Resource allocation method and device, electronic equipment and computer readable storage medium

Abstract

The invention provides a resource allocation method and device, electronic equipment and a computer readable storage medium, and can be applied to the technical fields of computer technology, artificial intelligence technology and task processing. The resource allocation method comprises the following steps: in response to a received resource allocation request, determining allocation weights respectively corresponding to M object identifiers according to the M object identifiers indicated by the resource allocation request; determining initial resource allocation information and initial deviation information respectively corresponding to the M object identifiers according to the quantity of the resources to be allocated and the allocation weights respectively corresponding to the M object identifiers; according to the initial deviation information corresponding to the M object identifiers, adjusting the initial resource allocation information corresponding to the M object identifiers to obtain resource allocation information corresponding to the M object identifiers; and allocating the N to-be-allocated resources to the objects corresponding to the M object identifiers according to the resource allocation information corresponding to the M object identifiers.

Description

Technical Field

[0001] The present disclosure relates to the fields of computer technology, artificial intelligence technology and task processing technology, and more specifically, to a resource allocation method and device, an electronic device, a computer-readable storage medium and a computer program product. Background Art

[0002] With the development of computer technology, Customer Relationship Management system (CRM) came into being.

[0003] A customer relationship management system is a software system used to help companies manage and maintain information related to customer relationships. Leads can refer to information about potential customers or sales opportunities. For example, a customer relationship management system can provide lead management functions to help companies effectively manage and track the entire sales process of leads.

[0004] In the process of realizing the concept of the present disclosure, the inventors found that there are at least the following problems in the related art: since the customer relationship management system has low flexibility and adaptability in lead allocation, it is impossible to effectively guarantee the efficiency and accuracy of lead allocation. Summary of the invention

[0005] In view of this, the present disclosure provides a resource allocation method and apparatus, an electronic device, a computer-readable storage medium, and a computer program product.

[0006] According to one aspect of the present disclosure, a resource allocation method is provided, comprising: in response to receiving a resource allocation request, determining allocation weights corresponding to each of the M object identifiers according to M object identifiers indicated in the resource allocation request, wherein the resource allocation request includes N resources to be allocated, and M and N are both integers greater than 1; determining initial resource allocation information and initial deviation information corresponding to each of the M object identifiers according to the number of resources to be allocated and the allocation weights corresponding to each of the M object identifiers; adjusting the initial resource allocation information corresponding to each of the M object identifiers according to the initial deviation information corresponding to each of the M object identifiers to obtain resource allocation information corresponding to each of the M object identifiers; and, according to the resource allocation information corresponding to each of the M object identifiers, allocating the N resources to be allocated to the objects corresponding to each of the M object identifiers.

[0007] According to an embodiment of the present disclosure, the resource allocation request includes an object set identifier. The above-mentioned response to receiving the resource allocation request, according to the M object identifiers indicated by the above-mentioned resource allocation request, determining the allocation weights corresponding to each of the above-mentioned M object identifiers includes: in response to receiving the above-mentioned resource allocation request, determining the above-mentioned M object identifiers corresponding to the above-mentioned object set identifier and P object label values ​​corresponding to each of the above-mentioned M object identifiers, where P is a positive integer; and determining the allocation weights corresponding to each of the above-mentioned M object identifiers according to the P object label values ​​corresponding to each of the above-mentioned M object identifiers.

[0008] According to an embodiment of the present disclosure, the above-mentioned determining the allocation weights corresponding to each of the M object identifiers according to the P object label values ​​corresponding to each of the M object identifiers includes: determining the object label cumulative values ​​corresponding to each of the M object identifiers according to the P object label values ​​corresponding to the M object identifiers; determining the set label cumulative value according to the object label cumulative values ​​corresponding to each of the M object identifiers; for each of the M object identifiers, determining the first ratio corresponding to the object identifier according to the set label cumulative value and the object label cumulative value corresponding to the object identifier; and determining the first ratio corresponding to the object identifier as the above-mentioned allocation weight.

[0009] According to an embodiment of the present disclosure, the above-mentioned initial resource allocation information includes a predicted initial resource allocation value and an actual initial resource allocation value, and the above-mentioned initial deviation information includes a current initial deviation value and a cumulative initial deviation value. The above-mentioned determination of the initial resource allocation information and initial deviation information corresponding to each of the above-mentioned M object identifiers according to the number of resources to be allocated and the allocation weights corresponding to each of the above-mentioned M object identifiers includes: for each of the above-mentioned M object identifiers, determining the historical cumulative initial deviation value corresponding to the above-mentioned object identifier from the data source; determining the above-mentioned predicted initial resource allocation value and the above-mentioned actual initial resource allocation value corresponding to the above-mentioned object identifier according to the above-mentioned number of resources to be allocated, the above-mentioned allocation weights and the above-mentioned historical cumulative initial deviation value; and determining the above-mentioned current initial deviation value and the above-mentioned cumulative initial deviation value corresponding to the above-mentioned object identifier according to the above-mentioned historical cumulative initial deviation value, the above-mentioned predicted initial resource allocation value and the above-mentioned actual initial resource allocation value.

[0010] According to an embodiment of the present disclosure, the above-mentioned determination of the above-mentioned predicted initial resource allocation value and the above-mentioned actual initial resource allocation value corresponding to the above-mentioned object identifier based on the above-mentioned number of resources to be allocated, the above-mentioned allocation weight and the above-mentioned historical accumulated initial deviation value includes: determining a first product value based on the above-mentioned number of resources to be allocated and the above-mentioned allocation weight; determining a first difference value based on the above-mentioned historical accumulated initial deviation value and the above-mentioned first product value; determining the above-mentioned predicted initial resource allocation value corresponding to the above-mentioned object identifier based on the above-mentioned first difference value; and determining the above-mentioned actual initial resource allocation value corresponding to the above-mentioned object identifier based on the above-mentioned predicted initial resource allocation value.

[0011] According to an embodiment of the present disclosure, the above-mentioned initial deviation value and the above-mentioned cumulative initial deviation value corresponding to the above-mentioned object identifier are determined based on the above-mentioned historical cumulative initial deviation value, the above-mentioned predicted initial resource allocation value and the above-mentioned actual initial resource allocation value, including: determining a second difference value based on the above-mentioned predicted initial resource allocation value and the above-mentioned actual initial resource allocation value; determining the above-mentioned initial deviation value corresponding to the above-mentioned object identifier based on the above-mentioned second difference value; and determining the above-mentioned cumulative initial deviation value corresponding to the above-mentioned object identifier based on the above-mentioned initial deviation value and the above-mentioned historical cumulative initial deviation value.

[0012] According to an embodiment of the present disclosure, the initial resource allocation information includes an actual initial resource allocation value, and the initial deviation information includes a cumulative initial deviation value. The initial resource allocation information corresponding to each of the M object identifiers is adjusted according to the initial deviation information corresponding to each of the M object identifiers to obtain the resource allocation information corresponding to each of the M object identifiers, including: determining the actual resource allocation total value according to the M actual initial resource allocation values; and, in the case where the actual resource allocation total value and the number of resources to be allocated do not meet a predetermined condition, adjusting the actual initial resource allocation value to obtain the actual resource allocation value.

[0013] According to an embodiment of the present disclosure, the above-mentioned actual initial resource allocation value is adjusted to obtain the actual resource allocation value, which includes: determining the target object identifier among the above-mentioned M object identifiers according to the accumulated initial deviation values ​​corresponding to each of the above-mentioned M object identifiers; and adjusting the actual initial resource allocation value corresponding to the above-mentioned target object identifier to obtain the actual resource allocation value corresponding to the above-mentioned target object identifier.

[0014] According to an embodiment of the present disclosure, it also includes, after adjusting the actual initial resource allocation value corresponding to the above-mentioned target object identifier to obtain the actual resource allocation value corresponding to the above-mentioned target object identifier: adjusting the above-mentioned cumulative initial deviation value according to the actual resource allocation value corresponding to the above-mentioned target object identifier to obtain the cumulative deviation value.

[0015] According to an embodiment of the present disclosure, the resource allocation information includes an actual resource allocation value. The N resources to be allocated are allocated to the objects corresponding to the M object identifiers according to the resource allocation information corresponding to the M object identifiers respectively, including: sorting the M object identifiers according to the actual resource allocation values ​​corresponding to the M object identifiers respectively to obtain a resource allocation sequence; and, according to the resource allocation sequence, allocating the N resources to be allocated in sequence to the objects corresponding to the M object identifiers respectively.

[0016] According to another aspect of the present disclosure, a resource allocation device is provided, comprising: a first determination module, for determining, in response to receiving a resource allocation request, the allocation weights corresponding to the M object identifiers indicated by the resource allocation request, wherein the resource allocation request includes N resources to be allocated, and M and N are both integers greater than 1; a second determination module, for determining, according to the number of resources to be allocated and the allocation weights corresponding to the M object identifiers, initial resource allocation information and initial deviation information corresponding to the M object identifiers; a first adjustment module, for adjusting the initial resource allocation information corresponding to the M object identifiers according to the initial deviation information corresponding to the M object identifiers to obtain the resource allocation information corresponding to the M object identifiers; and an allocation module, for allocating the N resources to be allocated to the objects corresponding to the M object identifiers according to the resource allocation information corresponding to the M object identifiers.

