Distribution method and device, electronic equipment, storage medium and program product

Abstract

The invention provides a distribution method and device, electronic equipment, a storage medium and a program product, and the method comprises the steps: obtaining a business record and a to-be-completed index of a first object in response to a distribution task; the to-be-completed index is determined according to the historical operation condition of the first object; determining a completed index of the first object according to an operation productivity result of the first object performing operation on a second object; according to the business record, the to-be-completed index and the completed index, determining an uncompleted index of the first object, and according to the uncompleted index, determining a first number of second objects needing to be allocated to the first object for operation; the first number of second objects are screened out from candidate second objects, the screened second objects are allocated to the first object, the candidate second objects are determined from a target database in advance according to the to-be-completed index, and the allocation efficiency and accuracy are improved.

Description

Technical Field

[0001] The present disclosure relates to the field of computer technology, and in particular to a distribution method, device, electronic device, storage medium and program product. Background Art

[0002] At present, for example, in the field of telemarketing, agents need to communicate with customers, and the allocation and management of customer lists are very important. In related technologies, the way to allocate customer lists to agents is usually to allocate them in batches according to static rules. However, this method is relatively limited, and agents and customers are diverse and changing. Static fixed allocation may not meet the needs of agents, reducing the accuracy of customer allocation. Summary of the invention

[0003] The present disclosure provides a distribution method, device, electronic device, storage medium and program product.

[0004] In a first aspect, the present disclosure provides an allocation method, the allocation method comprising:

[0005] In response to the assigned task, obtaining the business record and to-be-completed index of the first object; the to-be-completed index is determined according to the historical operation status of the first object;

[0006] Determining a completed indicator of the first object according to a result of the operation capacity of the first object operating on a second object, where the second object represents an object on which the first object needs to operate;

[0007] Determine the uncompleted indicator of the first object according to the business record, the to-be-completed indicator and the completed indicator, and determine the first quantity of the second objects to be assigned to perform operations on the first object according to the uncompleted indicator;

[0008] The first number of second objects are screened out from the candidate second objects, and the screened out second objects are assigned to the first object, wherein the candidate second objects are pre-determined from a target database according to the to-be-completed indicator, and the target database stores a plurality of second objects.

[0009] In a second aspect, the present disclosure provides an object allocation device, the object allocation device comprising:

[0010] An acquisition module, configured to acquire the business record and to-be-completed index of the first object in response to the assigned task; the to-be-completed index is determined according to the historical operation status of the first object;

[0011] A first determination module, configured to determine a completed indicator of the first object according to a result of an operation capacity of the first object operating on a second object, wherein the second object represents an object on which the first object needs to operate;

[0012] A second determination module is used to determine the uncompleted indicator of the first object according to the business record, the to-be-completed indicator and the completed indicator, and determine the first number of second objects that need to be assigned to perform operations on the first object according to the uncompleted indicator;

[0013] An allocation module is used to screen out the first number of second objects from candidate second objects and allocate the screened second objects to the first object, wherein the candidate second objects are pre-determined from a target database based on the to-be-completed indicators, and the target database stores a plurality of second objects.

[0014] In a third aspect, the present disclosure provides an electronic device comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores one or more computer programs executable by the at least one processor, and one or more of the computer programs are executed by the at least one processor so that the at least one processor can perform the above-mentioned allocation method.

[0015] In a fourth aspect, the present disclosure provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program implements the above-mentioned allocation method when executed by a processor.

[0016] In a fifth aspect, the present disclosure provides a computer program product, including a computer-readable code, or a non-volatile computer-readable storage medium carrying the computer-readable code. When the computer-readable code runs in a processor of an electronic device, the processor in the electronic device executes the above-mentioned allocation method.

[0017] The allocation method provided by the embodiment of the present disclosure can, in response to an allocation task, determine in real time a first number of second objects that need to be allocated to the first object for operation based on the business record, to-be-completed indicators and completed indicators of the first object, and then screen out a first number of second objects from the candidate second objects to allocate the screened second objects to the first object. In this way, intelligent scheduling and allocation for the second objects is achieved, the efficiency of allocation is improved, and the business record and indicator requirements of the first object can be dynamically responded to, the accuracy and rationality of allocation are improved, thereby also improving the operating efficiency and overall productivity of the first object for the second object.

[0018] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present disclosure, nor is it intended to limit the scope of the present disclosure. Other features of the present disclosure will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The accompanying drawings are used to provide a further understanding of the present disclosure and constitute a part of the specification. Together with the embodiments of the present disclosure, they are used to explain the present disclosure and do not constitute a limitation of the present disclosure. The above and other features and advantages will become more apparent to those skilled in the art by describing detailed example embodiments with reference to the accompanying drawings, in which:

[0020] Figure 1 An application scenario diagram provided for an embodiment of the present disclosure;

[0021] Figure 2 A flow chart of an allocation method provided in an embodiment of the present disclosure;

[0022] Figure 3 A flowchart of a reserved task in an embodiment of the present disclosure;

[0023] Figure 4 A flowchart of allocating tasks in an embodiment of the present disclosure;

[0024] Figure 5 A flowchart of dialing a task in an embodiment of the present disclosure;

[0025] Figure 6 A block diagram of a distribution device provided in an embodiment of the present disclosure;

[0026] Figure 7 A block diagram of an electronic device provided in an embodiment of the present disclosure. DETAILED DESCRIPTION

[0027] In order to enable those skilled in the art to better understand the technical solutions of the present disclosure, the exemplary embodiments of the present disclosure are described below in conjunction with the accompanying drawings, including various details of the embodiments of the present disclosure to facilitate understanding, which should be considered as merely exemplary. Therefore, those of ordinary skill in the art should recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of the present disclosure. Similarly, for the sake of clarity and conciseness, the description of well-known functions and structures is omitted in the following description.

[0028] In the absence of conflict, the various embodiments of the present disclosure and the various features therein may be combined with each other.

[0029] As used herein, the term "and / or" includes any and all combinations of one or more of the associated listed items.

[0030] The terms used herein are only used to describe specific embodiments and are not intended to limit the present disclosure. As used herein, the singular forms "a" and "the" are also intended to include plural forms, unless the context clearly indicates otherwise. It will also be understood that when the terms "including" and / or "made of" are used in this specification, the presence of the features, wholes, steps, operations, elements and / or components is specified, but the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or groups thereof is not excluded. "Connected" or "connected" and similar words are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect.

[0031] Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by those of ordinary skill in the art. It will also be understood that terms such as those defined in commonly used dictionaries should be interpreted as having a meaning consistent with their meaning in the context of the relevant art and the present disclosure, and will not be interpreted as having an idealized or overly formal meaning unless explicitly defined as such herein.

[0032] In the technical solution disclosed in this disclosure, the collection, storage, use, processing, transmission, provision and disclosure of user personal information involved are in compliance with the provisions of relevant laws and regulations and do not violate public order and good morals. The use of user data in this technical solution complies with relevant national laws and regulations (for example, the "Information Security Technology Personal Information Security Specification", etc.). For example: corresponding prescribed measures are taken for personal information access control; prescribed restrictions are imposed on the display of personal information; the purpose of using personal information does not exceed the scope of direct or reasonable association; when using personal information, clear identity orientation is eliminated to avoid precise positioning of specific individuals.

