CN113902263A

CN113902263A - Automatic resource allocation method and device, electronic equipment and computer readable medium

Info

Publication number: CN113902263A
Application number: CN202111096327.XA
Authority: CN
Inventors: 马巍; 杨林; 张骁逸; 宋旸; 蒋宏飞; 霍灿君
Original assignee: Zuoyebang Education Technology Beijing Co Ltd
Current assignee: Beijing Baige Feichi Technology Co.,Ltd.
Priority date: 2021-09-17
Filing date: 2021-09-17
Publication date: 2022-01-07

Abstract

A method, a device and an electronic device for automatically allocating resources are provided, wherein the method for automatically allocating resources comprises the following steps: evaluating and grading the resource carrying personnel; scoring the current access resource; and automatically allocating the access resources to resource carrying personnel at corresponding levels according to the scores of the access resources. According to the invention, the resource carrying personnel are graded, the accessed users are graded, and the graded users are automatically distributed to the resource carrying personnel of the corresponding grade by using an intelligent distribution algorithm to carry out one-to-one service, so that the distribution efficiency is maximized, the high-quality users can be matched with the resource carrying personnel with strong capability, the conversion probability of the users is improved, the user experience is improved, and the income of education institutions is increased.

Description

Automatic resource allocation method and device, electronic equipment and computer readable medium

Technical Field

The invention belongs to the technical field of machine learning, and particularly relates to a resource automatic allocation method, a resource automatic allocation device, electronic equipment and a computer readable medium.

Background

With the development of modern information technology and the demand of the education market, online education is being popularized and popularized continuously as an emerging education concept. In order to attract more users to buy online education products, the education institutions firstly popularize the online education products in the form of advertisements and the like, and when the users browse the education products through the advertisements, the education institutions arrange the working personnel of different seats to answer one to one, so that the buying intentions of the users are improved.

In the prior art, a sales agent randomly accesses to a telephone of a worker to allocate access resources through a program control device, and because the capacity of each worker is different, the allocation access mode cannot maximize the efficiency of the whole system, so how to automatically allocate corresponding resources by setting an intelligent matching algorithm in the program control device becomes a technical problem which needs to be solved urgently at present.

Disclosure of Invention

Technical problem to be solved

The invention aims to solve the technical problem of how to automatically allocate resources to maximize benefits.

(II) technical scheme

In order to solve the above technical problem, an aspect of the present invention provides an automatic resource allocation method, including:

evaluating and grading the resource carrying personnel;

scoring the current access resource;

and automatically allocating the access resources to resource carrying personnel at corresponding levels according to the scores of the access resources.

According to the preferred embodiment of the invention, the identity information and the behavior data of the resource adapting personnel are input into the trained first scoring model, and the score of the resource adapting personnel is output;

setting a grading interval corresponding to each level of the resource carrying personnel;

and setting a corresponding grade for the resource accepting personnel according to the resource accepting personnel scores.

According to a preferred embodiment of the present invention, the scoring the current access resource includes:

and inputting the identity information and the behavior data of the current user in the access resource into the trained second scoring model, and outputting the score of the user.

According to a preferred embodiment of the present invention, the automatically allocating the access resource to the resource accepting person of the corresponding level according to the score of the access resource includes:

inputting the grade of the user into a pre-trained allocation model to obtain the grade of the resource carrying personnel allocated to the user;

and screening the resource carrying personnel in the idle state from the resource carrying personnel level to serve the user.

According to a preferred embodiment of the present invention, the inputting the score of the user into a pre-trained allocation model to obtain the resource carrying person level allocated to the user further includes:

setting an initial average score for each level according to historical data, and setting a user number threshold for each level;

obtaining the score of the current user, and respectively calculating the difference between the score and the average score of each grade;

assigning the current user to the level with the smallest difference.

According to a preferred embodiment of the present invention, the assigning the current user to the level with the smallest difference further comprises:

detecting whether the number of the users contained in each level is lower than the user number threshold value or not in real time;

if the number of the included users is detected to be lower than the level of the user number threshold, respectively calculating the difference between the current user score and the average score of each level lower than the user number threshold, and distributing the current user to the level with the minimum difference in the levels lower than the threshold.

