Survey task pushing method and device, equipment and medium

Abstract

The invention discloses a survey task pushing method and device, equipment and a medium, relates to the technical field of computers and the technical field of financial science and technology, and aims to solve the technical problem that crowdsourcing tasks are matched only by relying on the ability of crowdsourcing personnel and the crowdsourcing task pushing accuracy is low in the prior art. The method comprises the following steps: constructing and regularly updating a crowdsourcing personnel database, wherein the crowdsourcing personnel database at least comprises business capability information and geographical location information of crowdsourcing personnel; performing task attribute analysis on the obtained survey task to obtain a first survey task feature corresponding to the service capability information and a second survey task feature corresponding to the geographical location information; and based on the first survey task feature and the second survey task feature, determining a target crowdsourcing personnel list and pushing the survey task. The method and the device are suitable for a solution for on-site survey task pushing of leasing equipment in scenes of a medical related leasing system, a financial related leasing system and the like.

Description

Technical Field

[0001] The present application relates to the fields of computer technology and financial technology, and in particular to methods, devices, equipment, and media for pushing survey tasks. Background Art

[0002] In the financial leasing industry, on-site inspections are a critical step in risk control. Traditional models rely on in-house teams or third-party professional organizations, resulting in high costs, slow response times, and limited coverage. Crowdsourcing uses technology to decompose inspection tasks and distribute them to appropriate service providers, optimizing resource allocation.

[0003] Therefore, equipment site inspections primarily rely on crowdsourcing tasks posted by rental companies, with crowdsourced personnel conducting on-site inspections. Existing crowdsourcing task delivery solutions include: 1. Quantitatively assessing the matching degree between crowdsourced workers and crowdsourced tasks to facilitate task delivery; 2. By deriving user competency scores through test questions, task recommendation queues are then created based on task urgency and difficulty.

[0004] The shortcomings of existing solutions include: relying solely on the capabilities of crowdsourcing personnel to match crowdsourcing tasks, being unable to ensure that the location of crowdsourcing personnel is near the task location, and having high survey costs. Summary of the Invention

[0005] In view of this, this application provides a method, device, equipment and medium for pushing survey tasks. The main purpose is to solve the technical problem that the allocation of existing survey tasks relies solely on the ability of crowdsourcing personnel to match crowdsourcing tasks, and cannot guarantee that the location of crowdsourcing personnel is near the task location, resulting in high survey costs.

[0006] According to one aspect of the present application, a method for pushing an investigation task is provided, the method comprising:

[0007] Building and regularly updating a crowdsourcing personnel database, wherein the crowdsourcing personnel database includes at least the business capability information and geographic location information of the crowdsourcing personnel, wherein the geographic location information includes at least residence information and stay point information;

[0008] Performing task attribute analysis on the acquired survey task to obtain a first survey task feature corresponding to the business capability information and a second survey task feature corresponding to the geographic location information;

[0009] Based on the first survey task characteristics and the second survey task characteristics, a target crowdsourcing personnel list is determined and the survey task is pushed.

[0010] According to another aspect of the present application, a device for pushing an investigation task is provided, the device comprising:

[0011] A construction module is used to construct and regularly update a crowdsourcing personnel database, wherein the crowdsourcing personnel database includes at least business capability information and geographic location information of the crowdsourcing personnel, wherein the geographic location information includes at least residence information and stay point information;

[0012] a parsing module, configured to parse the acquired survey task attributes to obtain a first survey task feature corresponding to the business capability information and a second survey task feature corresponding to the geographic location information;

[0013] A push module is used to determine a list of target crowdsourcing personnel and push the survey task based on the first survey task characteristics and the second survey task characteristics.

[0014] According to another aspect of the present application, a computer storage medium is provided, on which a computer program is stored. When the program is executed by a processor, the method for pushing the above-mentioned survey task is implemented.

[0015] According to another aspect of the present application, a computer device is provided, including a storage medium, a processor, and a computer program stored on the storage medium and executable on the processor, wherein the processor implements the above-mentioned method for pushing the survey task when executing the program.