[0033] For example, in the field of telemarketing, agents need to communicate with customers, such as calling customers to achieve marketing goals. Therefore, the allocation and management of customer lists are very important. In related technologies, the way to allocate customer lists to agents is usually to allocate them in batches according to static rules. However, this method is relatively limited. Agents and customers are diverse and changeable. For example, the attendance time of agents changes dynamically. If static fixed allocation is used, it may not meet the needs of agents, reducing the accuracy and effectiveness of customer allocation and the resource utilization of customer lists, thereby affecting the effectiveness and efficiency of telemarketing.

[0034] Therefore, an allocation method is provided in an embodiment of the present disclosure. In response to an allocation task, the completed indicators of the first object are determined, and based on the business record, to-be-completed indicators and completed indicators of the first object, a first number of second objects that need to be allocated to the first object for operation are determined. The first number of second objects can then be allocated to the first object. In this way, it is possible to dynamically respond to changes in the business records of the first object, and dynamically allocate the second objects in real time in combination with the completed indicators, thereby improving the accuracy and efficiency of allocation, and improving the utilization rate of the second object, thereby improving the operating efficiency and operating capacity of the first object for the second object.

[0035] Figure 1 The application scenario diagram of the object allocation method and device provided by the embodiment of the present disclosure is schematically shown.

[0036] like Figure 1 As shown, the application scenario of the embodiment of the present disclosure may include a terminal device 101, a network 103 and a server 102. The network 103 is used to provide a medium for a communication link between the terminal device 101 and the server 102. The network 103 may include various connection types, such as wired, wireless communication links or optical fiber cables, etc.

[0037] The user can use the terminal device 101 to interact with the server 102 through the network 103 to receive or send messages, etc. Various communication client applications can be installed on the terminal device 101, such as shopping applications, web browser applications, search applications, instant messaging tools, email clients, social platform software, etc. (only as examples). In addition, in the embodiment of the present disclosure, the terminal device 101 may include multiple, for example, the first object and the second object correspond to different terminal devices 101 respectively, and communication is performed based on the corresponding terminal device 101.

[0038] The terminal device 101 may be any electronic device having a display screen and supporting web browsing, including but not limited to a smart phone, a tablet computer, a laptop computer, a desktop computer, and the like.

[0039] The server 102 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 terminal device 101. The background management server may analyze and process received data such as user requests, and feed back processing results (such as web pages, information, or data obtained or generated according to user requests) to the terminal device.

[0040] It should be noted that the allocation method and apparatus provided in the embodiment of the present disclosure can be executed by the server 102. Accordingly, the allocation method and apparatus provided in the embodiment of the present disclosure can be set in the server 102. The allocation method and apparatus provided in the embodiment of the present disclosure can also be executed by a server or server cluster that is different from the server 102 and can communicate with the terminal device 101 and / or the server 102. Accordingly, the allocation method and apparatus provided in the embodiment of the present disclosure can also be set in a server or server cluster that is different from the server 102 and can communicate with the terminal device 101 and / or the server 102.

[0041] 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 implementation requirements.

[0042] Figure 2 A flow chart of a distribution method provided by an embodiment of the present disclosure. Figure 2 , the method comprising:

[0043] S201: In response to assigning a task, obtaining a business record and to-be-completed indicators of a first object, where the to-be-completed indicators are determined based on historical operation conditions of the first object.

[0044] In the embodiment of the present disclosure, in the field of telemarketing, a business record may represent the attendance information of a first object, and the to-be-completed indicator may represent the capacity indicator that the first object needs to complete. In actual operation scenarios, attendance may be recorded by clocking in or signing in. After the first object clocks in or signs in, a business record may be generated and saved in an attendance database, and then the allocation of a second object may be dynamically adjusted according to attendance or absence. For example, in a telemarketing scenario, the first object may be an agent, and the second object may be a customer list. The customer list assigned to the agent may be dynamically adjusted, and the agent may make calls to the customers in the customer list to complete the required capacity indicator. The capacity indicator is not restricted, and different capacity indicators may be set based on different types of customer lists or business needs. For example, for a login-type customer list, the capacity indicator may be the number of customers converted into registered users.

[0045] Among them, the condition for triggering the allocation task, in one possible embodiment, may be receiving a business record of the first object, such as a message of the first object punching in or signing in successfully; in another possible embodiment, it may be according to a set cycle, etc., which is not limited in the embodiments of the present disclosure. The main purpose of the embodiments of the present disclosure is to dynamically allocate the second object during the entire operation process, such as during a working day.

[0046] S202: Determine a completed indicator of the first object according to the operation capacity result of the first object operating on the second object, where the second object represents the object on which the first object needs to operate.

[0047] For example, the type of the second object is a browsing customer, and the operation capacity results of the first object for the second object include conversion into registered customers and non-conversion into registered customers. The completed indicator of the first object can be obtained by counting the operation capacity results of the first object for the second object, that is, the completed indicator can be the actual number of converted registered customers, which is n.

[0048] S203: Determine the unfinished indicators of the first object according to the business records, the indicators to be completed and the indicators completed, and determine the first quantity of the second objects that need to be allocated to the first object for operation according to the unfinished indicators.

[0049] For example, the first object has signed in for attendance, and the to-be-completed indicator is the number of m registered customers converted, and the completed indicator is the actual number of n registered customers. The unfinished indicator is the number that needs to be converted, which is mn. It can be determined that the first number of second objects that need to be allocated to the first object is at least mn. In one possible embodiment, since dynamic allocation can also be performed during the operation in the embodiment of the present disclosure, it is preferable to determine the first number to be mn at this time, and then the first object performs operations on the mn second objects. The completed indicators can be counted in real time. If they are still not completed, dynamic allocation can be performed again to improve utilization.

[0050] For another example, in the actual operation of telemarketing scenarios, different types of customer groups can usually be divided into different special projects. A special project is usually dialed by agents of one or more groups. A group includes multiple agents. The completed indicators of multiple first objects can be used to determine the completed indicators of the group to which the first object belongs, and then the completed indicators of the special project required for the first object can be determined. Therefore, in the embodiment of the present disclosure, the to-be-completed indicators of the first object and the first quantity of the second object required to be allocated can also be dynamically adjusted based on the to-be-completed indicators of the special project and the to-be-completed indicators of the group to which the first object belongs, and the business records of the group to which the first object belongs.

[0051] S204: Screening out a first number of second objects from the candidate second objects, and assigning the screened second objects to the first object, wherein the candidate second objects are pre-determined from a target database according to the indicators to be completed, and the target database stores a plurality of second objects.

[0052] In the embodiment of the present disclosure, in order to further improve the rationality and accuracy of the allocation of the second object, the second objects can also be graded. The object level represents the importance of the second object, and the object level is positively correlated with the importance. It can be understood that the higher the object level, the better the second object. Therefore, when allocating the first object, the object level of the second object can be combined for allocation.

[0053] Specifically for screening out a first number of second objects from candidate second objects in step S204, a possible implementation method is provided, including: determining a third number of second objects to be screened corresponding to each object level according to a preset second proportional coefficient and the first number corresponding to each object level; and screening out the corresponding third number of second objects from the candidate second objects included in each object level.