According to a preferred embodiment of the present invention, after assigning the current user to the level with the minimum difference, the method further comprises:

calculating an average score of the user scores in each level;

sorting the levels according to the sequence of average grading of the users of all levels from big to small;

and acquiring the score of the next user, respectively calculating the difference between the score of the user and the average score of each ranked level, and distributing the user to the corresponding level according to the difference until all the users are distributed.

According to a preferred embodiment of the present invention, the threshold value of the number of users is a preset value that the number of users in each level is not lower than the average value of the total number of users in all levels.

A second aspect of the present invention provides an apparatus for automatically allocating resources, including:

the resource carrying personnel grading module is used for evaluating and grading the resource carrying personnel;

the access resource scoring module is used for scoring the current access resource;

and the automatic resource allocation module is used for automatically allocating the access resources to the resource carrying personnel at the corresponding level according to the scores of the access resources.

A third aspect of the present invention provides an electronic device, comprising a processor and a memory, wherein the memory is used for storing a computer executable program, and when the computer program is executed by the processor, the processor executes any one of the above-mentioned automatic resource allocation methods.

The fourth aspect of the present invention also provides a computer-readable medium, which stores a computer-executable program, and when the computer-executable program is executed, the method for automatically allocating resources according to any one of the foregoing methods is implemented.

The fifth aspect of the present invention further provides a computer executable program, when executed, implementing the automatic resource allocation method described in any one of the above.

(III) advantageous effects

According to the invention, the resource carrying personnel are graded, the accessed users are graded, and the graded users are automatically distributed to the resource carrying personnel of the corresponding grade by using an intelligent distribution algorithm to carry out one-to-one service, so that the distribution efficiency is maximized, the high-quality users can be matched with the resource carrying personnel with strong capability, the conversion probability of the users is improved, the user experience is improved, and the income of education institutions is increased.

Drawings

Fig. 1 is a schematic view of an application scenario of an automatic resource allocation method according to an embodiment of the present invention;

FIG. 2 is a flowchart illustrating a method for automatically allocating resources according to an embodiment of the present invention;

FIG. 3 is a schematic flow chart of a real-time allocation algorithm according to an embodiment of the present invention;

FIG. 4 is a schematic diagram of an apparatus for automatically allocating resources according to an embodiment of the present invention;

fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present invention;

fig. 6 is a schematic diagram of a computer-readable recording medium provided by an embodiment of the present invention.

Detailed Description

In describing particular embodiments, specific details of structures, properties, effects, or other features are set forth in order to provide a thorough understanding of the embodiments by one skilled in the art. However, it is not excluded that a person skilled in the art may implement the invention in a specific case without the above-described structures, performances, effects or other features.

The flow chart in the drawings is only an exemplary flow demonstration, and does not represent that all the contents, operations and steps in the flow chart are necessarily included in the scheme of the invention, nor does it represent that the execution is necessarily performed in the order shown in the drawings. For example, some operations/steps in the flowcharts may be divided, some operations/steps may be combined or partially combined, and the like, and the execution order shown in the flowcharts may be changed according to actual situations without departing from the gist of the present invention.

The block diagrams in the figures generally represent functional entities and do not necessarily correspond to physically separate entities. I.e. these functional entities may be implemented in the form of software, or in one or more hardware modules or integrated circuits, or in different network and/or processing unit devices and/or microcontroller devices.

The same reference numerals in the respective drawings denote the same or similar elements, components, or parts, and thus a repetitive description thereof may be omitted hereinafter. It will be further understood that, although the terms first, second, third, etc. may be used herein to describe various elements, components, or sections, these elements, components, or sections should not be limited by these terms. That is, these phrases are used only to distinguish one from another. For example, a first device may also be referred to as a second device without departing from the spirit of the present invention. Furthermore, the term "and/or", "and/or" is intended to include all combinations of any one or more of the listed items.