[0017] According to another aspect of the present disclosure, an electronic device is provided, comprising: one or more processors; and a memory for storing one or more instructions, wherein when the one or more instructions are executed by the one or more processors, the one or more processors implement the method described in the present disclosure.

[0018] According to another aspect of the present disclosure, a computer-readable storage medium is provided, on which executable instructions are stored. When the executable instructions are executed by a processor, the processor implements the method described in the present disclosure.

[0019] According to another aspect of the present disclosure, a computer program product is provided. The computer program product includes computer executable instructions. When the computer executable instructions are executed, they are used to implement the method described in the present disclosure.

[0020] According to the embodiments of the present disclosure, by determining the allocation weight corresponding to the object identifier according to the object identifier indicated by the resource allocation request, resources can be reasonably allocated according to the needs and priorities of different objects, and a flexible resource allocation strategy can be implemented. Since the resource allocation information is obtained by adjusting the initial resource allocation information according to the initial deviation information, the initial resource allocation information and the initial deviation information are determined according to the number of resources to be allocated and the allocation weight, and more reasonable resource allocation information can be obtained. On this basis, by allocating the resources to be allocated to the object corresponding to the object identifier according to the resource allocation information corresponding to the object identifier, no manual intervention is required, and effective allocation and utilization of resources are achieved, at least partially overcoming the technical problems in the related art due to the low flexibility and adaptability of the customer relationship management system in lead allocation, and improving the efficiency and accuracy of resource allocation. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] The above and other objects, features and advantages of the present disclosure will become more apparent through the following description of the embodiments of the present disclosure with reference to the accompanying drawings, in which:

[0022] Figure 1 The system architecture to which the resource allocation method according to the embodiment of the present disclosure can be applied is schematically shown;

[0023] Figure 2 A flowchart of a resource allocation method according to an embodiment of the present disclosure is schematically shown;

[0024] Figure 3 An exemplary schematic diagram schematically illustrates a process of determining allocation weights corresponding to respective M object identifiers according to M object identifiers indicated by a resource allocation request according to an embodiment of the present disclosure;

[0025] Figure 4 An example schematic diagram of a process of determining initial resource allocation information and initial deviation information corresponding to each of the M object identifiers according to the number of resources to be allocated and the allocation weights corresponding to each of the M object identifiers according to an embodiment of the present disclosure is schematically shown;

[0026] Figure 5 An example schematic diagram of a process of adjusting initial resource allocation information corresponding to each of the M object identifiers according to initial deviation information corresponding to each of the M object identifiers to obtain resource allocation information corresponding to each of the M object identifiers according to an embodiment of the present disclosure is schematically shown;

[0027] Figure 6 An example schematic diagram of a process of obtaining an actual resource allocation value and an accumulated deviation value according to an embodiment of the present disclosure is schematically shown;

[0028] Figure 7An example schematic diagram of a process of obtaining an actual resource allocation value and an accumulated deviation value according to an embodiment of the present disclosure is schematically shown;

[0029] Figure 8 An example schematic diagram schematically shows a resource allocation process according to an embodiment of the present disclosure;

[0030] Fig. 9 A block diagram schematically shows a resource allocation device according to an embodiment of the present disclosure; and

[0031] Fig.10 A block diagram of an electronic device suitable for implementing a resource allocation method according to an embodiment of the present disclosure is schematically shown. DETAILED DESCRIPTION

[0032] Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the present disclosure. In the following detailed description, for ease of explanation, many specific details are set forth to provide a comprehensive understanding of the embodiments of the present disclosure. However, it is apparent that one or more embodiments may also be implemented without these specific details. In addition, in the following description, descriptions of known structures and technologies are omitted to avoid unnecessary confusion of the concepts of the present disclosure.

[0033] The terms used herein are only for describing specific embodiments and are not intended to limit the present disclosure. The terms "comprise", "include", etc. used herein indicate the existence of the features, steps, operations and / or components, but do not exclude the existence or addition of one or more other features, steps, operations or components.

[0034] All terms (including technical and scientific terms) used herein have the meanings commonly understood by those skilled in the art, unless otherwise defined. It should be noted that the terms used herein should be interpreted as having a meaning consistent with the context of this specification, and should not be interpreted in an idealized or overly rigid manner.

[0035] When using expressions such as "at least one of A, B, and C, etc.", they should generally be interpreted according to the meaning of the expression commonly understood by those skilled in the art (for example, "a system having at least one of A, B, and C" should include but is not limited to a system having A alone, B alone, C alone, A and B, A and C, B and C, and / or A, B, C, etc.).

[0036] In the embodiments of the present disclosure, the collection, updating, analysis, processing, use, transmission, provision, disclosure, storage, etc. of the data involved (for example, including but not limited to user personal information) are in compliance with the provisions of relevant laws and regulations, are used for legitimate purposes, and do not violate public order and good morals. In particular, necessary measures are taken for user personal information to prevent illegal access to user personal information data and maintain the security of user personal information, network security, and national security.

[0037] In the embodiments of the present disclosure, the user's authorization or consent is obtained before obtaining or collecting the user's personal information.

[0038] For example, after collecting the historical object information corresponding to each candidate object identifier, your information can be desensitized by using methods including de-identification or anonymization to protect the security of your information.

[0039] A lead can refer to an individual, a company or an organization. Leads usually include basic information of potential users, such as name, contact information, company, etc., as well as descriptions of their needs, interests, purchase intentions, etc. Leads are the starting point of sales and marketing activities. By tracking, developing and converting leads, companies can convert potential customers into actual sales opportunities and ultimately reach deals.

[0040] The customer relationship management system can provide lead management functions. Specifically, the customer relationship management system can focus on the management of customer data, record various interactions between the company and customers during the marketing and sales process, as well as the status of various related activities, and provide various data models to provide support for subsequent analysis and decision-making.

[0041] In related technologies, the customer relationship management system provides a dedicated access point for leads. The customer relationship management system puts the collected leads into a resource pool for sales staff to claim based on their personal assessments; or it divides the leads into categories according to simple flow rules and allows a certain group of authorized people to randomly assign them.

[0042] The above-mentioned lead allocation method does not conduct portrait-based allocation based on the characteristics of sales personnel, so the adaptability of lead allocation is low and the inclination is high; since it cannot be expanded, the flexibility of lead allocation is low, resulting in the inability to effectively guarantee the efficiency and accuracy of lead allocation, and thus the inability to guarantee the probability of follow-up and conversion of leads into business opportunities.

[0043] In order to at least partially solve the technical problems existing in the related art, the present disclosure provides a resource allocation method and device, an electronic device and a computer-readable storage medium, which can be applied to the fields of computer technology, artificial intelligence technology and task processing technology. The resource allocation method includes: in response to receiving a resource allocation request, determining the allocation weights corresponding to each of the M object identifiers according to the M object identifiers indicated by the resource allocation request, wherein the resource allocation request includes N resources to be allocated, and M and N are both integers greater than 1; determining the initial resource allocation information and initial deviation information corresponding to each of the M object identifiers according to the number of resources to be allocated and the allocation weights corresponding to each of the M object identifiers; adjusting the initial resource allocation information corresponding to each of the M object identifiers according to the initial deviation information corresponding to each of the M object identifiers to obtain the resource allocation information corresponding to each of the M object identifiers; allocating the N resources to be allocated to the objects corresponding to each of the M object identifiers according to the resource allocation information corresponding to each of the M object identifiers.

[0044] Figure 1 The system architecture to which the resource allocation method according to the embodiment of the present disclosure can be applied is schematically shown. It should be noted that: Figure 1 What is shown is merely an example of a system architecture to which the embodiments of the present disclosure can be applied, in order to help those skilled in the art understand the technical content of the present disclosure, but it does not mean that the embodiments of the present disclosure cannot be used in other devices, systems, environments or scenarios.

[0045] like Figure 1 As shown, the system architecture 100 according to this embodiment may include a first terminal device 101, a second terminal device 102, a third terminal device 103, a network 104 and a server 105. The network 104 is used to provide a medium for a communication link between the first terminal device 101, the second terminal device 102, the third terminal device 103 and the server 105. The network 104 may include various connection types, such as wired, wireless communication links or optical fiber cables, etc.

[0046] The user may use at least one of the first terminal device 101, the second terminal device 102, and the third terminal device 103 to interact with the server 105 through the network 104 to receive or send messages, etc. Various communication client applications may be installed on the first terminal device 101, the second terminal device 102, and the third terminal device 103, such as shopping applications, web browser applications, search applications, instant messaging tools, email clients, social platform software, etc. (only as examples).

[0047] The first terminal device 101, the second terminal device 102, and the third terminal device 103 may be various electronic devices having display screens and supporting web browsing, including but not limited to smart phones, tablet computers, laptop computers, desktop computers, and the like.

