CN114648374A

CN114648374A - Order processing method, device, server and computer readable storage medium

Info

Publication number: CN114648374A
Application number: CN202011522845.9A
Authority: CN
Inventors: 叶成鹏; 黄方胜
Original assignee: Beijing Sankuai Online Technology Co Ltd
Current assignee: Beijing Sankuai Online Technology Co Ltd
Priority date: 2020-12-21
Filing date: 2020-12-21
Publication date: 2022-06-21

Abstract

The application discloses an order processing method, an order processing device, a server and a computer readable storage medium, and belongs to the technical field of internet. The method comprises the following steps: receiving order information of a target order, wherein the order information comprises order placing time and order resources of the target order; determining the predicted order receiving time of the target order based on the order placing time of the target order; in response to the target order not being received within the projected order taking time, calculating additional resources for the target order based on the order resources for the target order; and determining the target delivery resources of the target order based on the additional resources of the target order and the original delivery resources of the target order. According to the method, the extra additional resources of the target order are calculated in a targeted manner according to the order resources of the target order, dynamic adjustment of the extra additional resources is achieved, the matching degree between the determined extra additional resources and the target order is higher, the accuracy of the determined extra additional resources is improved, and the receiving success rate of the target order is improved.

Description

Order processing method, device, server and computer readable storage medium

Technical Field

The embodiment of the application relates to the technical field of internet, in particular to an order processing method, an order processing device, a server and a computer readable storage medium.

Background

With the continuous development of internet technology, the association between the take-out industry and the internet technology is more and more close, and the take-out industry is gradually favored by consumers. The number of take-out orders received by merchants is increasing, and the number of riders is limited, resulting in the problem that take-out orders are not taken by people. Therefore, an order processing method is needed to improve the order taking rate of the take-away orders, so as to improve the processing success rate of the take-away orders.

In the related art, after a user submits a takeaway order on a takeaway platform, a merchant makes the takeaway order, the takeaway platform puts the takeaway order into an order taking pool, and a rider takes an order in the order taking pool. When the order is not taken by a rider for a fixed time, namely the takeout order is taken but is not taken, the takeout platform directly determines the takeout order as a loss order and makes corresponding subsidy for the takeout order, namely extra additional resources are added to the takeout order. For example, over 40 minutes, no order is received, with an additional X-ary addition. The final delivery fee is determined based on the additional amount and the original delivery fee of the order.

However, the matching degree between the determined extra amount of the take-out order and the take-out order in the above order processing method is low, which results in low accuracy of the determined extra amount, and thus low success rate of receiving the take-out order.

Disclosure of Invention

The embodiment of the application provides an order processing method, an order processing device, a server and a computer readable storage medium, which can be used for solving the problems in the related art. The technical scheme is as follows:

in one aspect, an embodiment of the present application provides an order processing method, where the method includes:

receiving order information of a target order, wherein the order information comprises order placing time and order resources of the target order;

determining the expected order taking time of the target order based on the order placing time of the target order;

responsive to the target order not being received within the projected order taking time, calculating additional resources for the target order based on the order resources for the target order;

and determining target delivery resources of the target order based on the additional resources of the target order and the original delivery resources of the target order, wherein the target delivery resources are used for improving the receiving success rate of the target order.

In one possible implementation, the calculating, in response to the target order not being received within the expected pick-up time, additional resources for the target order based on the order resources for the target order includes:

in response to the target order not being received within the projected order taking time, determining a probability that the target order is a loss order indicating an order that was successfully placed but not taken;

in response to the probability that the target order is a loss order being greater than a target probability, calculating additional resources for the target order based on the order resources of the target order.

In a possible implementation manner, the order information further includes an order feature of the target order;

calculating additional resources of the target order based on the order resources of the target order in response to the probability that the target order is a loss order being greater than a target probability, including:

in response to the fact that the probability that the target order is a loss order is larger than the target probability, determining an order difficulty coefficient of the target order based on the order characteristics of the target order;

calculating additional resources of the target order based on the order resources of the target order and the order difficulty coefficient of the target order.

In one possible implementation, the determining the probability that the target order is a loss order in response to the target order not being received within the expected order taking time includes:

in response to the target order not being received within the expected order taking time, inputting order characteristics of the target order into a target probability prediction model, wherein the target probability prediction model is used for determining the probability that the target order is a loss order;

and determining the probability that the target order is the loss order based on the output result of the target probability prediction model.

In one possible implementation, before determining the expected order taking time of the target order based on the order placing time of the target order, the method further includes:

acquiring cancel order data of a target time period, wherein the cancel order data comprises order placing time and cancel time of each cancel order;

determining the average order receiving time length based on the order placing time and the canceling time of each canceling order;

the determining the expected order taking time of the target order based on the order placing time of the target order comprises:

and determining the expected order taking time of the target order based on the order placing time of the target order and the average order taking time length.

In one possible implementation, the cancellation list data further includes a cancellation list number of the target time period;

before calculating additional resources for the target order based on the order resources of the target order in response to the target order not being received within the projected order taking time, the method further comprises:

determining an additional order quantity per unit time period based on the cancelled order quantity for the target time period;

calculating additional resources for the target order based on the order resources for the target order in response to the target order not being received within the projected order taking time, comprising:

in response to the target order not being received within the projected order taking time and the target order being within the additional order quantity, calculating additional resources for the target order based on the order resources for the target order.

In one possible implementation, the determining the additional order quantity per unit time period based on the cancel order quantity for the target time period includes:

determining the number of cancelled sheets in a unit time period based on the number of cancelled sheets in the target time period;

and determining the additional order quantity of the unit time period based on the cancelled order quantity and the order-to-order additional resource coefficient of the unit time period.

On the other hand, an embodiment of the present application provides an order processing apparatus, including:

the receiving module is used for receiving order information of a target order, wherein the order information comprises order placing time and order resources of the target order;

the first determination module is used for determining the predicted order receiving time of the target order based on the order placing time of the target order;

a calculation module for calculating additional resources for the target order based on order resources for the target order in response to the target order not being received within the projected order taking time;

a second determining module, configured to determine target delivery resources of the target order based on additional resources of the target order and original delivery resources of the target order, where the target delivery resources are used to improve a receiving success rate of the target order.