Fig. 1 is a schematic view of an application scenario of an automatic resource allocation method according to an embodiment of the present invention, where the present invention is described by taking an educational institution as an example, and access to resources includes, but is not limited to, visiting users, users 'phones, users' network requests, and the like. As shown in fig. 1, the back-office server ranks the salespersons in advance according to the identification information and behavior data of the salespersons of the education institution, the higher the ranking is, the stronger the sales capability is, when the user logs in the client through the APP of the education institution, the client can acquire the user information, in the process of browsing educational products by the user, the client sends the acquired behavior data of the user to the background server, the user is scored, different meanings are set for the scoring according to different conditions, the purchasing intention of the user can be represented, the quality of the user can also be represented, the higher the scoring is, the stronger the purchasing intention of the user is or the better the quality of the user is, at the moment, the background server automatically distributes the salespersons of corresponding levels to the user according to an intelligent distribution algorithm, and the salespersons provide one-to-one service for the user, so that the probability of purchasing educational products by the user is improved.

The intelligent allocation algorithm automatically allocates the salesmen of different grades to the users with different grades, so that the salesmen of each grade can be allocated to the corresponding users, certain salesmen are not busy and certain salesmen are not in idle states, and the resource utilization rate is improved.

In order that the objects, technical solutions and advantages of the present invention will become more apparent, the present invention will be further described in detail with reference to the accompanying drawings in conjunction with the following specific embodiments.

Fig. 2 is a flowchart illustrating a method for automatically allocating resources according to an embodiment of the present invention, where the method can automatically allocate appropriate resource receiving personnel to an accessing user.

As shown in fig. 2, the method includes:

and S101, evaluating and grading the resource carrying personnel.

In some embodiments, the server stores information for each salesperson, as well as recent salesperson behavior data, and scores the salespersons according to their different performance metrics by entering the salesperson information and behavior data into a trained first scoring model.

After the score of each salesman is obtained, all salesman are graded, according to the overall grading condition, a grading interval is set for each grade, so that the difference of the number of salesman in each grade is not large, for example, 100 salesman are divided into 5 grades, the score is between 0 and 1, the score is [0,0.3) into the 5 th grade, the score is [0.3,0.5) into the 4 th grade, the score is [0.5,0.7) into the 3 rd grade, the score is [0.7,0.85) into the 2 nd grade, and the score is [0.85,1] into the 1 st grade, so as to ensure that the number of salesman in each grade is about 20. The grading quantity and the score interval of each grade can be adjusted at any time according to the salesperson.

And S102, grading the current access resource.

In some embodiments, the method for scoring the visiting user is similar to the method for scoring the salesperson in the above embodiments, after the user logs in the client of the education institution, the server acquires the identity information of the user after the user authorizes the user, such as the age, the academic calendar, the location, the occupation and the income of the user, and in the process of browsing the education products, the server collects the behavior data of the user, such as the time the user stays on a certain education product page, the number of times of clicking a certain education product, and the like, and inputs the identity information and the behavior data of the user into the trained second scoring model, so that the scoring of the user is obtained, wherein the higher the scoring indicates that the quality of the user is better, and the purchase will be higher.

S103, automatically distributing the access resources to resource carrying personnel at corresponding levels according to the scores of the access resources.

In some embodiments, after a user accesses an education institution, the user score needs to be calculated in real time and corresponding sales staff needs to be allocated to the user score, because the number of users accessing the education institution every day is very large, the overall score condition of all users every day cannot be estimated in advance, the proportion of high-ranking customers to high-ranking customers or the proportion of low-ranking customers to low-ranking customers in a certain day is possibly large, in this case, the high-ranking customers cannot be allocated to the high-ranking sales staff according to a certain score, or the low-ranking customers are allocated to the low-ranking sales staff, if most of the high-ranking customers are allocated to the same-ranking sales staff, the sales staff in the ranking is too busy, the customer group loss caused by the failure to meet the user demand is caused, and the sales staff in other rankings are in an idle state, so that the resource utilization rate is low, and the income of the education institution is also influenced.

