Inventory Allocation Method and Apparatus, and Electronic Device Based on Activity Data

Abstract

The present invention discloses an inventory allocation method and apparatus and an electronic device based on activity data, relating to the field of fintech. Among them, the allocation method includes: matching the activity information of a target activity with a historical activity database to obtain historical activities with a similarity greater than a preset similarity threshold, obtaining the proportion of the number of successful customers of the historical activities, and based on the proportion of the number of successful customers, allocating inventory objects to each activity cluster of the target activity. The present invention solves the technical problem in the related art that the inventory quota is allocated to the sub-accounts of each activity cluster, and there is a large difference in matching with the actual number of users routed to each activity cluster, resulting in a low success rate of quota deduction.

Description

Technical Field

[0001] The present invention relates to the field of fintech, and in particular, to an inventory allocation method and apparatus, and an electronic device based on activity data. Background Art

[0002] In the related art, for the situation of updating hot account data in a high-concurrency scenario (for example, updating consumption coupon inventory in a consumption coupon collection activity), in order to avoid problems with the data of hot accounts, sub-accounts are generally established in each cluster, and the quota is evenly distributed to the sub-accounts of each cluster. Each time a request is received, the corresponding sub-account of the cluster is selected by hash calculation for deduction and accounting, and the concurrency of a single account is reduced by dispersing the hot spots. However, the users routed to each cluster are not always balanced, and there will be a situation where the total account has a quota, but the quotas of some sub-accounts are exhausted, resulting in the problem of failed quota deduction.

[0003] In view of the above problems, no effective solution has been proposed yet. Summary of the Invention

[0004] Embodiments of the present invention provide an inventory allocation method and apparatus, and an electronic device based on activity data, so as to at least solve the technical problem that the inventory quota is allocated to the sub-accounts of each activity cluster in the related art, and there is a large difference in matching with the actual number of users routed to each activity cluster, resulting in a low success rate of quota deduction.

[0005] According to one aspect of the embodiments of the present invention, an inventory allocation method based on activity data is provided, including: matching the activity information of a target activity with a historical activity database to obtain historical activities with a similarity greater than a preset similarity threshold; obtaining the proportion of successful customers of the historical activity, where the proportion of successful customers is the ratio of the number of customers who successfully completed the activity in the historical activity to the total number of customers; and allocating inventory objects to each activity cluster of the target activity based on the proportion of successful customers.

[0006] Optionally, before matching the activity information of the target activity with the historical activity database, the inventory allocation method further includes: collecting the total number of inventory objects to be allocated for the target activity, the activity type, the activity area, and the object value of each inventory object to obtain the activity information of the target activity.

[0007] Optionally, the step of matching the activity information of the target activity with the historical activity database to obtain historical activities with a similarity greater than a preset similarity threshold includes: querying the historical activity database for historical activities corresponding to the activity type of the target activity to obtain a first set of historical activities; querying the historical activity database for historical activities corresponding to the activity area where the target activity is carried out to obtain a second set of historical activities; determining the quantity range in which the total quantity of inventory objects of the target activity is located, and the value range in which the object value of the target activity is located; querying the historical activity database for historical activities corresponding to the quantity range to obtain a third set of historical activities; querying the historical activity database for historical activities corresponding to the value range to obtain a fourth set of historical activities; performing an intersection operation on the first set of historical activities, the second set of historical activities, the third set of historical activities, and the fourth set of historical activities to obtain historical activities with a similarity greater than a preset similarity threshold.

[0008] Optionally, after allocating inventory objects to each activity cluster of the target activity based on the proportion of successful customers, the inventory allocation method further includes: allocating a corresponding number of entity inventory variables according to the number of activity clusters of the target activity; adding a virtual cluster inventory variable to the target activity, where the virtual cluster inventory variable is used to adjust the quantity of the allocated inventory objects; combining the multiple entity inventory variables and the virtual cluster inventory variable to adjust the quantity of the inventory objects allocated to each activity cluster.

[0009] Optionally, the inventory allocation method further includes: setting a reserved proportion of object quantity adjustment for the virtual cluster inventory variable.

[0010] Optionally, after allocating inventory objects to each activity cluster of the target activity based on the proportion of successful customers, the inventory allocation method further includes: receiving a participation instruction for a user to participate in the activity; in response to the participation instruction, detecting the activity cluster to which the current user belongs to participate in the target activity; detecting whether there is an object quota of inventory objects in the entity inventory variable corresponding to the activity cluster; and deducting the inventory objects when there is an object quota of inventory objects in the entity inventory variable.