[0054] For example, the object level includes high level, medium level and low level, and each object level corresponds to a plurality of candidate second objects reserved. The second proportional coefficient corresponding to the high level is 15%, the second proportional coefficient corresponding to the medium level is 35%, and the second proportional coefficient corresponding to the low level is 50%. The first number is 100, and the third numbers corresponding to the high level, medium level and low level are calculated to be 15, 35 and 50 respectively. Then, 15 second objects can be screened out from the plurality of candidate second objects reserved for the high level, 35 second objects can be screened out from the plurality of candidate second objects reserved for the low level, and 50 second objects can be screened out from the plurality of candidate second objects reserved for the low level. When screening the second objects from each object level, they can be randomly selected, or they can be selected in order from high to low after sorting according to the scores of the object levels, so that a total of 100 screened out second objects are allocated to the first object.

[0055] Furthermore, in the embodiment of the present disclosure, after the allocation task is triggered, it is also possible to automatically determine whether the current remaining number of the reserved candidate second objects is sufficient for allocation or whether the to-be-completed indicator can be completed, and then dynamically adjust the reserved number of the candidate second objects. Specifically, the present disclosure provides possible implementation methods, including:

[0056] 1) Get the current remaining number of candidate second objects.

[0057] 2) When the current remaining quantity does not meet the preset requirement, determine the second quantity of the second objects that the first object needs to allocate to perform the operation according to the completed index and the to-be-completed index of the first object.

[0058] The preset requirement may be, for example, greater than or equal to a quantity threshold, or greater than or equal to a predicted reserved quantity corresponding to the first object, or satisfying an indicator to be completed of the first object.

[0059] In the embodiment of the present disclosure, when it is determined that the current remaining quantity does not meet the preset requirements, it can be said that the current remaining candidate second objects are insufficient for allocation, and the allocation amount of the first object is insufficient, which makes it difficult to complete its to-be-completed indicators. Therefore, in the embodiment of the present disclosure, the candidate second objects can also be dynamically adjusted to improve the allocation effectiveness.

[0060] 3) According to the second quantity, obtain second objects from other databases, and use the obtained second objects as candidate second objects.

[0061] For example, in an embodiment of the present disclosure, in a telemarketing scenario, manual seats can be combined with artificial intelligence dialing, and other databases represent AI reserved databases corresponding to artificial intelligence. If the candidate second objects reserved for manual seats are insufficient, the second object can be pulled from the AI ​​reserved database as the candidate second object for the manual seat.

[0062] In addition, in the embodiment of the present disclosure, when obtaining the second object from other databases, the object level calculation may be performed on the second objects in other databases, and then the second objects included in different object levels may be selected respectively.

[0063] In this way, in the embodiment of the present disclosure, the number of candidate second objects can be dynamically adjusted so that the reserved candidate second objects can meet the actual operating capacity and can also improve the resource utilization and fairness of the second objects.

[0064] Furthermore, in the embodiment of the present disclosure, after the allocation task is triggered, the business record of the first object may also be responded to. When the predicted business record has been reached and the to-be-completed index has been met, if there are still many reserved candidate second objects, it may cause a waste of resources. Therefore, in view of this, the embodiment of the present disclosure further provides possible implementation methods, including:

[0065] 1) Determine whether the business record of the group to which the first object belongs reaches the predicted business record.

[0066] 2) When the business record of the group to which the first object belongs reaches the predicted business record, determine the completed indicator of the group to which the first object belongs.

[0067] For example, the business record of group 1 to which the first object A belongs is 5 people, and the predicted business record of group 1 is 5 people. It can be known that the seats in group 1 have reached the predicted business record. The completed indicators of the 5 seats in group 1 can be added up to determine the completed indicators of group 1.

[0068] 3) When the completed indicators of the group to which the first object belongs meet the to-be-completed indicators of the group to which the first object belongs, and when it is determined that the current remaining number of candidate second objects is greater than a threshold, the candidate second objects greater than the threshold are allocated to the third object so that the third object performs operations on the allocated candidate second objects.

[0069] For example, each indicator is the conversion of a logged-in customer into a registered customer. If the completed indicator of Group 1 is 500 registered customers, and the to-be-completed indicator of Group 1 is 450, it can be known that Group 1 has met the required to-be-completed indicators. At this time, there are still many candidate second objects corresponding to Group 1, which may result in a waste of resources. Therefore, all or part of the remaining candidate second objects can be reallocated to other third objects for dialing, for example, the third object is artificial intelligence, etc.

[0070] Furthermore, when assigning candidate second objects greater than a threshold to a third object, the object levels of the remaining candidate second objects may be calculated and sorted, and then candidate second objects may be selected from different object levels to be assigned to the third object, thereby improving the rationality of the assignment.

[0071] Thus, in the disclosed embodiment, when it is determined that there are a large number of remaining candidate second objects, the candidate second objects can be automatically allocated to other third objects for operation, thereby realizing intelligent dynamic scheduling of the second objects and improving the utilization rate of the second object resources and the overall energy conversion efficiency.

[0072] In addition, in the embodiment of the present disclosure, after the second object is assigned to the first object, the first object can perform operations on the second object. Taking the telemarketing scenario as an example, the first object can call the second object to perform marketing operations. After completing a call, in the embodiment of the present disclosure, the call log information can be recorded and saved, and the completed indicators of the first object and the completed indicators of the group to which the first object belongs can be calculated based on the actual call connection status of the second object and whether the capacity conversion is actually achieved. This can facilitate the subsequent dynamic scheduling and allocation of the second object. The call log information includes, for example, customer portrait information, customer call behavior information, customer capacity intention level and other information of the second object. The customer portrait information represents customer attributes and identity characteristics, for example, whether the second object is a logged-in customer, a registered customer or an active customer. The customer call behavior information may include the customer's emotional state and degree of cooperation during the call. The customer capacity intention level represents the probability of customer capacity conversion.

[0073] In the disclosed embodiment, in response to assigning a task, the unfinished indicators of the first object can be determined based on the business record, to-be-completed indicators and completed indicators of the first object, and the first number of second objects that need to be assigned to the first object for operation can be determined based on the unfinished indicators, and then the first number of second objects can be screened out from the candidate second objects, and the screened out second objects can be assigned to the first object. In this way, the business records and indicators can be combined to automatically assign the second objects to the first object according to demand, thereby improving the allocation efficiency, and the allocation of the second objects is more accurate, thereby improving the capacity conversion rate of the second object and improving the operation effect on the second object.

[0074] In the disclosed embodiment, a reserved task can be executed during non-working hours. The reserved task mainly uses data analysis and mining techniques to determine the to-be-completed indicators of the first object during the working hours, predicted business records, and candidate second objects to be reserved, etc., which can be used to improve the allocation efficiency and accuracy during the working hours. The following is an explanation of the execution process of the reserved task in the disclosed embodiment. In a possible embodiment, the to-be-completed indicators are determined according to the historical operation status of the first object, and the historical operation status at least includes historical business records, historical to-be-completed business records, historical completed indicators, and historical to-be-completed indicators; the to-be-completed indicators and the candidate second objects are determined in the following manner:

[0075] S1. In response to a reserved task, obtain historical business records and to-be-completed business records of a first object in each group; wherein a plurality of first objects form a group.

[0076] The conditions for triggering the reserved task include, for example, reaching a certain time in the preset non-working hours. The pending business records can represent the preset scheduling information, such as the special projects divided into several customer groups, the number of groups arranged to call each special project, the number of seats in each group, and the seat scheduling of each group in the next predicted working period. The historical business records represent the attendance of each group in the preset historical statistical period.