[0048] The server 105 may be a server that provides various services, such as a background management server (only as an example) that provides support for websites browsed by users using the first terminal device 101, the second terminal device 102, and the third terminal device 103. The background management server may analyze and process the received data such as user requests, and feed back the processing results (such as web pages, information, or data obtained or generated according to user requests) to the terminal device.

[0049] It should be noted that the resource allocation method provided in the embodiment of the present disclosure can generally be executed by the server 105. Accordingly, the resource allocation device provided in the embodiment of the present disclosure can generally be set in the server 105. The resource allocation method provided in the embodiment of the present disclosure can also be executed by a server or server cluster that is different from the server 105 and can communicate with the first terminal device 101, the second terminal device 102, the third terminal device 103 and / or the server 105. Accordingly, the resource allocation device provided in the embodiment of the present disclosure can also be set in a server or server cluster that is different from the server 105 and can communicate with the first terminal device 101, the second terminal device 102, the third terminal device 103 and / or the server 105.

[0050] Alternatively, the resource allocation method provided in the embodiment of the present disclosure may also be executed by the first terminal device 101, the second terminal device 102, or the third terminal device 103, or may also be executed by other terminal devices different from the first terminal device 101, the second terminal device 102, or the third terminal device 103. Accordingly, the resource allocation apparatus provided in the embodiment of the present disclosure may also be arranged in the first terminal device 101, the second terminal device 102, or the third terminal device 103, or may be arranged in other terminal devices different from the first terminal device 101, the second terminal device 102, or the third terminal device 103.

[0051] It should be understood that Figure 1 The number of terminal devices, networks and servers in the embodiment is only for illustration. Any number of terminal devices, networks and servers may be provided according to the implementation requirements.

[0052] It should be noted that the sequence numbers of the operations in the following method are only used as representations of the operations for the purpose of description, and should not be regarded as representing the execution order of the operations. Unless explicitly stated, the method does not need to be executed completely in the order shown.

[0053] Figure 2 The flowchart of the resource allocation method according to the embodiment of the present disclosure is schematically shown.

[0054] like Figure 2 As shown, the resource allocation method 200 includes operations S210-S240.

[0055] In operation S210, in response to receiving a resource allocation request, allocation weights corresponding to the M object identifiers are determined according to the M object identifiers indicated in the resource allocation request, wherein the resource allocation request includes N resources to be allocated, and M and N are both integers greater than 1.

[0056] In operation S220, initial resource allocation information and initial deviation information corresponding to each of the M object identifiers are determined according to the number of resources to be allocated and the allocation weights corresponding to each of the M object identifiers.

[0057] In operation S230, the initial resource allocation information corresponding to each of the M object identifiers is adjusted according to the initial deviation information corresponding to each of the M object identifiers to obtain the resource allocation information corresponding to each of the M object identifiers.

[0058] In operation S240, N resources to be allocated are allocated to objects corresponding to the M object identifiers, respectively, according to resource allocation information corresponding to the M object identifiers, respectively.

[0059] According to an embodiment of the present disclosure, a code for generating a resource allocation request may be pre-written into a script, and in response to detecting a resource allocation operation initiated by a user, an object set identifier and at least one resource to be allocated may be obtained. The client may run the script to generate a resource allocation request message according to the object set identifier and the at least one resource to be allocated. The client may send the resource allocation request message to the server, so that the server may allocate the at least one resource to be allocated to at least one object corresponding to the object set identifier according to the resource allocation request message.

[0060] According to an embodiment of the present disclosure, resources to be allocated may refer to clues to be allocated. Clues to be allocated may refer to information corresponding to commodity providers, commodity consumers, commodity trading channels, etc. The object set identifier may serve as a unique identifier of the object set. Each object set may include at least one object. The object identifier may serve as a unique identifier of the object. Before executing the resource allocation method provided by the present disclosure, information corresponding to each of the at least one candidate objects may be processed in advance to obtain candidate object features corresponding to each of the at least one candidate objects. On this basis, at least one candidate object may be grouped according to the candidate object features corresponding to each of the at least one candidate objects to obtain at least one object set.

[0061] According to an embodiment of the present disclosure, the historical object information corresponding to each candidate object identifier can be acquired in advance. The historical object information corresponding to each candidate object identifier is processed respectively to obtain at least one candidate object label value corresponding to the candidate object identifier, and each candidate object identifier and at least one candidate object label value corresponding to the candidate object identifier are associated and stored in the data source. After receiving the resource allocation request, the server can determine the M object identifiers corresponding to the object set identifier according to the object set identifier in the resource allocation request. On this basis, for each of the M object identifiers, according to the actual business needs and the object identifier, at least one candidate object identifier in the data source can be matched, and at least one candidate object label value corresponding to the candidate object identifier can be determined as P object label values.

[0062] According to an embodiment of the present disclosure, after obtaining P object label values ​​corresponding to each of the M object identifiers, the total object label value corresponding to the object set identifier can be determined according to the P object label values ​​corresponding to each of the M object identifiers. For each of the M object identifiers, the sub-object label value corresponding to the object identifier can be determined according to the P object label values ​​corresponding to the object identifier. On this basis, the allocation weight corresponding to the object identifier can be determined according to the sub-object label value and the total object label value.

[0063] According to an embodiment of the present disclosure, after obtaining the allocation weights corresponding to the M object identifiers, for each of the M object identifiers, the historical accumulated initial deviation value corresponding to the object identifier can be obtained from the data source. The predicted initial resource allocation value corresponding to the object identifier can be determined based on the number of resources to be allocated, the historical accumulated initial deviation value and the allocation weight. On this basis, the actual initial resource allocation value corresponding to the object identifier can be determined based on the predicted initial resource allocation value.

[0064] According to an embodiment of the present disclosure, the initial deviation information may include an initial deviation value for that time and a cumulative initial deviation value. The initial deviation value for that time may refer to a deviation value corresponding to the current resource allocation operation. For example, the initial deviation value for that time may be determined based on a predicted initial resource allocation value and an actual initial resource allocation value. The cumulative initial deviation value may refer to a value obtained by accumulating deviation values ​​corresponding to each resource allocation operation. For example, the cumulative initial deviation value may be determined based on historical cumulative initial deviation values ​​and the initial deviation value for that time.

[0065] According to an embodiment of the present disclosure, after obtaining the initial resource allocation information and initial deviation information corresponding to each of the M object identifiers, the target object identifier can be determined from the M object identifiers according to the initial deviation information corresponding to each of the M object identifiers. On this basis, the initial resource allocation information corresponding to the target object identifier can be adjusted to obtain the resource allocation information corresponding to each of the M object identifiers.

[0066] According to an embodiment of the present disclosure, after obtaining resource allocation information corresponding to each of the M object identifiers, the M object identifiers can be sorted according to the resource allocation information corresponding to each of the M object identifiers to obtain a sorting result. The sorting result may include the M object identifiers sorted according to the resource allocation information corresponding to each of the M object identifiers. On this basis, the N resources to be allocated in the resource allocation request can be allocated to the objects corresponding to each of the M object identifiers according to the sorting result.

[0067] According to the embodiments of the present disclosure, by determining the allocation weight corresponding to the object identifier according to the object identifier indicated by the resource allocation request, resources can be reasonably allocated according to the needs and priorities of different objects, and a flexible resource allocation strategy can be implemented. Since the resource allocation information is obtained by adjusting the initial resource allocation information according to the initial deviation information, the initial resource allocation information and the initial deviation information are determined according to the number of resources to be allocated and the allocation weight, and more reasonable resource allocation information can be obtained. On this basis, by allocating the resources to be allocated to the object corresponding to the object identifier according to the resource allocation information corresponding to the object identifier, no manual intervention is required, and effective allocation and utilization of resources are achieved, at least partially overcoming the technical problems in the related art due to the low flexibility and adaptability of the customer relationship management system in lead allocation, and improving the efficiency and accuracy of resource allocation.

[0068] Reference below Figure 3 to Figure 8 , the resource allocation method 200 according to the embodiment of the present invention is further explained.

[0069] According to an embodiment of the present disclosure, the resource allocation request includes an object set identifier.

[0070] According to an embodiment of the present disclosure, operation S210 may include the following operations.

[0071] In response to receiving a resource allocation request, M object identifiers corresponding to the object set identifier and P object tag values ​​corresponding to each of the M object identifiers are determined, where P is a positive integer. Based on the P object tag values ​​corresponding to each of the M object identifiers, allocation weights corresponding to each of the M object identifiers are determined.

[0072] According to an embodiment of the present disclosure, after receiving a resource allocation request, at least one candidate object set identifier pre-stored in the data source may be matched according to the object set identifier in the resource allocation request, so as to determine the M object identifiers corresponding to the object set identifier. On this basis, for each object identifier in the M object identifiers, at least one candidate object identifier pre-stored in the data source may be matched according to the object identifier, so as to determine the P object tag values ​​corresponding to the object identifier.