[0011] Optionally, after detecting whether there is an object quota of inventory objects in the entity inventory variable corresponding to the activity cluster, the inventory allocation method further includes: detecting whether there is an object quota of inventory objects in the virtual cluster inventory variable when there is no object quota of inventory objects in the entity inventory variable; deducting the inventory objects when there is an object quota of inventory objects in the virtual cluster inventory variable; and returning an insufficient quota message when there is no object quota of inventory objects in the virtual cluster inventory variable.

[0012] According to another aspect of the embodiments of the present invention, there is also provided an inventory allocation device based on activity data, including: a matching unit, configured to match the activity information of a target activity with a historical activity database to obtain historical activities with a similarity greater than a preset similarity threshold; an obtaining unit, configured to obtain the proportion of successful customers of the historical activity, where the proportion of successful customers is the ratio of the number of customers who have successfully completed the activity to the total number of customers in the historical activity; and an allocation unit, configured to allocate inventory objects to each activity cluster of the target activity based on the proportion of successful customers.

[0013] Optionally, the inventory allocation device further includes: a first collection module, configured to collect the total number of inventory objects to be allocated for the target activity, the activity type, the activity execution area, and the object value of each inventory object before matching the activity information of the target activity with the historical activity database, so as to obtain the activity information of the target activity.

[0014] Optionally, the matching unit includes: a first query module, configured to query historical activities corresponding to the activity type of the target activity in the historical activity database to obtain a first set of historical activities; a second query module, configured to query historical activities corresponding to the activity execution area of the target activity in the historical activity database to obtain a second set of historical activities; a first determination module, configured to determine the quantity range in which the total number of inventory objects of the target activity is located, and the value range in which the object value of the target activity is located; a third query module, configured to query historical activities corresponding to the quantity range in the historical activity database to obtain a third set of historical activities; a fourth query module, configured to query historical activities corresponding to the value range in the historical activity database to obtain a fourth set of historical activities; and a first intersection module, configured to perform an intersection operation on the first set of historical activities, the second set of historical activities, the third set of historical activities, and the fourth set of historical activities to obtain historical activities with a similarity greater than a preset similarity threshold.

[0015] Optionally, the inventory allocation device further includes: a first allocation module, configured to allocate corresponding multiple entity inventory variables according to the number of activity clusters of the target activity after allocating inventory objects to each activity cluster of the target activity based on the proportion of successful customers; a first increase module, configured to increase a virtual cluster inventory variable for the target activity, where the virtual cluster inventory variable is used to adjust the quantity of the allocated inventory objects; and a first adjustment module, configured to adjust the quantity of the inventory objects allocated to each activity cluster by combining the multiple entity inventory variables and the virtual cluster inventory variable.

[0016] Optionally, the inventory allocation device further includes: a first setting module, configured to set an adjustment amount for the number of objects with a reserved ratio for the virtual cluster inventory variable.

[0017] Optionally, the inventory allocation device further includes: a first receiving module, configured to receive a participation instruction of a user in an activity after allocating inventory objects to each activity cluster of the target activity based on the proportion of successful customers; a first detection module, configured to detect the activity cluster to which the current user participates in the target activity in response to the participation instruction; a second detection module, configured to detect whether there is an object quota of an inventory object in the entity inventory variable corresponding to the activity cluster; a first deduction module, configured to deduct the inventory object when there is an object quota of an inventory object in the entity inventory variable.

[0018] Optionally, the inventory allocation device further includes: a third detection module, configured to detect whether there is an object quota of an inventory object in the virtual cluster inventory variable when there is no object quota of an inventory object in the entity inventory variable after detecting whether there is an object quota of an inventory object in the entity inventory variable corresponding to the activity cluster; a second deduction module, configured to deduct the inventory object when there is an object quota of an inventory object in the virtual cluster inventory variable; a first return module, configured to return an insufficient quota message when there is no object quota of an inventory object in the virtual cluster inventory variable.

[0019] According to another aspect of the embodiments of the present invention, there is also provided a computer-readable storage medium, where the computer-readable storage medium includes a stored computer program, and when the computer program runs, it controls the device where the computer-readable storage medium is located to execute the inventory allocation method based on activity data described in any one of the above.

[0020] According to another aspect of the embodiments of the present invention, there is also provided an electronic device, including one or more processors and a memory, where the memory is used to store one or more programs, and when the one or more programs are executed by the one or more processors, the one or more processors are caused to implement the inventory allocation method based on activity data described in any one of the above.

