A resource adaptation method, apparatus, electronic device, and readable storage medium

Abstract

This application provides a resource adaptation method, apparatus, electronic device, and readable storage medium. The method includes acquiring at least one object to be processed and at least one first candidate processing resource; acquiring a target score for each first candidate processing resource to process each object to be processed, wherein the target score represents the degree of matching between the first candidate processing resource and the object to be processed; sorting the first candidate processing resources according to the target score to obtain a first order; and selecting a processing resource to process the object to be processed from the first candidate processing resources according to the first order. Therefore, the embodiments of this application can automatically select the appropriate processing resource for the object to be processed based on the degree of matching between the first candidate processing resource and the object to be processed, without requiring operation by the resource supplier. Thus, the embodiments of this application can reduce the operating costs of the resource supplier and thereby improve resource adaptation efficiency.

Description

Technical Field

[0001] This application relates to the field of computer technology, and in particular to a resource adaptation method, apparatus, electronic device, and readable storage medium. Background Technology

[0002] With the continuous development of the internet, online home services have emerged. These services include maternity nurses, nannies, cleaning, nursing, hourly workers, and home relocation services. Online home services involve using online platforms to assign home service personnel to users, who then provide the corresponding services. In short, online home services enable a complete process from user order placement and dispatch to service personnel arriving at the user's home.

[0003] The current order allocation model involves the online platform allocating orders to merchants, who then allocate the orders to service personnel. This process is lengthy and requires merchants to manually allocate orders to service personnel, increasing their operational costs and reducing order allocation efficiency.

[0004] Correspondingly, other scenarios related to resource allocation also suffer from the same or corresponding drawbacks. Therefore, in existing technologies, scenarios involving the allocation of processing resources to service recipients, including online housekeeping services, all require manual allocation by the resource provider, thus increasing the provider's operational costs and reducing resource adaptation efficiency. Summary of the Invention

[0005] This application provides a resource adaptation method, apparatus, electronic device, and readable storage medium to solve the problem in the prior art that resource providers need to manually allocate processing resources to the processing objects, thereby increasing the operating costs of resource providers and reducing resource adaptation efficiency.

[0006] In a first aspect, embodiments of this application disclose a resource adaptation method, the method comprising:

[0007] Acquire at least one object to be processed and at least one first candidate processing resource;

[0008] Obtain the target score for each of the first candidate processing resources in processing each of the objects to be processed, wherein the target score represents the degree of matching between the first candidate processing resource and the object to be processed;

[0009] Based on the target score, the first candidate processing resources are sorted to obtain a first order;

[0010] According to the first order, a processing resource for processing the object to be processed is selected from the first candidate processing resources.

[0011] Secondly, embodiments of this application provide a resource adaptation device, the device comprising:

[0012] The first acquisition module is used to acquire at least one object to be processed and at least one first candidate processing resource;

[0013] The second acquisition module is used to acquire the target score of each of the first candidate processing resources for processing each of the objects to be processed, wherein the target score represents the degree of matching between the first candidate processing resource and the object to be processed;

[0014] The first sorting module is used to sort the first candidate processing resources according to the target score to obtain a first order;

[0015] The first selection module is used to select a processing resource from the first candidate processing resources to process the object to be processed, according to the first order.

[0016] Thirdly, embodiments of this application disclose an electronic device, the electronic device comprising:

[0017] One or more processors; and

[0018] One or more machine-readable media having instructions stored thereon, which, when executed by the one or more processors, cause the electronic device to perform the method described in the first aspect above.

[0019] Fourthly, embodiments of this application disclose a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the method described in the first aspect above.

[0020] The embodiments of this application have the following advantages:

[0021] In the embodiments of this application, at least one object to be processed and at least one first candidate processing resource can be obtained. A target score is then obtained for each first candidate processing resource to process each object to be processed. Based on the target score, the first candidate processing resources are sorted to obtain a first order. Based on the first order, a processing resource for processing the object to be processed is selected from the first candidate processing resources. The target score represents the degree of matching between the first candidate processing resource and the object to be processed. Therefore, in the embodiments of this application, when at least one object to be processed and at least one first candidate processing resource are obtained, the appropriate processing resource can be automatically selected for the object to be processed based on the degree of matching between the first candidate processing resource and the object to be processed, without requiring operation from the resource supplier. Therefore, the embodiments of this application can reduce the operating costs of the resource supplier, thereby improving resource adaptation efficiency. Furthermore, based on the degree of matching between the first candidate processing resource and the object to be processed, a more suitable processing resource can be selected for the object to be processed, thereby further improving the processing effect of the processing resource on the object to be processed. Attached Figure Description

[0022] Figure 1 This is a schematic diagram of the resource adaptation method of this application;

[0023] Figure 2 This is a schematic diagram of the resource adaptation device of this application. Detailed Implementation

[0024] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0025] The list processing method of this application embodiment can run on a terminal device or a server. The terminal device can be a local terminal device. When the method runs on a server, it can be used for cloud display.

[0026] In one optional implementation, cloud display refers to an information display method based on cloud computing. In the cloud display operating mode, the main body running the information processing program and the main body presenting the information screen are separate. The storage and operation of the display switching method are completed on the cloud display server. The role of the cloud display client is to receive and send data and present the information screen. For example, the cloud display client can be a display device with data transmission capabilities located close to the user, such as a mobile terminal, television, computer, or PDA; however, the terminal device for processing information data is the cloud display server in the cloud. When browsing, the user operates the cloud display client to send operation commands to the cloud display server. The cloud display server displays information according to the operation commands, encodes and compresses the data, returns it to the cloud display client via the network, and finally, the cloud display client decodes and outputs the displayed content.

[0027] In another alternative implementation, the terminal device can be a local terminal device. The local terminal device stores applications and is used to present the application interface. The local terminal device is used to interact with the user through a graphical user interface, i.e., conventionally downloading, installing, and running applications via an electronic device. The local terminal device can provide the graphical user interface to the user in various ways, such as rendering it on a terminal's display screen or providing it to the user through holographic projection. For example, the local terminal device can include a display screen for presenting the graphical user interface, which includes application screens, and a processor for running the application, generating the graphical user interface, and controlling the display of the graphical user interface on the display screen.

[0028] This application provides a resource adaptation method that can acquire at least one object to be processed and at least one first candidate processing resource, thereby obtaining a target score for each first candidate processing resource to process each object to be processed. Then, based on the target score, the first candidate processing resources are sorted to obtain a first order, and based on the first order, a processing resource for processing the object to be processed is selected from the first candidate processing resources. Here, the target score represents the degree of matching between the first candidate processing resource and the object to be processed. Therefore, in this application embodiment, when at least one object to be processed and at least one first candidate processing resource are acquired, the appropriate processing resource can be automatically selected for the object to be processed based on the degree of matching between the first candidate processing resource and the object to be processed, without requiring operation from the resource supplier. Therefore, the embodiments of this application can reduce the operating costs of the resource supplier, thereby improving resource adaptation efficiency. Furthermore, based on the degree of matching between the first candidate processing resource and the object to be processed, a more suitable processing resource can be selected for the object to be processed, thereby further improving the processing effect of the processing resource on the object to be processed.

[0029] The resource adaptation method provided in the embodiments of this application will be described in detail below.

[0030] See Figure 1 As shown, the resource adaptation method provided in this application includes the following steps 101 to 104:

[0031] Step 101: Obtain at least one object to be processed and at least one first candidate processing resource.

[0032] The aforementioned objects to be processed can include one or more objects, and candidate processing resources can be understood as the resources required to process the object. For example, the object could be a domestic service order (e.g., a cleaning service order, a moving service order), and the first candidate processing resource could be a domestic service worker; or, the object could be a food delivery order, and the first candidate processing resource could be a food delivery rider; or, the object to be processed could be a task to be processed (e.g., a cluster creation task, a node creation / update task, etc.), and the candidate processing resources can be understood as the resources required to process the corresponding task (e.g., cluster device resources, tool resources, node resources, traffic resources, etc.).