[0016] By means of the above technical solution, the method, device, equipment and medium for pushing survey tasks provided by this application, compared with the existing technical solution that relies solely on the ability of crowdsourcing personnel to match crowdsourcing tasks, cannot guarantee that the location of crowdsourcing personnel is near the task location, and has a high survey cost, this application constructs and regularly updates a crowdsourcing personnel database, the crowdsourcing personnel database at least includes the business ability information and geographic location information of the crowdsourcing personnel, the geographic location information at least includes residence information and stay point information; performs task attribute analysis on the obtained survey tasks, obtains a first survey task feature corresponding to the business ability information and a second survey task feature corresponding to the geographic location information; based on the first survey task feature and the second survey task feature, determines the target crowdsourcing personnel list and pushes the survey task. It can be seen that in addition to considering the first survey task feature related to the business ability of the crowdsourcing personnel, the second survey task feature related to the residence and stay point of the crowdsourcing personnel is fully considered to improve the matching degree between the survey task and the crowdsourcing personnel, thereby effectively improving the accuracy of task push and effectively reducing the cost of survey tasks.

[0017] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0019] Figure 1 A schematic diagram showing a flow chart of a method for pushing an investigation task provided in an embodiment of the present application is shown;

[0020] Figure 2 A schematic diagram showing a flow chart of another method for pushing an investigation task provided in an embodiment of the present application is shown;

[0021] Figure 3 A schematic diagram of the structure of a push device for an investigation task provided by an embodiment of the present application is shown;

[0022] Figure 4 A schematic structural diagram of another pushing device for survey tasks provided in an embodiment of the present application is shown. DETAILED DESCRIPTION

[0023] The present application will be described in detail below with reference to the accompanying drawings and in combination with embodiments. It should be noted that, unless there is a conflict, the embodiments and features in the embodiments of the present application can be combined with each other.

[0024] In the push scenario of crowdsourcing tasks related to the existing financial technology field, crowdsourcing tasks are usually matched only by the capabilities of crowdsourcing personnel, which makes it impossible to ensure that the location of crowdsourcing personnel is near the task location, and there is a technical problem of high survey costs. This embodiment provides a method for pushing survey tasks, which can fully consider the second survey task characteristics related to the residence and stay point of crowdsourcing personnel in addition to considering the first survey task characteristics related to the business capabilities of crowdsourcing personnel, so as to improve the matching degree between survey tasks and crowdsourcing personnel, thereby effectively improving the accuracy of task push and effectively reducing the cost of survey tasks. Figure 1 As shown, this method is used as an example to illustrate the crowdsourcing task allocation scenario of a platform related to the financial technology field, which may involve medical-related leasing systems, insurance-related leasing systems, financial-related leasing systems, digital business platforms, etc. The above method includes the following steps:

[0025] Step 101: Build and regularly update a crowdsourcing personnel database.

[0026] In this embodiment, the crowdsourcer database includes at least the crowdsourcer's business capability information and geographic location information, and the geographic location information includes at least residence information and stopover information. The constructed crowdsourcer database includes basic information provided by the crowdsourcer, such as name, contact information, and residence information; and includes location data collected from the crowdsourcer, such as location data obtained through analysis using the positioning function of the crowdsourcer client (crowdsourcing app), to determine the residence information and stopover information.

[0027] Step 102: Analyze the acquired survey task attributes to obtain a first survey task feature corresponding to the business capability information and a second survey task feature corresponding to the geographic location information.

[0028] In this embodiment, compared with the existing technology that only relies on the capabilities of crowdsourcing personnel to match crowdsourcing tasks, it can fully consider the second survey task characteristics corresponding to the geographic location information of the crowdsourcing personnel in the survey task. According to the needs of the actual application scenario, when the survey task is monitored, the geographic location information of the crowdsourcing personnel can also include the information of the most recent reporting point, thereby fully considering the degree of influence of the different geographic location information of the crowdsourcing personnel on the accuracy of survey task allocation in the survey task allocation scenario.

[0029] Step 103: Based on the first survey task characteristics and the second survey task characteristics, determine a list of target crowdsourcing personnel and push the survey task.

[0030] In this embodiment, when a survey task is monitored, based on the first survey task feature, after the initial crowdsourcing personnel are determined from the crowdsourcing personnel database, the second survey task feature is used as a reference weight value for calculating the task matching score of the initial crowdsourcing personnel according to the survey location information in the survey task and the geographic location information of the initial crowdsourcing personnel. The task matching score of the initial crowdsourcing personnel is calculated, and then sorted according to the task matching score to obtain a list of target crowdsourcing personnel.