[0073] According to an embodiment of the present disclosure, an object tag value can be used to characterize a specific numerical value corresponding to a portrait tag. The business table historical data can be obtained, and the business table historical data can be processed using a business data platform (Business Data Platform, BDP) to obtain an object tag value corresponding to the portrait tag. The portrait tag can be configured according to actual business needs and is not limited here. For example, the portrait tag may include at least one of the following: a lead conversion rate tag, a company age tag, a lead signing rate tag, a lead processing time tag, and a tag for the number of leads being followed up, etc.

[0074] Specifically, the object tag value corresponding to the lead conversion rate label can be determined based on the number of business opportunities created from the leads and the total number of leads. The object tag value corresponding to the company length label can be determined based on the number of months on the job. The object tag value corresponding to the lead signing rate label can be determined based on the number of business opportunities for which contracts have been signed and the number of business opportunities. The object tag value corresponding to the lead processing time label can be determined based on the closed-loop time, the start time of the pending conversion state, and the number of individual leads. The object tag value corresponding to the number of leads being followed up label can be determined based on the number of leads to be converted.

[0075] According to an embodiment of the present disclosure, an object identifier and an object tag value corresponding to the object identifier are determined by automatically responding to a resource allocation request, and then an allocation weight corresponding to each object identifier is calculated based on the object identifier and the object tag value, thereby achieving automated control over resource allocation. This allows resource allocation requests to be processed more efficiently, thereby improving the efficiency of resource allocation.

[0076] According to an embodiment of the present disclosure, determining the allocation weights corresponding to the M object identifiers respectively according to the P object tag values ​​corresponding to the M object identifiers respectively may include the following operations.

[0077] According to the P object tag values ​​corresponding to the M object identifiers, the object tag cumulative values ​​corresponding to each of the M object identifiers are determined. According to the object tag cumulative values ​​corresponding to each of the M object identifiers, the set tag cumulative value is determined. For each of the M object identifiers, according to the set tag cumulative value and the object tag cumulative value corresponding to the object identifier, a first ratio corresponding to the object identifier is determined. The first ratio corresponding to the object identifier is determined as the allocation weight.

[0078] According to an embodiment of the present disclosure, after obtaining P object label values ​​corresponding to each of the M object identifiers, for each of the M object identifiers, an object label cumulative value corresponding to the object identifier can be determined according to the P object label values ​​corresponding to the object identifier. The object label cumulative value can be determined as shown in the following formula (1).

[0079] W m =x1+x2+...+x t +...+x T (1)

[0080] Among them, W m Represents the cumulative value of the object label corresponding to the mth object identifier, x1, x2, ..., x t , …, x T Represents the object label value.

[0081] According to an embodiment of the present disclosure, after obtaining the object tag cumulative values ​​corresponding to each of the M object identifiers, the set tag cumulative value can be determined according to the object tag cumulative values ​​corresponding to each of the M object identifiers. The method for determining the set tag cumulative value can be shown in the following formula (2).

[0082] ∑W=(W1+W2+...+W m +...+W M ) (2)

[0083] Among them, ∑W represents the cumulative value of the set label, W1 represents the cumulative value of the object label corresponding to the first object identifier, W2 represents the cumulative value of the object label corresponding to the second object identifier, and W m Represents the cumulative value of the object label corresponding to the mth object identifier, W M Represents the accumulated value of the object label corresponding to the Mth object identifier.

[0084] According to an embodiment of the present disclosure, after obtaining the set tag cumulative value, a first ratio corresponding to the object identifier can be determined according to the set tag cumulative value and the object tag cumulative value corresponding to the object identifier, and the first ratio corresponding to the object identifier is determined as the allocation weight. The allocation weight can be determined as shown in the following formula (3).

[0085] wr=W m / ∑W (3)

[0086] Among them, wr represents the allocation weight, W m represents the cumulative value of the object label corresponding to the mth object identifier, and ∑W represents the cumulative value of the set label.

[0087] According to an embodiment of the present disclosure, the object tag cumulative value corresponding to the object identifier is determined according to the object tag value corresponding to the object identifier, so that the object tag cumulative value can be used to reflect the properties and characteristics of the object. The set tag cumulative value is determined according to the object tag cumulative value corresponding to the object identifier, so that the set tag cumulative value can be used to reflect the properties and characteristics of the entire object set. On this basis, the first ratio corresponding to the object identifier is determined according to the set tag cumulative value and the object tag cumulative value corresponding to the object identifier, and the first ratio corresponding to the object identifier is determined as the allocation weight, thereby achieving a reasonable determination of the allocation weight, which is conducive to the subsequent flexible allocation of resources according to the allocation weight corresponding to the object identifier.

[0088] Figure 3 An example schematic diagram of a process of determining allocation weights corresponding to each of the M object identifiers according to the M object identifiers indicated by the resource allocation request according to an embodiment of the present disclosure is schematically shown.

[0089] like Figure 3 As shown, in 300, resource allocation request 301 includes object set identifier 301_1. In response to receiving resource allocation request 301, M object identifiers 302 corresponding to object set identifier 301_1 and P object tag values ​​303 corresponding to each of the M object identifiers 302 may be determined.

[0090] According to the P object tag values ​​303 corresponding to the M object identifiers 302, the object tag cumulative value 304 corresponding to each of the M object identifiers 302 is determined. On this basis, according to the object tag cumulative value 304 corresponding to each of the M object identifiers 302, the set tag cumulative value 305 can be determined.

[0091] For each object identifier 302 among the M object identifiers 302, a first ratio 306 corresponding to the object identifier 302 is determined based on the set label cumulative value 305 and the object label cumulative value 304 corresponding to the object identifier 302, and the first ratio 306 corresponding to the object identifier 302 can be determined as the allocation weight 307.

[0092] According to an embodiment of the present disclosure, the initial resource allocation information includes a predicted initial resource allocation value and an actual initial resource allocation value, and the initial deviation information includes a current initial deviation value and a cumulative initial deviation value.

[0093] According to an embodiment of the present disclosure, operation S220 may include the following operations.

[0094] For each of the M object identifiers, determine the historical cumulative initial deviation value corresponding to the object identifier from the data source. Determine the predicted initial resource allocation value and the actual initial resource allocation value corresponding to the object identifier based on the number of resources to be allocated, the allocation weight, and the historical cumulative initial deviation value. Determine the current initial deviation value and the cumulative initial deviation value corresponding to the object identifier based on the historical cumulative initial deviation value, the predicted initial resource allocation value, and the actual initial resource allocation value.

[0095] According to an embodiment of the present disclosure, the predicted initial resource allocation value may refer to a value obtained by directly performing mathematical calculations on the number of resources to be allocated, the allocation weight, and the historical accumulated initial deviation value, and the predicted initial resource allocation value may include decimals. The actual initial resource allocation value may refer to a value determined based on the predicted initial resource allocation value, for example, the actual initial resource allocation value may be obtained by rounding the predicted initial resource allocation value.

[0096] According to an embodiment of the present disclosure, the current initial deviation value may refer to a deviation value corresponding to the current resource allocation operation. For example, the current initial deviation value may be determined based on the predicted initial resource allocation value and the actual initial resource allocation value. The cumulative initial deviation value may refer to a value obtained by accumulating the deviation values ​​corresponding to each resource allocation operation. For example, the cumulative initial deviation value may be determined based on the historical cumulative initial deviation value and the current initial deviation value.

[0097] According to the embodiments of the present disclosure, since the determination of the predicted initial resource allocation value and the actual initial resource allocation value takes into account the number of resources to be allocated, the allocation weight and the historical accumulated initial deviation value, the deviation of the object in the past allocation process can be used as a reference to achieve more accurate resource allocation. On this basis, since the determination of the current initial deviation value and the accumulated initial deviation value takes into account the historical accumulated initial deviation value, the predicted initial resource allocation value and the actual initial resource allocation value, the current initial deviation value can reflect the deviation in the current allocation process, and the accumulated initial deviation value can reflect the sum of historical deviations. The deviation changes in the allocation process can be monitored and adjusted, further improving the accuracy and efficiency of resource allocation.

[0098] According to an embodiment of the present disclosure, determining a predicted initial resource allocation value and an actual initial resource allocation value corresponding to an object identifier according to the number of resources to be allocated, allocation weights, and historical accumulated initial deviation values ​​may include the following operations.

[0099] Determine a first product value according to the number of resources to be allocated and the allocation weight. Determine a first difference value according to the historical accumulated initial deviation value and the first product value. Determine a predicted initial resource allocation value corresponding to the object identifier according to the first difference value. Determine an actual initial resource allocation value corresponding to the object identifier according to the predicted initial resource allocation value.

[0100] According to the embodiment of the present disclosure, since the number of resources to be allocated in this batch has been determined, and the number of objects in the object set (i.e., the clue pool) has also been determined, the predicted initial resource allocation value can be calculated based on the allocation weight (i.e., weight ratio) corresponding to each object identifier. If there is an object corresponding to a certain object identifier that has never participated in the allocation, the initial value can be set to 0. The method for determining the predicted initial resource allocation value can be shown in the following formula (4).

