to be statistically analyzed. For example, when the statistical dimension is the service area dimension, the volunteer information corresponding to the statistical dimension is the service area of ​​each volunteer, and the feature index is the service area of ​​the volunteer.

[0089] Optionally, after determining the feature indicators, the feature indicators are used as input to a preset model, and the volunteer type corresponding to each volunteer to be counted is determined by the preset model. Optionally, the preset model is used to classify each volunteer to be counted according to the feature indicators corresponding to each volunteer to be counted, so as to determine the volunteer type corresponding to each volunteer to be counted.

[0090] Alternatively, in one embodiment, reference is made to Figure 5 Step S52 includes the following steps:

[0091] Step S521: Obtain the classification intervals corresponding to the statistical dimensions and the threshold ranges corresponding to each classification interval;

[0092] Step S522: Compare the feature indicators with the threshold range corresponding to the classification interval to determine the classification interval corresponding to each feature indicator;

[0093] Step S523: Determine the volunteer type corresponding to the classification interval according to the preset correspondence between classification intervals and volunteer types;

[0094] Step S524: Determine the volunteer type corresponding to the classification interval as the volunteer type of the volunteers to be counted.

[0095] Optionally, when determining the statistical dimension, the corresponding classification interval and the threshold range of each classification interval are determined. Different statistical dimensions correspond to different classification intervals, and different classification intervals correspond to different threshold ranges. For example, when the statistical dimension is the service area dimension, a classification interval can be set according to different service areas. In this case, the threshold range corresponding to the classification interval is the boundary position of the service area. When the statistical dimension is the duration dimension, a classification interval can be set according to different durations, such as [0,20], [20,40], [40,...]. There is no limitation here. When the statistical dimension is a combination of the region dimension and the age dimension, the classification interval includes a first classification interval and a second classification interval. The first classification interval is used to classify each volunteer to be counted for the first time. After the first classification is completed, the volunteers to be counted in each first classification interval are classified according to the second classification interval.

[0096] Optionally, after obtaining the classification intervals and the threshold ranges corresponding to each classification interval, the feature indicators are compared with the threshold ranges corresponding to the classification intervals to determine the classification intervals corresponding to each feature indicator. The classification intervals corresponding to each feature indicator are the classification intervals to which the resource to be statistically analyzed belongs.

[0097] Optionally, after determining the classification interval to which each volunteer to be counted belongs, the statistical device also stores a preset correspondence between classification intervals and volunteer types, and then determines the volunteer type corresponding to the classification interval to which the volunteer to be counted belongs based on the preset correspondence between classification intervals and volunteer types, and determines the volunteer type corresponding to the classification interval to which the volunteer to be counted belongs as the volunteer type of the volunteer to be counted.

[0098] Optionally, after determining the volunteer type of each volunteer to be counted, statistical analysis is performed on the volunteers to be counted based on the volunteer distribution corresponding to the volunteer type, and an analysis report is generated based on the statistical analysis results. Specifically, refer to... Figure 6 Step S53 includes:

[0099] Step S531: Determine the volunteers to be counted for each classification interval based on the feature indicators contained in each classification interval.

[0100] Step S532: Determine the volunteer distribution for each volunteer type based on the volunteers to be counted for each classification interval.

[0101] Step S533: Obtain the number of volunteers corresponding to each volunteer type based on the volunteer distribution, and determine the statistical analysis result based on the number of volunteers corresponding to each volunteer type.

[0102] Step S534: Generate the analysis report based on the statistical analysis results.

[0103] Optionally, after summarizing each feature indicator into its corresponding classification interval, based on the correspondence between the feature indicators and each volunteer to be counted, the volunteers to be counted in each classification interval are determined according to the feature indicators contained in each classification interval. Since different classification intervals correspond to different volunteer types, the volunteer distribution corresponding to each volunteer type can be determined based on the volunteers to be counted in each classification interval. The volunteer distribution includes the number of volunteers to be counted corresponding to each volunteer type.