[0077] S2. Determine the predicted business records for each group based on historical business records and pending business records.

[0078] In the disclosed embodiment, a two-dimensional array can be created for each group, in which the first column is used to store the date of the business record, and the second column is used to store the number of business records corresponding to the date. Then, based on the date and the number of business records in the historical business records, data fitting and analysis are performed to obtain business record change trend information, and based on the business record change trend information and the business records to be completed, the predicted business records of the group in the next working period to be predicted are determined.

[0079] In a possible embodiment, an autoregressive moving average model (ARMA) can be used for prediction. Taking the prediction of a group as an example, for the two-dimensional array of the group, an extended Dickey-Fuller (ADF) check and a trend stability check method, such as Kwiatkowski-Phillips-Schmidt-Shin (KPSS) check, are used to ensure the stability of the time series data of historical business records. If it is not stable, it is difficult to capture its statistical characteristics that change over time, and direct modeling will lead to inaccurate prediction results. Therefore, differential processing can be performed until the data becomes stable; the autocorrelation function (ACF) and partial autocorrelation function (PAC) are used to check the stability of the time series data of historical business records. Function, PACF) to determine the ARMA model order, according to ACF and PACF, select the last Lag value that exceeds the threshold as the p value (autoregressive order) and q value (moving average order); use ARMA (p, q) to fit the model and evaluate the parameters; check whether the residuals of the ARMA model are close to the normal distribution and independent of each other, and test the autocorrelation of the residuals; use the fitted ARMA model to calculate the predicted business records of the group and save them.

[0080] S3. Obtain the historical completed indicators and historical to-be-completed indicators of the first object in each group.

[0081] S4. Determine the to-be-completed indicators for each group based on the historical completed indicators and the historical to-be-completed indicators, and determine the to-be-completed indicators for the first object in each group based on the to-be-completed indicators for each group and the predicted business records.

[0082] For example, in the telemarketing scenario, the corresponding scheduling groups and seats in the groups are divided according to the special projects. Each seat is traversed, and the historical completed indicators of each group are calculated based on the historical completed indicators of the seats. The historical completed indicators of each special project are calculated based on the historical completed indicators of each group.

[0083] Then, for each special project, for example, based on the Prophet model, data fitting and analysis can be performed according to the special project's historical completed indicators and historical to-be-completed indicators, so as to obtain historical indicator trend information, and then determine the to-be-completed indicators to be completed for the special project on the next working day. Based on the to-be-completed indicators of the special project, the to-be-completed indicators of each group corresponding to the special project are calculated, and based on the to-be-completed indicators of each group and the corresponding predicted business records, the to-be-completed indicators that need to be completed by the agents in each group are calculated.

[0084] S5. According to the to-be-completed indicators of each group, select the candidate second objects corresponding to each group from the target database.

[0085] In the disclosed embodiment, after the predicted business records and indicators to be completed for each special project and each group are determined, it is necessary to screen candidate second objects that meet the corresponding requirements for allocation during the working hours. In order to improve the rationality and fairness of the allocation, the second objects can also be graded, and reservation pools of different object levels can be pre-set for reserved tasks to store candidate second objects of different object levels.

[0086] Specifically, the present disclosure provides a possible implementation method, which selects the candidate second objects corresponding to each group from the target database according to the to-be-completed indicators of each group, including:

[0087] 1) For multiple second objects in the target database, determine the object levels and capacity prediction values ​​of the multiple second objects, wherein the object level represents the importance of the second object, and the capacity prediction value represents the capacity conversion score in the operation capacity result of the second object.

[0088] Among them, the object level can be understood as the quality level of different customers, and can be comprehensively judged based on multi-dimensional information. In a possible embodiment, for each second object in the target database, the attribute information, operation behavior information and production capacity intention level of the second object are obtained; the object level of the second object is determined based on the attribute information and the first parameter weight, the operation behavior information and the second parameter weight, and the production capacity intention level and the third parameter weight.

[0089] For example, object level = (attribute information x first parameter weight + work behavior information x second parameter weight + capacity intention level x third parameter weight) x object capacity parameter / object level coefficient.

[0090] Among them, the first parameter weight, the second parameter weight, the third parameter weight, the object capacity parameter and the object level coefficient can be set according to actual experience and needs, and different attribute information is assigned different values. For example, the attribute information includes logged-in customer tags, registered customer tags and active customer tags, etc. Different operation behavior information is also assigned different values. For example, the operation behavior information includes calm, intense, angry tone, etc. Different capacity intention levels correspond to different values. The capacity intention level can be input after the first object and the second object have a conversation, or it can be automatically determined according to the call information.

[0091] In this way, in the embodiment of the present disclosure, based on the calculated object level score and the preset classification threshold, the object with a score greater than the first threshold can be classified as a high level, the object with a score greater than the second threshold and less than or equal to the first threshold can be classified as a medium level, and the object with a score less than or equal to the second threshold can be classified as a low level.

[0092] The capacity prediction value may be understood as a probability score of the actual conversion of the customer's capacity. In a possible embodiment, the capacity prediction value of the second object is determined according to the object level and the capacity coefficient.

[0093] For example, capacity forecast value = object level x capacity coefficient.

[0094] Among them, the capacity coefficient is set according to actual experience and needs, and the specific value is not restricted.

[0095] 2) Sort the plurality of second objects according to the object levels.

[0096] Specifically, in the disclosed embodiment, a plurality of second objects in the target database may be sorted from high to low according to the scores of the object levels, and a higher ranking indicates a higher quality.

[0097] 3) According to the predicted capacity value and the to-be-completed indicator of each group, determine the candidate second objects corresponding to each group and the reserved number of the candidate second objects from the sorted plurality of second objects.

[0098] Specifically, the present disclosure provides a possible implementation, including: for any group in each group, according to a preset first proportional coefficient corresponding to each object level, select the second object under each object level from the sorted multiple second objects, use the selected second object as the candidate second object, and determine the sum of the capacity prediction values ​​corresponding to the selected candidate second objects according to the capacity prediction value, until the sum is greater than or equal to the to-be-completed indicator of any group, and obtain the candidate second objects corresponding to any group and the reserved number of the candidate second objects.

[0099] For example, there are high level, medium level and low level divisions, and selection is made from multiple second objects of different object levels respectively. In order to improve the job conversion rate, when selecting in each object level, the second object with a higher ranking can be preferentially selected as the candidate second object according to the sorting information from high to low, and then the multiple second objects under different object levels are screened respectively, so that the candidate second objects of different object levels can be obtained, thereby improving the fairness and accuracy of subsequent allocation.

[0100] Regarding the specific selection method, in one possible embodiment, for a certain group, the group's to-be-completed indicators are split into each object level according to the group's to-be-completed indicators and the first proportional coefficient corresponding to each object level, and each object level corresponds to a sub-to-be-completed indicator. Then, selection is made from the sorted second objects under each object level, and the sum of the capacity forecast values ​​of the selected candidate second objects is calculated until the sum is greater than or equal to the corresponding sub-to-be-completed indicator. In this way, the sum of the capacity forecast values ​​of the selected candidate second objects corresponding to all object levels meets the requirements of the group's to-be-completed indicators.