In one possible implementation, the calculation module is configured to determine, in response to the target order not being received within the expected order receiving time, a probability that the target order is a loss order indicating an order that has been successfully placed but not received; in response to the probability that the target order is a loss order being greater than a target probability, calculating additional resources for the target order based on the order resources of the target order.

the calculating module is used for responding that the probability that the target order is the loss order is greater than the target probability, and determining an order difficulty coefficient of the target order based on the order characteristics of the target order; calculating additional resources of the target order based on the order resources of the target order and the order difficulty coefficient of the target order.

In one possible implementation, the calculation module is configured to, in response to the target order not being received within the expected order receiving time, input an order characteristic of the target order into a target probability prediction model, where the target probability prediction model is configured to determine a probability that the target order is a loss order; and determining the probability that the target order is the loss order based on the output result of the target probability prediction model.

In one possible implementation, the apparatus further includes:

the acquisition module is used for acquiring the order canceling data of the target time period, wherein the order canceling data comprises order placing time and canceling time of each order;

the first determining module is further configured to determine an average order receiving time length based on the order placing time and the cancellation time of each cancellation order; and determining the expected order taking time of the target order based on the order placing time of the target order and the average order taking time length.

the second determining module is further used for determining the number of additional orders in the unit time period based on the number of cancelled orders in the target time period;

the calculation module is configured to calculate additional resources of the target order based on the order resources of the target order in response to the target order not being received within the expected order taking time and the target order being within the additional order quantity.

In a possible implementation manner, the first determining module is configured to determine the number of the cancellation orders in the unit time period based on the number of the cancellation orders in the target time period;

In another aspect, an embodiment of the present application provides a server, where the server includes a processor and a memory, where the memory stores at least one program code, and the at least one program code is loaded and executed by the processor, so as to implement any one of the order processing methods described above.

In another aspect, a computer-readable storage medium is provided, in which at least one program code is stored, and the at least one program code is loaded and executed by a processor to implement any of the above order processing methods.

In another aspect, a computer program or a computer program product is provided, in which at least one computer instruction is stored, and the at least one computer instruction is loaded and executed by a processor to implement any of the above order processing methods.

The technical scheme provided by the embodiment of the application at least has the following beneficial effects:

according to the technical scheme provided by the embodiment of the application, when the target order is not received within the expected order receiving time, the extra additional resources of the target order are calculated in a targeted manner according to the order resources of the target order, the dynamic determination of the extra additional resources is realized, the matching degree between the determined extra additional resources and the target order is higher, and the accuracy of the determined extra additional resources can be improved. After the target delivery resources of the target order are determined, when the order is dispatched according to the target delivery resources, the dispatching of the delivery resources can be stimulated, so that the order receiving probability of the target order is improved, namely the receiving success rate of the target order is improved.

Drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the description below are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings without creative efforts.

Fig. 1 is a schematic diagram of an implementation environment of an order processing method according to an embodiment of the present application;

fig. 2 is a flowchart of an order processing method according to an embodiment of the present application;

FIG. 3 is a distribution diagram of the placing time and the canceling time of a canceling order provided by an embodiment of the present application;

FIG. 4 is a schematic diagram illustrating a method for determining a probability that a target order is a loss order according to an embodiment of the present disclosure;

fig. 5 is a schematic diagram illustrating a value of determining a list-average additional resource coefficient according to an embodiment of the present disclosure;

fig. 6 is a schematic diagram of a correspondence relationship between a time weighting result and a time coefficient provided in an embodiment of the present application;

FIG. 7 is a flowchart of a process for processing a target order according to an embodiment of the present application;

FIG. 8 is an architecture diagram of an order processing provided by an embodiment of the present application;

fig. 9 is a schematic structural diagram of an order processing apparatus according to an embodiment of the present application;

fig. 10 is a schematic structural diagram of a server provided in an embodiment of the present application;

fig. 11 is a schematic structural diagram of an electronic device according to an embodiment of the present application.

Detailed Description

To make the objects, technical solutions and advantages of the present application more clear, embodiments of the present application will be described in further detail below with reference to the accompanying drawings.

Fig. 1 is a schematic diagram of an implementation environment of an order processing method according to an embodiment of the present application, and as shown in fig. 1, the implementation environment includes: a server 101 and an electronic device 102.

The server 101 is a server, or a server cluster formed by a plurality of servers, or the server 101 is at least one of a cloud computing platform and a virtualization center, which is not limited in the embodiment of the present application. The server 101 is connected to the electronic device 102 through a wired network or a wireless network. The server 101 is configured to execute the order processing method provided in the embodiment of the present application. Of course, the server 101 may also include other functional servers to provide more comprehensive and diversified services.

The electronic device 102 is at least one of a smart phone, a game console, a desktop computer, a tablet computer, an e-book reader, an MP3(Moving Picture Experts Group Audio Layer III, motion Picture Experts compression standard Audio Layer 3) player, an MP4(Moving Picture Experts Group Audio Layer IV, motion Picture Experts compression standard Audio Layer 4) player, and a laptop computer. The electronic device 102 is a rider electronic device for receiving the target order, the electronic device 102 is configured to receive order information of the target order sent by the server 101, and the electronic device 102 is further configured to receive target distribution resources of the target order transferred by the server 101.

The electronic device 102 may be generally referred to as one of a plurality of electronic devices, and the embodiment is merely illustrated by the electronic device 102. Those skilled in the art will appreciate that the number of electronic devices 102 described above may be greater or fewer. For example, the number of the electronic devices 102 may be only one, or the number of the electronic devices 102 may be tens or hundreds, or more, and the number of the electronic devices and the device types are not limited in the embodiment of the present application.

Based on the foregoing implementation environment, an embodiment of the present application provides an order processing method, which may be executed by the server 101 in fig. 1 by taking a flowchart of the order processing method provided in the embodiment of the present application as an example, as shown in fig. 2. As shown in fig. 2, the method comprises the steps of:

in step 201, order information of the target order is received, wherein the order information includes order placing time and order resources of the target order.