[0104] Optionally, after determining the distribution of volunteers for each volunteer type, the statistical analysis results are determined based on the number of volunteers to be counted for each volunteer type. Specifically, when the statistical dimension is a regional dimension, each regional dimension includes the classification intervals corresponding to each province, that is, the volunteer types include different provinces, and the statistical analysis results include: Jiangsu Province: 100 volunteers, Guangdong Province: 200 volunteers. Alternatively, when the regional dimension is a year dimension, each year dimension corresponds to the classification intervals corresponding to each year, that is, the volunteer types include different years, and the statistical analysis results include: 2000, 100 volunteers; 2001, 105 volunteers, etc.

[0105] Optionally, the method of determining the statistical analysis results based on the number of volunteers to be counted for each volunteer type also includes determining the proportion of each volunteer type based on the number of volunteers corresponding to each volunteer type and the number of volunteers to be counted, and generating the statistical analysis results based on the proportion of each volunteer type.

[0106] Optionally, after determining the statistical analysis results, the analysis report is generated based on the statistical analysis results. The analysis report is used to statistically analyze the volunteers to be analyzed. Specifically, each volunteer to be analyzed can be added to the analysis report according to different volunteer types.

[0107] Optionally, the analysis report can also be generated by comparing the number of volunteers corresponding to each volunteer type to sort each volunteer type, and then adding each volunteer to be counted to the analysis report according to the sorting and the volunteer type.

[0108] Optionally, after generating the analysis report, the analysis report is displayed on the information system so that users can manage all volunteers within their designated target service area. Specifically, the analysis report is output in a preset display format, which includes at least one of a list format, a tree diagram format, and a pie chart format. (See reference...) Figures 7a-7b , Figures 7a-7b The diagram illustrates the output of analysis reports in different preset display modes.

[0109] Understandably, classifying and analyzing volunteers according to different statistical dimensions allows users to quickly understand the relationship between the volunteers and the statistical dimensions based on the analysis reports, thus intuitively displaying the key information of the volunteers and facilitating management departments to understand the volunteers' volunteer service situation.

[0110] Example 1: When the statistical dimension is the service area dimension, the relationship between the number of volunteers to be counted and the geographical location is calculated based on the number of volunteers to be counted in each region.

[0111] Example 2: When the statistical dimension is the year dimension, the annual growth rate of the volunteers to be counted is determined according to the number of volunteers to be counted in each year. The annual growth rate can be used to know how the number of volunteers changes with the increase of the year.

[0112] Example 3: When the statistical dimension is a combination of the service category dimension and the service area dimension, the distribution of volunteers of different service categories in each service area can be known based on the number of volunteers to be counted for each volunteer type.

[0113] Example 4: When the statistical dimension is gender, the relationship between the number of volunteers and the gender factor can be obtained based on the number of volunteers to be counted for different genders.

[0114] Optionally, the above examples are merely illustrative. The information system in this embodiment of the application performs classification and statistical analysis on each resource to be counted through volunteer statistics instructions. Based on the volunteers to be counted after classification and statistical analysis, the volunteer type corresponding to each resource to be counted and the distribution of volunteers corresponding to each volunteer type can be determined. Then, the information system can perform corresponding operations on volunteers of different volunteer types. For example, when the statistical dimension is the service category dimension, service items of different service categories are assigned to volunteers corresponding to different volunteer types. When the statistical dimension is the region dimension, service items of different regions are assigned to volunteers corresponding to different volunteer types. Volunteers to be assigned can also be assigned according to volunteers corresponding to different volunteer types. When the statistical dimension is the real-name status dimension, when the volunteer type is real-name status, corresponding service items or corresponding volunteer teams are assigned to volunteers in real-name status. Automatic real-name authentication is performed on volunteers in non-real-name status, or the volunteer is deleted, etc. In addition, after outputting the analysis report, the system can also receive and respond to user management operations on each categorized volunteer to be counted, record the management operations, and store the management operations in the information system. This allows the information system to directly perform operations on the categorized volunteers to be counted based on the management operations, without requiring user intervention.