[0101] In the disclosed embodiments, statistical analysis and mining can be used to predict the predicted business records of the working period based on historical business records and pending business records, and the pending indicators can be automatically determined based on the historical completed indicators, historical pending indicators and predicted business records, and the candidate second objects to be reserved and the reserved quantity to be determined. In this way, reasonable pending indicators can be determined for each group and first object more accurately, and candidate second objects that better meet the needs can be reserved to be provided for allocation to the working period, thereby realizing intelligent allocation of the second objects and improving allocation efficiency.

[0102] The following uses a specific application scenario for illustration. Taking a telemarketing scenario as an example, in the embodiment of the present disclosure, in the telemarketing scenario, the second object represents a customer list, the first object represents an agent, and in the embodiment of the present disclosure, the customer groups can be divided into types, each type of customer group can be called a special project, and a special project can be dialed by agents of one or more groups, and a small group usually includes multiple agents. The object allocation method in the embodiment of the present disclosure can be divided into the following aspects for illustration:

[0103] The first aspect: reserved tasks.

[0104] In the embodiment of the present disclosure, a reserved task can be executed during non-working hours to allocate candidate second objects, to-be-completed indicators, predicted business records, etc. required for prediction to the second object during the working hours. For example, the reserved task can be executed for the next working day during non-working hours of the day, such as the night time period.

[0105] Specific reference Figure 3 As shown, it is a flowchart of the reserved task in the embodiment of the present disclosure, including:

[0106] S301: Create a reserved task.

[0107] In the embodiment of the present disclosure, in order to further improve processing efficiency, a reserved task table may be designed to record reserved task information, for example, as shown in Table 1, which is an example of a reserved task table in the embodiment of the present disclosure.

[0108] Table 1.

[0109] Fields Field Type Remark Reserve task execution time Date (datetime) Number of reserved customer lists integer Number of customer lists to which human agents are assigned integer Number of customer lists recovered by AI integer Number of customer lists assigned AI integer

[0110] For example, during a preset non-working period, a reservation task may be automatically triggered and created, and the reservation task may correspond to initializing candidate list pools of different object levels, such as high, medium, and low candidate list pools.

[0111] S302: Obtain pending business records and historical business records, and determine predicted business records.

[0112] For example, as shown in Table 2, Table 2 is an example of an attendance record table in an embodiment of the present disclosure. The attendance record table can be used to record the predicted business records predicted by data analysis every day, and during the working hours, when the agent attendance sign-in is successful, the business record is recorded. Taking the business record as an example to represent the attendance information, the attendance number of each group can be counted when recording.

[0113] Table 2.

[0114] Fields Field Type Remark Reserve task execution time datetime Special logo bigint Group ID bigint Forecasting business records integer Business Records integer

[0115] Among them, bigint is a special numeric type that supports integers of arbitrary length.

[0116] For example, Figure 3 As shown, the special items for the next day's operation can be queried, including Special 1, Special 2, etc., and the scheduling information corresponding to each special item can be obtained. Taking Special 1 as an example, there are two groups corresponding to Special 1 to dial. The pending business records in Group 1 are 5 planned attendances, and the pending business records in Group 2 are 6 planned attendances. Then, each special item is traversed to obtain the historical business records of the groups corresponding to each special item, and the predicted business records for the next day are determined. For example, it is determined that the predicted business records of Group 1 are 5 predicted attendances, and the predicted business records of Group 2 are 6 predicted attendances.

[0117] S303: Obtain historical completed indicators and historical to-be-completed indicators, and determine the to-be-completed indicators.

[0118] For example, as shown in Table 3, Table 3 is an example of a target record table in an embodiment of the present disclosure, and the target record table can be used to record information such as the actual daily allocation quantity, to-be-completed indicators, and completed indicators.

[0119] Table 3.

[0120] Fields Field Type Remark Reserve task execution time datetime Seat ID bigint Special logo bigint Group ID bigint Actual Allocated Quantity integer Indicators to be completed bigdecimal Completed indicators bigdecimal

[0121] S304: Determine the reserved number of candidate second objects.

[0122] In the embodiment of the present disclosure, based on the customer list database, the object level and capacity prediction value of the customer list in the customer list database can be determined, and the customer lists can be sorted according to the object level, so that the candidate customer list can be screened out from the customer list database according to the to-be-completed indicators and the predicted business records and the capacity prediction value, and the reserved number of the candidate customer list can be determined, for example, Figure 3 As shown, taking Special 1 as an example, the reserved quantity of Group 1 corresponding to Special 1 is 10,000, the predicted business record is 5, the reserved quantity of each first object in Group 2 is 2,000, the reserved quantity of Group 2 is 10,000, the predicted business record is 6, and the reserved data of each first object in Group 2 is 1,600.

[0123] S305: Save the candidate second object into the reserved pool.

[0124] In the embodiment of the present disclosure, the screened candidate second objects are saved in reserved pools of different object levels according to the object levels of the candidate second objects. For example, Figure 3 As shown, they can be saved in high-level, medium-level or low-level reserved pools respectively.

[0125] S306: Save detailed information of the candidate second object.

[0126] For example, detailed information includes customer telephone contact information, age, attribute information, object level, work behavior information, etc.

[0127] S307: Save the reserved task record.

[0128] For example, the reservation task record may include log information of the reservation task, the reservation quantity of the candidate second object, predicted business records, indicators to be completed, and the like.

[0129] In this way, in the embodiment of the present disclosure, historical data can be statistically analyzed to predict business records for working hours, and based on the predicted business records, indicators to be completed can be determined and candidate second objects can be selected, thereby improving accuracy, predicting more reasonable indicators to be completed, and reserving more accurate and reasonable candidate second objects. The reserved quantity can be adjusted dynamically so that the reserved candidate second objects are more in line with the actual processing capacity, thereby improving the management efficiency of the second objects, and also classifying and sorting the second objects according to multi-dimensional factors, and making more detailed object class distinctions, so that allocation can be more accurate and fairer.

[0130] The second aspect: assigning tasks.

[0131] In the disclosed embodiment, during working hours, agents usually go to work by clocking in or signing in for attendance. After successfully signing in, a business record is generated and saved in a preset attendance database. The business record of the group to which the agent belongs can be updated in real time. The attendance time of each agent may be different. Therefore, in the disclosed embodiment, customer lists can be dynamically allocated in real time for agents who have punched in. For example, after the agent punches in, they can be allocated according to the corresponding to-be-completed indicators, and in the process of the agent making calls, the completed indicators can be calculated in real time. Then, according to the business records, completed indicators, etc., the customer list allocation can be dynamically adjusted to improve the effectiveness and utilization of the customer list allocation.

[0132] This article will explain the dynamic adjustment during the dialing process. For details, please refer to Figure 4 As shown, it is a flowchart of allocating tasks in an embodiment of the present disclosure, including:

[0133] S401: Determine whether the current remaining number of the candidate second object meets the preset requirement, if yes, execute step S406, if no, execute step S402.

[0134] In the disclosed embodiment, since the customer list is assigned and dynamically adjusted after the agent reports for attendance, the number of remaining candidate customer lists decreases as the number of attendees increases. When an agent signs in for attendance later or the completed indicators of the assigned agent do not meet the requirements and the customer list needs to be reallocated, there may not be enough remaining candidate customer lists. Therefore, in the disclosed embodiment, when triggering the assignment task, it can be determined first whether the candidate customer list still meets the preset requirements, and then determine how to proceed subsequently, where the preset requirements may be, for example, that the number is greater than a threshold.

[0135] S402: Calculate the completed indicators of the project to which the first object belongs.