In the embodiment of the present application, an application for order processing is installed and executed in the server, and the application is any type of application, which is not limited in the embodiment of the present application. The electronic device has a take-away application installed and running therein. The server and the electronic device are in communication connection through a wired network or a wireless network. The take-out application program in the electronic equipment is used for receiving the take-out order, sending order information of the take-out order to the server, and processing the take-out order by the application program used for order processing in the server.

In one possible implementation manner, the target user orders in a take-away application installed in the electronic device, and in response to the target user clicking an order placing button or the target user paying for order resources of the target order, the electronic device sends order information of the target order to the server, where the order information includes order placing time and order resources of the target order. That is, the server receives order information for the target order. Wherein the order resource is the order price of the target order.

Illustratively, the target user places a single target order with 30-element order resources at 10 o' clock 45, the electronic device sends order information of the target order to the server in response to the order placing operation of the target user, and the order information of the target order received by the server is respectively: the order-giving time is as follows: 10 point 45 point, order resources of the target order: 30 yuan.

In step 202, an estimated order taking time for the target order is determined based on the order placing time for the target order.

In a possible implementation manner, before determining the expected order receiving time of the target order based on the order placing time of the target order, an average order receiving time length needs to be determined, and the determination process of the average order receiving time length comprises the following steps 1 to 2.

Step 1, acquiring cancellation list data of a target time period.

The cancel list data comprises list placing time and cancel time of each cancel list.

In a possible implementation manner, the storage space of the server stores the order information of the order in each time period, and the server randomly determines a time period in the storage space of the server, and takes the time period as the target time period. The server acquires the order in the target time period and extracts order information of the cancelled order in the target time period, namely, the server acquires the order cancellation data in the target time period.

Or, the user sets a time period in the server in advance, the server takes the time period set by the user as a target time period, the server extracts order information of the order in the target time period from a storage space of the server, and extracts order information of the cancelled order in the target time period, that is, the server acquires the cancellation order data in the target time period.

And 2, determining the average order receiving time length based on the order placing time and the canceling time of each canceling order.

In a possible implementation manner, after the target order is placed, the target order is identified at different times, and the probabilities that the target order is a loss order are all inconsistent, so that in order to more accurately identify whether the target order is the loss order, a reasonable average order receiving time length needs to be determined according to the order placing time and the order canceling time of the loss order, and therefore the expected order receiving time of the target order is determined according to the average order receiving time length and the order placing time of the target order. When the target order is not received within the expected order receiving time, it means that the target order needs to be identified to determine whether the target order is a loss order. The loss order is used to indicate an order that has been successfully placed but not picked, i.e., an order that has been successfully placed by the merchant but not picked by the rider.

Fig. 3 is a distribution diagram of the order placing time and the cancellation time of the cancellation order provided in the embodiment of the present application, in fig. 3, the cancellation order is generally cancelled in about 19 minutes after the order placing, that is, the order is placed after the order, and if there is no rider receiving or sending within 19 minutes, the user will cancel the order with a high probability. Therefore, the order needs to be identified within 19 minutes after placing the order to determine if the order is a loss order. From the identification experience of the loss order, it is known that identifying the order 14 minutes after placing the order determines that the order is a loss order with an accuracy of 36%, and identifying the order 18 minutes after placing the order determines that the order is a loss order with an accuracy of 64%. Since the accuracy of recognition carried out 18 minutes after the order is placed is higher than that of recognition carried out 14 minutes after the order is placed, in order to more accurately recognize whether the target order is a loss order, the average order receiving time length is determined to be 18 minutes, namely, whether the order is received by a rider within 18 minutes after the order placing time is judged, and if the order is received by the rider, the order is waited to be sent by the rider; if the order is not taken by the rider, the order is identified at the 18 th minute after the order placement time.

In one possible implementation manner, after the average order taking time length is determined, the expected order taking time of the target order is determined according to the average order taking time length and the order placing time of the target order. When the target order is received by the rider within the expected order taking time, it is determined that the target order is not a loss order. When the target order is not received by the rider within the expected order taking time, the target order needs to be identified to determine whether the target order is a loss order.

Illustratively, the order placing time of the target order is 10 o 'clock 45 minutes, the average order taking time length is 18 minutes, and the expected order taking time of the target order is 11 o' clock 03 minutes, that is, when the target order is not received before 11 o 'clock 03 minutes, the target order is identified at 11 o' clock 03 minutes, so as to determine whether the target order is a loss order.

It should be noted that, the above is only exemplified by the average order receiving time length being 18 minutes, and the average order receiving time length may be other time lengths, which is not limited in the embodiment of the present application.

In step 203, in response to the target order not being received within the expected pick-up time, additional resources for the target order are calculated based on the order resources of the target order.

In one possible implementation, in response to the target order not being received within the expected pick-up time, the process of calculating additional resources for the target order based on the order resources of the target order includes steps 2031 to 2032 described below.

Step 2031, responsive to the target order not being received within the projected order receiving time, determining a probability that the target order is a loss order.

In a possible implementation manner, the order information of the target order further includes order features of the target order, and the order features include a real-time feature, an offline feature, a prediction feature, and a meal loss feature. The real-time characteristics are merchant dimension characteristics, and the merchant dimension characteristics comprise the quantity of orders cancelled by merchants corresponding to the target orders in the target time period and other characteristics. The offline characteristics are area dimension characteristics, and the area dimension characteristics are characteristics such as the quantity of orders cancelled in the target time period in an area where a merchant corresponding to the target order is located. The forecast characteristics include a meal time, a purchase order time and a delivery time, wherein the meal time is the time required by the merchant to make the target order after receiving the target order, the purchase order time is the time between the order issuance of the merchant and the order taking by the rider, and the delivery time is the time required by the rider to deliver the target order to the user after the rider dispatches the target order to the geographic location data of the user. The meal loss characteristics comprise order dimension characteristics, assessment related characteristics and attention characteristics, wherein the order dimension characteristics comprise the geographical position data of the user, the geographical position data of a merchant corresponding to the target order, the distance between the user and the merchant and other characteristics; the assessment related characteristics comprise the predicted delivery time of the target order; the focus feature is a user's focus on a target order after placing the target order.