[0031] In this embodiment, a crowdsourcing personnel database can be constructed and regularly updated according to the above scheme. The crowdsourcing personnel database includes at least the business capability information and geographic location information of the crowdsourcing personnel, and the geographic location information includes at least residence information and stopover information. The obtained survey task is parsed for task attributes to obtain a first survey task feature corresponding to the business capability information and a second survey task feature corresponding to the geographic location information. Based on the first survey task feature and the second survey task feature, a list of target crowdsourcing personnel is determined and the survey task is pushed. Compared with existing technical solutions that rely solely on matching crowdsourcing tasks to the capabilities of crowdsourcing personnel, cannot guarantee that the location of crowdsourcing personnel is near the task location, and have high survey costs, this embodiment, in addition to considering the first survey task feature related to the business capability of the crowdsourcing personnel, fully considers the second survey task feature related to the residence and stopover of the crowdsourcing personnel to improve the matching degree between the survey task and the crowdsourcing personnel, thereby effectively improving the accuracy of task push and effectively reducing the cost of survey tasks.

[0032] Furthermore, as a refinement and expansion of the specific implementation methods of the above-mentioned embodiment, in order to fully illustrate the specific implementation process of this embodiment, another method for pushing survey tasks is provided. This embodiment can be applied to scenarios involving crowdsourcing task allocation, such as medical-related leasing systems, insurance-related leasing systems, financial-related leasing systems, and digital business platforms. By fully considering the first survey task characteristics related to the business capability information of the crowdsourcing personnel and the second survey task characteristics related to the geographic location information of the crowdsourcing personnel, the matching degree between the survey task and the crowdsourcing personnel can be effectively improved, thereby effectively improving the accuracy of task push, while effectively reducing the cost of the survey task.

[0033] On-site inspection mainly refers to the arrival inspection of the leased equipment by the leasing company. As the lessor, the leasing company purchases the equipment from the equipment supplier and signs a contract with the lessee to lease the equipment to the lessee. However, in the actual process, there is a risk of embezzling the leasing company's funds, such as false shipments, the location of the inspection equipment not being consistent with the location agreed in the financial leasing business, and other issues. Therefore, the leasing company needs to conduct an on-site inspection of the leased equipment to ensure that the equipment has arrived in real time and is not damaged, so as to strengthen business risk control. Figure 2 As shown, the method of this embodiment includes:

[0034] Step 201: Build and regularly update a crowdsourcing personnel database.

[0035] To illustrate the specific implementation of step 201, as a preferred embodiment, this embodiment also includes: regularly updating the stay point information of crowdsourcing personnel, specifically including: clustering the positioning data of crowdsourcing personnel collected within a preset time period to determine multiple location clusters; determining and updating the stay point information of crowdsourcing personnel based on the multiple location clusters; wherein, the determination conditions of the location cluster include that the location cluster is within a preset area and the reporting frequency of positioning data within the location cluster is within a preset reporting frequency range.

[0036] In order to illustrate the specific implementation method of step 201, as a preferred embodiment, the step of determining and updating the crowdsourcing personnel's stay point information based on the multiple location clusters specifically includes: obtaining multiple initial stay point locations with time tags based on the multiple location clusters; obtaining the rental equipment location information corresponding to the crowdsourcing personnel's rental order information based on the time tags; and determining and updating the crowdsourcing personnel's stay point information by comparing the rental equipment location information with the multiple initial stay point locations.

[0037] During implementation, step 201 is consistent with step 101. By collecting crowdsourcing personnel information, a crowdsourcing personnel database is established, which specifically includes the crowdsourcing personnel's geographic location information and business capability information. The geographic location information at least includes residence information (which can be multiple permanent addresses), stop point information, and the most recent reporting point information; the business capability information at least includes business skill level (such as mechanical engineering knowledge, electronic circuit knowledge, and other related professional knowledge or certificates), years of experience, survey experience (such as survey experience of specific equipment such as engineering machinery and electronic equipment), historical rental orders (such as historical survey tasks and historical success rates), etc. Specifically, crowdsourcing personnel register through the crowdsourcing platform provided by the leasing company and fill in basic information such as residence information, business skill level, and years of experience. During daily use, the crowdsourcing personnel's client application (crowdsourcing APP) regularly sends the crowdsourcing personnel's positioning data to the crowdsourcing personnel information management module, so that the crowdsourcing personnel information management module performs clustering processing based on the positioning data, determines multiple location clusters, and then determines and updates the crowdsourcing personnel's stop point information.