In order to solve the above problem, the embodiment of the present invention applies a real-time allocation algorithm to evenly allocate new users to the salespeople of each level in real time, so that the number of users allocated to the salespeople of each level is substantially the same.

The scores of the users can be input into a pre-trained allocation model to obtain the resource carrying personnel levels allocated to the users, the allocation model can be obtained by training a machine learning model by using a real-time allocation algorithm according to the most trained samples of the historical users, and the real-time allocation algorithm can also be directly substituted into a common model to be used as the allocation model.

Fig. 3 is a schematic flow chart of a real-time allocation algorithm according to an embodiment of the present invention, and as shown in fig. 3, the real-time allocation algorithm includes the following steps:

and S1031, taking each salesman level as a set, setting an initial average score for each set, wherein the initial average scores of each set are the same, and the initial average scores can be determined by historical experience, for example, the average scores of all users in the previous days are ensured to be smaller than the score difference of the current user.

S1032, setting a threshold value of the number of users for each set, setting a preset numerical value, such as 1%, 5% and the like, of the number of users in each set, wherein the number of users in each set cannot be lower than the average value of the total number of users in all sets, and for the sets lower than the threshold value, the users are preferentially distributed to the set, so that the number of users in each set is guaranteed not to be too different from those in other sets.

S1033, obtaining the score of the current user, respectively calculating the difference between the user score and the average score of each set, and distributing the user to the set with the minimum difference, namely distributing the user score to the set closest to the average score of the set.

Preferably, the step of allocating the current user to the corresponding set specifically includes the following steps:

s10331, sorting all the sets according to the average score from big to small.

S10332, judging the number of the current sets meeting the requirement,

(1) when the number of the sets is only 1, directly allocating the current user to the set;

(2) when the number of the sets is 2, distributing the current user to the set which is closer to the average score;

(3) when the number of the sets is more than 2, judging the relation between the score of the current user and the maximum value and the minimum value of the average score of each set, and if the score of the current user is more than the maximum value of the average score, directly distributing the score of the user to the set with the minimum sequence number; if the score of the current user is smaller than the minimum value of the average score, directly distributing the user score to a set with the largest sequence number; if the score of the current user is between the maximum average score and the minimum average score, the set of the maximum average score and the set of the minimum average score are excluded, and then the steps of S10331 and S10332 are performed again, so that after the user in one day is distributed, a set with sequence numbers arranged from small to large is obtained, and the corresponding average scores are also arranged from small to large. Each time a user' S score is obtained, the steps S10331 and S10332 are performed.

For example, 5 levels of salespeople are currently configured, corresponding to sets 1-5, an initial average score of 0.1 is set for each set, which is equivalent to an initial user, and then the sets 1-5 are respectively expressed as: 1: [1,0.1],2: [1,0.1],3: [1,0.1],4: [1,0.1],5: [1,0.1], wherein the first value in [ ] represents the number of users to which the collection is assigned, the second value represents the current average score for the collection, and the number of users per collection cannot be less than 5% of the average of the total number of users for all collections.

When the first score is 0.16, the user needs to be assigned, the 5 sets are firstly sorted according to the step S10331, the order is not changed because the average scores of the sets are the same at this time, and then according to the step S10331, the user is assigned to the set 1 because 0.16 is larger than the average scores of all the sets at present; at this time, the set 1 is equivalent to two users, the average score is also 0.13, the average value of the total number of all the users in the set is 1.2, and the number of the users in the sets 2-5 is 1 and is lower than the set threshold, so that the second user is only distributed to one of the sets 2-5. When the second score is 0.2 user needs to be assigned, the user is assigned to set 2 according to steps S10331 and S10332, and the algorithm step proceeds, for example, when the 30 th assignment is performed, the current set is sorted according to step S10331 into: 1: [10,0.184000],4: [5,0.160000],2: [6,0.148333],3: [5,0.146000],5: [8,0.113750], the 30 th user score is 0.15, according to the case (3) of step S10332, 0.15 is between the maximum mean 0.184000 and the minimum mean 0.113750, so excluding the corresponding sets 1 and 5, the remaining sets are sorted again according to step S10331, at this time, the remaining sets are 3, according to the case (3) of step S10332, 0.15 is between the maximum mean 0.160000 and the minimum mean 0.146000, so continuing to exclude the corresponding sets 4 and 3, continuing to perform the sorting of the remaining sets according to step S10331, at this time, the remaining sets are 1, according to the case (1) of step S10332, the user is directly assigned to the set 2, and the result after 200 assignments is: 1: [46,0.218913],2: [46,0.187826],3: [32,0.164063],4: [43,0.154884],5: [38,0.100000].