[0021] In the present disclosure, the activity information of the target activity is matched with the historical activity database to obtain historical activities with a similarity greater than a preset similarity threshold. The proportion of successful customers of the historical activities is obtained, and inventory objects are allocated to each activity cluster of the target activity based on the proportion of successful customers. In this application, by selecting historical activities similar to the current activity from the historical activity database and allocating inventory objects to each activity cluster of the current activity based on the proportion of successful customers in the historical activity, the matching degree between the inventory quota allocation and the actual number of customers can be effectively improved, the success rate of quota deduction can be increased, the activity efficiency can be enhanced, and thus the technical problem in the related art that the inventory quota is allocated to the sub-accounts of each activity cluster and there is a large difference in the matching with the actual number of users routed to each activity cluster, resulting in a low success rate of quota deduction, is solved. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The schematic embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation to the present invention. In the drawings:

[0023] Figure 1 is a flowchart of an optional inventory allocation method based on activity data according to an embodiment of the present invention;

[0024] Figure 2 is a flowchart of an optional inventory allocation according to an embodiment of the present invention;

[0025] Figure 3 is a flowchart of an optional quota deduction according to an embodiment of the present invention;

[0026] Figure 4 is a schematic diagram of an optional inventory allocation device based on activity data according to an embodiment of the present invention;

[0027] Figure 5 is a hardware structure block diagram of an electronic device (or mobile device) for an inventory allocation method based on activity data according to an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0028] In order to enable those skilled in the art of the present technology to better understand the present invention solution, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without making creative efforts shall fall within the scope of protection of the present invention.

[0029] It should be noted that the terms "first", "second", etc. in the description, claims and the above-mentioned drawings of the present invention are used to distinguish similar objects, and do not necessarily have to be used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged under appropriate circumstances, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device comprising a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0030] It should be noted that the inventory allocation method and device based on activity data in the present disclosure can be used in the financial technology field when allocating inventory, and can also be used in any field other than the financial technology field when allocating inventory. The application field of the inventory allocation method and device based on activity data in the present disclosure is not limited.

[0031] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for display, data for analysis, etc.) involved in the present disclosure are all information and data authorized by the user or fully authorized by all parties.

[0032] The following embodiments of the present invention can be applied to various systems / applications / devices for allocating inventory based on activity data. The activities involved in the present invention are high-concurrency activities, such as consumer coupon redemption activities. By selecting historical activities similar to the current activity from the historical activity database and allocating inventory objects to each activity cluster of the current activity based on the proportion of successful customers in the historical activity, the matching degree between the inventory quota allocation and the actual number of customers can be effectively improved. At the same time, virtual quotas can be increased, which can effectively avoid the deficiencies in guiding quota allocation in the historical activity database, improve the success rate of quota deduction, and enhance the activity efficiency.

[0033] The present invention will be described in detail below in conjunction with each embodiment.

[0034] Embodiment 1

[0035] According to an embodiment of the present invention, there is provided an embodiment of an inventory allocation method based on activity data. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. And although the logical order is shown in the flowchart, in some cases, the steps shown or described herein can be executed in a different order than here.

[0036] Figure 1It is a flowchart of an optional inventory allocation method based on activity data according to an embodiment of the present invention. As Figure 1 shown, the method includes the following steps:

[0037] Step S101, match the activity information of the target activity with the historical activity database to obtain historical activities with a similarity greater than a preset similarity threshold.

[0038] Step S102, obtain the proportion of successful customers in the historical activity, where the proportion of successful customers is the ratio of the number of customers who successfully completed the activity to the total number of customers in the historical activity.

[0039] Step S103, based on the proportion of successful customers, allocate inventory objects to each activity cluster of the target activity.

[0040] Through the above steps, the activity information of the target activity can be matched with the historical activity database to obtain historical activities with a similarity greater than a preset similarity threshold, obtain the proportion of successful customers in the historical activity, and based on the proportion of successful customers, allocate inventory objects to each activity cluster of the target activity. In the embodiment of the present invention, by selecting historical activities similar to the current activity from the historical activity database and based on the proportion of successful customers in the historical activity, inventory objects are allocated to each activity cluster of the current activity, which can effectively improve the matching degree between the inventory quota allocation and the actual number of customers, improve the success rate of quota deduction, enhance the activity efficiency, and thus solve the technical problem in the related art that the inventory quota is allocated to the sub-accounts of each activity cluster, and there is a large difference in the matching with the actual number of users routed to each activity cluster, resulting in a low success rate of quota deduction.

[0041] The embodiments of the present invention will be described in detail below in combination with the above steps.

[0042] In the embodiment of the present invention, before matching the activity information of the target activity with the historical activity database, the inventory allocation method further includes: collecting the total number of inventory objects to be allocated for the target activity, the activity type, the activity area where the activity is carried out, and the object value of each inventory object to obtain the activity information of the target activity.