[0038] During implementation, the system backend can collect positioning data based on a certain time threshold every time interval of the crowdsourcing personnel, and extract the stay point information through cluster aggregation processing. Cluster aggregation needs to meet the requirements that the positioning data is within the preset radius and the number of positioning data exceeds the preset reporting quantity. It should be noted that the above positioning data does not include the positioning data during the period when the crowdsourcing personnel perform other survey tasks. According to the needs of the actual application scenario, the crowdsourcing personnel report positioning data when performing the survey task. Therefore, when collecting positioning data, the positioning data can be screened based on the positioning data during the period when the crowdsourcing personnel perform other survey tasks. It can also be based on the positioning data during the period when the crowdsourcing personnel perform other survey tasks. Invalid stay points can be eliminated from the extracted stay point information. The screening of positioning data and the determination of stay point information are not specifically limited here.

[0039] Specifically, when the crowdsourcing APP of the crowdsourcing personnel is in the open state, the crowdsourcing APP can upload positioning data at regular intervals. For example, every 5 minutes, the system records a GPS data list so that the same positioning data can be clustered and aggregated based on the GPS data list, and the location cluster of continuous stay time is regarded as a stay point. For example, if a positioning area is stayed for 1.5 hours continuously and then left, and there is a stay for several consecutive days, it is regarded as a stay point.

[0040] Step 202: Analyze the acquired survey task attributes to obtain a first survey task feature corresponding to the business capability information.

[0041] To illustrate the specific implementation of step 202, as a preferred embodiment, prior to step 202, the process further includes: constructing a mapping relationship between the rental equipment identifier and the crowdsourcer's business capability information based on the success rate of historical survey tasks, the rental equipment identifier in the historical survey tasks, and the crowdsourcer's business capability information. Accordingly, as a preferred embodiment, step 202 includes: utilizing the mapping relationship based on the rental equipment identifier in the survey task to determine a first survey task feature corresponding to the survey task, which is used to represent the crowdsourcer's business capability matching score.

[0042] During implementation, the customer manager of the leasing company creates an equipment survey task on the task release interface of the crowdsourcing platform, queries the corresponding leasing order information based on the obtained survey task request, and generates survey task information based on the leasing order information and the survey task request, which at least includes the type of leasing equipment (such as large-scale construction equipment requires crowdsourcing personnel with knowledge of construction engineering and mechanical principles, or small office equipment such as electronic equipment requires crowdsourcing personnel with relevant electronic technology), the survey location (precise geographic location range), the urgency of the survey task (based on the multi-device collaboration level to determine whether it needs to be prioritized), etc.

[0043] Specifically, the required business capability information for the survey task is analyzed and matched against the business capability information in the crowdsourced personnel database. For example, if the rental equipment for the survey task is a high-precision electronic measuring instrument, the survey experience and business skill level should be that of a crowdsourced personnel with experience in surveying electronic measuring instruments and possessing expertise in electronic engineering. It should be noted that weights can be assigned to each piece of business capability information to calculate a business capability matching score for each crowdsourced personnel.

[0044] Step 203: Analyze the acquired survey task attributes to obtain a second survey task feature corresponding to the geographic location information.

[0045] In order to illustrate the specific implementation method of step 203, as a preferred embodiment, the second survey task characteristics include at least the survey task priority, and step 203 includes: obtaining the rental order information corresponding to the survey task; determining the survey task priority based on the rental equipment information in the rental order information; the rental equipment information includes at least the rental equipment location information, rental equipment model, estimated survey time, and multi-device collaboration level.

[0046] Step 204: Determine initial crowdsourcing personnel from a crowdsourcing personnel database based on the first survey task characteristics.

[0047] Step 205: Determine a list of target crowdsourcing personnel based on the survey location information in the survey task and the second survey task characteristics and the geographic location information of the initial crowdsourcing personnel.

[0048] To illustrate the specific implementation of step 205, as a preferred embodiment, step 205 includes: obtaining the latest reporting point information of the initial crowdsourcing personnel; calculating the geographic location matching score based on the weight values ​​corresponding to the residence information, the stay point information and the latest reporting point information respectively according to the distance information of the residence information, the stay point information and the latest reporting point information from the survey location information; using the second survey task feature as the weight value of the geographic location matching score to calculate the matching score of the initial crowdsourcing personnel; sorting the initial crowdsourcing personnel based on the matching score of the initial crowdsourcing personnel to obtain a list of target crowdsourcing personnel.