In one possible implementation, in response to the target order not being received within the expected order receiving time, the order characteristics of the target order are input into the target probability prediction model, and the probability that the target order is a loss order is determined according to the output result of the target probability prediction model.

The target probability prediction model is used for determining the probability that the target order is the loss order according to the order features of the target order. The target probability prediction model is any type of model, which is not limited in the embodiment of the present application, for example, the target probability prediction model is a Gradient boost (XGBoost) model.

Fig. 4 is a schematic diagram for determining a probability that a target order is a loss order according to an embodiment of the present application, where in fig. 4, an order feature of the target order is input into a loss order identification model, and a probability that the target order is a loss order is obtained according to an output result of the loss order identification model.

In response to the probability that the target order is a loss order being less than the target probability, determining that the target order is not a loss order does not require additional resources to calculate the target order. In response to the probability that the target order is a loss order being greater than the target probability, the target order is determined to be a loss order and additional resources for the target order are calculated according to step 2032 below.

Illustratively, the target probability is 80% and the probability that the target order is a loss order is 75%, and the target order is determined not to be a loss order because the probability that the target order is a loss order is less than the target probability. For another example, the target probability is 80%, the probability that the target order is a loss order is 90%, and the target order is determined to be a loss order because the probability that the target order is a loss order is greater than the target probability.

It should be noted that the numerical value of the target probability may be set empirically, or may be adjusted according to the order resource of the target order, which is not limited in the embodiment of the present application.

Step 2032, in response to the probability that the target order is a loss order being greater than the target probability, calculating additional resources of the target order based on the order resources of the target order.

In one possible implementation, in response to the target order having a probability of being a loss order being greater than the target probability, a determination is also made as to whether the target order is within the additional order quantity before calculating additional resources for the target order. If within the additional order quantity, additional resources for the target order are calculated, and if not, no additional resources for the target order need be calculated.

Wherein, the process of determining the number of the additional order is as follows:

determining the number of cancel tickets in a unit time period based on the number of cancel tickets in the target time period; and determining the additional order quantity of the unit time period based on the cancel order quantity of the unit time period and the order-average additional resource coefficient. Wherein, the value range of the single-average additional resource coefficient is [0.2,0.3 ].

In one possible implementation, based on the number of cancelled orders per unit time period and the order-average additional resource coefficient, the number X of additional orders per unit time period is determined according to the following formula (1):

in the above formula (1), σ is a single-average additional resource coefficient, a value range of σ is [0.2,0.3], σ represents a proportion of the additional resource to the order resource, and Num _ refund is a cancellation list number in a unit time period.

It should be noted that the determination process of the value of σ is determined according to a proportional-integral-derivative (PID) control principle. The determination process of the value of σ is shown in fig. 5 below, and in fig. 5, the value of σ is determined by using the fact that the lost-meal order paid resource is equal to the extra additional resource of the lost-meal order as a constraint condition.

Illustratively, the target time period is from 19 days 8 month to 20 days 8 month in 2020, the number of tickets for the target time period is 200 tickets, and the number of tickets for the unit time period (e.g., 1 day) is calculated as 100 tickets based on the number of tickets for the target time period. Taking σ as an example, 0.2, the number of extra orders per unit time period is calculated as 500 according to the above equation (1), that is, within the unit time period (1 day), the delivery resources of the first 500 loss orders are additionally added, and the delivery resources of the following loss orders are not additionally added.

Illustratively, the target order is a loss order and is a 450 th loss order, and therefore, the target order meets additional resource requirements and additional additions are made to the delivery resources of the target order.

In one possible implementation, in response to the target order being a loss order and the target order being within the additional order quantity, determining an order difficulty coefficient for the target order based on an order characteristic of the target order; additional resources for the target order are determined based on the order resources for the target order and the order difficulty factor for the target order.

In one possible implementation, the process of determining the order difficulty factor of the target order based on the order characteristics of the target order is as follows:

extracting the meal delivery time, the order grabbing time and the delivery time of the target order from the order characteristics of the target order, carrying out weighted summation on the meal delivery time, the order grabbing time and the delivery time to obtain a time weighted result, and determining a time coefficient corresponding to the time weighted result according to the time weighted result. And determining the order difficulty coefficient of the target order based on the time coefficient corresponding to the time weighting result. The corresponding relationship between the time weighting result and the time coefficient is shown in fig. 6, the time weighting result is proportional to the time coefficient, and the larger the time weighting result is, the larger the time coefficient is, and vice versa.

And performing weighted summation on the meal delivery time, the order grabbing time and the delivery time of the target order to obtain a time weighted result of the target order, and determining a time coefficient corresponding to the time weighted result according to the time weighted result and the corresponding relation between the time weighted result and the time coefficient shown in fig. 6. Based on the time coefficient, an order difficulty coefficient alpha is determined, and according to the order difficulty coefficient alpha and the order resource, additional resources of the target order are determined.

In one possible implementation manner, based on the order resource of the target order and the order difficulty coefficient of the target order, the additional resource subsidy _ price of the target order is determined according to the following formula (2):

subsidy_price＝(α+γ)*pkg_price (2)

in the above formula (2), α is an order difficulty coefficient, pkg _ price is an order resource of the target order, γ is any positive number not equal to zero, and γ has a value range of [0.05,0.15 ].

Illustratively, γ takes a value of 0.10 and the order resource of the target order is 30And the meal taking time, the order grabbing time and the delivery time of the target order are respectively 15 minutes, 10 minutes and 15 minutes. And calculating the time weighting result of the target order to be 40 minutes, determining the time coefficient corresponding to the time weighting result to be 0.23 according to the time weighting result, and further determining the order difficulty coefficient of the target order to be 0.003. Calculating the additional resource of the order as susidy according to the order difficulty coefficient and the above formula (2)_price(0.003+0.10) × 30 ═ 3.09 yuan.

In step 204, target delivery resources of the target order are determined based on the additional resources of the target order and the original delivery resources of the target order, and the target delivery resources are used for improving the receiving success rate of the target order.

