CN111901485A - Control method and device of outbound system - Google Patents
Control method and device of outbound system Download PDFInfo
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- CN111901485A CN111901485A CN202010806918.0A CN202010806918A CN111901485A CN 111901485 A CN111901485 A CN 111901485A CN 202010806918 A CN202010806918 A CN 202010806918A CN 111901485 A CN111901485 A CN 111901485A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04M—TELEPHONIC COMMUNICATION
- H04M3/00—Automatic or semi-automatic exchanges
- H04M3/42—Systems providing special services or facilities to subscribers
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N20/00—Machine learning
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04M—TELEPHONIC COMMUNICATION
- H04M3/00—Automatic or semi-automatic exchanges
- H04M3/42—Systems providing special services or facilities to subscribers
- H04M3/50—Centralised arrangements for answering calls; Centralised arrangements for recording messages for absent or busy subscribers ; Centralised arrangements for recording messages
Abstract
The invention discloses a control method and a device of an outbound system, wherein the method comprises the following steps: obtaining an outbound service list of an outbound system, wherein the outbound service list comprises: a plurality of users to be called; determining outbound time preference information of each user to be called in an outbound service list at different time points by using a pre-trained machine learning model; and controlling the outbound system to execute the outbound service task according to the outbound time preference information of each user to be called at different time points. The method and the device predict the outbound time preference information of each user to be called by using the machine learning model, can dynamically adjust the sequence of the outbound users at each time point based on the user time preference, can improve the user experience of the outbound system, and can enable the outbound service of the outbound system to achieve the maximum benefit.
Description
Technical Field
The invention relates to the field of software, in particular to a control method and a control device of an outbound system.
Background
This section is intended to provide a background or context to the embodiments of the invention that are recited in the claims. The description herein is not admitted to be prior art by inclusion in this section.
The intelligent outbound is imported into the user list after the outbound flow and the call are set, and dialing can be performed one by one according to the sequence of the user list, and the user preference, especially the time preference, is not considered in the set of flows from the aspect of user experience. Because the served willingness of the users of different ages and different jobs to receive the outbound call at different time points is different, the existing outbound call system adopts a fixed outbound call sequence, and the condition of calling the user at an improper time point can occur, thereby causing the problem of user dislike and failing to achieve the optimal benefit of the whole outbound call task.
In view of the above problems, no effective solution has been proposed.
Disclosure of Invention
The embodiment of the invention provides a control method of an outbound system, which is used for solving the technical problem that the existing outbound system calls by adopting a fixed outbound sequence and is easy to call users at improper time points, and comprises the following steps: obtaining an outbound service list of an outbound system, wherein the outbound service list comprises: a plurality of users to be called; determining outbound time preference information of each user to be called in an outbound service list at different time points by using a pre-trained machine learning model; and controlling the outbound system to execute the outbound service task according to the outbound time preference information of each user to be called at different time points.
The embodiment of the invention also provides a control device of the outbound system, which is used for solving the technical problem that the existing outbound system calls by adopting a fixed outbound sequence and is easy to call users at improper time points, and the device comprises: the system comprises an outbound service list acquisition module, a call-out service list acquisition module and a call-out service list acquisition module, wherein the outbound service list acquisition module is used for acquiring an outbound service list of an outbound system, and the outbound service list comprises: a plurality of users to be called; the outbound time preference information prediction module is used for determining the outbound time preference information of each user to be called in the outbound service list at different time points by utilizing a pre-trained machine learning model; and the outbound system control module is used for controlling the outbound system to execute the outbound service task according to the outbound time preference information of each user to be called at different time points.
The embodiment of the invention also provides computer equipment for solving the technical problem that the existing outbound system adopts a fixed outbound sequence to call and is easy to call a user at an improper time point.
An embodiment of the present invention further provides a computer-readable storage medium, which is used to solve the technical problem that a user is easily called at an inappropriate time point when an existing outbound system calls in a fixed outbound sequence, and the computer-readable storage medium stores a computer program for executing the control method of the outbound system.
In the embodiment of the invention, after the outbound service list of the outbound system is acquired, the pre-trained machine learning model is utilized to determine the outbound time preference information of each user to be called in the outbound service list at different time points, and then the outbound system is controlled to execute the outbound service task according to the outbound time preference information of each user to be called at different time points.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts. In the drawings:
fig. 1 is a flowchart of a control method of an outbound call system according to an embodiment of the present invention;
fig. 2 is a flowchart of a control method of an alternative outbound system provided in an embodiment of the present invention;
fig. 3 is a schematic diagram of a control device of an outbound call system according to an embodiment of the present invention;
fig. 4 is a schematic diagram of a control apparatus of an alternative outbound system provided in an embodiment of the present invention;
fig. 5 is a schematic diagram of a computer device provided in an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the embodiments of the present invention are further described in detail below with reference to the accompanying drawings. The exemplary embodiments and descriptions of the present invention are provided to explain the present invention, but not to limit the present invention.