[0043] In the embodiments of the present invention, a historical activity database may be constructed first. By obtaining historical data within a preset time period (for example, historical transaction data in the recent 3 months or 6 months, which may include: the total number of inventory objects, activity types, activity regions, and the object value of each inventory object, etc.), and according to these data, calculating the proportion of the number of customers who have successfully completed activities on each activity cluster (i.e., the proportion of successful customers), a historical activity database is formed. Moreover, the data in the historical activity database can be updated regularly. Taking the consumption voucher redemption activity (various promotional activities carried out in the form of redeeming coupons, generally with a limit on the total number of consumption vouchers, first come, first served under the condition of meeting the participation requirements) as an example, according to historical data (such as transaction data in the recent 3 months or 6 months), calculate the proportion of the number of successful redemption customers on each activity cluster according to the total number of consumption vouchers, consumption voucher types, activity regions, and consumption voucher denominations to form a historical activity database, and the data in this database can be updated regularly.

[0044] In this embodiment, before matching the activity information of the target activity with the historical activity database, the total number of inventory objects to be allocated for this activity, activity type, activity region, and the object value of each inventory object may be collected first to obtain the activity information of this activity.

[0045] Step S101: Match the activity information of the target activity with the historical activity database to obtain historical activities with a similarity greater than a preset similarity threshold.

[0046] Optionally, the step of matching the activity information of the target activity with the historical activity database to obtain historical activities with a similarity greater than a preset similarity threshold includes: querying the historical activities corresponding to the activity type of the target activity in the historical activity database to obtain a first set of historical activities; querying the historical activities corresponding to the activity region of the target activity in the historical activity database to obtain a second set of historical activities; determining the quantity range in which the total number of inventory objects of the target activity is located, and the value range in which the object value of the target activity is located; querying the historical activities corresponding to the quantity range in the historical activity database to obtain a third set of historical activities; querying the historical activities corresponding to the value range in the historical activity database to obtain a fourth set of historical activities; performing an intersection operation on the first set of historical activities, the second set of historical activities, the third set of historical activities, and the fourth set of historical activities to obtain historical activities with a similarity greater than a preset similarity threshold.

[0047] In an embodiment of the present invention, the newly launched activity (i.e., the target activity) can be sequentially matched with the historical activity database according to the total number of inventory objects to be allocated for the activity, the activity type, the activity area, and the object value of each inventory object (i.e., matching the activity information of the target activity with the historical activity database), so as to obtain historical activities with a similarity greater than a preset similarity threshold (which can be set according to the actual situation). Among them, the activity type and the activity area can be precisely matched, while for the total number of inventory objects and the corresponding object value, the closest quantity value can be selected. Specifically:

[0048] Query the historical activities corresponding to the activity type of this activity in the historical activity database to obtain the first set of historical activities; query the historical activities corresponding to the activity area of this activity in the historical activity database to obtain the second set of historical activities; determine the quantity range in which the total number of inventory objects of this activity is located (i.e., a range centered on the total number of inventory objects of this activity and increasing and / or decreasing the fluctuation preset value, which can be set according to the actual situation), and the value range of the object value of the target activity (i.e., a range centered on the object value of this activity and increasing and / or decreasing the fluctuation preset value, which can be set according to the actual situation); query the historical activities corresponding to the quantity range in the historical activity database to obtain the third set of historical activities; query the historical activities corresponding to the value range in the historical activity database to obtain the fourth set of historical activities; then, an intersection operation can be performed on the first set of historical activities, the second set of historical activities, the third set of historical activities, and the fourth set of historical activities to finally obtain historical activities with a similarity greater than the preset similarity threshold.

[0049] Step S102: Obtain the proportion of the number of successful customers in the historical activity, where the proportion of the number of successful customers is the ratio of the number of customers who have successfully completed the activity in the historical activity to the total number of customers.

[0050] In an embodiment of the present invention, if a historical activity with a similarity greater than the preset similarity threshold is found, then the proportion of the number of successful customers on each activity cluster in this historical activity is taken out, and the proportion of the number of successful customers is the ratio of the number of customers who have successfully completed the activity in the historical activity to the total number of customers.

[0051] Step S103: Allocate inventory objects to each activity cluster of the target activity based on the proportion of the number of successful customers.

[0052] In an embodiment of the present invention, inventory objects can be allocated to each activity cluster of the target activity according to the proportion of the number of successful customers in the successfully matched historical activity.

[0053] Optionally, after allocating inventory objects to each activity cluster of the target activity based on the proportion of successful customers, the inventory allocation method further includes: allocating a corresponding plurality of entity inventory variables according to the number of activity clusters of the target activity; adding a virtual cluster inventory variable to the target activity, where the virtual cluster inventory variable is used to adjust the quantity of the allocated inventory objects; combining the plurality of entity inventory variables and the virtual cluster inventory variable to adjust the quantity of the inventory objects allocated to each activity cluster.