In one possible implementation, the value corresponding to the original delivery resource of the target order is a fixed value, for example, the original delivery resource of the target order is 3-ary. And obtaining the target delivery resources of the target order based on the original delivery resources of the target order and the additional resources of the target order. There are two ways to determine the target delivery resources for a target order as follows.

The first implementation mode is that the original distribution resources and the extra additional resources of the target order are added to obtain the target distribution resources of the target order.

In one possible implementation, the additional resources of the target order are accumulated on the original delivery resources of the target order, so as to obtain the target delivery resources of the target order.

Illustratively, the original delivery resource of the target order is 3 yuan, the additional resource is 3.09 yuan, and the additional resource is accumulated on the basis of the original delivery resource to obtain the target delivery resource of the target order which is 6.09 yuan.

And determining the target delivery resources of the target order based on the original delivery resources, the additional resources, the weight parameters of the original delivery resources and the weight parameters of the additional resources of the target order.

In a possible implementation manner, a weight parameter is respectively allocated to the original delivery resource of the target order and the additional resource of the target order, and the target delivery resource of the target order is determined based on the original delivery resource of the target order, the weight parameter of the original delivery resource, the additional resource of the target order and the weight parameter of the additional resource.

The weight parameter of the original distributed resource and the weight parameter of the additional resource may be any values, which is not limited in the embodiment of the present application.

Illustratively, the original delivery resource of the target order is 3 yuan, and the weight parameter of the original delivery resource is 0.8; the extra additional resource is 3.09 yuan, the weight parameter of the extra additional resource is 0.8, and the target delivery resource of the target order is determined to be 4.872 yuan according to the original delivery resource, the weight parameter of the original delivery resource, the extra additional resource and the weight parameter of the extra additional resource.

It should be noted that any one of the above implementations may be selected to determine the target delivery resources of the target order, which is not limited in the embodiment of the present application.

In a possible implementation manner, after the target delivery resources of the target order are determined, the order information of the target order is sent to any electronic device used by the rider, the order information of the target order is displayed on the electronic device so that the rider can view the order information, and if the rider receives the target order and finishes delivery, the target delivery resources of the target order are transferred to an account corresponding to the rider. And if the rider rejects the target order, namely the rider does not receive the target order, continuously sending the order information of the target order to the electronic equipment used by the other rider until the rider receives the order and delivery is completed, and transferring the target delivery resource of the target order to an account corresponding to the rider receiving the order.

In a possible implementation manner, after the target delivery resources of the target order are determined, the target order and the target delivery resources of the target order may be placed into an order taking pool, where there are multiple orders and the target delivery resources corresponding to each order. And in response to the rider snatching the target order from the order grabbing pool and completing delivery, transferring the target delivery resource of the target order to an account corresponding to the snatched rider.

FIG. 7 is a flow chart illustrating a process for processing a target order according to an embodiment of the present application, in FIG. 7, a user places an order at 11:21, and a merchant receives the order and issues the order to the system; the 11:29 system makes a first order dispatch, 11:30 dispatches the order to rider A, but rider A rejects, while beginning a second order dispatch; 11:31 to the rider B, but is rejected by the rider B, and simultaneously starts to dispatch for the third time; the order is sent to the rider C in a ratio of 11:35, the rider C takes the order, and the rider C cancels the order taking at a ratio of 11:37 for personal reasons; the method comprises the steps of reaching the expected order receiving time of an order at 11:39, identifying the order, calculating additional amount of the order in response to the order being a loss order, putting the order and the target delivery amount of the order into an order taking pool at 11:40, carrying out order taking by a rider D at 11:45, carrying out order taking by the rider D at 11:50, delivering the order to a user by a rider D at 12:05, namely completing delivery by the rider D, clicking a button for indicating completion of delivery by the rider D, receiving a message for completing delivery by the rider D by a server, and transferring the target delivery amount of the order to an account corresponding to the rider D.

In the embodiment of the application, when the target order is not received within the expected order receiving time, the extra additional resources of the target order are calculated in a targeted manner according to the order resources of the target order, and dynamic adjustment of the extra additional resources is realized, so that the matching degree between the determined extra additional resources and the target order is higher, and the accuracy of the determined extra additional resources can be improved. After the target delivery resources of the target order are determined, when the order is dispatched according to the target delivery resources, the dispatching of the delivery resources can be stimulated, so that the order receiving probability of the target order is improved, namely the receiving success rate of the target order is improved.

Fig. 8 is an architecture diagram of order processing according to an embodiment of the present application, where in fig. 8, the architecture diagram includes a scheduling engineering module and a settlement engineering module. The scheduling engineering module is configured to receive order information of the target order, identify whether the target order is a loss order, where the loss order is used to indicate an order that has been successfully made but has not been accepted, and the identification process is consistent with the identification process in step 203, and is not described herein again. In response to the target order not being a loss order, wait for the rider to pick up the order. In response to the target order being the loss order, calculating additional resources of the target order in the settlement engineering module, wherein the calculation process of the additional resources is consistent with the calculation process in the step 203, and is not described herein again. Determining the target delivery resources of the target order according to the additional resources of the target order, where the determining process of the target delivery resources is consistent with the determining process in step 204, and is not described herein again. And putting the target order and the target distribution resources of the target order into an order grabbing pool, and waiting for the rider to grab the order.

Fig. 9 is a schematic structural diagram of an order processing apparatus according to an embodiment of the present application, and as shown in fig. 9, the apparatus includes:

a receiving module 901, configured to receive order information of a target order, where the order information includes order placing time and order resources of the target order;

a first determining module 902, configured to determine an expected order taking time of the target order based on an order placing time of the target order;

a calculating module 903, configured to calculate, in response to the target order not being received within the expected order taking time, additional resources of the target order based on the order resources of the target order;

a second determining module 904, configured to determine target delivery resources of the target order based on the additional resources of the target order and the original delivery resources of the target order, where the target delivery resources are used to improve a receiving success rate of the target order.

In one possible implementation, the calculating module 903 is configured to determine a probability that the target order is a loss order in response to the target order not being received within the expected order receiving time, wherein the loss order is used for indicating an order that has been successfully taken but not received; in response to the probability that the target order is a loss order being greater than the target probability, additional resources for the target order are calculated based on the order resources for the target order.