[0033] In different application scenarios, the objects to be processed and the candidate processing resources can be set according to the scenario requirements, and this embodiment of the invention does not limit this.

[0034] In addition, the resource adaptation method of this application embodiment can be applied to a network platform. When the network platform detects the generation of a new object to be processed, steps 101 to 104 can be executed to allocate corresponding processing resources to the newly generated objects to be processed in sequence. Alternatively, the network platform can execute steps 101 to 104 every preset time interval for objects to be processed generated within that time interval to allocate corresponding processing resources to the objects to be processed generated within that time interval. The time interval should be as small as possible to avoid processing delays.

[0035] Step 102: Obtain the target score for each of the first candidate processing resources for each of the objects to be processed.

[0036] The target score represents the degree of matching between the first candidate processing resource and the object to be processed; that is, the higher the target score, the higher the degree of matching between the first candidate processing resource and the object to be processed.

[0037] Furthermore, if the target score for each of the first candidate processing resources for each of the objects to be processed is known data, it can be obtained directly. If it is not directly obtainable data, then the target score for each of the first candidate processing resources for each of the objects to be processed can be generated based on the corresponding basic data. The specific method for determining the target score will be described in detail later.

[0038] Step 103: Sort the first candidate processing resources according to the target score to obtain the first order.

[0039] The first order is obtained by ranking the first candidate processing resources according to the target score. Therefore, the ranking of the first candidate processing resource in the first order is related to the degree of matching between the first candidate processing resource and each object to be processed. Thus, according to the first order, more suitable processing resources can be selected from the first candidate processing resources, thereby further improving the processing effect of the processing resources on the objects to be processed.

[0040] Step 104: According to the first order, select a processing resource from the first candidate processing resources to process the object to be processed.

[0041] As can be seen from steps 101 to 104 above, in the embodiments of this application, at least one object to be processed and at least one first candidate processing resource can be obtained, thereby obtaining the target score for each first candidate processing resource to process each object to be processed. Then, based on the target score, the first candidate processing resources are sorted to obtain a first order, and based on the first order, a processing resource for processing the object to be processed is selected from the first candidate processing resources. Here, the target score represents the degree of matching between the first candidate processing resource and the object to be processed. Therefore, in the embodiments of this application, when at least one object to be processed and at least one first candidate processing resource are obtained, the appropriate processing resource can be automatically selected for the object to be processed based on the degree of matching between the first candidate processing resource and the object to be processed, without requiring operation from the resource supplier. Therefore, the embodiments of this application can reduce the operating costs of the resource supplier, thereby improving resource adaptation efficiency. Furthermore, based on the degree of matching between the first candidate processing resource and the object to be processed, a more suitable processing resource can be selected for the object to be processed, thereby further improving the processing effect of the processing resource on the object to be processed.

[0042] Optionally, obtaining the target score for each of the first candidate processing resources for each of the objects to be processed includes:

[0043] According to the first preset formula Calculate the target score for the k-th first candidate processing resource to process the i-th object to be processed.

[0044] in, W represents the degree of matching between the v-th information dimension of the k-th first candidate processing resource and the i-th object to be processed, where i is an integer from 1 to U, and U represents the number of objects to be processed. v This represents the v-th weight value, where V represents the number of information dimensions of the first candidate processing resource involved in calculating the target score.

[0045] Therefore, the target score for the k-th first candidate processing resource in processing the i-th object is determined based on the matching degree between the 1st to V information dimensions of the k-th first candidate processing resource and the i-th object. That is, the weighted sum of the matching degree between each dimension of a first candidate processing resource and an object is the target score for that first candidate processing resource in processing that object.

[0046] For example, if the matching degree between a first-candidate processing resource and the object to be processed in three dimensions is x1, x2, and x3, and the weights are W1, W2, and W3, then the target score for the first-candidate processing resource in processing the object to be processed is = x1*W1 + x2*W2 + x3*W3. It should be noted that W1 to W3... V The specific values ​​can be modified according to the actual situation. Furthermore, the difference between any two of these weight values ​​should be less than a preset threshold to prevent the target score from being unable to accurately represent the matching degree between the first candidate processing resource and the object to be processed due to excessive differences between these weights.

[0047] Optional, to Each of the following is at least one of the first to seventh parameters:

[0048] The first parameter represents the reassignment probability after the kth first candidate processing resource processes the i-th object to be processed.

[0049] The second parameter represents the degree of matching between the navigation path of the object assigned to the k-th first candidate processing resource and the processing address of the i-th object to be processed.

[0050] The third parameter represents the degree of matching between the processing time of the object allocated to the k-th first candidate processing resource and the processing time of the i-th object to be processed.

[0051] The fourth parameter indicates whether the k-th first candidate processing resource has processed the processing object of the target user corresponding to the i-th object to be processed, and whether the target user has given negative comment information to the k-th first candidate processing resource;

[0052] The fifth parameter represents the processing status of the k-th first candidate processing resource on the processing object within a first preset time period;

[0053] The sixth parameter indicates whether the k-th first candidate processing resource has been allocated to a processing object;

[0054] The seventh parameter represents the processing equipment available for the k-th first candidate processing resource.

[0055] Therefore, the target score can be a weighted sum of at least one of the first to seventh parameters.

[0056] Wherein, the first parameter represents the reassignment probability after the k-th first candidate processing resource processes the i-th object to be processed. In this embodiment of the application, the larger the value of the first parameter, the smaller the reassignment probability after the k-th first candidate processing resource processes the i-th object to be processed. Conversely, the smaller the value of the first parameter, the larger the reassignment probability after the k-th first candidate processing resource processes the i-th object to be processed.

[0057] The second parameter mentioned above represents the degree of matching between the navigation path of the object assigned to the k-th first candidate processing resource (this object generally only includes processing objects that have been assigned to the k-th first candidate processing resource and have not yet been processed by the k-th first candidate processing resource; of course, it may also include other objects assigned to the k-th first candidate processing resource, such as processing objects that have been processed, but this embodiment of the present invention does not limit this) and the processing address of the i-th object to be processed. It can also represent the distance of the navigation path added by the k-th first candidate processing resource after processing the i-th object to be processed. In this embodiment, the larger the value of the second parameter, the greater the degree of matching between the navigation path of the object already allocated to the k-th first candidate processing resource and the processing address of the i-th object to be processed; that is, the smaller the distance of the navigation path added by the k-th first candidate processing resource after processing the i-th object to be processed. Conversely, the smaller the value of the second parameter, the smaller the degree of matching between the navigation path of the object already allocated to the k-th first candidate processing resource and the processing address of the i-th object to be processed; that is, the greater the distance of the navigation path added by the k-th first candidate processing resource after processing the i-th object to be processed.

[0058] The third parameter mentioned above represents the degree of matching between the processing time of the object allocated to the k-th first candidate processing resource and the processing time of the i-th object to be processed. It can also represent the interval between the processing time of the i-th object to be processed and the processing time of the object allocated to the k-th first candidate processing resource. In this embodiment, the larger the value of the third parameter, the greater the degree of matching between the processing time of the object allocated to the k-th first candidate processing resource and the processing time of the i-th object to be processed; that is, the smaller the interval between the processing time of the i-th object to be processed and the processing time of the object allocated to the k-th first candidate processing resource. Conversely, the smaller the value of the third parameter, the smaller the degree of matching between the processing time of the object allocated to the k-th first candidate processing resource and the processing time of the i-th object to be processed; that is, the larger the interval between the processing time of the i-th object to be processed and the processing time of the object allocated to the k-th first candidate processing resource.