[0136] S403: Calculate the completed index of the group to which the first object belongs.

[0137] S404: Calculate a second quantity to be allocated to the second object according to the completed indicator and the to-be-completed indicator.

[0138] S405: Acquire candidate second objects from the AI ​​list pool according to the second quantity.

[0139] For example, the customer lists in the AI ​​list pool are also graded, such as being divided into three object grades: high, medium, and low. Then, according to the corresponding proportion of each object and the required second quantity, multiple customer lists can be selected from the high, medium, and low object grades, respectively, as candidate customer lists for manual seats, and saved in the reserved pools of different object grades in the reserved pool. In addition, after pulling the candidate customer list from the AI ​​list pool, the number of customer lists in the AI ​​list pool can also be updated synchronously.

[0140] S406: Acquire the business record of the group to which the first object belongs.

[0141] S407: Determine whether there are any persons who have not been present in the group to which the first object belongs. If yes, execute step S412; otherwise, execute step S408.

[0142] S408: Obtain the current remaining number of candidate second objects.

[0143] S409: Determine whether it is greater than a threshold. If so, execute step S410. If not, no processing is required and the data is still stored in the reserved pool.

[0144] S410: Allocate candidate second objects greater than a threshold to third objects according to the object level.

[0145] In the disclosed embodiment, when the business record has reached the predicted business record, it means that all seats have been assigned to obtain customer lists. If there are still a large number of candidate customer lists in the reserved pool at this time, it will lead to waste of resources. Therefore, in the disclosed embodiment, part of the candidate customer list can be automatically reallocated to a third object, such as AI, so that AI can dial the assigned candidate customer list, thereby improving the customer list reach rate and overall conversion efficiency. In addition, the number of customer lists assigned to AI can also be updated synchronously.

[0146] S411: Update the candidate second object.

[0147] S412: Acquire the business record of the first object.

[0148] For example, Figure 4 As shown, in the disclosed embodiment, the assigned tasks are linked to the attendance system. After the agent punches in or signs in, a business record is generated, and the business record can be synchronously pushed to the message system, such as the Kafka system. Kafka is a highly reliable, high-throughput, and low-latency distributed publish-subscribe message system, so that the assigned tasks can consume and obtain business records from the Kalfa system.

[0149] S413: Determine the completion index of the first object.

[0150] S414: Determine the completed indicator of the group to which the first object belongs.

[0151] S415: Determine the completed indicators of the special project to which the first object belongs.

[0152] S416: Determine the first quantity of the second objects that need to be assigned to the first object for operation based on the completed indicators of the project, group and first object, as well as the indicators to be completed.

[0153] S417: Allocate the second object to the first object according to the first quantity.

[0154] For example, according to the first quantity, the second object is obtained from the high-level, medium-level, and low-level reserved pools in proportion and allocated to the first object.

[0155] S418: Save the allocation record.

[0156] In this way, in the embodiment of the present disclosure, business records can be obtained in real time when actual allocation is made during working hours, customer lists can be allocated in a timely and accurate manner, and in the work process, customer lists can be dynamically allocated based on actual completion targets, etc., thereby improving efficiency, and improving the accuracy and rationality of allocation. In addition, it can also work in collaboration with AI to dynamically adjust the reserved pool, and can respond quickly when the business records of the agents change, thereby improving the resource utilization and allocation accuracy of the customer list.

[0157] The third aspect: dial the task.

[0158] In the embodiment of the present disclosure, taking the task of the first object for the second object as a dialing task as an example, after the customer list is assigned to the agent, the agent can make a call to the customer to communicate with him to complete the marketing goal of the phone call. Figure 5 As shown, it is a flowchart of dialing a task in an embodiment of the present disclosure, including:

[0159] S501: Save the attribute information of the second object.

[0160] For example, the attribute information includes a user type label of the second object, etc.

[0161] S502: Save the operation behavior information of the second object.

[0162] For example, the task behavior information includes the emotional state of the second object, the communication duration, etc.

[0163] S503: Save the production capacity intention level of the second object.

[0164] For example, after the agent communicates with the customer, the agent can determine the possibility of the customer's capacity conversion and then choose from multiple pre-given capacity intention levels.

[0165] S504: Update detailed information of the second object.

[0166] S505: Determine the completed indicator of the first object and save it.

[0167] In the disclosed embodiment, after the agent communicates with the customer on the phone, the agent can update the relevant marketing result information to the customer list, which can be provided for use in subsequent allocations, and the agent's completed indicators can also be calculated in real time, which is convenient for use in dynamic allocation of the customer list.

[0168] It can be understood that the above-mentioned various method embodiments mentioned in the present disclosure can be combined with each other to form a combined embodiment without violating the principle logic. Due to space limitations, the present disclosure will not repeat them. It can be understood by those skilled in the art that in the above-mentioned method of the specific implementation method, the specific execution order of each step should be determined according to its function and possible internal logic.

[0169] In addition, the present disclosure also provides a distribution device, an electronic device, and a computer-readable storage medium, all of which can be used to implement any distribution method provided by the present disclosure. The corresponding technical solutions and descriptions are referred to the corresponding records in the method part and will not be repeated here.

[0170] Figure 6 A block diagram of a distribution device provided in an embodiment of the present disclosure.

[0171] Reference Figure 6 , an embodiment of the present disclosure provides a dispensing device, the dispensing device comprising:

[0172] An acquisition module 61 is used to acquire the business record and to-be-completed index of the first object in response to the assigned task; the to-be-completed index is determined according to the historical operation status of the first object;

[0173] A first determination module 62, configured to determine a completed indicator of the first object according to a result of the operation capacity of the first object operating on a second object, the second object representing an object on which the first object needs to operate;

[0174] A second determining module 63 is used to determine the uncompleted indicator of the first object according to the business record, the to-be-completed indicator and the completed indicator, and determine the first number of second objects that need to be assigned to perform operations on the first object according to the uncompleted indicator;

[0175] The allocation module 64 is used to screen out the first number of second objects from the candidate second objects and allocate the screened second objects to the first object, wherein the candidate second objects are pre-determined from a target database based on the to-be-completed indicators, and the target database stores multiple second objects.

[0176] In a possible embodiment, it further includes a reservation processing module 65;

[0177] The historical operation status at least includes historical business records, historical to-be-completed business records, historical completed indicators, and historical to-be-completed indicators; the to-be-completed indicators and the candidate second objects are determined by the reservation processing module 65 in the following manner:

[0178] In response to the reserved task, obtaining historical business records and to-be-completed business records of the first object in each group; wherein a plurality of first objects form a group;

[0179] Determining the predicted business records of each group according to the historical business records and the to-be-completed business records;

[0180] Obtain the historical completed index and the historical to-be-completed index of the first object in each group;

[0181] Determine the to-be-completed indicator of each group according to the historical completed indicator and the historical to-be-completed indicator, and determine the to-be-completed indicator of the first object in each group according to the to-be-completed indicator of each group and the predicted business record;

[0182] According to the to-be-completed indicators of each group, the candidate second objects corresponding to each group are screened out from the target database.