In one possible implementation, the order information further includes order characteristics of the target order;

the calculating module 903 is configured to determine an order difficulty coefficient of the target order based on the order features of the target order in response to that the probability that the target order is the loss order is greater than the target probability; additional resources for the target order are calculated based on the order resources for the target order and the order difficulty factor for the target order.

In one possible implementation, the calculating module 903 is configured to, in response to the target order not being received within the expected order receiving time, input the order characteristics of the target order into a target probability prediction model, where the target probability prediction model is configured to determine a probability that the target order is a loss order; and determining the probability that the target order is the loss order based on the output result of the target probability prediction model.

In one possible implementation, the apparatus further includes:

the first determining module 902 is further configured to determine an average order receiving time length based on the order placing time and the cancellation time of each cancellation order; and determining the expected order receiving time of the target order based on the order placing time of the target order and the average order receiving time length.

In a possible implementation manner, the cancellation list data further includes a cancellation list number;

the second determining module 904 is further configured to determine an additional order quantity per unit time period based on the cancel order quantity for the target time period;

the calculating module 903 is configured to calculate additional resources of the target order based on the order resources of the target order in response to the target order not being received within the expected order taking time and the target order being within the additional order quantity.

In a possible implementation manner, the first determining module 902 is configured to determine the number of the cancellation tickets in the unit time period based on the number of the cancellation tickets in the target time period; and determining the additional order quantity of the unit time period based on the cancel order quantity of the unit time period and the order-to-order additional resource coefficient.

In the embodiment of the application, when the target order is not received within the expected order receiving time, the extra additional resources of the target order are calculated in a targeted manner according to the order resources of the target order, the dynamic adjustment of the extra additional resources is realized, the matching degree between the determined extra additional resources and the target order is higher, and the accuracy of the determined extra additional resources can be improved. After the target delivery resources of the target order are determined, when the order is dispatched according to the target delivery resources, the dispatching of the delivery resources can be stimulated, so that the order receiving probability of the target order is improved, namely the receiving success rate of the target order is improved.

It should be noted that: in order processing, the order processing apparatus provided in the above embodiment is only illustrated by dividing the above functional modules, and in practical applications, the above function allocation may be completed by different functional modules according to needs, that is, the internal structure of the order processing apparatus is divided into different functional modules to complete all or part of the above described functions. In addition, the order processing apparatus and the order processing method provided in the above embodiments belong to the same concept, and specific implementation processes thereof are described in the method embodiments and are not described herein again.

Fig. 10 is a schematic structural diagram of a server according to an embodiment of the present application. The server 1000 is installed and operated with an order processing application, and the server 1000 comprises a transceiver 1001 and a processor 1002;

the transceiver 1001 is configured to receive order information of a target order, where the order information includes an order placing time and an order resource of the target order;

the processor 1002 is configured to determine an expected order taking time of the target order based on the order placing time of the target order; responsive to the target order not being received within the projected order receiving time, calculating additional resources for the target order based on the order resources for the target order; and determining target distribution resources of the target order based on the additional resources of the target order and the original distribution resources of the target order, wherein the target distribution resources are used for improving the receiving success rate of the target order.

In one possible implementation, the processor 1002 is configured to determine a probability that the target order is a loss order indicating an order that was successfully placed but not received in response to the target order not being received within the expected order receiving time; in response to the probability that the target order is a loss order being greater than the target probability, additional resources for the target order are calculated based on the order resources for the target order.

In a possible implementation manner, the order information further includes an order characteristic of the target order, and the processor 1002 is configured to determine an order difficulty coefficient of the target order based on the order characteristic of the target order in response to that the probability that the target order is the loss order is greater than the target probability, and calculate additional resources of the target order based on the order resource of the target order and the order difficulty coefficient of the target order.

In one possible implementation, the processor 1002 is configured to, in response to the target order not being received within the expected order receiving time, input an order characteristic of the target order into a target probability prediction model, where the target probability prediction model is configured to determine a probability that the target order is a loss order; and determining the probability that the target order is the loss order based on the output result of the target probability prediction model.

In a possible implementation manner, the processor 1002 is further configured to obtain cancellation list data of a target time period, where the cancellation list data includes a list placing time and a cancellation time of each cancellation list; determining the average order receiving time length based on the order placing time and the canceling time of each canceling order; and determining the expected order taking time of the target order based on the order placing time of the target order and the average order taking time length.

the processor 1002, further configured to determine an additional order quantity per unit time period based on the cancel order quantity for the target time period; in response to the target order not being received within the projected order taking time and the target order being within the additional order quantity, additional resources for the target order are calculated based on the order resources for the target order.

In a possible implementation manner, the processor 1002 is configured to determine the number of cancellation orders per unit time period based on the number of cancellation orders in the target time period; and determining the additional order quantity of the unit time period based on the cancel order quantity of the unit time period and the order-to-order additional resource coefficient.

Fig. 11 is a schematic structural diagram of an electronic device according to an embodiment of the present application. The electronic device 1100 may be: a smart phone, a tablet computer, an MP3(Moving Picture Experts Group Audio Layer III, motion video Experts compression standard Audio Layer 3) player, an MP4(Moving Picture Experts Group Audio Layer IV, motion video Experts compression standard Audio Layer 4) player, a notebook computer or a desktop computer. Electronic device 1100 may also be referred to by other names as user equipment, portable electronic device, laptop electronic device, desktop electronic device, and so on.

In general, the electronic device 1100 includes: one or more processors 1101 and one or more memories 1102.

Processor 1101 may include one or more processing cores, such as a 4-core processor, an 8-core processor, or the like. The processor 1101 may be implemented in at least one hardware form of a DSP (Digital Signal Processing), an FPGA (Field-Programmable Gate Array), and a PLA (Programmable Logic Array). The processor 1101 may also include a main processor and a coprocessor, where the main processor is a processor for Processing data in an awake state, and is also called a Central Processing Unit (CPU); a coprocessor is a low power processor for processing data in a standby state. In some embodiments, the processor 1101 may be integrated with a GPU (Graphics Processing Unit) that is responsible for rendering and drawing the content that the display screen needs to display. In some embodiments, the processor 1101 may further include an AI (Artificial Intelligence) processor for processing computing operations related to machine learning.