[0059] The fourth parameter mentioned above indicates whether the k-th first candidate processing resource has previously processed the processing object of the target user corresponding to the i-th object to be processed, and whether the target user has given the k-th first candidate processing resource negative comments. In this embodiment, if the k-th first candidate processing resource has previously processed the processing object of the target user corresponding to the i-th object to be processed, and the target user has not given the k-th first candidate processing resource negative comments, then the fourth parameter takes a larger value; if the k-th first candidate processing resource has not previously processed the processing object of the target user corresponding to the i-th object to be processed, or the target user has given the k-th first candidate processing resource negative comments, then the fourth parameter takes a smaller value, and the more negative comments there are, the smaller the fourth parameter can be.

[0060] Negative reviews, as mentioned here, can be understood as negative feedback. For example, in modern online shopping, buyers can give evaluations of the goods, services, and third-party services necessary for the transaction, based on their subjective opinions or objective assessments. Sellers can also give evaluations of the buyer's attitude and language during the transaction, based on their subjective opinions or objective assessments. These are categorized as positive, neutral, and negative feedback, with negative feedback being the lowest rating.

[0061] The aforementioned fifth parameter represents the processing status of the k-th first candidate processing resource on the processing object within the first preset time period, and can also be understood as representing the processing capability of the k-th first candidate processing resource on the processing object within the first preset time period. In the embodiments of this application, the larger the value of the fifth parameter, the better the processing status of the k-th first candidate processing resource on the processing object within the first preset time period (e.g., more completed items, higher completion efficiency, etc.); conversely, the smaller the value of the fifth parameter, the worse the processing status of the k-th first candidate processing resource on the processing object within the first preset time period (e.g., fewer completed items, lower completion efficiency, etc.).

[0062] The sixth parameter mentioned above indicates whether the k-th first candidate processing resource has been assigned a processing object. In this embodiment, if the k-th first candidate processing resource has been assigned a processing object, the sixth parameter takes a larger value; conversely, if the k-th first candidate processing resource has not been assigned a processing object, the sixth parameter takes a smaller value.

[0063] The seventh parameter mentioned above represents the processing equipment situation of the k-th first candidate processing resource, or it can represent the processing equipment capability of the k-th first candidate processing resource. In the embodiments of this application, the larger the value of the seventh parameter, the better the processing equipment situation of the k-th first candidate processing resource, and the greater the processing equipment capability (for example, the more processing equipment (i.e., the equipment required by the candidate processing resource to process the object to be processed) or the more types of processing equipment it has); conversely, the smaller the value of the seventh parameter, the worse the processing equipment situation of the k-th first candidate processing resource, and the smaller the processing equipment capability (for example, the fewer processing equipment it has or the fewer types of processing equipment it has).

[0064] As can be seen from the above, the larger the value of the first to seventh parameters, the greater the matching degree between the first candidate processing resource and the object to be processed. Therefore, by combining at least one of the first to seventh parameters, a target score representing the matching degree between the first candidate processing resource and the object to be processed can be obtained.

[0065] Optionally, the process of obtaining the first parameter includes:

[0066] The feature information of the i-th object to be processed and the feature information of the k-th first candidate processing resource are input into the pre-established reassignment rate model, and the first parameter is output.

[0067] The aforementioned characteristic information of the objects to be processed may include the city where the first processing address of the object is located, and the first processing address; the characteristic information of the aforementioned first candidate processing resources may include the processing object reassignment ratio, the number of objects accepted for processing, and the number of objects rejected for processing by the first candidate processing resources within the sixth preset time period. It is understood that the characteristic information of the objects to be processed and the characteristic information of the first candidate processing resources are not limited to these.

[0068] The aforementioned reassignment rate model can be a pre-determined extreme gradient boosting (XGBoost) model.

[0069] In addition, the training method for the reassignment rate model is the same as that for existing models. For example, multiple training samples can be collected in advance (each training sample includes feature information of the processing object and feature information of the candidate processing resources), and then the XGBoost algorithm can be used to train the training sample to obtain the aforementioned reassignment rate model.

[0070] Optionally, the process of obtaining the second parameter includes:

[0071] If the first processing address of the i-th object to be processed is located on the target navigation route, the second parameter is determined to be a first preset value, wherein the target navigation route is the navigation route of the processing object that has been allocated to the k-th first candidate processing resource;

[0072] If the first processing address is not on the target navigation route, obtain the second processing address of the last object in the processing order among the objects that have been allocated to the kth first candidate processing resource, and obtain the navigation distance from the second processing address to the first processing address;

[0073] The navigation distance is normalized to obtain a first value;

[0074] The difference between the first preset value and the first value is calculated to obtain the second parameter.

[0075] For example, if the k-th first candidate processing resource has been assigned to two processing objects with processing addresses A and B respectively, and the processing address of the i-th object to be processed is address C, then if address C is located on the navigation route from address A to address B, then address C can be reached on the way from address A to address B without incurring additional distance. In this case, the first parameter = the first preset value - 0, that is, the first parameter = the first preset value. However, if address C is not located on the navigation route from address A to address B, then after reaching address B from address A, it is still necessary to reach address C from address B to process the i-th object to be processed. In this case, the second parameter = the first preset value - the normalized value of the navigation distance from address B to address C.

[0076] Therefore, in the embodiments of this application, the second parameter is determined based on the increased navigation distance of the kth first candidate processing resource processing the i-th object to be processed. That is, the second parameter = the first preset value - the normalized value of the increased navigation path distance of the kth first candidate processing resource processing the i-th object to be processed. The first preset value is a constant. Therefore, the smaller the increased navigation path distance of the kth first candidate processing resource processing the i-th object to be processed, the larger the second parameter; conversely, the larger the increased navigation path distance of the kth first candidate processing resource processing the i-th object to be processed, the smaller the second parameter.

[0077] Optionally, the process of obtaining the third parameter includes:

[0078] Get the processing end time of the object that has been allocated the first candidate processing resource for the kth one;

[0079] Calculate the time interval between the start time of the i-th object to be processed and the end time of each of the processing steps;

[0080] Calculate the average value of the time intervals;

[0081] The average value is normalized to obtain a second value;

[0082] The difference between the second preset value and the second value is calculated to obtain the third parameter.

[0083] For example, if the k-th first candidate processing resource has been assigned to two processing objects with processing end times of TA and TB respectively, and the start processing time of the k-th object to be processed is TC, then the third parameter = the second preset value - the normalized value of the average of the time intervals between TA and TC and between TB and TC. Therefore, the smaller the average of the time intervals between TA and TC and between TB and TC, the larger the third parameter; conversely, the larger the average of the time intervals between TA and TC and between TB and TC, the smaller the third parameter.

[0084] Optionally, the process of obtaining the fourth parameter includes:

[0085] If the target user's object has been processed by the kth first candidate processing resource, and the target user has not given the kth first candidate processing resource any negative comments, then the fourth parameter is determined to be the third preset value.

[0086] If the target user's object has not been processed by the kth first candidate processing resource, or if the target user has given negative comments to the kth first candidate processing resource, the fourth parameter is determined to be the fourth preset value.

[0087] Wherein, the third preset value is greater than the fourth preset value, for example, the third preset value is 1 and the fourth preset value is 0. Therefore, in the embodiments of this application, if the k-th first candidate processing resource has processed the object of the target user and the target user has not given the k-th first candidate processing resource negative comment information, then the fourth parameter takes a larger value; if the k-th first candidate processing resource has not processed the object of the target user, or the target user has given the k-th first candidate processing resource negative comment information, then the fourth parameter takes a smaller value.