[0115] Optionally, while outputting the analysis report, this embodiment can also classify and store the volunteers to be counted after classification and statistics. The Elasticsearch search engine consists of an Elasticsearch search engine cluster, which includes multiple storage nodes, each storing different data. After classifying and counting each volunteer, the volunteers corresponding to each volunteer type are determined, and a corresponding index table is generated for each volunteer type. Volunteers belonging to the same volunteer type are grouped into the same index table. The index table includes indexes associated with each volunteer to be counted. The index of each volunteer to be counted can be determined based on the volunteer information associated with the volunteer to be counted. The index can be a field corresponding to the volunteer's name or a field corresponding to the volunteer's gender, which is not limited here. Optionally, a volunteer to be counted can be associated with at least one index, and each index associated with the volunteer to be counted corresponds to the same volunteer to be counted. After generating the index table and the indexes corresponding to each volunteer to be counted, the volunteers to be counted are classified and stored in the Elasticsearch search engine according to different index tables.

[0116] In this embodiment, a volunteer management department table is pre-defined for the service areas under the jurisdiction of each management department, and a national volunteer table is generated based on the volunteer information of all volunteers. The volunteer management department table includes the service areas under the jurisdiction of each management department, and the national volunteer table includes the volunteer information of all volunteers. Upon receiving a team statistics instruction, the target service area of ​​the management department to be counted is obtained through the volunteer management department table corresponding to the management department to be counted. Then, the volunteer to be counted and the volunteer information associated with each volunteer to be counted in the target service area are obtained. The characteristic indicators corresponding to each volunteer to be counted are filtered according to the statistical dimensions corresponding to the team statistics instruction. The characteristic dimensions are used as input to a preset model. The volunteer type corresponding to each volunteer to be counted is determined through the preset model. Then, the volunteer to be counted is statistically analyzed according to the volunteer distribution corresponding to each volunteer type, and an analysis report is generated based on the statistical analysis results. This embodiment performs statistical analysis on volunteers to be counted from multiple dimensions, which facilitates the management department to issue appropriate policies based on relevant circumstances and to conduct appropriate management actions based on relevant volunteer data. At the same time, it also intuitively displays the volunteer service status of each volunteer to be counted, which is convenient for the management department to understand the volunteer service status of each volunteer in the service areas under its jurisdiction.

[0117] Second Embodiment

[0118] Reference Figure 8Based on the first embodiment, step S52 includes:

[0119] Step S525: Determine the number of clusters corresponding to the statistical dimension;

[0120] Step S526: Cluster the feature indicators according to the number of clusters to generate each target cluster;

[0121] Step S527: Determine the volunteer type based on the target cluster to which the volunteers to be counted belong.

[0122] In this application embodiment, the preset model can be a clustering model, which is obtained by iteratively training the training data using a preset clustering algorithm. The preset clustering algorithm can be at least one of KMeans clustering algorithm, hierarchical clustering algorithm, and density clustering algorithm. Preferably, this application uses KMeans clustering algorithm as an example for analysis.

[0123] Optionally, the number of clusters K can be directly determined based on the statistical dimension. For example, if the statistical dimension includes a gender dimension, the K value is 2. Alternatively, the number of clusters K can also be determined according to the elbow rule. Specifically, a range of k values ​​is randomly determined, a loss function is obtained, and the sum of squared errors for each k value in the range of k values ​​is determined based on the loss function. The k value corresponding to the sum of squared errors is then determined as the number of clusters.