Memory 1102 may include one or more computer-readable storage media, which may be non-transitory. Memory 1102 can also include high-speed random access memory, as well as non-volatile memory, such as one or more magnetic disk storage devices, flash memory storage devices. In some embodiments, a non-transitory computer readable storage medium in memory 1102 is used to store at least one program code for execution by processor 1101 to implement the order processing methods provided by the method embodiments herein.

In some embodiments, the electronic device 1100 may also optionally include: a peripheral interface 1103 and at least one peripheral. The processor 1101, memory 1102 and peripheral interface 1103 may be connected by a bus or signal lines. Various peripheral devices may be connected to the peripheral interface 1103 by buses, signal lines, or circuit boards. Specifically, the peripheral device includes: at least one of radio frequency circuitry 1104, display screen 1105, camera 1106, audio circuitry 1107, positioning component 1108, and power supply 1109.

The peripheral interface 1103 may be used to connect at least one peripheral associated with I/O (Input/Output) to the processor 1101 and the memory 1102. In some embodiments, the processor 1101, memory 1102, and peripheral interface 1103 are integrated on the same chip or circuit board; in some other embodiments, any one or two of the processor 1101, the memory 1102 and the peripheral device interface 1103 may be implemented on separate chips or circuit boards, which is not limited by this embodiment.

The Radio Frequency circuit 1104 is used to receive and transmit RF (Radio Frequency) signals, also called electromagnetic signals. The radio frequency circuit 1104 communicates with communication networks and other communication devices via electromagnetic signals. The radio frequency circuit 1104 converts an electric signal into an electromagnetic signal to transmit, or converts a received electromagnetic signal into an electric signal. Optionally, the radio frequency circuit 1104 includes: an antenna system, an RF transceiver, one or more amplifiers, a tuner, an oscillator, a digital signal processor, a codec chipset, a subscriber identity module card, and so forth. The radio frequency circuit 1104 may communicate with other electronic devices via at least one wireless communication protocol. The wireless communication protocols include, but are not limited to: metropolitan area networks, various generation mobile communication networks (2G, 3G, 4G, and 5G), Wireless local area networks, and/or WiFi (Wireless Fidelity) networks. In some embodiments, the rf circuit 1104 may further include NFC (Near Field Communication) related circuits, which are not limited in this application.

The display screen 1105 is used to display a UI (User Interface). The UI may include graphics, text, icons, video, and any combination thereof. When the display screen 1105 is a touch display screen, the display screen 1105 also has the ability to capture touch signals on or over the surface of the display screen 1105. The touch signal may be input to the processor 1101 as a control signal for processing. At this point, the display screen 1105 may also be used to provide virtual buttons and/or a virtual keyboard, also referred to as soft buttons and/or a soft keyboard. In some embodiments, the display screen 1105 may be one, providing the front panel of the electronic device 1100; in other embodiments, the display screens 1105 may be at least two, respectively disposed on different surfaces of the electronic device 1100 or in a folded design; in some embodiments, the display 1105 may be a flexible display disposed on a curved surface or a folded surface of the electronic device 1100. Even further, the display screen 1105 may be arranged in a non-rectangular irregular pattern, i.e., a shaped screen. The Display screen 1105 may be made of LCD (Liquid Crystal Display), OLED (Organic Light-Emitting Diode), and the like.

Camera assembly 1106 is used to capture images or video. Optionally, camera assembly 1106 includes a front camera and a rear camera. Generally, a front camera is disposed on a front panel of an electronic apparatus, and a rear camera is disposed on a rear surface of the electronic apparatus. In some embodiments, the number of the rear cameras is at least two, and each rear camera is any one of a main camera, a depth-of-field camera, a wide-angle camera and a telephoto camera, so that the main camera and the depth-of-field camera are fused to realize a background blurring function, and the main camera and the wide-angle camera are fused to realize panoramic shooting and VR (Virtual Reality) shooting functions or other fusion shooting functions. In some embodiments, camera assembly 1106 may also include a flash. The flash lamp can be a single-color temperature flash lamp or a double-color temperature flash lamp. The double-color-temperature flash lamp is a combination of a warm-light flash lamp and a cold-light flash lamp, and can be used for light compensation at different color temperatures.

The audio circuitry 1107 may include a microphone and a speaker. The microphone is used for collecting sound waves of a user and the environment, converting the sound waves into electric signals, and inputting the electric signals to the processor 1101 for processing or inputting the electric signals to the radio frequency circuit 1104 to achieve voice communication. For stereo capture or noise reduction purposes, multiple microphones may be provided, each at a different location of the electronic device 1100. The microphone may also be an array microphone or an omni-directional pick-up microphone. The speaker is used to convert electrical signals from the processor 1101 or the radio frequency circuit 1104 into sound waves. The loudspeaker can be a traditional film loudspeaker or a piezoelectric ceramic loudspeaker. When the speaker is a piezoelectric ceramic speaker, the speaker can be used for purposes such as converting an electric signal into a sound wave audible to a human being, or converting an electric signal into a sound wave inaudible to a human being to measure a distance. In some embodiments, the audio circuitry 1107 may also include a headphone jack.

The positioning component 1108 is used to locate a current geographic Location of the electronic device 1100 for navigation or LBS (Location Based Service). The Positioning component 1108 may be a Positioning component based on the united states GPS (Global Positioning System), the chinese beidou System, the russian graves System, or the european union galileo System.

The power supply 1109 is used to provide power to the various components within the electronic device 1100. The power supply 1109 may be alternating current, direct current, disposable or rechargeable. When the power supply 1109 includes a rechargeable battery, the rechargeable battery may support wired or wireless charging. The rechargeable battery may also be used to support fast charge technology.

In some embodiments, the electronic device 1100 also includes one or more sensors 1110. The one or more sensors 1110 include, but are not limited to: acceleration sensor 1111, gyro sensor 1112, pressure sensor 1113, fingerprint sensor 1114, optical sensor 1115, and proximity sensor 1116.