[0088] Optionally, the process of obtaining the fifth parameter includes:

[0089] The fifth parameter is determined based on at least one of the following: the number of objects processed by the kth first candidate processing resource within a first preset time period, the on-time rate, the comment information of the user to which the processed object belongs, the number of times the location of the processed object is reported, the number of times the assigned processing object is reassigned by the resource provider, and the number of times the object is not preempted according to the predetermined rules.

[0090] For example: the larger the number of objects processed by the k-th candidate processing resource within the first preset time period, the larger the fifth parameter will be;

[0091] The greater the on-time rate of the kth first candidate processing resource within the first preset time period, the greater the fifth parameter;

[0092] The more times the kth first candidate processing resource receives negative comments within the first preset time period, the smaller the fifth parameter becomes;

[0093] The greater the number of times the kth first candidate processing resource reports its location when processing objects within the first preset time period, the larger the fifth parameter will be;

[0094] The greater the number of times the kth first candidate processing resource is reassigned to a processing object by the resource supplier within the first preset time period, the smaller the fifth parameter will be;

[0095] The greater the number of times the k-th first candidate processing resource fails to preempt objects according to the predetermined rules within the first preset time period, the smaller the fifth parameter becomes. (For example, if a processing resource reassigns objects more than a certain number of times within a certain time period, it is recorded as the processing resource failing to preempt objects according to the predetermined rules).

[0096] Optionally, the process of obtaining the sixth parameter includes:

[0097] If the kth first candidate processing resource has been allocated to a processing object, the sixth parameter is determined to be the fifth preset value;

[0098] If no processing object is assigned to the kth first candidate processing resource, the sixth parameter is determined to be the sixth preset value.

[0099] In this embodiment, the sixth preset value is greater than the fourth preset value; for example, the sixth preset value is 1 and the fifth preset value is 0. Therefore, in the embodiments of this application, if the k-th first candidate processing resource has been assigned a processing object, the sixth parameter takes a larger value; if the k-th first candidate processing resource has not been assigned a processing object, the fourth parameter takes a smaller value.

[0100] Optionally, the process of obtaining the seventh parameter includes:

[0101] The seventh parameter is determined based on the type and quantity of processing equipment possessed by the kth first candidate processing resource.

[0102] For example, if the kth first candidate processing resource has a specific processing device, the value of the seventh parameter is increased by Y1; if the kth first candidate processing resource does not have the specific processing device, the value of the seventh parameter is decreased by Y2.

[0103] The larger the number of processing devices in the kth first candidate processing resource, the larger the seventh parameter will be;

[0104] The larger the number of different types of processing devices the kth first candidate processing resource has, the larger the seventh parameter will be.

[0105] Furthermore, in this embodiment of the application, the specific implementation of step 103, "sorting the first candidate processing resources according to the target score to obtain a first order," can be as follows: Method 1 or Method 2.

[0106] Method 1: Optionally, the step of sorting the first candidate processing resources according to the target score to obtain a first order includes:

[0107] Based on the calculation of the target score to And the second preset formula Calculate the target parameters on the v-th information dimension of the k-th first candidate processing resource.

[0108] according to to At least one parameter in the above parameters is used to sort the first candidate processing resources to obtain a first order.

[0109] Therefore, we can know the target parameter on the v-th information dimension of the k-th first candidate processing resource. Let v be the information dimension of the k-th first candidate processing resource and the matching degree between the 1st to U-th objects to be processed (i.e. to The sum of ). Therefore, This represents the overall matching degree between the v-th information dimension of the k-th first candidate processing resource and each object to be processed. Therefore, based on the above... to At least one parameter in the above parameters is used to rank the first candidate processing resources.

[0110] For example, according to to One of the parameters in the algorithm, when sorting the first candidate processing resources, can be: sorting the first candidate processing resources in descending order according to the parameter.

[0111] For example, according to to When sorting the first candidate processing resources using at least two of the parameters, the sorting can be specifically as follows: sorting the first candidate processing resources in descending order of the sum (or weighted sum) of the at least two parameters.

[0112] Method 2: Optionally, the step of sorting the first candidate processing resources according to the target score to obtain a first order includes:

[0113] Obtain a second candidate processing resource with a preset tag recorded in the first candidate processing resource, and a third candidate processing resource without the preset tag recorded.

[0114] Based on the calculation of the target score to And the second preset formula Calculate the target parameters on the v-th information dimension of the k-th first candidate processing resource.

[0115] according to to At least one parameter in the above, the third candidate processing resource is divided into multiple processing levels;

[0116] The second candidate processing resource is taken as a level and placed before the third candidate processing resource. Different levels are sorted in order from high to low, and processing resources in the same level are sorted in order from large to small according to the target score, thus obtaining the first order.

[0117] Therefore, in the embodiments of this application, the level of the second candidate processing resource with a preset marker is higher than that of the third candidate processing resource without a preset marker. That is, whether or not a preset marker is recorded indicates whether the candidate processing resource is at the highest level.

[0118] For example, when the candidate processing resource is service personnel, some service personnel within the resource provider (i.e., service merchant) are rated as excellent service personnel and have long-term cooperative relationships with the merchant. This indicates that these service personnel can provide better services to users. Therefore, setting these service personnel at the highest level allows for priority selection of service personnel to handle pending matters (such as housekeeping service orders). In other words, it prioritizes selecting excellent service personnel to provide services to users, thereby improving the user's service experience.

[0119] Among them, the above This represents the overall matching degree between the v-th information dimension of the k-th first candidate processing resource and each object to be processed. Therefore, based on the above... to The third candidate processing resource is divided into multiple processing levels based on at least one parameter in the information dimension. That is, the third candidate processing resource is divided into multiple levels according to the degree of matching between the third candidate processing resource and each object to be processed in at least one information dimension. For example, the higher the level, the higher the degree of matching between the third candidate processing resource and each object to be processed.

[0120] In addition, the above "according to to "Dividing the third candidate processing resource into multiple processing levels using at least one parameter (e.g., a hierarchical division parameter)" may include: dividing the third candidate processing resource into multiple levels according to a predetermined correspondence between the value range of the hierarchical division parameter and the levels. For example, the correspondence may be: X1 to X2 correspond to the first level; X3 to X4 correspond to the second level, and the first level is equivalent to the second level. If the hierarchical division parameter of a certain third candidate processing resource is all between X3 and X4, then the third candidate service personnel belongs to the second level.

[0121] As can be seen from the above, in the embodiments of this application, in the first order, the second candidate processing resource with a preset mark is located before all processing resources at all levels, and the processing resources at higher levels are arranged before the processing resources at lower levels. The processing resources at the same level are arranged from largest to smallest according to the target score. In this way, the processing resources at lower levels will only be processed after there are no processing resources at higher levels that can accept the object to be processed. This allows for the priority assignment of excellent and high-quality processing resources to the object to be processed, thereby improving the user's service experience.

[0122] Furthermore, it is understood that "sorting the first candidate processing resources according to the target score to obtain a first order" is not limited to the above method one or method two. For example, the first candidate processing resources can also be sorted according to the target score from largest to smallest to obtain a first order. That is, the first candidate processing resources can be sorted only according to the size of the target score.

[0123] Optionally, selecting a processing resource from the first candidate processing resources to process the object to be processed according to the first order includes:

[0124] The first N processing resources are selected from the first order as the fourth candidate processing resources, where N is an integer greater than 0;

[0125] Obtain the second parameter for each of the fourth candidate processing resources to process each of the objects to be processed, wherein the second parameter of the fourth candidate processing resource represents the degree of matching between the navigation path of the object of the fourth candidate processing resource and the processing address of the object to be processed;

[0126] The sum of the second parameters for the same fourth candidate processing resource is calculated to obtain the sorting parameters;

[0127] The fourth candidate processing resources are sorted in descending order according to the sorting parameters of the fourth candidate processing resources to obtain a second order;

[0128] According to the second order, a processing resource for processing the object to be processed is selected from the fourth candidate processing resources.