[0054] Optionally, the inventory allocation method further includes: setting an adjustment amount for the quantity of objects with a reserved proportion for the virtual cluster inventory variable.

[0055] In an embodiment of the present invention, a corresponding plurality of entity inventory variables can be allocated according to the number of activity clusters of the target activity. For example, taking the consumption coupon redemption activity as an example, assuming there are a total of n coupon redemption clusters, the allocated entity inventory variables can be set as Coupon1, Coupon2,..., Couponn. And, a virtual cluster inventory variable Coupon(n + 1) can be added. This virtual cluster inventory variable can be used to avoid the situation of deduction failure when the prediction deviation is large (that is, the virtual cluster inventory variable is used to adjust the quantity of the allocated inventory objects). After that, the quantity of the inventory objects allocated to each activity cluster can be adjusted by combining the plurality of entity inventory variables and the virtual cluster inventory variable.

[0056] And, the virtual cluster inventory variable Coupon(n + 1) can set an adjustment amount for the quantity of objects with a reserved proportion according to the parameters. For example, it can be set as 5% of the total amount.

[0057] Figure 2 FIG. is a flowchart of an optional inventory allocation according to an embodiment of the present invention. Taking the coupon redemption activity as an example, the inventory allocation process of this activity is: first create a coupon redemption activity, match this activity with the historical activity database, detect whether there is a similar activity. If there is a similar activity, reserve the remaining amount of the virtual cluster inventory variable, and allocate inventory to each activity cluster according to the proportion of successful customers of the similar activity; if there is no similar activity, reserve the remaining amount of the virtual cluster inventory variable, and allocate inventory to each activity cluster in an average manner.

[0058] Optionally, after allocating inventory objects to each activity cluster of the target activity based on the proportion of successful customers, the inventory allocation method further includes: receiving a participation instruction for the user to participate in the activity; in response to the participation instruction, detecting the activity cluster to which the current user belongs to participate in the target activity; detecting whether there is an object quota of inventory objects in the entity inventory variable corresponding to the activity cluster; and deducting the inventory objects when there is an object quota of inventory objects in the entity inventory variable.

[0059] Optionally, after detecting whether there is an object quota of an inventory object in the entity inventory variable corresponding to the active cluster, the inventory allocation method further includes: when there is no object quota of an inventory object in the entity inventory variable, detecting whether there is an object quota of an inventory object in the virtual cluster inventory variable; when there is an object quota of an inventory object in the virtual cluster inventory variable, deducting the inventory object; when there is no object quota of an inventory object in the virtual cluster inventory variable, returning an insufficient quota message.

[0060] In an embodiment of the present invention, when a user participates in the activity (i.e., receiving a participation instruction of the user in the activity and responding to the participation instruction), the activity cluster to which the current user participates in the target activity can be detected first, and then it is detected whether there is an object quota of an inventory object in the entity inventory variable corresponding to the activity cluster. If there is an object quota of an inventory object in the entity inventory variable, the inventory object is deducted.

[0061] If there is no object quota of an inventory object in the entity inventory variable, it is detected whether there is an object quota of an inventory object in the virtual cluster inventory variable. If there is an object quota of an inventory object in the virtual cluster inventory variable, the inventory object is deducted; if there is no object quota of an inventory object in the virtual cluster inventory variable, an insufficient quota message is returned.

[0062] Taking the example that a customer participates in a coupon-receiving activity, when the customer participates in the coupon-receiving activity, it can be first determined whether there is still a quota in the virtual cluster inventory variable Coupon(n + 1). If the quota is zero, an error is directly reported and an insufficient quota message is returned to the customer. If the quota is sufficient, it can be routed to the corresponding activity cluster in a hash manner, and the quota of the current cluster is judged. If the quota is sufficient, it is directly deducted. If the quota of the current cluster is insufficient, it is judged whether there is still a quota in the virtual cluster inventory variable Coupon(n + 1). If the quota is sufficient, it is directly deducted. If the quota is insufficient, an insufficient quota message is returned to the customer.