[0049] During implementation, when generating survey task information, the system's backend task analysis module determines the required business capabilities for the survey task based on the rental equipment identifier. For example, if the rental equipment type is a large construction crane, the task analysis module determines that a crowdsourced individual with mechanical engineering knowledge and crane operation experience is required. Furthermore, based on the survey location and the urgency of the survey task, the module determines a distance threshold that matches the survey location. Based on the area range corresponding to this distance matching threshold and the geographic location information of the crowdsourced individuals who meet the business capability requirements, the module selects crowdsourced individuals who match the area range.

[0050] It should be noted that when setting the distance threshold for matching the survey location, if the survey task is urgent, that is, it is necessary to arrive at the site quickly, the distance threshold is set to within 10 kilometers. If the survey task is normal, the distance threshold is set to within 50 kilometers. Therefore, based on the area range corresponding to the distance matching threshold, the residence information, stay point information, and last reported point information of the crowdsourcers who meet the business capability information are compared with the area range corresponding to the distance matching threshold, and the crowdsourcers who match the area range are screened out.

[0051] Based on the needs of the actual application scenario, the geographic location information of the selected crowdsourcers matching the area is calculated. The matching score is calculated by assigning weights to the residence information, the stop information, and the last reported point information. The last reported point is given the highest weight, followed by the residence, and the stop information is given the lowest weight. The stop information weight can be dynamically adjusted based on the cumulative length of stay. If no matching crowdsourcer is found within 10 kilometers, the distance threshold is further increased until a crowdsourcer with matching geographic location information is found.

[0052] For example, the geographic location information of crowdsourcers A and B matches the area scope of survey task A. Crowdsourcer A's most recent reported location is within the area scope, his residence is not, and his remaining points are. The matching score for crowdsourcer A's geographic location information is 100*0.5+0*0.2+100*0.3=80. Crowdsourcer B's most recent reported location, residence, and remaining points are all within the area scope. The matching score for crowdsourcer B's geographic location information is 100*0.5+100*0.2+100*0.3=100. Therefore, crowdsourcer B has a higher matching score for the survey task.

[0053] During implementation, after the top n target crowdsourcers are automatically selected based on this embodiment, the survey task is pushed to the client of the target crowdsourcer. The push information of the survey task includes detailed information of the task (equipment type, survey location, survey requirements, etc.), reward information, and the deadline of the task. For example, the specific model of the crane, the detailed address of the survey location, the task reward of X yuan, and the task needs to be completed within 24 hours. Among them, the system's task push module continuously monitors the response of the target crowdsourcer to the task. If a crowdsourcer has accepted the task, the task start time is recorded; if the target crowdsourcer rejects the task, the next batch of crowdsourcers with higher rankings are reselected for push until the task is accepted or the maximum number of pushes (for example, 3 times) is reached.

[0054] It can be seen that in terms of human resource optimization: based on the business capability information and geographic location information of crowdsourcers, human resources can be used more reasonably. Tasks can be assigned to the most suitable personnel to avoid the waste of resources caused by personnel with mismatched business capabilities participating in tasks; in terms of cost resource optimization: from a cost perspective, accurate task push can reduce additional costs such as rework and recommunication caused by improper task assignment. At the same time, utilizing the geographical location advantages of crowdsourcers can reduce costs such as transportation. Reasonable task push can help reduce the operating costs of the entire crowdsourcing project and improve resource utilization efficiency while ensuring the quality of tasks; in terms of task matching: crowdsourcers are more inclined to accept tasks that match their professional capabilities. When they receive task pushes that match their business capabilities, they can effectively improve the success rate of order acceptance.