[0129] The calculation method for the second parameter of the fourth candidate processing resource is the same as that for the calculation method of the second parameter of the first candidate processing resource, and will not be repeated here.

[0130] In addition, select the top N processing resources from the above first order as the fourth candidate processing resources, and then calculate the sorting parameter according to the second parameter of the fourth candidate processing resources, so as to perform a secondary sorting on the fourth candidate processing resources according to the sorting parameter, and based on the result of the secondary sorting, select the corresponding processing resources for the object to be processed. In this way, it is possible to further select, from the perspective of the path, the processing resources that are more matched with the processing address of the object to be processed from the top N processing resources with a higher matching degree with the object to be processed in the first order, thereby further improving the processing quality of the object to be processed.

[0131] Optionally, the step of selecting the processing resources for processing the object to be processed from the fourth candidate processing resources according to the second order includes:

[0132] In the case where object robbing and dispatching is enabled, select the top M processing resources from the second order as the fifth candidate processing resources, and configure the fifth candidate processing resources to perform robbing and dispatching on the object to be processed, where U ≤ M < N, and M is an integer, and U is the number of objects to be processed;

[0133] In the case where object robbing and dispatching is not enabled, allocate the object to be processed to the top U processing resources in the second order.

[0134] It can be seen from this that in the embodiments of the present application, if object robbing and dispatching is currently enabled, configure the top M (for example, the top 10) processing resources in the foregoing second order to perform robbing and dispatching on the object to be processed; if object robbing and dispatching is not currently enabled and there is one object to be processed, allocate the object to be processed to the first processing resource in the second order; if object robbing and dispatching is not currently enabled and there are multiple objects to be processed, the multiple objects to be processed can be sequentially allocated to the processing resources in the second order according to the second order and the generation order of the multiple objects to be processed.

[0135] Optionally, before obtaining the target scores of each of the first candidate processing resources for processing each of the objects to be processed, the method further includes:

[0136] Eliminate the processing resources that meet the preset conditions among the first candidate processing resources;

[0137] Among them, the preset conditions include at least one of the following:

[0138] The processing range of the processing resource does not cover the first processing address of the object to be processed;

[0139] The number of complaints reaches the seventh preset value within the second preset time period;

[0140] The number of redirected objects reaches the eighth preset value within the third preset time period;

[0141] The ratio of the number of times an object signs in during the fourth preset time period to the number of times an object receives processing during the fourth preset time period is less than the ninth preset value;

[0142] The time interval between the end time of the most recently processed object and the start time of the object to be processed is greater than the tenth preset value;

[0143] Objects of the preset type have been processed within the fifth preset time period.

[0144] Firstly, in the embodiments of this application, each processing resource record has a processing range. For example, the address bound to the processing resource can be used as the center, and a second preset value can be used as the radius. A circle can be drawn on an electronic map, and the area covered by this circle on the electronic map is the range of the processing resource. Wherein, if the processing range of a processing resource covers the first processing address, it means that the processing resource can process the object to be processed; if the processing range of a processing resource does not cover the first processing address, it means that the processing address of the object to be processed exceeds the processing range of the processing resource, i.e., the processing resource cannot process the object to be processed. Therefore, in the embodiments of this application, processing resources whose processing range does not cover the first processing address can be eliminated from the first candidate processing resources.

[0145] Secondly, if the number of complaints against a processing resource reaches a seventh preset value within a second preset time period, it indicates a relatively high probability of such complaints. In this embodiment, processing resources that have reached the seventh preset value within the second preset time period are removed, thus implementing a penalty filtering effect on their processing. If the number of complaints against a processing resource is less than the seventh preset value in the next second preset time period, it will no longer be removed.

[0146] Thirdly, if the number of times an object is reassigned reaches the eighth preset value within the third preset time period, the processing resource will be identified as an object that has not been preempted according to the predetermined rules (e.g., considered as cheating), and thus it can be removed.

[0147] Fourthly, if the ratio of the number of times a processing object signs in during the fourth preset time period to the number of times a processing object is received during the fourth preset time period is less than the ninth preset value, it indicates that the processing resource has failed to sign in at the processing location (i.e. provide services) many times after receiving processing objects during the fourth preset time period. In this case, the processing resource will be identified as a fake resource and can be removed.

[0148] It should be noted here that the "sign-in" in "number of times the processed object signs in during the fourth preset time period" refers to the sign-in process after the processing resource arrives at the processing location.

[0149] Fifthly, if the time interval between the end time of the most recently processed object and the start time of the object to be processed is greater than the tenth preset value, it indicates that the end time of the most recently processed object of the processing resource is far from the start time of the object to be processed. Therefore, the processing resource is not suitable for processing the object to be processed and can be removed.

[0150] Sixthly, the aforementioned preset type of processing object can be an object whose processing time exceeds the predetermined duration, such as deep cleaning service. Deep cleaning service requires a long time, which does not match the time of the housekeeping service order to be processed.

[0151] In this way, by removing the processing resources that meet the above preset conditions from the first candidate processing resources, in the subsequent process of obtaining the target score of the first candidate processing resources, only the target score of the remaining first candidate processing resources can be obtained, without needing to obtain the target score of the removed processing resources. This reduces the number of calls to the target score acquisition method and saves system resources.

[0152] Furthermore, when the target score is obtained by weighted summation of the first to seventh parameters, and the second parameter is equal to the first preset value minus the normalized value of the distance of the navigation path added by the kth first candidate processing resource to the i-th object to be processed, the calculation of the second parameter requires calling the navigation distance, and the calculation of the navigation distance is costly and slow. However, in the embodiments of this application, by removing the processing resources that meet the above preset conditions from the first candidate processing resources, the number of calls to calculate the navigation distance can be reduced, thereby speeding up the allocation speed of the objects to be processed.

[0153] Optionally, the process of acquiring the first candidate processing resource includes:

[0154] Obtain the target resource provider to which the target processing range belongs, wherein the target processing range is the resource provider processing range that covers the first processing address of the object to be processed;

[0155] Obtain the processing resources of the target resource supplier as the first candidate processing resource.

[0156] In this embodiment of the application, each resource provider records a resource provider processing range. For example, the resource provider's address can be used as the center and a first preset value can be used as the radius to draw a circle on an electronic map. The area covered by the circle on the electronic map is the resource provider processing range.

[0157] In this embodiment of the application, if the processing range of a resource provider covers the first processing address, it means that the resource provider can provide processing resources for the object to be processed; if the processing range of a resource provider does not cover the first processing address, it means that the processing address of the object to be processed exceeds the processing range of the resource provider, that is, the resource provider cannot provide processing resources for the object to be processed.

[0158] The processing resources of the target resource supplier are those that have a cooperative relationship with the target resource supplier. Therefore, in this embodiment of the application, after determining the resource supplier (i.e., the target resource supplier) that can provide processing resources for the object to be processed, all the processing resources of the target resource supplier are taken as the first candidate processing resources, so that the processing resources that can process the object to be processed can be selected from the first candidate processing resources.

[0159] In summary, when the resource adaptation method of this application is applied to the scenario of assigning service personnel to orders to be assigned, the specific implementation method can be described in the following steps H1 to H10:

[0160] Step H1: Obtain the first processing address of the order to be assigned;

[0161] Step H2: Obtain the target merchants to which the target service area belongs, where the target service area is the service area of ​​the merchants covering the first processing address;

[0162] Step H3: Obtain the service personnel of the target merchant as the first candidate service personnel;

[0163] Step H4: Eliminate service personnel who meet the preset criteria from the first pool of candidate service personnel;

[0164] The preset conditions include at least one of the following:

[0165] The service personnel's service area did not cover the primary processing address;

[0166] The number of complaints received within the second preset time period reached the seventh preset value;

[0167] The number of times orders are reassigned within the third preset time period reaches the eighth preset value;

[0168] The ratio of the number of times orders were received and checked in during the fourth preset time period to the number of times orders were received during the third preset time period is less than the ninth preset value.