The acceleration sensor 1111 may detect the magnitude of acceleration on three coordinate axes of a coordinate system established with the electronic device 1100. For example, the acceleration sensor 1111 may be configured to detect components of the gravitational acceleration in three coordinate axes. The processor 1101 may control the display screen 1105 to display the user interface in a landscape view or a portrait view according to the gravitational acceleration signal collected by the acceleration sensor 1111. The acceleration sensor 1111 may also be used for acquisition of motion data of a game or a user.

The gyro sensor 1112 may detect a body direction and a rotation angle of the electronic device 1100, and the gyro sensor 1112 may cooperate with the acceleration sensor 1111 to acquire a 3D motion of the user on the electronic device 1100. From the data collected by gyroscope sensor 1112, processor 1101 may implement the following functions: motion sensing (such as changing the UI according to a user's tilting operation), image stabilization while shooting, game control, and inertial navigation.

The pressure sensor 1113 may be disposed on a side bezel of the electronic device 1100 and/or on an underlying layer of the display screen 1105. When the pressure sensor 1113 is disposed on the side frame of the electronic device 1100, the holding signal of the user to the electronic device 1100 can be detected, and the processor 1101 performs left-right hand recognition or shortcut operation according to the holding signal collected by the pressure sensor 1113. When the pressure sensor 1113 is disposed at the lower layer of the display screen 1105, the processor 1101 controls the operability control on the UI interface according to the pressure operation of the user on the display screen 1105. The operability control comprises at least one of a button control, a scroll bar control, an icon control and a menu control.

The fingerprint sensor 1114 is configured to collect a fingerprint of the user, and the processor 1101 identifies the user according to the fingerprint collected by the fingerprint sensor 1114, or the fingerprint sensor 1114 identifies the user according to the collected fingerprint. Upon recognizing that the user's identity is a trusted identity, the user is authorized by the processor 1101 to perform relevant sensitive operations including unlocking the screen, viewing encrypted information, downloading software, paying for and changing settings, etc. The fingerprint sensor 1114 may be disposed on the front, back, or side of the electronic device 1100. When a physical key or vendor Logo is provided on the electronic device 1100, the fingerprint sensor 1114 may be integrated with the physical key or vendor Logo.

Optical sensor 1115 is used to collect ambient light intensity. In one embodiment, the processor 1101 may control the display brightness of the display screen 1105 based on the ambient light intensity collected by the optical sensor 1115. Specifically, when the ambient light intensity is high, the display brightness of the display screen 1105 is increased; when the ambient light intensity is low, the display brightness of the display screen 1105 is reduced. In another embodiment, processor 1101 may also dynamically adjust the shooting parameters of camera assembly 1106 based on the ambient light intensity collected by optical sensor 1115.

The proximity sensor 1116, also referred to as a distance sensor, is typically disposed on the front panel of the electronic device 1100. The proximity sensor 1116 is used to capture the distance between the user and the front of the electronic device 1100. In one embodiment, the processor 1101 controls the display screen 1105 to switch from a bright screen state to a dark screen state when the proximity sensor 1116 detects that the distance between the user and the front face of the electronic device 1100 is gradually decreasing; when the proximity sensor 1116 detects that the distance between the user and the front face of the electronic device 1100 becomes progressively larger, the display screen 1105 is controlled by the processor 1101 to switch from a breath-screen state to a bright-screen state.

Those skilled in the art will appreciate that the configuration shown in fig. 11 does not constitute a limitation of the electronic device 1100, and may include more or fewer components than those shown, or combine certain components, or employ a different arrangement of components.

In an exemplary embodiment, there is also provided a computer readable storage medium having at least one program code stored therein, the at least one program code being loaded and executed by a processor of a computer device to implement any of the order processing methods described above.

Alternatively, the computer-readable storage medium may be a Read-Only Memory (ROM), a Random Access Memory (RAM), a Compact Disc Read-Only Memory (CD-ROM), a magnetic tape, a floppy disk, an optical data storage device, and the like.

In an exemplary embodiment, there is also provided a computer program or a computer program product having at least one computer instruction stored therein, the at least one computer instruction being loaded and executed by a processor to implement any of the order processing methods described above.

It should be understood that reference to "a plurality" herein means two or more. "and/or" describes the association relationship of the associated objects, meaning that there may be three relationships, e.g., a and/or B, which may mean: a exists alone, A and B exist simultaneously, and B exists alone. The character "/" generally indicates that the former and latter associated objects are in an "or" relationship.

The above-mentioned serial numbers of the embodiments of the present application are merely for description and do not represent the merits of the embodiments.

The above description is only exemplary of the present application and should not be taken as limiting the present application, and any modifications, equivalents, improvements and the like that are made within the spirit and principle of the present application should be included in the protection scope of the present application.

Claims

1. An order processing method, characterized in that the method comprises:

2. The method of claim 1, wherein calculating additional resources for the target order based on the order resources for the target order in response to the target order not being received within the projected order taking time comprises:

3. The method of claim 2, wherein the order information further comprises an order characteristic of the target order;

determining an order difficulty coefficient of the target order based on the order characteristics of the target order in response to the fact that the probability that the target order is the loss order is greater than the target probability;

4. The method of claim 2 or 3, wherein said determining a probability that the target order is a loss order in response to the target order not being received within the projected order taking time comprises:

5. The method of claim 1, wherein prior to determining the projected time to take the target order based on the time to place the target order, the method further comprises:

6. The method of claim 1 or 5, wherein the cancellation list data further comprises a cancellation list number for a target time period;

7. The method of claim 6, wherein determining the additional order quantity per time unit based on the cancel order quantity for the target time unit comprises:

determining the number of the cancel orders in the unit time period based on the number of the cancel orders in the target time period;

8. An order processing apparatus, characterized in that the apparatus comprises:

a calculation module for calculating additional resources of the target order based on order resources of the target order in response to the target order not being received within the projected order taking time;

9. A server, characterized in that the server comprises a processor and a memory, in which at least one program code is stored, which is loaded and executed by the processor to implement the order processing method according to any of claims 1 to 7.

10. A computer-readable storage medium having stored therein at least one program code, the at least one program code being loaded and executed by a processor to implement the order processing method of any of claims 1 to 7.