[0101] iv=T×wr-cd (4)

[0102] Among them, iv represents the predicted initial resource allocation value, T represents the number of resources to be allocated, wr represents the allocation weight, and cd represents the historical accumulated initial deviation value.

[0103] According to an embodiment of the present disclosure, the predicted initial resource allocation value may be rounded to obtain an actual initial resource allocation value. The actual initial resource allocation value may be determined as shown in the following formula (5).

[0104] av=around[iv] (5)

[0105] Among them, av represents the actual initial resource allocation value, iv represents the predicted initial resource allocation value, and around[] represents an integer.

[0106] According to an embodiment of the present disclosure, determining the current initial deviation value and the accumulated initial deviation value corresponding to the object identifier according to the historical accumulated initial deviation value, the predicted initial resource allocation value and the actual initial resource allocation value may include the following operations.

[0107] Determine the second difference value based on the predicted initial resource allocation value and the actual initial resource allocation value. Determine the current initial deviation value corresponding to the object identifier based on the second difference value. Determine the cumulative initial deviation value corresponding to the object identifier based on the current initial deviation value and the historical cumulative initial deviation value.

[0108] According to an embodiment of the present disclosure, the method for determining the initial deviation value may be as shown in the following formula (6).

[0109] sd=iv-av (6)

[0110] Among them, sd represents the initial deviation value at that time, iv represents the predicted initial resource allocation value, and av represents the actual initial resource allocation value.

[0111] According to an embodiment of the present disclosure, the cumulative initial deviation value may be determined as shown in the following formula (7).

[0112] cd′=cd+sd (7)

[0113] Among them, cd′ represents the cumulative initial deviation value, cd represents the historical cumulative initial deviation value, and sd represents the current initial deviation value.

[0114] According to the embodiments of the present disclosure, since the predicted initial resource allocation value (i.e., iv) has a deviation, the actual initial resource allocation value (i.e., av), the initial deviation value (i.e., sd), and the cumulative initial deviation value (i.e., cd′) all have deviations. The above deviations are prone to the following situations: first, the total number of resources to be allocated in this batch is equal to the sum of the resources already claimed by all objects in the object set; second, the total number of resources to be allocated in this batch is greater than the sum of the resources already claimed by all objects, which means that there are resources that have not been claimed; third, the total number of resources to be allocated in this batch is less than the sum of the resources already claimed by all objects, which means that the same resource is claimed by multiple objects. In view of the above situation, the initial resource allocation information corresponding to each of the M object identifiers can be adjusted according to the initial deviation information corresponding to each of the M object identifiers to obtain the resource allocation information corresponding to each of the M object identifiers.

[0115] According to the embodiments of the present disclosure, it is possible to effectively calculate and adjust the deviation blocks in the resource allocation process, provide accurate predicted initial resource allocation values ​​and actual initial resource allocation values, and monitor and manage the changes and accumulation of deviations, thereby improving the accuracy and efficiency of resource allocation.

[0116] Figure 4 An example schematic diagram of a process of determining initial resource allocation information and initial deviation information corresponding to each of M object identifiers according to the number of resources to be allocated and the allocation weights corresponding to each of the M object identifiers according to an embodiment of the present disclosure is schematically shown.

[0117] like Figure 4 As shown, in 400, for each object identifier 401 in the M object identifiers 401, an allocation weight 402 corresponding to the object identifier can be determined, and a historical accumulated initial deviation value 403 corresponding to the object identifier 401 can be determined from a data source. A first product value 405 is determined based on the number of resources to be allocated 404 and the allocation weight 402. A first difference value 406 is determined based on the historical accumulated initial deviation value 403 and the first product value 405. On this basis, a predicted initial resource allocation value 407 corresponding to the object identifier 401 can be determined based on the first difference value 406. Based on the predicted initial resource allocation value 407, an actual initial resource allocation value 408 corresponding to the object identifier 401 is determined.

[0118] Further, the second difference 409 can be determined according to the predicted initial resource allocation value 407 and the actual initial resource allocation value 408. On this basis, the current initial deviation value 410 corresponding to the object identifier 401 can be determined according to the second difference 409. The accumulated initial deviation value 411 corresponding to the object identifier 401 is determined according to the current initial deviation value 410 and the historical accumulated initial deviation value 403.

[0119] According to an embodiment of the present disclosure, the initial resource allocation information includes an actual initial resource allocation value, and the initial deviation information includes a cumulative initial deviation value.

[0120] According to an embodiment of the present disclosure, operation S230 may include the following operations.

[0121] The actual resource allocation total value is determined according to the M actual initial resource allocation values. When the actual resource allocation total value and the number of resources to be allocated do not meet a predetermined condition, the actual initial resource allocation value is adjusted to obtain the actual resource allocation value.

[0122] According to the embodiments of the present disclosure, the predetermined condition can be configured according to actual business requirements and is not limited here. For example, the predetermined condition can be that the total value of actual resource allocation is equal to the number of resources to be allocated. In this case, the predetermined condition can be shown in the following formula (8).

[0123] T = ∑av? (8)

[0124] Among them, T represents the number of resources to be allocated, and ∑av represents the total value of actual resource allocation.

[0125] According to an embodiment of the present disclosure, when the actual total resource allocation value and the number of resources to be allocated meet the predetermined conditions, the accumulated initial deviation value can be directly cached, the resource allocation process can be entered, and the resources can be allocated according to the actual initial resource allocation value. Alternatively, when the actual total resource allocation value and the number of resources to be allocated do not meet the predetermined conditions, the resource allocation information and deviation information adjustment process can be entered until the actual total resource allocation value and the number of resources to be allocated meet the predetermined conditions. In this case, the actual initial resource allocation value and the accumulated initial deviation value corresponding to each object identifier have been determined.

[0126] Figure 5 The diagram schematically shows an example process of adjusting the initial resource allocation information corresponding to each of the M object identifiers according to the initial deviation information corresponding to each of the M object identifiers to obtain the resource allocation information corresponding to each of the M object identifiers according to an embodiment of the present disclosure.

[0127] like Figure 5As shown, in 500, initial resource allocation information 501 includes actual initial resource allocation value 501_1. According to M actual initial resource allocation values ​​501_1, an actual resource allocation total value 502 may be determined. After the actual resource allocation total value 502 is obtained, operation S510 may be performed.

[0128] In operation S510, it is determined whether the actual resource allocation total value and the number of resources to be allocated meet a predetermined condition. If so, the actual initial resource allocation value 501_1 can be directly determined as the actual resource allocation value 503. If not, the actual initial resource allocation value 501_1 can be adjusted to obtain the actual resource allocation value 503.

[0129] According to an embodiment of the present disclosure, adjusting the actual initial resource allocation value to obtain the actual resource allocation value may include the following operations.

[0130] According to the accumulated initial deviation values ​​corresponding to the M object identifiers, the target object identifier is determined from the M object identifiers. The actual initial resource allocation value corresponding to the target object identifier is adjusted to obtain the actual resource allocation value corresponding to the target object identifier.

[0131] According to the embodiments of the present disclosure, the size relationship between the total value of actual resource allocation and the number of resources to be allocated can be determined. For example, in the case where the total value of actual resource allocation is greater than the number of resources to be allocated, the target object identifier corresponding to the minimum cumulative initial deviation value can be determined based on the cumulative initial deviation values ​​corresponding to each of the M object identifiers. According to the first predetermined value, the actual initial resource allocation value corresponding to the target object identifier is adjusted to obtain the actual resource allocation value corresponding to the target object. For example, the first predetermined value can be set to "+1".

[0132] According to an embodiment of the present disclosure, alternatively, when the total actual resource allocation value is less than the number of resources to be allocated, the target object identifier corresponding to the maximum cumulative initial deviation value can be determined according to the cumulative initial deviation values ​​corresponding to each of the M object identifiers. According to a second predetermined value, the actual initial resource allocation value corresponding to the target object identifier is adjusted to obtain the actual resource allocation value corresponding to the target object. For example, the second predetermined value can be set to "-1".

[0133] According to an embodiment of the present disclosure, by determining the total actual resource allocation value based on the actual initial resource allocation value, and comparing the accumulated initial deviation value to determine the target object identifier that needs to be adjusted, and then adjusting its actual initial resource allocation value, it can be ensured that the total actual resource allocation value and the number of resources to be allocated meet predetermined conditions, thereby achieving adaptive adjustment of the actual initial resource allocation value, thereby improving the accuracy and flexibility of resource allocation.

[0134] According to an embodiment of the present disclosure, the resource allocation method 200 may further include the following operations.

[0135] The accumulated initial deviation value is adjusted according to the actual resource allocation value corresponding to the target object identifier to obtain the accumulated deviation value.

[0136] According to an embodiment of the present disclosure, after obtaining the adjusted actual resource allocation value, the accumulated initial deviation value may be adjusted, that is, the accumulated initial deviation value may be recalculated to obtain the adjusted accumulated deviation value.