[0169] The time interval between the end time of the most recent received order and the start time of the order to be assigned is greater than the tenth preset value;

[0170] The service of the preset type has been received within the fifth preset time period;

[0171] Step H5: According to the first preset formula Calculate the target score for the k-th first candidate service personnel to process the i-th order to be assigned.

[0172] in, W represents the degree of matching between the v-th information dimension of the k-th first candidate service personnel and the i-th order to be assigned, where i is an integer from 1 to U, and U represents the number of orders to be assigned. v This represents the v-th weight value, where V represents the number of information dimensions of the first candidate service personnel involved in calculating the target score.

[0173] Additionally, V can take the value 7, which involves the calculation of the target score. to The first to seventh parameters can be described separately. The specific meanings and acquisition methods of the first and seventh parameters can be found in the previous text, and will not be repeated here.

[0174] Step H6: Obtain the second candidate service personnel with preset tags recorded in the first candidate service personnel, and the third candidate service personnel without preset tags recorded;

[0175] Step H7: Based on the calculation of the target score... to And the second preset formula Calculate the target parameter on the v-th information dimension of the k-th first candidate service personnel.

[0176] Step H8: According to to At least one parameter in the above, the third candidate service personnel are divided into multiple processing levels;

[0177] Step H9: The second candidate service personnel is placed as a level and ranked before the third candidate service personnel. Different service levels are sorted in order from high to low, and service personnel in the same level are sorted in order from high to low target scores to obtain the first order.

[0178] Step H10: Select the first N service personnel from the first order as the fourth candidate service personnel, where N is an integer greater than 0;

[0179] Step H11: Calculate the sum of the second parameters of the same fourth candidate service personnel to obtain the ranking parameters;

[0180] It should be noted that in the process of calculating the above target scores, the second parameters of each first candidate service person for processing each to-be-allocated order are used. Therefore, in step H10, the second parameters of each to-be-allocated order processed by the same fourth candidate service person can be summed to obtain the above sorting parameter;

[0181] Step H12: Sort the fourth candidate service persons in descending order according to their sorting parameters to obtain a second order;

[0182] Step H13: In the case of enabling order grabbing and dispatching, select the top M service persons from the second order as the fifth candidate service persons, and configure the fifth candidate service persons to grab the to-be-allocated orders, where U ≤ M < N, M is an integer, and U is the number of to-be-allocated orders;

[0183] Step H14: In the case of not enabling order grabbing and dispatching, allocate the to-be-allocated orders to the top K service persons in the second order.

[0184] As can be seen from the above, in the above embodiment, all order information can be directly obtained through the network platform, and then the information of all service persons can be obtained, so as to directly allocate the orders to the service persons. This not only reduces the operation cost of the merchants, but also can perform overall optimization, improve the overall order-taking efficiency of the service persons, urge the service persons to improve the service quality, thereby improving the overall quality and brand influence of the network platform, and further improving the benefits of the service persons, merchants, and network platform.

[0185] It should be noted that for the method embodiments, for the sake of simple description, they are all expressed as a series of action combinations. However, those skilled in the art should know that the embodiments of the present application are not limited by the described action sequences, because according to the embodiments of the present application, some steps can be performed in other sequences or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions involved are not necessarily required by the embodiments of the present application.

[0186] Referring to Figure 2 , a structural block diagram of a resource adaptation device in an embodiment of the present application is shown. The resource adaptation device may include the following modules:

[0187] The first acquisition module 201 is configured to acquire at least one to-be-processed object and at least one first candidate processing resource;

[0188] The second acquisition module 202 is configured to acquire the target scores of each of the first candidate processing resources for processing each of the to-be-processed objects, where the target score represents the matching degree between the first candidate processing resource and the to-be-processed object;

[0189] The first sorting module 203 is used to sort the first candidate processing resources according to the target score to obtain a first order;

[0190] The first selection module 204 is used to select a processing resource from the first candidate processing resources to process the object to be processed according to the first order.

[0191] Optionally, the second acquisition module 202 includes:

[0192] The first calculation submodule is used to calculate according to the first preset formula. Calculate the target score for the k-th first candidate processing resource to process the i-th object to be processed.

[0193] in, W represents the degree of matching between the v-th information dimension of the k-th first candidate processing resource and the i-th object to be processed, where i is an integer from 1 to U, and U represents the number of objects to be processed. v This represents the v-th weight value, where V represents the number of information dimensions of the first candidate processing resource involved in calculating the target score.

[0194] Optional, to Each of the following is at least one of the first to seventh parameters:

[0195] The first parameter represents the reassignment probability after the kth first candidate processing resource processes the i-th object to be processed.

[0196] The second parameter represents the degree of matching between the navigation path of the object assigned to the k-th first candidate processing resource and the processing address of the i-th object to be processed.

[0197] The third parameter represents the degree of matching between the processing time of the object allocated to the k-th first candidate processing resource and the processing time of the i-th object to be processed.

[0198] The fourth parameter indicates whether the k-th first candidate processing resource has processed the processing object of the target user corresponding to the i-th object to be processed, and whether the target user has given negative comment information to the k-th first candidate processing resource;

[0199] The fifth parameter represents the processing status of the k-th first candidate processing resource on the processing object within a first preset time period;

[0200] The sixth parameter indicates whether the k-th first candidate processing resource has been allocated to a processing object;

[0201] The seventh parameter represents the processing equipment available for the k-th first candidate processing resource.

[0202] Optionally, the second acquisition module 202 further includes:

[0203] The first parameter determination submodule is used to input the feature information of the i-th object to be processed and the feature information of the k-th first candidate processing resource into the pre-established reassignment rate model and output the first parameter.

[0204] Optionally, the second acquisition module 202 further includes a second parameter determination submodule;

[0205] The second parameter determination submodule is used for:

[0206] If the first processing address of the i-th object to be processed is located on the target navigation route, the second parameter is determined to be a first preset value, wherein the target navigation route is the navigation route of the processing object that has been allocated to the k-th first candidate processing resource;

[0207] If the first processing address is not on the target navigation route, obtain the second processing address of the last object in the processing order among the objects that have been allocated to the kth first candidate processing resource, and obtain the navigation distance from the second processing address to the first processing address;

[0208] The navigation distance is normalized to obtain a first value;

[0209] The difference between the first preset value and the first value is calculated to obtain the second parameter.

[0210] Optionally, the second acquisition module 202 further includes: a third parameter determination submodule;

[0211] The third parameter determination submodule is used for:

[0212] Get the processing end time of the object that has been allocated the first candidate processing resource for the kth one;

[0213] Calculate the time interval between the start time of the i-th object to be processed and the end time of each of the processing steps;

[0214] Calculate the average value of the time intervals;

[0215] The average value is normalized to obtain a second value;

[0216] The difference between the second preset value and the second value is calculated to obtain the third parameter.

[0217] Optionally, the second acquisition module 202 further includes a fourth parameter determination submodule;

[0218] The fourth parameter determination submodule is used for:

[0219] If the target user's object has been processed by the kth first candidate processing resource, and the target user has not given the kth first candidate processing resource any negative comments, then the fourth parameter is determined to be the third preset value.

[0220] If the target user's object has not been processed by the kth first candidate processing resource, or if the target user has given negative comments to the kth first candidate processing resource, the fourth parameter is determined to be the fourth preset value.