[0055] By applying the technical solution of this embodiment, it is possible to ensure that the pushed tasks can simultaneously meet the geographical location matching of the crowdsourcing personnel based on the first survey task characteristics related to the business capabilities of the crowdsourcing personnel and the second survey task characteristics related to the geographical location information such as the residence and stopover of the crowdsourcing personnel, thereby avoiding the high cost of the crowdsourcing personnel reaching the survey location. At the same time, through precise push, it is possible to ensure that the survey tasks are consistent with the business capabilities of the crowdsourcing personnel, thereby avoiding pushing complex equipment that requires personnel with professional knowledge to crowdsourcing personnel who do not have relevant knowledge, thereby affecting the quality and efficiency of the survey. Compared with the existing technical solutions that rely solely on the allocation of crowdsourcing tasks to match crowdsourcing tasks with the capabilities of crowdsourcing personnel, cannot ensure that the location of crowdsourcing personnel is near the task location, and have high survey costs, this embodiment uses a matching algorithm to comprehensively match the business capability information and geographical location information of crowdsourcing personnel with the viewing task to calculate the matching score between crowdsourcing personnel and task, and then sort the crowdsourcing personnel according to the matching score and push tasks to the crowdsourcing personnel with the highest ranking, thereby realizing the entire process of equipment survey tasks from creation to push. It can be seen that crowdsourcing tasks can be accurately pushed to suitable crowdsourcing personnel through the internal matching and push algorithms of the crowdsourcing platform.

[0056] Further, as Figure 1 The specific implementation of the method, the embodiment of the present application provides a push device for the survey task, such as Figure 3 As shown, the device includes: a construction module 31, a parsing module 32, and a pushing module 33.

[0057] The construction module 31 is used to construct and regularly update a crowdsourcing personnel database, which at least includes the business capability information and geographic location information of the crowdsourcing personnel, and the geographic location information at least includes residence information and stay point information.

[0058] The parsing module 32 is configured to perform task attribute parsing on the acquired survey task to obtain a first survey task feature corresponding to the business capability information and a second survey task feature corresponding to the geographic location information.

[0059] The push module 33 is used to determine a list of target crowdsourcing personnel and push the survey task based on the first survey task characteristics and the second survey task characteristics.

[0060] In specific application scenarios, such as Figure 4 As shown, the construction module 31 includes an updating submodule 311 .

[0061] The updating submodule 311 is used to regularly update the stay point information of the crowdsourcing personnel, specifically to cluster the positioning data of the crowdsourcing personnel collected within a preset time period to determine multiple location clusters; based on the multiple location clusters, the stay point information of the crowdsourcing personnel is determined and updated; wherein, the determination conditions of the location cluster include that the location cluster is within a preset area and the reporting frequency of the positioning data within the location cluster is within a preset reporting frequency range.

[0062] In a specific application scenario, the step of determining and updating the crowdsourcing personnel's stay point information based on the multiple location clusters specifically includes: obtaining multiple initial stay point locations with time tags based on the multiple location clusters; obtaining the rental equipment location information corresponding to the crowdsourcing personnel's rental order information based on the time tags; and determining and updating the crowdsourcing personnel's stay point information by comparing the rental equipment location information with the multiple initial stay point locations.

[0063] In a specific application scenario, the parsing module 32 includes a first parsing submodule 321 and a second parsing submodule 322 .

[0064] The first parsing submodule 321 is used to construct a mapping relationship between the rental equipment identifier and the business capability information of the crowdsourcing personnel based on the success rate of historical survey tasks, the rental equipment identifier in the historical survey tasks and the business capability information of the crowdsourcing personnel; and, based on the rental equipment identifier in the survey task, use the mapping relationship to determine the first survey task feature corresponding to the survey task for characterizing the business capability matching score of the crowdsourcing personnel.

[0065] The second parsing submodule 322 is used to obtain the rental order information corresponding to the survey task; determine the survey task priority based on the rental equipment information in the rental order information; the rental equipment information at least includes the rental equipment location information, rental equipment model, estimated survey time, and multi-device collaboration level, and the second survey task characteristics at least include the survey task priority.

[0066] In a specific application scenario, the push module 33 includes: a first determination submodule 331 and a second determination submodule 332 .

[0067] The first determining submodule 331 is configured to determine initial crowdsourcing personnel from a crowdsourcing personnel database according to the first survey task characteristics.

[0068] The second determining submodule 332 is configured to determine a list of target crowdsourcing personnel according to the survey location information in the survey task and the second survey task characteristics and the geographic location information of the initial crowdsourcing personnel.

[0069] In a specific application scenario, the second determination submodule 332 is specifically used to obtain the latest reporting point information of the initial crowdsourcing personnel; calculate the geographic location matching score based on the weight values ​​corresponding to the residence information, stay point information and latest reporting point information respectively according to the distance information of the residence information, stay point information and the latest reporting point information from the survey location information; use the second survey task feature as the weight value of the geographic location matching score to calculate the matching score of the initial crowdsourcing personnel; sort the initial crowdsourcing personnel based on the matching score of the initial crowdsourcing personnel to obtain a list of target crowdsourcing personnel.