[0063] Figure 3It is a flowchart of an optional deduction amount according to an embodiment of the present invention. Taking the coupon-receiving activity as an example, when a customer comes to participate in the coupon-receiving activity, first determine whether the virtual cluster inventory variable Coupon(n + 1) is greater than 0. If not, the coupon-receiving fails and an error is directly reported to the customer. If it is, use the hash method to determine the routing to the corresponding cluster set (denoted as set1, ……, setn), and determine whether the Coupon of the current set (correspondingly denoted as Coupon1, ……, Couponn) is greater than 0. If it is greater than 0, then Coupon = Coupon - 1 and record the details; if it is not greater than 0, then determine whether Coupon(n + 1) is greater than 0. If it is greater than 0, then Coupon(n + 1) = Coupon(n + 1) - 1 and record the details, otherwise the coupon-receiving fails and an error is directly reported to the customer.

[0064] Through the above inventory allocation method and deduction amount method in the embodiments of the present invention, the matching degree between the hot account amount allocation and the actual number of customers based on the sub-account method can be improved. At the same time, by increasing the virtual amount, the deficiency in guiding the amount allocation by the historical activity database can be effectively avoided, the success rate of amount deduction can be effectively improved, and the activity efficiency can be enhanced.

[0065] Embodiment 2

[0066] An inventory allocation device based on activity data provided in this embodiment includes multiple implementation units, and each implementation unit corresponds to each implementation step in Embodiment 1 above.

[0067] Figure 4 It is a schematic diagram of an optional inventory allocation device based on activity data according to an embodiment of the present invention. As Figure 4 shown, the allocation device may include: a matching unit 40, an acquisition unit 41, and an allocation unit 42, where

[0068] The matching unit 40 is used to match the activity information of the target activity with the historical activity database to obtain historical activities with a similarity greater than a preset similarity threshold;

[0069] The acquisition unit 41 is used to obtain the proportion of the number of successful customers in the historical activity, where the proportion of the number of successful customers is the ratio of the number of customers who successfully completed the activity to the total number of customers in the historical activity;

[0070] The allocation unit 42 is used to allocate inventory objects to each activity cluster of the target activity based on the proportion of the number of successful customers.

[0071] The above-mentioned allocation device can match the activity information of the target activity with the historical activity database through the matching unit 40 to obtain historical activities with a similarity greater than the preset similarity threshold, obtain the proportion of successful customers of the historical activities through the obtaining unit 41, and allocate inventory objects to each activity cluster of the target activity based on the proportion of successful customers through the allocation unit 42. In the embodiment of the present invention, by selecting historical activities similar to the current activity from the historical activity database and allocating inventory objects to each activity cluster of the current activity based on the proportion of successful customers in the historical activities, the matching degree between the inventory quota allocation and the actual number of customers can be effectively improved, the success rate of quota deduction can be increased, the activity efficiency can be enhanced, and thus the technical problem in the related art that the inventory quota is allocated to the sub-accounts of each activity cluster and there is a large difference in the matching with the actual number of users routed to each activity cluster, resulting in a low success rate of quota deduction, is solved.

[0072] Optionally, the inventory allocation device further includes: a first collection module, configured to collect the total number of inventory objects to be allocated for the target activity, the activity type, the activity area where the activity is carried out, and the object value of each inventory object before matching the activity information of the target activity with the historical activity database, so as to obtain the activity information of the target activity.

[0073] Optionally, the matching unit includes: a first query module, configured to query historical activities corresponding to the activity type of the target activity in the historical activity database to obtain a first set of historical activities; a second query module, configured to query historical activities corresponding to the activity area where the target activity is carried out in the historical activity database to obtain a second set of historical activities; a first determination module, configured to determine the quantity range in which the total number of inventory objects of the target activity is located and the value range in which the object value of the target activity is located; a third query module, configured to query historical activities corresponding to the quantity range in the historical activity database to obtain a third set of historical activities; a fourth query module, configured to query historical activities corresponding to the value range in the historical activity database to obtain a fourth set of historical activities; a first intersection module, configured to perform an intersection operation on the first set of historical activities, the second set of historical activities, the third set of historical activities, and the fourth set of historical activities to obtain historical activities with a similarity greater than the preset similarity threshold.

[0074] Optionally, the inventory allocation device further includes: a first allocation module, configured to allocate corresponding multiple entity inventory variables according to the number of activity clusters of the target activity after allocating inventory objects to each activity cluster of the target activity based on the proportion of successful customers; a first increase module, configured to increase virtual cluster inventory variables for the target activity, where the virtual cluster inventory variables are used to adjust the quantity of the allocated inventory objects; a first adjustment module, configured to combine the multiple entity inventory variables and the virtual cluster inventory variables to adjust the quantity of the inventory objects allocated to each activity cluster.

[0075] Optionally, the inventory allocation device further includes: a first setting module configured to set an adjustment amount of the reserved ratio object quantity for the virtual cluster inventory variable.