[0221] Optionally, the second acquisition module 202 further includes a fifth parameter determination submodule;

[0222] The fifth parameter determination submodule is used for:

[0223] The fifth parameter is determined based on at least one of the following: the number of objects processed by the kth first candidate processing resource within a first preset time period, the on-time rate, the comment information of the user to which the processed object belongs, the number of times the location of the processed object is reported, the number of times the assigned processing object is reassigned by the resource provider, and the number of times the object is not preempted according to the predetermined rules.

[0224] Optionally, the second acquisition module 202 further includes a sixth parameter determination submodule;

[0225] The sixth parameter determination submodule is used for:

[0226] If the kth first candidate processing resource has been allocated to a processing object, the sixth parameter is determined to be the fifth preset value;

[0227] If no processing object is assigned to the kth first candidate processing resource, the sixth parameter is determined to be the sixth preset value.

[0228] Optionally, the second acquisition module 202 further includes a seventh parameter determination submodule;

[0229] The seventh parameter determination submodule is used for:

[0230] The seventh parameter is determined based on the type and quantity of processing equipment possessed by the kth first candidate processing resource.

[0231] Optionally, the first sorting module 203 includes:

[0232] The second calculation submodule is used to calculate the target score based on the relevant factors. to And the second preset formula Calculate the target parameters on the v-th information dimension of the k-th first candidate processing resource.

[0233] The first sorting submodule is used to sort according to... to At least one parameter in the above parameters is used to sort the first candidate processing resources to obtain a first order.

[0234] Optionally, the first sorting module 203 includes:

[0235] The filtering submodule is used to obtain the second candidate processing resource that has a preset mark recorded in the first candidate processing resource, and the third candidate processing resource that has not recorded the preset mark.

[0236] The third calculation submodule is used to calculate the target score based on the relevant information. to And the second preset formula Calculate the target parameters on the v-th information dimension of the k-th first candidate processing resource.

[0237] Hierarchical sub-modules are used to divide modules according to... to At least one parameter in the above, the third candidate processing resource is divided into multiple processing levels;

[0238] The second sorting submodule is used to treat the second candidate processing resource as a level and place the second candidate processing resource before the third candidate processing resource. Different levels are sorted in order from high to low, and processing resources in the same level are sorted in order from large to small according to the target score, thus obtaining the first order.

[0239] Optionally, the first selection module 204 includes:

[0240] The first selection submodule is used to select the top N processing resources from the first order as the fourth candidate processing resources, where N is an integer greater than 0.

[0241] The parameter acquisition submodule is used to acquire the second parameters of each of the fourth candidate processing resources for processing each of the objects to be processed, wherein the second parameters of the fourth candidate processing resource represent the degree of matching between the navigation path of the object of the fourth candidate processing resource and the processing address of the object to be processed;

[0242] The fourth calculation submodule is used to calculate the sum of the second parameters of the same fourth candidate processing resource to obtain the sorting parameters;

[0243] A third sorting sub-module, configured to sort the fourth candidate processing resources in descending order according to the sorting parameters of the fourth candidate processing resources, so as to obtain a second order.

[0244] A second selection sub-module, configured to select a processing resource for processing the to-be-processed object from the fourth candidate processing resources according to the second order.

[0245] Optionally, the second selection sub-module is specifically configured to:

[0246] When object preemption is enabled, select the top M processing resources from the second order as the fifth candidate processing resources, and configure the fifth candidate processing resources to perform preemption on the to-be-processed object, where U≤M<N, M is an integer, and U is the number of to-be-processed objects;

[0247] When object preemption is not enabled, allocate the to-be-processed object to the top U processing resources in the second order.

[0248] Optionally, the apparatus further includes:

[0249] A resource elimination module, configured to eliminate the processing resources in the first candidate processing resources that meet the preset conditions;

[0250] Wherein, the preset conditions include at least one of the following:

[0251] The processing range of the processing resource does not cover the first processing address of the to-be-processed object;

[0252] The number of complaints reaches a seventh preset value within a second preset time period;

[0253] The number of reassigned objects reaches an eighth preset value within a third preset time period;

[0254] The ratio of the number of check-ins of the processed objects to the number of received processed objects within a fourth preset time period is less than a ninth preset value;

[0255] The time interval between the end time of the most recently processed object and the start time of the to-be-processed object is greater than a tenth preset value;

[0256] Has received processed objects of a preset type within a fifth preset time period.

[0257] Optionally, the first obtaining module 201 obtains the first candidate processing resources, specifically for:

[0258] Obtain the target resource provider to which the target processing range belongs, wherein the target processing range is the resource provider processing range that covers the first processing address of the object to be processed;

[0259] Obtain the processing resources of the target resource supplier as the first candidate processing resource.

[0260] As the device embodiment is basically similar to the method embodiment, the description is relatively simple, and relevant parts can be found in the description of the method embodiment.

[0261] This application also provides an electronic device, including:

[0262] One or more processors; and

[0263] One or more machine-readable media storing instructions thereon, when executed by the one or more processors, cause the electronic device to perform the resource adaptation method described in the embodiments of this application.

[0264] This application also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the resource adaptation method described in this application.

[0265] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. The same or similar parts between the various embodiments can be referred to each other.

[0266] Those skilled in the art will understand that embodiments of this application can be provided as methods, apparatus, or computer program products. Therefore, embodiments of this application can take the form of entirely hardware embodiments, entirely software embodiments, or embodiments combining software and hardware aspects. Furthermore, embodiments of this application can take the form of computer program products implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0267] This application describes embodiments with reference to flowchart illustrations and / or block diagrams of methods, terminal devices (systems), and computer program products according to embodiments of this application. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing terminal device to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing terminal device, generate instructions for implementing the flowchart illustrations. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0268] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing terminal device to operate in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0269] These computer program instructions can also be loaded onto a computer or other programmable data processing terminal equipment, causing a series of operational steps to be performed on the computer or other programmable terminal equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable terminal equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0270] Although preferred embodiments of the present application have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of the embodiments of the present application.

[0271] Finally, it should be noted that in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or terminal device 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 terminal device. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or terminal device that includes said element.

[0272] The resource adaptation method and apparatus provided in this application have been described in detail above. Specific examples have been used to illustrate the principles and implementation methods of this application. The description of the above embodiments is only for the purpose of helping to understand the method and core ideas of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A resource adaptation method, characterized in that, The method includes: Acquire at least one object to be processed and at least one first candidate processing resource; Obtain the target score for each of the first candidate processing resources in processing each of the objects to be processed, wherein the target score represents the degree of matching between the first candidate processing resource and the object to be processed; Based on the target score, the first candidate processing resources are sorted to obtain a first order; According to the first order, a processing resource for processing the object to be processed is selected from the first candidate processing resources; The step of selecting a processing resource from the first candidate processing resources to process the object to be processed according to the first order includes: The first N processing resources are selected from the first order as the fourth candidate processing resources, where N is an integer greater than 0; Obtain the second parameter for each of the fourth candidate processing resources to process each of the objects to be processed, wherein the second parameter of the fourth candidate processing resource represents the degree of matching between the navigation path of the object of the fourth candidate processing resource and the processing address of the object to be processed; The sum of the second parameters for the same fourth candidate processing resource is calculated to obtain the sorting parameters; The fourth candidate processing resources are sorted in descending order according to the sorting parameters of the fourth candidate processing resources to obtain a second order; According to the second order, a processing resource for processing the object to be processed is selected from the fourth candidate processing resources.

2. The method of claim 1, wherein, The step of obtaining the target score for each of the first candidate processing resources for each of the objects to be processed includes: According to the first preset formula, calculate the target score for the kth first candidate processing resource to process the i-th object to be processed; Wherein, represents the matching degree between the vth information dimension of the kth first candidate processing resource and the ith object to be processed, i is an integer from 1 to U, U represents the number of objects to be processed, represents the vth weight value, and V represents the number of information dimensions of the first candidate processing resources involved in calculating the target score.