Tables 1-3 are distribution data for different numbers of people (threshold taken to be 1%):

TABLE 1

The number of distributed people: 200	Actual number of persons who are distributed	Actual average score	Ideal number of persons to be distributed	Ideal mean score
					Set 1	41	0.20804878	40	0.23225000
Set 2	46	0.16782609	40	0.20250000
					Set 3	39	0.17230769	40	0.17575000
Set 4	39	0.15871795	40	0.14100000
					Set 5	40	0.13150000	40	0.09650000

TABLE 2

The number of distributed people: 1000	Actual number of persons who are distributed	Actual average score	Ideal number of persons to be distributed	Ideal mean score
					Set 1	198	0.21994949	200	0.23485000
Set 2	215	0.19345455	200	0.20500000
					Set 3	193	0.17155440	200	0.17580000
Set 4	197	0.15000000	200	0.14210000
					Set 5	197	0.11472081	200	0.09660000

TABLE 3

The number of distributed people: 10000	Actual number of persons who are distributed	Actual average score	Ideal number of persons to be distributed	Ideal mean score
					Set 1	1905	0.21994226	2000	0.23512000
Set 2	1903	0.19980032	2000	0.20581000
					Set 3	2388	0.17522357	2000	0.17629000
Set 4	1901	0.15013151	2000	0.14074000
					Set 5	1903	0.10677352	2000	0.09534500

As can be seen from tables 1 to 3, the larger the number of distributed users is, the closer the average value of the sets is to the ideal average value, and the smaller the difference between the number of users distributed to each set and the number of ideal users is, the more recent users can be distributed to sets of different levels.

In addition, different thresholds are set, which also has an influence on the distribution result, the larger the threshold is set, the closer the actual average score of each set is to the ideal average score, but the difference between the number of people distributed to each set becomes large, so that corresponding indexes can be set according to different situations, for example, if the number of users in each set is guaranteed to be average, the threshold is set to be small, and if the number of users distributed to each set is guaranteed to be close to the ideal score, the larger threshold can be set.

Different levels of salesmen can be set, when the number of salesmen is enough, a plurality of levels of salesmen can be set, and the score interval of the salesmen of each level is smaller, so that users with different scores can be more accurately served.

S1034, screening the resource carrying personnel in the idle state from each set to serve the user. After the users are distributed to the corresponding sets, the salespeople in the idle state at present is screened out from the levels corresponding to the sets, one-to-one service is carried out on the users, the salespeople is logged in from the users, the time of the whole process of the server is several milliseconds, and the resource utilization rate is improved.

According to the method, the accessed users are graded through the grading of the resource carrying personnel, the graded users are automatically distributed to the resource carrying personnel of the corresponding grade through the intelligent distribution algorithm to carry out one-to-one service, the distribution efficiency is maximized, the high-quality users can be matched with the resource carrying personnel with strong capacity, the conversion probability of the users is improved, the user experience is improved, and meanwhile the income of education institutions is increased.

Those skilled in the art will appreciate that all or part of the steps to implement the above-described embodiments are implemented as programs (computer programs) executed by a computer data processing apparatus. When the computer program is executed, the method provided by the invention can be realized. Furthermore, the computer program may be stored in a computer readable storage medium, which may be a readable storage medium such as a magnetic disk, an optical disk, a ROM, a RAM, or a storage array composed of a plurality of storage media, such as a magnetic disk or a magnetic tape storage array. The storage medium is not limited to centralized storage, but may be distributed storage, such as cloud storage based on cloud computing.