[0137] Figure 6 An example schematic diagram of a process for obtaining an actual resource allocation value and an accumulated deviation value according to an embodiment of the present disclosure is schematically shown.

[0138] like Figure 6 As shown, in 600, after obtaining the actual resource allocation total value 601, operation S610 may be performed. In operation S610, it is determined whether the actual resource allocation total value is less than the number of resources to be allocated.

[0139] If not, the first target object identifier 602 can be determined from the M object identifiers according to the accumulated initial deviation values ​​corresponding to each of the M object identifiers. The first actual initial resource allocation value 603 corresponding to the first target object identifier 602 is adjusted according to the first predetermined value 604 to obtain a first actual resource allocation value 605 corresponding to the first target object identifier 602. On this basis, the first accumulated initial deviation value can be adjusted 606 according to the first actual resource allocation value 605 corresponding to the first target object identifier 602 to obtain a first accumulated deviation value 607.

[0140] If so, the second target object identifier 608 can be determined from the M object identifiers according to the accumulated initial deviation values ​​corresponding to each of the M object identifiers. The second actual initial resource allocation value 609 corresponding to the second target object identifier 608 is adjusted according to the second predetermined value 610 to obtain a second actual resource allocation value 611 corresponding to the second target object identifier 608. On this basis, the second accumulated initial deviation value can be adjusted 612 according to the second actual resource allocation value 611 corresponding to the second target object identifier 608 to obtain a second accumulated deviation value 613.

[0141] According to an embodiment of the present disclosure, the resource allocation information includes actual resource allocation values.

[0142] According to an embodiment of the present disclosure, operation S240 may include the following operations.

[0143] According to the actual resource allocation values ​​corresponding to the M object identifiers, the M object identifiers are sorted to obtain a resource allocation sequence. According to the resource allocation sequence, the N resources to be allocated are sequentially allocated to the objects corresponding to the M object identifiers.

[0144] According to an embodiment of the present disclosure, the M object identifiers can be sorted in ascending order according to the actual resource allocation values ​​corresponding to each of the M object identifiers to obtain a resource allocation sequence, thereby ensuring that objects with a higher allocation weight can receive resources as soon as possible. The N resources to be allocated are dequeued and allocated one by one using a task queue. On this basis, the N resources to be allocated in the task queue can be allocated in sequence to the objects corresponding to each of the M object identifiers in the resource allocation sequence according to the resource allocation sequence and the task queue.

[0145] According to an embodiment of the present disclosure, for each of the M object identifiers, when the actual resource allocation value corresponding to the object identifier is less than the number of resources already claimed, the next round of resource allocation and resource claiming operations may be performed. Alternatively, when the actual resource allocation value corresponding to the object identifier is equal to the number of resources already claimed, the object corresponding to the object identifier does not enter the resource allocation sequence.

[0146] According to an embodiment of the present disclosure, a resource allocation sequence is determined by sorting based on actual resource allocation values ​​corresponding to object identifiers, and resources to be allocated are allocated to objects in an orderly manner according to the resource allocation sequence, thereby achieving reasonable sorting and orderly allocation of resource allocation, thereby improving resource utilization efficiency and fairness.

[0147] Figure 7 An example schematic diagram of a process for obtaining an actual resource allocation value and an accumulated deviation value according to an embodiment of the present disclosure is schematically shown.

[0148] like Figure 7 As shown, in 700, resource allocation information 701 may include actual resource allocation value 701_1. The M object identifiers may be sorted according to the actual resource allocation values ​​701_1 corresponding to the M object identifiers, to obtain a resource allocation sequence 702.

[0149] On this basis, the mth object identifier 703 can be determined in sequence in the resource allocation sequence 702, the nth resource to be allocated 705 can be determined in sequence in the resource queue 704, and the nth resource to be allocated 705 can be allocated to the object corresponding to the mth object identifier 703.

[0150] After obtaining the nth resource to be allocated 705, operation S710 may be performed. In operation S710, it is determined whether the total value of actual resource allocation is less than the number of allocated resources. If yes, the resource allocation process may continue to be performed. If no, the resource allocation process may be terminated.

[0151] Figure 8 An example schematic diagram of a resource allocation process according to an embodiment of the present disclosure is schematically shown.

[0152] like Figure 8 As shown, in 800, in response to receiving a resource allocation request 801, the object label value corresponding to each of the M object identifiers 802 can be obtained from the object portrait database 804 according to the M object identifiers 802 indicated by the resource allocation request 801, and the allocation weight 805 corresponding to each of the M object identifiers 802 can be determined.

[0153] After obtaining the allocation weight 805, the initial resource allocation information 806 and the initial deviation information 807 corresponding to each of the M object identifiers 802 can be determined according to the number of resources to be allocated and the allocation weight 805 corresponding to each of the M object identifiers 802. According to the initial deviation information 807 corresponding to each of the M object identifiers 802, the initial resource allocation information 806 corresponding to each of the M object identifiers 802 is adjusted to obtain the resource allocation information 808 corresponding to each of the M object identifiers 802. Further, the adjusted deviation information 809 can be obtained, and the deviation information 809 is cached into the cumulative deviation storage repository 810.

[0154] After obtaining the resource allocation information 808 , the N resources to be allocated 803 in the resource allocation request 801 may be allocated to the objects corresponding to the M object identifiers 802 respectively according to the resource allocation information 808 corresponding to the M object identifiers 802 respectively.

[0155] According to the embodiments of the present disclosure, by utilizing data to process sales portrait labels, label weighting and introducing cumulative deviation value technology, the deviation technology can be fine-tuned in each allocation execution process, which can ensure that resources can be flexibly adjusted and allocated according to business requirements, thereby improving the accuracy of accurately allocating leads to people, thereby increasing the probability of converting leads into business opportunities.

[0156] The above are only exemplary embodiments, but are not limited thereto, and may also include other resource allocation methods known in the art, as long as the efficiency and accuracy of resource allocation can be improved.

[0157] Fig. 9 The block diagram of a resource allocation device according to an embodiment of the present disclosure is schematically shown.

[0158] like Fig. 9As shown, the resource allocation apparatus 900 may include a first determination module 910 , a second determination module 920 , a first adjustment module 930 and an allocation module 940 .

[0159] The first determination module 910 is used to determine the allocation weights corresponding to the M object identifiers respectively in response to receiving a resource allocation request, according to the M object identifiers indicated in the resource allocation request, wherein the resource allocation request includes N resources to be allocated, and M and N are both integers greater than 1.

[0160] The second determining module 920 is used to determine the initial resource allocation information and initial deviation information corresponding to each of the M object identifiers according to the number of resources to be allocated and the allocation weights corresponding to each of the M object identifiers.

[0161] The first adjustment module 930 is used to adjust the initial resource allocation information corresponding to each of the M object identifiers according to the initial deviation information corresponding to each of the M object identifiers, so as to obtain the resource allocation information corresponding to each of the M object identifiers.

[0162] The allocation module 940 is used to allocate N resources to be allocated to objects corresponding to the M object identifiers respectively according to the resource allocation information corresponding to the M object identifiers respectively.

[0163] According to an embodiment of the present disclosure, the resource allocation request includes an object set identifier.

[0164] According to an embodiment of the present disclosure, the first determining module 910 may include a first determining unit and a second determining unit.

[0165] The first determining unit is configured to determine, in response to receiving a resource allocation request, M object identifiers corresponding to the object set identifier and P object tag values ​​corresponding to each of the M object identifiers, wherein P is a positive integer.

[0166] The second determining unit is used to determine the allocation weights corresponding to the M object identifiers respectively according to the P object label values ​​corresponding to the M object identifiers respectively.

[0167] According to an embodiment of the present disclosure, the second determining unit may include a first determining subunit, a second determining subunit, a third determining subunit, and a fourth determining subunit.

[0168] The first determining subunit is used to determine the object label accumulation value corresponding to each of the M object identifiers according to the P object label values ​​corresponding to the M object identifiers.

[0169] The second determining subunit is used to determine the set label cumulative value according to the object label cumulative values ​​corresponding to each of the M object identifiers.

[0170] The third determining subunit is used to determine, for each object identifier among the M object identifiers, a first ratio corresponding to the object identifier according to the accumulated value of the set label and the accumulated value of the object label corresponding to the object identifier.

[0171] The fourth determining subunit is used to determine the first ratio corresponding to the object identifier as the allocation weight.

[0172] According to an embodiment of the present disclosure, the initial resource allocation information includes a predicted initial resource allocation value and an actual initial resource allocation value, and the initial deviation information includes a current initial deviation value and a cumulative initial deviation value.

[0173] According to an embodiment of the present disclosure, the second determining module 920 may include a third determining unit, a fourth determining unit, and a fifth determining unit.

[0174] The third determining unit is used to determine, for each object identifier among the M object identifiers, a historical accumulated initial deviation value corresponding to the object identifier from the data source.

[0175] The fourth determining unit is used to determine the predicted initial resource allocation value and the actual initial resource allocation value corresponding to the object identifier according to the number of resources to be allocated, the allocation weight and the historical accumulated initial deviation value.