3. The method of claim 2, wherein, Each of the following is at least one of the first to seventh parameters: The first parameter represents the reassignment probability after the kth first candidate processing resource processes the i-th object to be processed. The second parameter represents the degree of matching between the navigation path of the object assigned to the k-th first candidate processing resource and the processing address of the i-th object to be processed. The third parameter represents the degree of matching between the processing time of the object allocated to the k-th first candidate processing resource and the processing time of the i-th object to be processed. The fourth parameter indicates whether the k-th first candidate processing resource has processed the processing object of the target user corresponding to the i-th object to be processed, and whether the target user has given negative comment information to the k-th first candidate processing resource; The fifth parameter represents the processing status of the k-th first candidate processing resource on the processing object within a first preset time period; The sixth parameter indicates whether the k-th first candidate processing resource has been allocated to a processing object; The seventh parameter represents the processing equipment available for the k-th first candidate processing resource.

4. The method of claim 3, wherein, The process of obtaining the first parameter includes: The feature information of the i-th object to be processed and the feature information of the k-th first candidate processing resource are input into the pre-established reassignment rate model, and the first parameter is output.

5. The method of claim 3, wherein, The process of obtaining the second parameter includes: If the first processing address of the i-th object to be processed is located on the target navigation route, the second parameter is determined to be a first preset value, wherein the target navigation route is the navigation route of the processing object that has been allocated to the k-th first candidate processing resource; If the first processing address is not on the target navigation route, obtain the second processing address of the last object in the processing order among the objects that have been allocated to the kth first candidate processing resource, and obtain the navigation distance from the second processing address to the first processing address; The navigation distance is normalized to obtain a first value; The difference between the first preset value and the first value is calculated to obtain the second parameter.

6. The method of claim 3, wherein, The process of obtaining the third parameter includes: Get the processing end time of the object that has been allocated the first candidate processing resource for the kth one; Calculate the time interval between the start time of the i-th object to be processed and the end time of each of the processing steps; Calculate the average value of the time intervals; The average value is normalized to obtain a second value; The difference between the second preset value and the second value is calculated to obtain the third parameter.

7. The method of claim 3, wherein, The process of obtaining the fourth parameter includes: If the target user's object has been processed by the kth first candidate processing resource, and the target user has not given the kth first candidate processing resource any negative comments, then the fourth parameter is determined to be the third preset value. If the target user's object has not been processed by the kth first candidate processing resource, or if the target user has given negative comments to the kth first candidate processing resource, the fourth parameter is determined to be the fourth preset value.

8. The method of claim 3, wherein, The process of obtaining the fifth parameter includes: The fifth parameter is determined based on at least one of the following: the number of objects processed by the k-th first candidate processing resource within the first preset time period, the on-time rate, the comment information of the user to which the processed object belongs, the number of times the location was reported when processing the object, the number of times the assigned processing object was reassigned by the resource provider, and the number of times the object was not preempted according to the predetermined rules.

9. The method of claim 3, wherein, The process of obtaining the sixth parameter includes: If the kth first candidate processing resource has been allocated to a processing object, the sixth parameter is determined to be the fifth preset value; If no processing object is assigned to the kth first candidate processing resource, the sixth parameter is determined to be the sixth preset value.

10. The method of claim 3, wherein, The process of obtaining the seventh parameter includes: The seventh parameter is determined based on the type and quantity of processing equipment possessed by the kth first candidate processing resource.

11. The method of claim 2, wherein, The step of sorting the first candidate processing resources according to the target score to obtain a first order includes: Calculate the target parameter on the v-th information dimension of the k-th first candidate processing resource according to the involved parameters from to and the second preset formula when calculating the target score; Sort the first candidate processing resources according to at least one of the parameters from to to obtain a first order.

12. The method of claim 2, wherein, The sorting the first candidate processing resources according to the target score to obtain a first order includes: Obtain the second candidate processing resources with a preset mark recorded in the first candidate processing resources and the third candidate processing resources without the preset mark recorded; Calculate the target parameter on the v-th information dimension of the k-th first candidate processing resource according to the involved parameters from to and the second preset formula when calculating the target score; Divide the third candidate processing resources into multiple processing levels according to at least one of the parameters from to; Take the second candidate processing resources as one level, arrange the second candidate processing resources before the third candidate processing resources, and sort different levels in descending order from high to low, and sort the processing resources in the same level in descending order according to the target score to obtain the first order.

13. The method of claim 1, wherein, The selecting the processing resource for processing the to-be-processed object from the fourth candidate processing resources according to the second order includes: In the case of enabling object preemption, select the top M processing resources from the second order as the fifth candidate processing resources, and configure the fifth candidate processing resources to preempt the to-be-processed object, where U ≤ M < N, and M is an integer, and U is the number of to-be-processed objects; In the case of not enabling object preemption, allocate the to-be-processed object to the top U processing resources in the second order.

14. The method according to claim 1, characterized in that, Before obtaining the target score of each first candidate processing resource for processing each to-be-processed object, the method further includes: Eliminate the processing resources in the first candidate processing resources that meet the preset conditions; Among them, the preset conditions include at least one of the following: The processing range of the processing resource does not cover the first processing address of the to-be-processed object; The number of complaints reaches the seventh preset value within the second preset time period; The number of reassigned objects reaches the eighth preset value within the third preset time period; The ratio of the number of check-ins of the processed objects to the number of received to-be-processed objects within the fourth preset time period is less than the ninth preset value; The time interval between the end time of the most recent processed object and the start time of the to-be-processed object is greater than the tenth preset value; Has received a to-be-processed object of a preset type within the fifth preset time period.

15. The method of claim 1, wherein, The process of obtaining the first candidate processing resources includes: Obtain the target resource provider to which the target processing range belongs, where the target processing range is the resource provider processing range covering the first processing address of the to-be-processed object; Obtain the processing resources of the target resource provider as the first candidate processing resources.

16. A resource adaptation apparatus, characterized by, The device includes: A first acquisition module, configured to acquire at least one to-be-processed object and at least one first candidate processing resource; The second acquisition module is used to acquire the target score of each of the first candidate processing resources for processing each of the objects to be processed, wherein the target score represents the degree of matching between the first candidate processing resource and the object to be processed; The first sorting module is used to sort the first candidate processing resources according to the target score to obtain a first order; The first selection module is used to select a processing resource from the first candidate processing resources to process the object to be processed according to the first order. The first selection module includes: The first selection submodule is used to select the top N processing resources from the first order as the fourth candidate processing resources, where N is an integer greater than 0. The parameter acquisition submodule is used to acquire the second parameters of each of the fourth candidate processing resources for processing each of the objects to be processed, wherein the second parameters of the fourth candidate processing resource represent the degree of matching between the navigation path of the object of the fourth candidate processing resource and the processing address of the object to be processed; The fourth calculation submodule is used to calculate the sum of the second parameters of the same fourth candidate processing resource to obtain the sorting parameters; The third sorting submodule is used to sort the fourth candidate processing resources in descending order according to the sorting parameters of the fourth candidate processing resources to obtain a second order; The second selection submodule is used to select a processing resource from the fourth candidate processing resources to process the object to be processed, according to the second order.

17. An electronic device, comprising: The electronic device includes: One or more processors; and One or more machine-readable media having instructions stored thereon, which, when executed by the one or more processors, cause the electronic device to perform the resource adaptation method as described in any one of claims 1-15.

18. A computer-readable storage medium, characterized in that, A computer program is stored on the computer-readable storage medium, and when executed by a processor, the computer program implements the steps of the resource adaptation method as described in any one of claims 1 to 15.

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