[0070] It should be noted that for other corresponding descriptions of the functional units involved in the push device for an investigation task provided in the embodiment of the present application, reference can be made to Figure 1 and Figure 2 The corresponding description in will not be repeated here.

[0071] Based on the above Figure 1 and Figure 2 The method shown in FIG. 1 is a method for performing the above-mentioned operation. Accordingly, the embodiment of the present application further provides a computer storage medium having a computer program stored thereon, which implements the above-mentioned operation when the computer program is executed by the processor. Figure 1 and Figure 2 The push method of the survey task shown.

[0072] Based on this understanding, the technical solution of the present application can be embodied in the form of a software product, which can be stored in a storage medium (which can be a CD-ROM, USB flash drive, mobile hard disk, etc.), including a number of instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute the methods described in each implementation scenario of the present application.

[0073] Based on the above Figure 1 、 Figure 2 The method shown, and Figure 3 In order to achieve the above-mentioned purpose, the embodiment of the present application further provides a computer device, which can be a personal computer, a server, a network device, etc. The physical device includes a storage medium and a processor; the storage medium is used to store a computer program; the processor is used to execute the computer program to achieve the above-mentioned Figure 1 and Figure 2 The push method of the survey task shown.

[0074] Optionally, the computer device may further include a user interface, a network interface, a camera, a radio frequency (RF) circuit, a sensor, an audio circuit, a Wi-Fi module, etc. The user interface may include a display, an input unit such as a keyboard, etc., and may optionally include a USB interface, a card reader interface, etc. The network interface may optionally include a standard wired interface, a wireless interface (such as a Bluetooth interface, a Wi-Fi interface), etc.

[0075] Those skilled in the art will understand that the computer device structure provided in this embodiment does not constitute a limitation on the physical device, and may include more or fewer components, or a combination of certain components, or different component arrangements.

[0076] The storage medium may also include an operating system and a network communication module. An operating system is a program that manages the hardware and software resources of a computer device, supporting the execution of information processing programs and other software and / or programs. The network communication module facilitates communication between components within the storage medium, as well as with other hardware and software within the physical device.

[0077] Through the description of the above implementation methods, those skilled in the art can clearly understand that the present application can be implemented by means of software plus the necessary general hardware platform, or by hardware. At the same time, the non-company software tools or components that appear in the embodiments of the present application are merely examples and do not represent actual use. By applying the technical solution of the present application, compared with the technical solution that the allocation of existing survey tasks relies solely on the ability of crowdsourcing personnel to match crowdsourcing tasks, which cannot guarantee that the location of crowdsourcing personnel is near the location of the task and has a higher survey cost, the present embodiment is based on a matching algorithm, which comprehensively matches the business ability information and geographic location information of the crowdsourcing personnel with the viewing task to calculate the matching score between the crowdsourcing personnel and the task, and then sorts the crowdsourcing personnel according to the matching score and pushes the task to the crowdsourcing personnel with the highest ranking, thereby realizing the whole process of equipment survey tasks from creation to push. It can be seen that crowdsourcing tasks can accurately push crowdsourcing tasks to suitable crowdsourcing personnel through the internal matching and push algorithms of the crowdsourcing platform.

[0078] Those skilled in the art will understand that the accompanying drawings are only schematic diagrams of a preferred implementation scenario, and the modules or processes in the accompanying drawings are not necessarily required to implement the present application. Those skilled in the art will understand that the modules in the devices in the implementation scenario can be distributed in the devices of the implementation scenario according to the implementation scenario description, or can be changed accordingly and located in one or more devices different from the implementation scenario. The modules of the above-mentioned implementation scenario can be combined into one module, or can be further split into multiple units.

[0079] The serial numbers of the above application are for descriptive purposes only and do not represent the advantages or disadvantages of the implementation scenarios. The above disclosure only discloses several specific implementation scenarios of the present application, but the present application is not limited thereto. Any changes that can be conceived by those skilled in the art should fall within the scope of protection of the present application.