Embodiments of the apparatus of the present invention are described below, which may be used to perform method embodiments of the present invention. The details described in the device embodiments of the invention should be regarded as complementary to the above-described method embodiments; reference is made to the above-described method embodiments for details not disclosed in the apparatus embodiments of the invention.

Fig. 4 is a schematic diagram of an apparatus for automatically allocating resources according to an embodiment of the present invention, as shown in fig. 4, the apparatus 200 includes:

a resource carrying person grading module 201, configured to evaluate and grade resource carrying persons;

an access resource scoring module 202, configured to score a current access resource;

and the resource automatic allocation module 203 is configured to automatically allocate the access resources to resource carrying personnel at corresponding levels according to the scores of the access resources.

The resource carrying person grading module 201 is further configured to input the identity information and the behavior data of the resource carrying person into the trained first scoring model, and output a score of the resource carrying person; setting a grading interval corresponding to each level of the resource carrying personnel; and setting a corresponding grade for the resource accepting personnel according to the resource accepting personnel scores.

The access resource scoring module 202 is further configured to input the identity information and the behavior data of the current user in the access resource into the trained second scoring model, and output the score of the user.

The automatic resource allocation module 203 is further configured to input the score of the user into a pre-trained allocation model to obtain a resource carrying staff level allocated to the user; wherein the pre-trained assignment model is obtained by: taking the scores of the historical users output by the scoring model as samples, taking the resource carrying personnel grades distributed by the historical users as labels, and training the model by using a real-time distribution algorithm to obtain a trained distribution model; and screening the resource carrying personnel in the idle state from the resource carrying personnel level to serve the user. The automatic resource allocation module 203 is further configured to set an initial average score for each of the levels according to historical data, and set a threshold for the number of users for each of the levels; obtaining the score of the current user, and respectively calculating the difference between the score and the average score of each grade; assigning the current user to the level with the smallest difference. The automatic resource allocation module 203 is further configured to detect whether the number of users currently included in each of the levels is lower than the threshold number of users in real time; if the number of the included users is detected to be lower than the level of the user number threshold, respectively calculating the difference between the current user score and the average score of each level lower than the user number threshold, and distributing the current user to the level with the minimum difference in the levels lower than the threshold. After the current user is allocated to the level with the minimum difference, the automatic resource allocation module 203 is further configured to calculate an average score of user scores in each level; sorting the levels according to the sequence of average grading of the users of all levels from big to small; and acquiring the score of the next user, respectively calculating the difference between the score of the user and the average score of each ranked level, and distributing the user to the corresponding level according to the difference until all the users are distributed. The user number threshold is a preset numerical value that the number of users at each level is not lower than the average value of the total number of users at all levels.

Fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present invention, where the electronic device includes a processor and a memory, where the memory is used to store a computer-executable program, and when the computer program is executed by the processor, the processor executes a teaching video automatic clipping method.

As shown in fig. 5, the electronic device is in the form of a general purpose computing device. The processor can be one or more and can work together. The invention also does not exclude that distributed processing is performed, i.e. the processors may be distributed over different physical devices. The electronic device of the present invention is not limited to a single entity, and may be a sum of a plurality of entity devices.

The memory stores a computer executable program, typically machine readable code. The computer readable program may be executed by the processor to enable an electronic device to perform the method of the invention, or at least some of the steps of the method.

The memory may include volatile memory, such as Random Access Memory (RAM) and/or cache memory, and may also be non-volatile memory, such as read-only memory (ROM).

Optionally, in this embodiment, the electronic device further includes an I/O interface, which is used for data exchange between the electronic device and an external device. The I/O interface may be any suitable device or interface and represent one or more of several levels of bus structures, including a memory unit bus or memory unit controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.

It should be understood that the electronic device shown in fig. 5 is only one example of the present invention, and elements or components not shown in the above example may be further included in the electronic device of the present invention. For example, some electronic devices further include a display unit such as a display screen, and some electronic devices further include a human-computer interaction element such as a button, a keyboard, and the like. Electronic devices are considered to be covered by the present invention as long as the electronic devices are capable of executing a computer-readable program in a memory to implement the method of the present invention or at least a part of the steps of the method.