[0183] In a possible embodiment, when the candidate second objects corresponding to each group are screened out from the target database according to the to-be-completed indicators of each group, the reservation processing module 65 is used to:

[0184] For a plurality of second objects in the target database, determine object levels and capacity prediction values ​​of the plurality of second objects, wherein the object level represents the importance of the second object, and the capacity prediction value represents the capacity conversion score in the operation capacity result of the second object;

[0185] sorting the plurality of second objects according to the object level;

[0186] According to the predicted capacity value and the to-be-completed indicator of each group, the candidate second objects corresponding to each group and the reserved quantity of the candidate second objects are determined from the sorted plurality of second objects.

[0187] In a possible embodiment, when determining the object levels and capacity prediction values ​​of the plurality of second objects, the reservation processing module 65 is configured to:

[0188] For each second object in the target database, obtaining attribute information, operation behavior information, and capacity intention level of the second object;

[0189] Determining the object level of the second object according to the attribute information and the first parameter weight, the operation behavior information and the second parameter weight, and the capacity intention level and the third parameter weight;

[0190] A capacity prediction value of the second object is determined according to the object level and the capacity coefficient.

[0191] In a possible embodiment, when determining the candidate second objects corresponding to each group and the reserved quantity of the candidate second objects from the sorted plurality of second objects according to the capacity forecast value and the to-be-completed indicator of each group, the reservation processing module 65 is used to:

[0192] For any group in each group, according to the preset first proportional coefficient corresponding to each object level, the second object under each object level is selected from the sorted multiple second objects, and the selected second object is used as the candidate second object. According to the capacity forecast value, the sum of the capacity forecast values ​​corresponding to the selected candidate second objects is determined until the sum is greater than or equal to the to-be-completed indicator of any group, and the candidate second objects corresponding to any group and the reserved number of the candidate second objects are obtained.

[0193] A possible embodiment further includes a first adjustment module 66, which is used to:

[0194] Obtaining the current remaining number of the candidate second objects;

[0195] When the current remaining quantity does not meet the preset requirement, determining the second quantity of the second objects required to be allocated to the first object according to the completed index and the to-be-completed index of the first object;

[0196] According to the second number, second objects are acquired from other databases, and the acquired second objects are used as the candidate second objects.

[0197] A possible embodiment further includes a second adjustment module 67, which is used to:

[0198] Determining whether the business record of the group to which the first object belongs reaches the predicted business record;

[0199] In a case where the business record of the group to which the first object belongs reaches the predicted business record, determining a completed indicator of the group to which the first object belongs;

[0200] When the completed indicators of the group to which the first object belongs meet the to-be-completed indicators of the group to which the first object belongs, and when it is determined that the current remaining number of the candidate second objects is greater than a threshold, the candidate second objects greater than the threshold are allocated to the third object so that the third object performs operations on the allocated candidate second objects.

[0201] In a possible embodiment, when the first number of second objects are screened out from the candidate second objects, the allocation module 64 is configured to:

[0202] Determine a third number of objects to be screened corresponding to each object level according to a preset second proportional coefficient corresponding to each object level and the first number;

[0203] The corresponding third number of second objects are screened out from the candidate second objects included in each object level.

[0204] Each module in the above-mentioned distribution device can be implemented in whole or in part by software, hardware or a combination thereof. Each module can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute the operations corresponding to each module.

[0205] Figure 7 A block diagram of an electronic device provided in an embodiment of the present disclosure.

[0206] Reference Figure 7 An embodiment of the present disclosure provides an electronic device, which includes: at least one processor 701; at least one memory 702, and one or more I / O interfaces 703, connected between the processor 701 and the memory 702; wherein the memory 702 stores one or more computer programs that can be executed by the at least one processor 701, and the one or more computer programs are executed by the at least one processor 701 so that the at least one processor 701 can execute the above-mentioned allocation method.

[0207] Each module in the above electronic device can be implemented in whole or in part by software, hardware, or a combination thereof. Each module can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute operations corresponding to each module.

[0208] The embodiment of the present disclosure also provides a computer-readable storage medium on which a computer program is stored, wherein the computer program implements the above-mentioned allocation method when executed by a processor. The computer-readable storage medium may be a volatile or non-volatile computer-readable storage medium.

[0209] The embodiment of the present disclosure also provides a computer program product, including a computer-readable code, or a non-volatile computer-readable storage medium carrying the computer-readable code. When the computer-readable code runs in a processor of an electronic device, the processor in the electronic device executes the above-mentioned allocation method.

[0210] It will be appreciated by those skilled in the art that all or some of the steps, systems, and functional modules / units in the methods disclosed above may be implemented as software, firmware, hardware, and appropriate combinations thereof. In a hardware implementation, the division between the functional modules / units mentioned in the above description does not necessarily correspond to the division of physical components; for example, a physical component may have multiple functions, or a function or step may be performed by several physical components in cooperation. Some or all physical components may be implemented as software executed by a processor, such as a central processing unit, a digital signal processor, or a microprocessor, or may be implemented as hardware, or may be implemented as an integrated circuit, such as an application-specific integrated circuit. Such software may be distributed on a computer-readable storage medium, which may include a computer storage medium (or a non-transitory medium) and a communication medium (or a temporary medium).

[0211] As is known to those of ordinary skill in the art, the term computer storage media includes volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storing information (such as computer-readable program instructions, data structures, program modules or other data). Computer storage media include, but are not limited to, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), static random access memory (SRAM), flash memory or other memory technology, portable compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical disk storage, magnetic cassettes, magnetic tapes, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to store desired information and can be accessed by a computer. In addition, it is known to those of ordinary skill in the art that communication media typically contain computer-readable program instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transmission mechanism, and may include any information delivery medium.

[0212] The computer-readable program instructions described herein can be downloaded from a computer-readable storage medium to each computing / processing device, or downloaded to an external computer or external storage device via a network, such as the Internet, a local area network, a wide area network, and / or a wireless network. The network can include copper transmission cables, optical fiber transmissions, wireless transmissions, routers, firewalls, switches, gateway computers, and / or edge servers. The network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in the computer-readable storage medium in each computing / processing device.

[0213] The computer program instructions for performing the operation of the present disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-related instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages, such as Smalltalk, C++, etc., and conventional procedural programming languages, such as "C" language or similar programming languages. Computer-readable program instructions may be executed completely on a user's computer, partially on a user's computer, as an independent software package, partially on a user's computer, partially on a remote computer, or completely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., using an Internet service provider to connect via the Internet). In some embodiments, an electronic circuit, such as a programmable logic circuit, a field programmable gate array (FPGA), or a programmable logic array (PLA), may be customized by utilizing the state information of the computer-readable program instructions, and the electronic circuit may execute the computer-readable program instructions, thereby realizing various aspects of the present disclosure.

[0214] The computer program product described herein may be implemented in hardware, software, or a combination thereof. In one optional embodiment, the computer program product is embodied as a computer storage medium, and in another optional embodiment, the computer program product is embodied as a software product, such as a software development kit (SDK), etc.

[0215] Various aspects of the present disclosure are described herein with reference to the flowcharts and / or block diagrams of the methods, devices (systems) and computer program products according to the embodiments of the present disclosure. It should be understood that each box in the flowchart and / or block diagram and the combination of each box in the flowchart and / or block diagram can be implemented by computer-readable program instructions.

[0216] These computer-readable program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, thereby producing a machine, so that when these instructions are executed by the processor of the computer or other programmable data processing device, a device that implements the functions / actions specified in one or more boxes in the flowchart and / or block diagram is generated. These computer-readable program instructions can also be stored in a computer-readable storage medium, and these instructions cause the computer, programmable data processing device, and / or other equipment to work in a specific manner, so that the computer-readable medium storing the instructions includes a manufactured product, which includes instructions for implementing various aspects of the functions / actions specified in one or more boxes in the flowchart and / or block diagram.