[0076] Optionally, the inventory allocation device further includes: a first receiving module configured to receive a participation instruction of a user participating in an activity after allocating inventory objects to each activity cluster of a target activity based on the proportion of successful customers; a first detection module configured to, in response to the participation instruction, detect the activity cluster to which the current user belongs for participating in the target activity; a second detection module configured to detect whether there is an object quota of an inventory object in the entity inventory variable corresponding to the activity cluster; a first deduction module configured to, when there is an object quota of an inventory object in the entity inventory variable, deduct the inventory object.

[0077] Optionally, the inventory allocation device further includes: a third detection module configured to, after detecting whether there is an object quota of an inventory object in the entity inventory variable corresponding to the activity cluster, detect whether there is an object quota of an inventory object in the virtual cluster inventory variable when there is no object quota of an inventory object in the entity inventory variable; a second deduction module configured to, when there is an object quota of an inventory object in the virtual cluster inventory variable, deduct the inventory object; a first return module configured to, when there is no object quota of an inventory object in the virtual cluster inventory variable, return an insufficient quota message.

[0078] The above-mentioned allocation device may further include a processor and a memory. The above-mentioned matching unit 40, obtaining unit 41, allocation unit 42, etc. are all stored in the memory as program units, and the corresponding functions are implemented by the processor executing the above-mentioned program units stored in the memory.

[0079] The above-mentioned processor includes a kernel, and the kernel retrieves the corresponding program units from the memory. One or more kernels can be set, and the inventory objects are allocated to each activity cluster of the target activity by adjusting the kernel parameters.

[0080] The above-mentioned memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of, for example, read-only memory (ROM) or flash memory (flash RAM), and the memory includes at least one storage chip.

[0081] The present application further provides a computer program product, which is suitable for executing a program initialized with the following method steps when executed on a data processing device: matching the activity information of a target activity with a historical activity database to obtain historical activities with a similarity greater than a preset similarity threshold, obtaining the proportion of successful customers of the historical activities, and allocating inventory objects to each activity cluster of the target activity based on the proportion of successful customers.

[0082] According to another aspect of the embodiments of the present invention, there is also provided a computer-readable storage medium, which includes a stored computer program. When the computer program runs, it controls the device where the computer-readable storage medium is located to execute the inventory allocation method based on activity data in any one of the above.

[0083] According to another aspect of the embodiments of the present invention, there is also provided an electronic device, which includes one or more processors and a memory. The memory is used to store one or more programs. When the one or more programs are executed by the one or more processors, the one or more processors are caused to implement the inventory allocation method based on activity data in any one of the above.

[0084] Figure 5 is a hardware structure block diagram of an electronic device (or mobile device) for an inventory allocation method based on activity data according to an embodiment of the present invention. As Figure 5 shown, the electronic device may include one or more processors 502 (shown as 502a, 502b,..., 502n in the figure) (the processor 502 may include, but is not limited to, a processing device such as a microprocessor MCU or a programmable logic device FPGA), and a memory 504 for storing data. In addition, it may further include: a display, an input / output interface (I / O interface), a universal serial bus (USB) port (which may be included as one of the ports of the I / O interface), a network interface, a keyboard, a power supply, and / or a camera. Those of ordinary skill in the art can understand that Figure 5 the structure shown is only schematic and does not limit the structure of the above electronic device. For example, the electronic device may further include more or fewer components than Figure 5 shown, or have a different configuration from Figure 5 shown.

[0085] The serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages or disadvantages of the embodiments.

[0086] In the above embodiments of the present invention, the descriptions of the respective embodiments have their own emphases. For parts not detailed in a certain embodiment, reference may be made to the relevant descriptions of other embodiments.

[0087] In several embodiments provided by the present application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are merely illustrative. For example, the division of the units can be a logical function division. In actual implementation, there can be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed coupling, direct coupling, or communication connection between each other can be through some interfaces. The indirect coupling or communication connection of units or modules can be in an electrical or other form.

[0088] The units described as separate components may or may not be physically separated. The components displayed as units may or may not be physical units, that is, they can be located in one place, or they can be distributed to multiple units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0089] In addition, in each embodiment of the present invention, the functional units can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above-mentioned integrated units can be implemented in the form of hardware or in the form of software functional units.

[0090] If the above-mentioned integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in each embodiment of the present invention. The foregoing storage medium includes: USB flash drives, read-only memories (ROMs), random access memories (RAMs), mobile hard disks, magnetic disks, or optical discs and other various media that can store program codes.

[0091] The above is only the preferred embodiment of the present invention. It should be noted that for those of ordinary skill in the art, without departing from the principle of the present invention, several improvements and refinements can be made, and these improvements and refinements should also be regarded as the protection scope of the present invention.