The embodiment of the present invention provides a control method of an outbound system, fig. 1 is a flowchart of the control method of the outbound system provided in the embodiment of the present invention, and as shown in fig. 1, the method includes the following steps:
s101, an outbound service list of an outbound system is obtained, wherein the outbound service list comprises: a plurality of subscribers to be called.
It should be noted that the list of the outbound services in S101 includes: the plurality of users to be called by the outbound system, each user to be called in the outbound service list may be pre-configured, or may be the remaining users after the outbound system has called a part of users.
And S102, determining outbound time preference information of each user to be called in the outbound service list at different time points by using a pre-trained machine learning model.
Since it takes a certain time for each subscriber to be called by the outbound system, in one embodiment, the above S102 may be implemented by the following steps: acquiring an outbound service time period of an outbound system; dividing an outbound service time period into a plurality of time intervals according to a preset time interval; and determining the outbound time preference information of each user to be called in the outbound service list in each time interval by using a pre-trained machine learning model.
Optionally, the machine learning model adopted in the embodiment of the present invention is a LightGBM model. The LigthGBM model is a gradient Boosting framework and uses a learning algorithm based on a decision tree. It can be said to be distributed, high-efficient, has the following advantage: faster training efficiency; low memory usage; higher accuracy; support parallelization learning; large-scale data can be processed, etc.
And S103, controlling the outbound system to execute the outbound service task according to the outbound time preference information of each user to be called at different time points.
It should be noted that, in the embodiment of the present invention, in order to implement quantitative evaluation on the preference information of the outbound time of each user, a will value is introduced, and different preference levels of the outbound time are represented by the will value. Thus, in one embodiment, the outbound time preference information determined in the embodiment of the present invention at least includes: a willingness value; the willingness values of the users to be called at different time points are determined through the S102, and then the outbound system is controlled to execute the outbound service task according to the willingness values of the users to be called at different time points through the S103.
In one example, as shown in fig. 2, the above S103 may be implemented by the following steps:
s1031, acquiring the willingness value of each user to be called at the time point of waiting calling, and determining a first alternative user and a second alternative user called by the outbound system at the time point of waiting calling according to the willingness value of each user to be called at the time point of waiting calling, wherein the first alternative user is the user to be called with the largest willingness value, and the second alternative user is the user to be called of which the willingness value is only smaller than that of the first alternative user;
s1032, if the first difference value between the maximum will value of the first alternative user at each time point and the will value of the first alternative user at the time point of waiting for calling is less than or equal to the second difference value between the will value of the first alternative user at the time point of waiting for calling and the will value of the second alternative user at the time point of waiting for calling, controlling the outbound system to call the first alternative user at the time point of waiting for calling;
s1033, if a first difference value between the maximum will value of the first alternative user at each time point and the will value of the first alternative user at the waiting call time point is larger than a second difference value between the will value of the first alternative user at the waiting call time point and the will value of the second alternative user at the waiting call time point, controlling the outbound system to call the second alternative user at the waiting call time point.
From the above, the embodiment of the present invention provides a method for controlling an outbound system, which, after obtaining an outbound service list of the outbound system, determining outbound time preference information of each user to be called in an outbound service list at different time points by using a machine learning model trained in advance, further controlling the outbound system to execute the outbound service task according to the outbound time preference information of each user to be called at different time points, compared with the outbound system which adopts a fixed outbound sequence to call in the prior art, the embodiment of the invention utilizes the machine learning model to predict the outbound time preference information of each user to be called, can be based on the user time preference, the order of the outbound users is dynamically adjusted at each time point, so that the user experience of the outbound system can be improved, and the outbound service of the outbound system can achieve the maximum benefit.
The control method of the outbound system provided by the embodiment of the invention comprises the following two aspects in specific implementation:
firstly, an intelligent outbound time interval (working time) allowed by a policy is divided in half an hour, the traditional intelligent outbound and manual outbound data are collected, and the traditional intelligent outbound and manual outbound data comprise basic user information such as working age and the like, account information such as balance and the like, transaction information such as admission and payment conditions and the like, outbound time, outbound type (input data used as a model) and whether outbound is successful (1 is successful and 0 is failed) (target label and value predicted by the model), and a machine learning algorithm such as lightGBM (model structure is tree model and automatic splitting) is used for modeling.
Secondly, when an outbound task list is imported, the willingness values of all users at all time points are immediately calculated by using a model, the predicted probability value is taken, the value range is between 0 and 1, and the conversion into 0 or 1 is not needed. In the process of executing the outbound task, when a next outbound user needs to be selected, selecting the outbound users one by one according to the following principle according to the current time point (each outbound task time takes task evaluation interaction time): the will value of the user at the current time point is the maximum among all users; the difference value between the willingness value of the user at the current time point and the maximum willingness value of the user at all time points is not larger than the difference value between the willingness value of the user at the current time point and the second willingness value ranked at the current time point.