[0217] Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device so that a series of operating steps are performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, thereby causing the instructions executed on the computer, other programmable data processing apparatus, or other device to implement the functions / actions specified in one or more boxes in the flowchart and / or block diagram.

[0218] The flow chart and block diagram in the accompanying drawings show the possible architecture, function and operation of the system, method and computer program product according to multiple embodiments of the present disclosure. In this regard, each square box in the flow chart or block diagram can represent a part of a module, program segment or instruction, and a part of the module, program segment or instruction includes one or more executable instructions for realizing the specified logical function. In some alternative implementations, the function marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two continuous square boxes can actually be executed substantially in parallel, and they can sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs the specified function or action, or can be implemented with a combination of special hardware and computer instructions.

[0219] Example embodiments have been disclosed herein, and although specific terms are employed, they are used and should be interpreted only in a general illustrative sense and not for limiting purposes. In some instances, it will be apparent to those skilled in the art that, unless otherwise expressly noted, features, characteristics, and / or elements described in conjunction with a particular embodiment may be used alone or in combination with features, characteristics, and / or elements described in conjunction with other embodiments. Therefore, those skilled in the art will appreciate that various changes in form and detail may be made without departing from the scope of the present disclosure as set forth in the appended claims.

Claims

1. A distribution method, characterized in that: include: In response to the assigned task, obtaining the business record and to-be-completed index of the first object; the to-be-completed index is determined according to the historical operation status of the first object; Determining a completed indicator of the first object according to a result of the operation capacity of the first object operating on a second object, where the second object represents an object on which the first object needs to operate; Determine the uncompleted indicator of the first object according to the business record, the to-be-completed indicator and the completed indicator, and determine the first quantity of the second objects to be assigned to perform operations on the first object according to the uncompleted indicator; The first number of second objects are screened out from the candidate second objects, and the screened out second objects are assigned to the first object, wherein the candidate second objects are pre-determined from a target database according to the to-be-completed indicator, and the target database stores a plurality of second objects.

2. The method according to claim 1, characterized in that The historical operation status at least includes historical business records, historical business records to be completed, historical completed indicators, and historical indicators to be completed; the indicators to be completed and the candidate second objects are determined in the following manner: In response to the reserved task, obtaining historical business records and to-be-completed business records of the first object in each group; wherein a plurality of first objects form a group; Determining the predicted business records of each group according to the historical business records and the to-be-completed business records; Obtain the historical completed index and the historical to-be-completed index of the first object in each group; Determine the to-be-completed indicator of each group according to the historical completed indicator and the historical to-be-completed indicator, and determine the to-be-completed indicator of the first object in each group according to the to-be-completed indicator of each group and the predicted business record; According to the to-be-completed indicators of each group, the candidate second objects corresponding to each group are screened out from the target database.

3. The method according to claim 2, characterized in that The step of screening out the candidate second objects corresponding to each group from the target database according to the to-be-completed indicators of each group includes: For a plurality of second objects in the target database, determine object levels and capacity prediction values ​​of the plurality of second objects, wherein the object level represents the importance of the second object, and the capacity prediction value represents the capacity conversion score in the operation capacity result of the second object; sorting the plurality of second objects according to the object level; According to the predicted capacity value and the to-be-completed indicator of each group, the candidate second objects corresponding to each group and the reserved quantity of the candidate second objects are determined from the sorted plurality of second objects.

4. The method according to claim 3, characterized in that The determining the object levels and capacity prediction values ​​of the plurality of second objects comprises: For each second object in the target database, obtaining attribute information, operation behavior information, and capacity intention level of the second object; Determining the object level of the second object according to the attribute information and the first parameter weight, the operation behavior information and the second parameter weight, and the capacity intention level and the third parameter weight; A capacity prediction value of the second object is determined according to the object level and the capacity coefficient.

5. The method according to claim 3, characterized in that: The determining, from the sorted plurality of second objects, the candidate second objects corresponding to each group and the reserved quantity of the candidate second objects according to the predicted capacity value and the to-be-completed indicator of each group, comprises: For any group in each group, according to the preset first proportional coefficient corresponding to each object level, the second object under each object level is selected from the sorted multiple second objects, and the selected second object is used as the candidate second object. According to the capacity forecast value, the sum of the capacity forecast values ​​corresponding to the selected candidate second objects is determined until the sum is greater than or equal to the to-be-completed indicator of any group, and the candidate second objects corresponding to any group and the reserved number of the candidate second objects are obtained.

6. The method according to any one of claims 1 to 5, characterized in that: The method further comprises: Obtaining the current remaining number of the candidate second objects; When the current remaining quantity does not meet the preset requirement, determining the second quantity of the second objects to be assigned to the first object for operation according to the completed index and the to-be-completed index of the first object; According to the second number, second objects are acquired from other databases, and the acquired second objects are used as the candidate second objects.

7. The method according to any one of claims 2 to 5, characterized in that: The method further comprises: Determining whether the business record of the group to which the first object belongs reaches the predicted business record; In a case where the business record of the group to which the first object belongs reaches the predicted business record, determining a completed indicator of the group to which the first object belongs; When the completed indicators of the group to which the first object belongs meet the to-be-completed indicators of the group to which the first object belongs, and when it is determined that the current remaining number of the candidate second objects is greater than a threshold, the candidate second objects greater than the threshold are allocated to the third object so that the third object performs operations on the allocated candidate second objects.

8. The method according to any one of claims 3 to 5, characterized in that: The step of selecting the first number of second objects from the candidate second objects includes: Determine a third number of objects to be screened corresponding to each object level according to a preset second proportional coefficient corresponding to each object level and the first number; The corresponding third number of second objects are screened out from the candidate second objects included in each object level.

9. A dispensing device, characterized in that: include: An acquisition module, configured to acquire the business record and to-be-completed index of the first object in response to the assigned task; the to-be-completed index is determined according to the historical operation status of the first object; A first determination module, configured to determine a completed indicator of the first object according to a result of an operation capacity of the first object operating on a second object, wherein the second object represents an object on which the first object needs to operate; A second determination module is used to determine the uncompleted indicator of the first object according to the business record, the to-be-completed indicator and the completed indicator, and determine the first number of second objects that need to be assigned to perform operations on the first object according to the uncompleted indicator; An allocation module is used to screen out the first number of second objects from candidate second objects and allocate the screened second objects to the first object, wherein the candidate second objects are pre-determined from a target database based on the to-be-completed indicators, and the target database stores a plurality of second objects.

10. An electronic device, characterized in that: include: at least one processor; as well as a memory communicatively connected to the at least one processor; wherein, The memory stores one or more computer programs executable by the at least one processor, wherein the one or more computer programs are executed by the at least one processor so as to enable the at least one processor to perform the allocation method according to any one of claims 1 to 8.

11. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the computer program implements the allocation method according to any one of claims 1 to 8.

12. A computer program product, characterized in that The invention comprises a computer-readable code, or a non-volatile computer-readable storage medium carrying the computer-readable code. When the computer-readable code runs in a processor of an electronic device, the processor in the electronic device executes the allocation method according to any one of claims 1 to 8.

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