Claims

1. An inventory allocation method based on activity data, characterized in that, it includes: Matching the activity information of the target activity with the historical activity database to obtain historical activities with a similarity greater than a preset similarity threshold; Obtaining the proportion of successful customers of the historical activity, where the proportion of successful customers is the ratio of the number of customers who successfully completed the activity to the total number of customers in the historical activity; Based on the proportion of successful customers, allocating inventory objects to each activity cluster of the target activity; After allocating inventory objects to each activity cluster of the target activity based on the proportion of successful customers, the inventory allocation method further includes: allocating a corresponding number of entity inventory variables according to the number of activity clusters of the target activity; adding a virtual cluster inventory variable to the target activity, where the virtual cluster inventory variable is used to adjust the quantity of the allocated inventory objects; combining the multiple entity inventory variables and the virtual cluster inventory variable to adjust the quantity of the inventory objects allocated to each activity cluster.

2. The inventory allocation method according to claim 1, characterized in that, Before matching the activity information of the target activity with the historical activity database, the inventory allocation method further includes: Collecting the total quantity of inventory objects to be allocated for the target activity, activity type, activity area, and the object value of each inventory object to obtain the activity information of the target activity.

3. The inventory allocation method according to claim 2, characterized in that, The step of matching the activity information of the target activity with the historical activity database to obtain historical activities with a similarity greater than a preset similarity threshold includes: Querying the historical activities corresponding to the activity type of the target activity in the historical activity database to obtain a first set of historical activities; Querying the historical activities corresponding to the activity area of the target activity in the historical activity database to obtain a second set of historical activities; Determining the quantity range in which the total quantity of inventory objects of the target activity is located, and the value range in which the object value of the target activity is located; Querying the historical activities corresponding to the quantity range in the historical activity database to obtain a third set of historical activities; Querying the historical activities corresponding to the value range in the historical activity database to obtain a fourth set of historical activities; Performing an intersection operation on the first set of historical activities, the second set of historical activities, the third set of historical activities, and the fourth set of historical activities to obtain historical activities with a similarity greater than a preset similarity threshold.

4. The inventory allocation method according to claim 1, characterized in that, The inventory allocation method further includes: Setting a reserved proportion of object quantity adjustment for the virtual cluster inventory variable.

5. The inventory allocation method according to claim 1, characterized in that, After allocating inventory objects to each activity cluster of the target activity based on the proportion of successful customers, the inventory allocation method further includes: Receiving a participation instruction for a user to participate in the activity; Responding to the participation instruction and detecting the activity cluster to which the current user belongs to participate in the target activity; Check whether there is an object quota of an inventory object in the entity inventory variable corresponding to the activity cluster; In the case that there is an object quota of an inventory object in the entity inventory variable, deduct the inventory object.

6. The inventory allocation method according to claim 5, characterized in that, after checking whether there is an object quota of an inventory object in the entity inventory variable corresponding to the activity cluster, the inventory allocation method further includes: In the case that there is no object quota of an inventory object in the entity inventory variable, check whether there is an object quota of an inventory object in the virtual cluster inventory variable; In the case that there is an object quota of an inventory object in the virtual cluster inventory variable, deduct the inventory object; In the case that there is no object quota of an inventory object in the virtual cluster inventory variable, return a quota insufficient message.

7. An inventory allocation device based on activity data, characterized in that, comprising: A matching unit for matching the activity information of a target activity with a historical activity database to obtain historical activities with a similarity greater than a preset similarity threshold; An obtaining unit for obtaining the proportion of successful customers of the historical activity, where the proportion of successful customers is the ratio of the number of customers who successfully completed the activity to the total number of customers in the historical activity; An allocation unit for allocating inventory objects to each activity cluster of the target activity based on the proportion of successful customers; The inventory allocation device further includes: a first allocation module for, after allocating inventory objects to each activity cluster of the target activity based on the proportion of successful customers, allocating a corresponding plurality of entity inventory variables according to the number of activity clusters of the target activity; a first increasing module for adding a virtual cluster inventory variable for the target activity, where the virtual cluster inventory variable is used to adjust the quantity of the allocated inventory objects; a first adjustment module for combining the plurality of entity inventory variables and the virtual cluster inventory variable to adjust the quantity of the inventory objects allocated to each activity cluster.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored computer program, where, when the computer program runs, it controls the device where the computer-readable storage medium is located to execute the inventory allocation method based on activity data according to any one of claims 1 to 6.

9. An electronic device, characterized in that, comprises one or more processors and a memory, the memory is used to store one or more programs, where, when the one or more programs are executed by the one or more processors, the one or more processors implement the inventory allocation method based on activity data according to any one of claims 1 to 6.

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