Fig. 6 is a schematic diagram of a computer-readable recording medium provided by an embodiment of the present invention. As shown in fig. 6, the computer-readable recording medium has stored therein a computer-executable program which, when executed, implements the above-described teaching video automatic clipping method of the present invention. The computer readable storage medium may include a propagated data signal with readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A readable storage medium may also be any readable medium that is not a readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a readable storage medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

The computer readable medium carries one or more programs which, when executed by a device, cause the computer readable medium to perform the functions of: evaluating and grading the resource carrying personnel; scoring the current access resource; and automatically allocating the access resources to resource carrying personnel at corresponding levels according to the scores of the access resources.

Program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C + + or the like and conventional procedural programming languages, such as the "C" programming language or hierarchical programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device and partly on a remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any of a variety of levels of networks, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computing device (e.g., through the internet using an internet service provider).

From the above description of the embodiments, those skilled in the art will readily appreciate that the present invention can be implemented by hardware capable of executing a specific computer program, such as the system of the present invention, and electronic processing units, servers, clients, mobile phones, control units, processors, etc. included in the system. The invention may also be implemented by computer software for performing the method of the invention. It should be noted, however, that the computer software for executing the method of the present invention is not limited to be executed by one or a specific hardware entity, but may also be implemented in a distributed manner by hardware entities without specific details, for example, some method steps executed by a computer program may be executed by a mobile client, and another part may be executed by a smart meter, a smart pen, or the like. For computer software, the software product may be stored in a computer readable storage medium (which may be a CD-ROM, a usb disk, a removable hard disk, etc.) or may be distributed over a network, as long as it enables the electronic device to perform the method according to the present invention.

In summary, the invention may be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. Those skilled in the art will appreciate that some or all of the functionality of some or all of the components in embodiments in accordance with the invention may be implemented in practice using a general purpose data processing device such as a microprocessor or a Digital Signal Processor (DSP). The present invention may also be embodied as apparatus or device programs (e.g., computer programs and computer program products) for performing a portion or all of the methods described herein. Such programs implementing the present invention may be stored on computer-readable media or may be in the form of one or more signals. Such a signal may be downloaded from an internet website or provided on a carrier signal or in any other form.

While the foregoing embodiments have described the objects, aspects and advantages of the present invention in further detail, it should be understood that the present invention is not inherently related to any particular computer, virtual machine or electronic device, and various general-purpose machines may be used to implement the present invention. The invention is not to be considered as limited to the specific embodiments thereof, but is to be understood as being modified in all respects, all changes and equivalents that come within the spirit and scope of the invention.

Claims

1. A method for automatically allocating resources, comprising:

evaluating and grading the resource carrying personnel;

scoring the current access resource;

2. The method according to claim 1, wherein the step of rating the resource accepting person further comprises:

inputting the identity information and the behavior data of the resource carrying personnel into a trained first scoring model, and outputting the score of the resource carrying personnel;

3. The method of claim 1, wherein the step of scoring the current access resource comprises:

4. The method according to claim 3, wherein the step of automatically allocating the access resource to the resource accepting person of the corresponding level according to the score of the access resource further comprises:

5. The method according to claim 4, wherein the step of inputting the user's score into a pre-trained allocation model to obtain the level of resource-accepting person allocated to the user further comprises:

assigning the current user to the level with the smallest difference.

6. The method of claim 5, wherein the step of assigning the current user to the level with the minimum difference further comprises:

7. The method of claim 5, wherein after assigning the current user to the level with the smallest difference, the method further comprises:

calculating an average score of the user scores in each level;

8. The method of claim 5, wherein the threshold number of users is a preset number that the number of users in each level is not lower than the average number of users in all levels.

9. An apparatus for automatically allocating resources, comprising:

10. An electronic device comprising a processor and a memory, the memory for storing a computer-executable program, characterized in that:

the computer program, when executed by the processor, performs the method of any one of claims 1-8.