Claims

1. A method for pushing an investigation task, characterized in that: include: Building and regularly updating a crowdsourcing personnel database, wherein the crowdsourcing personnel database includes at least the business capability information and geographic location information of the crowdsourcing personnel, wherein the geographic location information includes at least residence information and stay point information; Performing task attribute analysis on the acquired survey task to obtain a first survey task feature corresponding to the business capability information and a second survey task feature corresponding to the geographic location information; Based on the first survey task characteristics and the second survey task characteristics, a target crowdsourcing personnel list is determined and the survey task is pushed.

2. The method according to claim 1, characterized in that Also includes: Regularly update the crowdsourcers' stay information, including: Clustering the location data of crowdsourced personnel collected within a preset time period to determine multiple location clusters; Determining and updating the stay point information of the crowdsourcing personnel based on the multiple location clusters; The determination condition of the location cluster includes that the location cluster is within a preset area and the reporting frequency of positioning data in the location cluster is within a preset reporting frequency range.

3. The method according to claim 2, characterized in that The step of determining and updating the stay point information of the crowdsourcing personnel based on the multiple location clusters specifically includes: Obtaining a plurality of initial stay point positions with time tags according to the plurality of position clusters; According to the time tag, obtaining the rental equipment location information corresponding to the rental order information of the crowdsourcing personnel; By comparing the rental equipment location information with the multiple initial stay point locations, the stay point information of the crowdsourcing personnel is determined and updated.

4. The method according to claim 1, wherein Before the step of parsing the acquired survey task attributes to obtain the first survey task feature corresponding to the business capability information, the method further includes: Based on the success rate of historical survey tasks, as well as the rental equipment identification and crowdsourcing personnel's business capability information in the historical survey tasks, a mapping relationship between the rental equipment identification and the crowdsourcing personnel's business capability information is constructed; The step of performing task attribute analysis on the acquired survey task to obtain a first survey task feature corresponding to the business capability information includes: According to the rental equipment identifier in the survey task, the mapping relationship is used to determine a first survey task feature corresponding to the survey task and used to characterize the business capability matching score of the crowdsourcing personnel.

5. The method according to claim 1 or 4, characterized in that The second survey task feature includes at least a survey task priority. The step of performing task attribute analysis on the acquired survey task to obtain the second survey task feature corresponding to the geographic location information includes: Obtaining the rental order information corresponding to the survey task; Determine the priority of the survey task based on the leased equipment information in the lease order information; The rental equipment information includes at least the rental equipment location information, the rental equipment model, the estimated inspection time, and the multi-equipment coordination level.

6. The method according to claim 1, characterized in that The step of determining a target crowdsourcing personnel list and pushing the survey task based on the first survey task characteristics and the second survey task characteristics includes: Determining initial crowdsourcing personnel from a crowdsourcing personnel database according to the first survey task characteristics; According to the survey location information in the survey task and the second survey task characteristics, a list of target crowdsourcing personnel is determined according to the geographic location information of the initial crowdsourcing personnel.

7. The method according to claim 6, characterized in that The step of determining a list of target crowdsourcing personnel according to the survey location information in the survey task and the second survey task characteristics and the geographic location information of the initial crowdsourcing personnel includes: Obtaining the latest reporting point information of the initial crowdsourcing personnel; Calculate the geographic location matching score based on the distance information of the residence information, the stay point information and the most recently reported point information from the survey location information and the weight values ​​corresponding to the residence information, the stay point information and the most recently reported point information respectively; The second survey task feature is used as a weight value of the geographic location matching score to calculate the matching score of the initial crowdsourcing personnel; The initial crowdsourcing personnel are sorted based on their matching scores to obtain a list of target crowdsourcing personnel.

8. A pushing device for an investigation task, characterized in that: include: A construction module is used to construct and regularly update a crowdsourcing personnel database, wherein the crowdsourcing personnel database includes at least business capability information and geographic location information of the crowdsourcing personnel, wherein the geographic location information includes at least residence information and stay point information; a parsing module, configured to parse the acquired survey task attributes to obtain a first survey task feature corresponding to the business capability information and a second survey task feature corresponding to the geographic location information; A push module is used to determine a list of target crowdsourcing personnel and push the survey task based on the first survey task characteristics and the second survey task characteristics.

9. A computer storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method for pushing the survey task described in any one of claims 1 to 7 is implemented.

10. A computer device comprising a storage medium, a processor, and a computer program stored in the storage medium and executable on the processor, wherein: When the processor executes the program, the method for pushing the survey task according to any one of claims 1 to 7 is implemented.

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