[0176] The fifth determining unit is used to determine the current initial deviation value and the accumulated initial deviation value corresponding to the object identifier according to the historical accumulated initial deviation value, the predicted initial resource allocation value and the actual initial resource allocation value.

[0177] According to an embodiment of the present disclosure, the fourth determining unit may include a fifth determining subunit, a sixth determining subunit, a seventh determining subunit, and an eighth determining subunit.

[0178] The fifth determining subunit is used to determine a first product value according to the quantity of resources to be allocated and the allocation weight.

[0179] The sixth determining subunit is used to determine the first difference value according to the historical accumulated initial deviation value and the first product value.

[0180] The seventh determining subunit is configured to determine a predicted initial resource allocation value corresponding to the object identifier according to the first difference.

[0181] The eighth determining subunit is used to determine the actual initial resource allocation value corresponding to the object identifier according to the predicted initial resource allocation value.

[0182] According to an embodiment of the present disclosure, the fifth determining unit may include a ninth determining subunit, a tenth determining subunit, and an eleventh determining subunit.

[0183] The ninth determining subunit is configured to determine a second difference value according to the predicted initial resource allocation value and the actual initial resource allocation value.

[0184] The tenth determining subunit is used to determine the current initial deviation value corresponding to the object identifier according to the second difference.

[0185] The eleventh determination subunit is used to determine the cumulative initial deviation value corresponding to the object identifier according to the current initial deviation value and the historical cumulative initial deviation value.

[0186] According to an embodiment of the present disclosure, the initial resource allocation information includes an actual initial resource allocation value, and the initial deviation information includes a cumulative initial deviation value.

[0187] According to an embodiment of the present disclosure, the first adjustment module 930 may include a sixth determining unit and an adjusting unit.

[0188] The sixth determining unit is used to determine the total actual resource allocation value according to the M actual initial resource allocation values.

[0189] The adjustment unit is used to adjust the actual initial resource allocation value to obtain the actual resource allocation value when the actual resource allocation total value and the amount of resources to be allocated do not meet the predetermined conditions.

[0190] According to an embodiment of the present disclosure, the adjusting unit may include a twelfth determining subunit and an adjusting subunit.

[0191] The twelfth determining subunit is used to determine the target object identifier among the M object identifiers according to the accumulated initial deviation values ​​corresponding to each of the M object identifiers.

[0192] The adjustment subunit is used to adjust the actual initial resource allocation value corresponding to the target object identifier to obtain the actual resource allocation value corresponding to the target object identifier.

[0193] According to an embodiment of the present disclosure, the resource allocation apparatus 900 may further include a second adjustment module.

[0194] The second adjustment module is used to adjust the accumulated initial deviation value according to the actual resource allocation value corresponding to the target object identifier to obtain the accumulated deviation value.

[0195] According to an embodiment of the present disclosure, the resource allocation information includes actual resource allocation values.

[0196] According to an embodiment of the present disclosure, the allocation module 940 may include a sorting unit and an allocation unit.

[0197] The sorting unit is used to sort the M object identifiers according to the actual resource allocation values ​​corresponding to each of the M object identifiers to obtain a resource allocation sequence.

[0198] The allocation unit is used to allocate N resources to be allocated in sequence to the objects corresponding to the M object identifiers respectively according to the resource allocation sequence.

[0199] According to the embodiments of the present invention, any one or more of the modules, submodules, units, and subunits, or at least part of the functions of any one of them can be implemented in one module. According to the embodiments of the present invention, any one or more of the modules, submodules, units, and subunits can be split into multiple modules for implementation. According to the embodiments of the present invention, any one or more of the modules, submodules, units, and subunits can be at least partially implemented as hardware circuits, such as field programmable gate arrays (FPGAs), programmable logic arrays (PLAs), systems on chips, systems on substrates, systems on packages, application specific integrated circuits (ASICs), or can be implemented by hardware or firmware in any other reasonable way of integrating or packaging the circuit, or implemented in any one of the three implementation methods of software, hardware, and firmware, or in any appropriate combination of any of them. Alternatively, according to the embodiments of the present invention, one or more of the modules, submodules, units, and subunits can be at least partially implemented as computer program modules, and when the computer program modules are run, the corresponding functions can be performed.

[0200] For example, any multiple of the first determination module 910, the second determination module 920, the first adjustment module 930, and the allocation module 940 can be combined in one module / unit / subunit for implementation, or any one of the modules / units / subunits can be split into multiple modules / units / subunits. Alternatively, at least part of the functions of one or more of these modules / units / subunits can be combined with at least part of the functions of other modules / units / subunits and implemented in one module / unit / subunit. According to an embodiment of the present disclosure, at least one of the first determination module 910, the second determination module 920, the first adjustment module 930, and the allocation module 940 can be at least partially implemented as a hardware circuit, such as a field programmable gate array (FPGA), a programmable logic array (PLA), a system on a chip, a system on a substrate, a system on a package, an application specific integrated circuit (ASIC), or can be implemented by hardware or firmware such as any other reasonable way of integrating or packaging the circuit, or by any one of the three implementation methods of software, hardware, and firmware, or by a suitable combination of any of them. Alternatively, at least one of the first determination module 910 , the second determination module 920 , the first adjustment module 930 , and the allocation module 940 may be at least partially implemented as a computer program module, and when the computer program module is executed, a corresponding function may be performed.

[0201] It should be noted that the resource allocation device part in the embodiment of the present disclosure corresponds to the resource allocation method part in the embodiment of the present disclosure. The description of the resource allocation device part specifically refers to the resource allocation method part, which will not be repeated here.

[0202] Fig.10 A block diagram of an electronic device suitable for implementing a resource allocation method according to an embodiment of the present disclosure is schematically shown. Fig.10 The electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present disclosure.

[0203] like Fig.10 As shown, the computer electronic device 1000 according to the embodiment of the present disclosure includes a processor 1001, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 1002 or the program loaded from the storage part 1009 to the random access memory (RAM) 1003. The processor 1001 may include, for example, a general-purpose microprocessor (such as a CPU), an instruction set processor and / or a related chipset and / or a special-purpose microprocessor (for example, an application-specific integrated circuit (ASIC)), etc. The processor 1001 may also include an onboard memory for caching purposes. The processor 1001 may include a single processing unit or multiple processing units for performing different actions of the method flow according to the embodiment of the present disclosure.

[0204] In RAM 1003, various programs and data required for the operation of electronic device 1000 are stored. Processor 1001, ROM 1002 and RAM 1003 are connected to each other via bus 1004. Processor 1001 performs various operations of the method flow according to the embodiment of the present disclosure by executing the program in ROM 1002 and / or RAM 1003. It should be noted that the program can also be stored in one or more memories other than ROM 1002 and RAM 1003. Processor 1001 can also perform various operations of the method flow according to the embodiment of the present disclosure by executing the program stored in the one or more memories.

[0205] According to an embodiment of the present disclosure, the electronic device 1000 may further include an input / output (I / O) interface 1005, which is also connected to the bus 1004. The electronic device 1000 may further include one or more of the following components connected to the input / output (I / O) interface 1005: an input portion 1006 including a keyboard, a mouse, etc.; an output portion 1007 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage portion 1008 including a hard disk, etc.; and a communication portion 1009 including a network interface card such as a LAN card, a modem, etc. The communication portion 1009 performs communication processing via a network such as the Internet. A drive 1010 is also connected to the input / output (I / O) interface 1005 as needed. A removable medium 1011, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 1010 as needed, so that a computer program read therefrom is installed into the storage portion 1008 as needed.

[0206] According to an embodiment of the present disclosure, the method flow according to an embodiment of the present disclosure can be implemented as a computer software program. For example, an embodiment of the present disclosure includes a computer program product, which includes a computer program carried on a computer-readable storage medium, and the computer program contains a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through the communication part 1009, and / or installed from the removable medium 1011. When the computer program is executed by the processor 1001, the above-mentioned functions defined in the system of the embodiment of the present disclosure are executed. According to an embodiment of the present disclosure, the system, equipment, device, module, unit, etc. described above can be implemented by a computer program module.

[0207] The present disclosure also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments; or may exist independently without being assembled into the device / apparatus / system. The above computer-readable storage medium carries one or more programs, and when the above one or more programs are executed, the method according to the embodiment of the present disclosure is implemented.

[0208] According to an embodiment of the present disclosure, the computer-readable storage medium may be a non-volatile computer-readable storage medium. For example, it may include, but is not limited to: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in combination with an instruction execution system, apparatus, or device.

[0209] For example, according to an embodiment of the present disclosure, the computer-readable storage medium may include the ROM 1002 and / or the RAM 1003 described above and / or one or more memories other than the ROM 1002 and the RAM 1003 .

[0210] An embodiment of the present disclosure also includes a computer program product, which includes a computer program, and the computer program contains program code for executing the method provided by the embodiment of the present disclosure. When the computer program product runs on an electronic device, the program code is used to enable the electronic device to implement the resource allocation method provided by the embodiment of the present disclosure.