[0124] Optionally, after determining the number of clusters, the method of clustering the feature indicators according to the number of clusters includes selecting a number of feature indicators from the feature indicators according to the maximum distance method based on the number of clusters, using the selected feature indicators as cluster centers, clustering the feature indicators other than the cluster centers according to the initial cluster centers, that is, obtaining the distance between each feature indicator other than the cluster centers and the initial cluster centers, assigning each feature indicator to the cluster closest to the cluster centers, determining the average feature indicator of each cluster according to the feature indicators contained in each cluster after obtaining each cluster, replacing the cluster centers according to the average feature indicator of each cluster, and then re-clustering each feature indicator according to the cluster centers, and repeating this process until the clustering condition is met. The clustering condition can be that the number of clusterings reaches a preset number of clusterings, or that the difference between the final average feature indicator and the cluster centers is less than a set threshold.

[0125] Optionally, after the clustering conditions are met, the last obtained clusters are determined as the target clusters corresponding to the volunteers to be counted. Each target cluster includes several feature indicators, and the similarity of feature indicators in the same target cluster is higher than the similarity of feature indicators in different target clusters.

[0126] Optionally, after generating the target clusters, based on the association between the feature indicators and the corresponding volunteers to be counted, and after determining the feature indicators contained in each target cluster, the target cluster to which each volunteer to be counted belongs can be determined according to the volunteers to be counted associated with the feature indicators. Then, the volunteer type can be determined according to the target cluster to which the volunteer to be counted belongs. Specifically, the volunteer type corresponding to the target cluster is determined according to the cluster center corresponding to the target cluster, and then the volunteer type corresponding to the volunteer to be counted is determined according to the volunteer type corresponding to each target cluster. For example, if the cluster centers are 25 years old, 40 years old, and 60 years old respectively, the volunteer type corresponding to each target cluster can be determined as youth type, middle-aged type, and elderly type.

[0127] Optionally, after determining the volunteer type for each volunteer, refer to Figure 9 Step S53 includes:

[0128] Step S535: Determine the number of volunteers to be counted for each volunteer type based on the number of feature indicators contained in each target cluster, and determine the number of volunteers to be counted for each volunteer type as the volunteer distribution.

[0129] Step S536: Determine the statistical analysis results based on the number of volunteers to be counted for each volunteer type;

[0130] Step S537: Generate the analysis report based on the statistical analysis results.

[0131] Optionally, the volunteer distribution for each volunteer type is determined based on the number of feature indicators included in the target cluster, wherein the volunteer distribution includes the number of volunteers to be counted for each volunteer type.

[0132] Optionally, after determining the distribution of volunteers corresponding to each volunteer type, the statistical analysis results are determined according to the analysis and statistical method of the first embodiment, and then the analysis report is generated based on the statistical analysis results. This has been described in detail in the first embodiment and will not be repeated here.

[0133] In this embodiment, after obtaining the corresponding feature indicators, the feature indicators are clustered according to a preset clustering algorithm to generate multiple target clusters. The feature indicators in the same target cluster have a high degree of similarity. Based on dividing each volunteer to be counted into a target cluster, the user can set corresponding management strategies for each volunteer to be counted according to each target cluster, thereby improving management efficiency.

[0134] Furthermore, embodiments of the present invention also propose a computer-readable storage medium storing a statistical program, which, when executed by a processor, implements the steps of the various embodiments described above.

[0135] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or system 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 system. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or system that includes that element.

[0136] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0137] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) as described above, and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in the various embodiments of the present invention.

[0138] The above are merely preferred embodiments of the present invention and do not limit the scope of the patent. Any equivalent structural or procedural transformations made based on the description and drawings of the present invention, or direct or indirect applications in other related technical fields, are similarly included within the scope of patent protection of the present invention.