[0211] When the computer program is executed by the processor 1001, the above functions defined in the system / device of the embodiment of the present disclosure are executed. According to the embodiment of the present disclosure, the system, device, module, unit, etc. described above can be implemented by a computer program module.

[0212] In one embodiment, the computer program may rely on tangible storage media such as optical storage devices, magnetic storage devices, etc. In another embodiment, the computer program may also be transmitted and distributed in the form of signals on a network medium, and downloaded and installed through the communication part 1009, and / or installed from the removable medium 1011. The program code contained in the computer program may be transmitted using any appropriate network medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0213] According to an embodiment of the present disclosure, the program code for executing the computer program provided by the embodiment of the present disclosure can be written in any combination of one or more programming languages. Specifically, these computing programs can be implemented using high-level process and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages ​​include, but are not limited to, Java, C++, python, "C" language or similar programming languages. The program code can be executed entirely on the user computing device, partially on the user device, partially on the remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device can be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computing device (for example, using an Internet service provider to connect through the Internet).

[0214] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each box in the flowchart or block diagram may represent a module, a program segment, or a part of a code, and the above-mentioned module, program segment, or a part of the code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box may also occur in an order different from that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, and the combination of boxes in the block diagram or flowchart, can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions. It can be understood by those skilled in the art that the features recorded in the various embodiments and / or claims of the present disclosure can be combined and / or combined in a variety of ways, even if such a combination or combination is not explicitly recorded in the present disclosure. In particular, without departing from the spirit and teaching of the present disclosure, the features described in the various embodiments and / or claims of the present disclosure may be combined and / or combined in a variety of ways. All of these combinations and / or combinations fall within the scope of the present disclosure.

[0215] The embodiments of the present disclosure are described above. However, these embodiments are only for illustrative purposes and are not intended to limit the scope of the present disclosure. Although the embodiments are described above separately, this does not mean that the measures in the various embodiments cannot be used in combination to advantage. The scope of the present disclosure is defined by the attached claims and their equivalents. Without departing from the scope of the present disclosure, those skilled in the art may make a variety of substitutions and modifications, which should all fall within the scope of the present disclosure.

Claims

1. A resource allocation method, comprising: In response to receiving a resource allocation request, determining allocation weights corresponding to each of the M object identifiers according to the M object identifiers indicated by the resource allocation request, wherein the resource allocation request includes N resources to be allocated, and M and N are both integers greater than 1; Determine initial resource allocation information and initial deviation information corresponding to each of the M object identifiers according to the number of resources to be allocated and the allocation weights corresponding to each of the M object identifiers; Adjusting the initial resource allocation information corresponding to each of the M object identifiers according to the initial deviation information corresponding to each of the M object identifiers to obtain the resource allocation information corresponding to each of the M object identifiers; and According to the resource allocation information corresponding to each of the M object identifiers, the N resources to be allocated are allocated to the objects corresponding to each of the M object identifiers.

2. The method according to claim 1, wherein: The resource allocation request includes an object set identifier; In response to receiving the resource allocation request, determining, according to the M object identifiers indicated by the resource allocation request, an allocation weight corresponding to each of the M object identifiers comprises: In response to receiving the resource allocation request, determining the M object identifiers corresponding to the object set identifier and P object tag values ​​corresponding to each of the M object identifiers, where P is a positive integer; and According to the P object label values ​​corresponding to the M object identifiers, the allocation weights corresponding to the M object identifiers are determined.

3. The method according to claim 2, wherein: The determining, according to the P object label values ​​corresponding to the M object identifiers, respectively, the allocation weights corresponding to the M object identifiers respectively comprises: Determine, according to the P object label values ​​corresponding to the M object identifiers, an object label cumulative value corresponding to each of the M object identifiers; Determine a set label cumulative value according to the object label cumulative values ​​corresponding to each of the M object identifiers; For each of the M object identifiers, Determining a first ratio corresponding to the object identifier according to the set tag cumulative value and the object tag cumulative value corresponding to the object identifier; and A first ratio corresponding to the object identifier is determined as the allocation weight.

4. The method according to claim 1, wherein: The initial resource allocation information includes a predicted initial resource allocation value and an actual initial resource allocation value, and the initial deviation information includes a current initial deviation value and a cumulative initial deviation value; The determining, according to the number of resources to be allocated and the allocation weights corresponding to the M object identifiers, the initial resource allocation information and the initial deviation information corresponding to each of the M object identifiers comprises: For each of the M object identifiers, Determining a historical accumulated initial deviation value corresponding to the object identifier from a data source; Determining the predicted initial resource allocation value and the actual initial resource allocation value corresponding to the object identifier according to the number of resources to be allocated, the allocation weight and the historical accumulated initial deviation value; and The current initial deviation value and the accumulated initial deviation value corresponding to the object identifier are determined according to the historical accumulated initial deviation value, the predicted initial resource allocation value and the actual initial resource allocation value.

5. The method according to claim 4, wherein: The determining, according to the number of resources to be allocated, the allocation weight and the historical accumulated initial deviation value, the predicted initial resource allocation value and the actual initial resource allocation value corresponding to the object identifier comprises: Determining a first product value according to the number of resources to be allocated and the allocation weight; Determining a first difference value according to the historical accumulated initial deviation value and the first product value; determining the predicted initial resource allocation value corresponding to the object identifier according to the first difference; and The actual initial resource allocation value corresponding to the object identifier is determined according to the predicted initial resource allocation value.

6. The method according to claim 4, wherein: The determining, according to the historical accumulated initial deviation value, the predicted initial resource allocation value, and the actual initial resource allocation value, the current initial deviation value and the accumulated initial deviation value corresponding to the object identifier comprises: Determining a second difference value according to the predicted initial resource allocation value and the actual initial resource allocation value; determining the current initial deviation value corresponding to the object identifier according to the second difference; and The accumulated initial deviation value corresponding to the object identifier is determined according to the current initial deviation value and the historical accumulated initial deviation value.

7. The method according to any one of claims 1 to 6, wherein: The initial resource allocation information includes an actual initial resource allocation value, and the initial deviation information includes a cumulative initial deviation value; The adjusting the initial resource allocation information corresponding to each of the M object identifiers according to the initial deviation information corresponding to each of the M object identifiers to obtain the resource allocation information corresponding to each of the M object identifiers includes: Determining a total actual resource allocation value according to the M actual initial resource allocation values; and When the actual resource allocation total value and the number of resources to be allocated do not meet a predetermined condition, the actual initial resource allocation value is adjusted to obtain an actual resource allocation value.

8. The method according to claim 7, wherein: The adjusting the actual initial resource allocation value to obtain the actual resource allocation value comprises: Determining a target object identifier among the M object identifiers according to the accumulated initial deviation values ​​corresponding to each of the M object identifiers; and The actual initial resource allocation value corresponding to the target object identifier is adjusted to obtain an actual resource allocation value corresponding to the target object identifier.

9. The method according to claim 7, further comprising, after adjusting the actual initial resource allocation value corresponding to the target object identifier to obtain the actual resource allocation value corresponding to the target object identifier: The accumulated initial deviation value is adjusted according to the actual resource allocation value corresponding to the target object identifier to obtain an accumulated deviation value.

10. The method according to any one of claims 1 to 6, wherein: The resource allocation information includes actual resource allocation values; The allocating the N resources to be allocated to the objects corresponding to the M object identifiers respectively according to the resource allocation information corresponding to the M object identifiers respectively comprises: Sorting the M object identifiers according to actual resource allocation values ​​corresponding to the M object identifiers to obtain a resource allocation sequence; as well as According to the resource allocation sequence, the N resources to be allocated are allocated in sequence to the objects corresponding to the M object identifiers respectively.

11. A resource allocation device, comprising: A first determination module is configured to, in response to receiving a resource allocation request, determine allocation weights corresponding to the M object identifiers respectively according to the M object identifiers indicated by the resource allocation request, wherein the resource allocation request includes N resources to be allocated, and M and N are both integers greater than 1; A second determination module is used to determine initial resource allocation information and initial deviation information corresponding to each of the M object identifiers according to the number of resources to be allocated and the allocation weights corresponding to each of the M object identifiers; a first adjustment module, configured to adjust the initial resource allocation information corresponding to each of the M object identifiers according to the initial deviation information corresponding to each of the M object identifiers, so as to obtain the resource allocation information corresponding to each of the M object identifiers; and The allocation module is used to allocate the N resources to be allocated to the objects corresponding to the M object identifiers respectively according to the resource allocation information corresponding to the M object identifiers respectively.

12. An electronic device comprising: one or more processors; a memory for storing one or more instructions, Wherein, when the one or more instructions are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1 to 10.

13. A computer-readable storage medium having executable instructions stored thereon, wherein when the executable instructions are executed by a processor, the processor is enabled to implement the method according to any one of claims 1 to 10.

14. A computer program product, comprising computer executable instructions, which are used to implement the method of any one of claims 1 to 10 when executed.

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