Claims

1. A statistical method applied to an information system for terminal equipment, characterized in that, The steps of the statistical method include: Pre-code the service areas corresponding to each volunteer management department to generate a table of volunteer management departments corresponding to each service area; Upon receiving a volunteer statistics instruction, the target service area of ​​the department to be counted is obtained from the volunteer management department table. Based on the target service area, obtain the volunteer information associated with the volunteers to be counted from the national volunteer table, wherein the national volunteer table includes the volunteer information of all stored volunteers; The obtained volunteer information is then parsed. Statistical analysis is performed according to the statistical dimensions in the volunteer statistical instructions, and corresponding analysis reports are generated based on the statistical analysis results. The analysis reports are then displayed on the information system so that users can manage all volunteers within their designated target service area. The volunteer statistical instructions include statistical dimensions. The process of performing statistical analysis based on the statistical dimensions specified in the volunteer statistical instructions, and generating corresponding analysis reports based on the statistical analysis results, includes: The volunteer information corresponding to the statistical dimensions is filtered from the volunteer information. The statistical dimensions are one of the following: service area dimension, age dimension, service category dimension, characteristic skill dimension, gender dimension, and service duration dimension, or a combination of the following dimensions: area dimension, age dimension, service category dimension, characteristic skill dimension, gender dimension, and service duration dimension. The volunteer information corresponding to the statistical dimensions is determined as the characteristic indicators of each volunteer to be statistically analyzed. The feature indicators are used as input to a preset model, and the volunteer type corresponding to each volunteer to be counted is determined through the preset model. Based on the volunteer distribution corresponding to the volunteer type, statistical analysis is performed on the volunteers to be counted, and an analysis report is generated based on the statistical analysis results. The volunteer distribution includes the number of volunteers to be counted for each volunteer type. The preset model includes a clustering model, and the step of using the feature indicators as input to the preset model to determine the volunteer type corresponding to each volunteer to be counted includes: Determine the number of clusters corresponding to the statistical dimension; The feature indicators are clustered according to the number of clusters to generate each target cluster; The volunteer type is determined based on the target cluster to which the volunteers to be counted belong; The step of performing statistical analysis on the volunteers to be counted based on the volunteer distribution corresponding to the volunteer type, and generating an analysis report based on the statistical analysis results, includes: The number of volunteers to be counted for each volunteer type is determined based on the number of feature indicators contained in each target cluster, and the number of volunteers to be counted for each volunteer type is determined as the volunteer distribution. The statistical analysis results are determined based on the number of volunteers to be counted for each volunteer type. The analysis report is generated based on the statistical analysis results.

2. The statistical method as described in claim 1, characterized in that, The step of using the feature indicators as input to a preset model and determining the volunteer type corresponding to each volunteer to be counted through the preset model includes: Obtain the classification intervals corresponding to the statistical dimensions and the threshold ranges corresponding to each classification interval; The feature indicators are compared with the threshold ranges corresponding to the classification intervals to determine the classification intervals corresponding to each feature indicator. The volunteer type corresponding to the preset classification interval is determined according to the correspondence between the classification interval and the volunteer type; The volunteer type corresponding to the classification interval is determined as the volunteer type of the volunteers to be counted.

3. The statistical method as described in claim 2, characterized in that, The steps of performing statistical analysis on the volunteers to be counted based on the volunteer distribution corresponding to the volunteer type, and generating an analysis report based on the statistical analysis results, include: The volunteers to be counted for each classification interval are determined based on the characteristic indicators contained in each classification interval. The distribution of volunteers for each volunteer type is determined based on the volunteers to be counted for each category interval. Based on the volunteer distribution, the number of volunteers corresponding to each volunteer type is obtained, and the statistical analysis results are determined based on the number of volunteers corresponding to each volunteer type. The analysis report is generated based on the statistical analysis results.

4. The statistical method as described in claim 1, characterized in that, The step of displaying the analysis report on the information system includes: The analysis report is output in a preset display mode, which includes at least one of a list mode, a tree diagram mode, and a pie chart mode.

5. A terminal device, characterized in that, The terminal device includes: a memory, a processor, and a statistical program stored in the memory and executable on the processor, wherein the statistical program, when executed by the processor, implements the steps of the statistical method as described in any one of claims 1 to 4.

6. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a statistical program, which, when executed by a processor, implements the steps of the statistical method as described in any one of claims 1 to 4.

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