Supposing that the users with willingness values of the waiting calling time points ranked in the second order are U1 and U2, the willingness values are A, B respectively, the maximum willingness value of U1 at all the time points is C, and judging whether C-A is less than or equal to A-B; if the answer is satisfied, selecting U1 as the user of the calling system at the waiting calling time point; on the contrary, the U2 is selected as the user of the outbound system calling at the waiting call time point, in the embodiment of the invention, the method of dynamically selecting the next outbound user can ensure that the total willingness value of the final outbound task is maximum, and the best benefit of the outbound service is achieved on the premise of improving the user experience.
Based on the same inventive concept, the embodiment of the present invention further provides a control device of an outbound system, as described in the following embodiments. Because the principle of the device for solving the problems is similar to the control method of the outbound system, the implementation of the device can refer to the implementation of the control method of the outbound system, and repeated parts are not described again.
Fig. 3 is a schematic diagram of a control apparatus of an outbound system according to an embodiment of the present invention, and as shown in fig. 3, the apparatus may include: an outbound service list acquisition module 31, an outbound time preference information prediction module 32 and an outbound system control module 33.
The outbound service list obtaining module 31 is configured to obtain an outbound service list of an outbound system, where the outbound service list includes: a plurality of users to be called; the outbound time preference information prediction module 32 is used for determining the outbound time preference information of each user to be called in the outbound service list at different time points by using a pre-trained machine learning model; and the outbound system control module 33 is configured to control the outbound system to execute the outbound service task according to the outbound time preference information of each user to be called at different time points.
As can be seen from the above, the embodiment of the present invention provides a control apparatus for an outbound system, which obtains an outbound service list of the outbound system through the outbound service list obtaining module 31; determining outbound time preference information of each user to be called in an outbound service list at different time points by using a pre-trained machine learning model through an outbound time preference information prediction module 32; the outbound system control module 33 controls the outbound system to execute the outbound service task according to the outbound time preference information of each user to be called at different time points, and compared with the outbound system which adopts a fixed outbound sequence to call in the prior art, the outbound system provided by the embodiment of the invention predicts the outbound time preference information of each user to be called by using a machine learning model, can dynamically adjust the sequence of the outbound users at each time point based on the user time preference, can improve the user experience of the outbound system, and can enable the outbound service of the outbound system to achieve the maximum benefit.
In one embodiment, the outbound time preference information prediction module 32 is further configured to: acquiring an outbound service time period of an outbound system; dividing an outbound service time period into a plurality of time intervals according to a preset time interval; and determining the outbound time preference information of each user to be called in the outbound service list in each time interval by using a pre-trained machine learning model.
Optionally, the machine learning model adopted by the outbound time preference information prediction module 32 in the embodiment of the present invention is a LightGBM model.
In specific implementation, in the embodiment of the present invention, the wish value is used to represent the outbound time preference information of each to-be-called user, so in an embodiment, as shown in fig. 4, the outbound system control module 33 may specifically include: a user screening module 331, a first execution module 332 and a second execution module 333.
The user screening module 331 is configured to obtain an intention value of each to-be-called user at a to-be-called time point, and determine a first alternative user and a second alternative user, which are called by the outbound system at the to-be-called time point, according to the intention value of each to-be-called user at the to-be-called time point, where the first alternative user is the to-be-called user with the largest intention value, and the second alternative user is the to-be-called user whose intention value is only smaller than that of the first alternative user; a first executing module 332, configured to control the outbound system to call the first alternative user at the time point to be called if a first difference between a maximum will value of the first alternative user at each time point and a will value of the first alternative user at the time point to be called is less than or equal to a second difference between the will value of the first alternative user at the time point to be called and a will value of the second alternative user at the time point to be called; a second executing module 333, configured to control the outbound system to call the second alternative user at the time point of the waiting call if a first difference between the maximum will value of the first alternative user at each time point and the will value of the first alternative user at the time point of the waiting call is greater than a second difference between the will value of the first alternative user at the time point of the waiting call and the will value of the second alternative user at the time point of the waiting call.
Based on the same inventive concept, the embodiment of the present invention further provides a computer device, so as to solve the technical problem that the existing outbound system calls in a fixed outbound sequence, and a user is easily called at an inappropriate time point, fig. 5 is a schematic diagram of the computer device provided in the embodiment of the present invention, as shown in fig. 5, the computer device includes a memory 501, a processor 502, and a computer program stored on the memory 501 and operable on the processor 502, and the processor 502 implements the control method of the outbound system when executing the computer program.
Based on the same inventive concept, an embodiment of the present invention further provides a computer-readable storage medium, for solving the technical problem that the existing outbound system calls in a fixed outbound sequence, and is easy to call a user at an inappropriate time point, where the computer-readable storage medium stores a computer program for executing the control method of the outbound system.
In summary, embodiments of the present invention provide a method, an apparatus, a computer device, and a computer readable storage medium for controlling an outbound system, and a method for intelligently adjusting an outbound user sequence based on user time preference, and according to the time preference of a user for receiving an outbound service, calculate a success rate of each user for receiving a service at each time point, calculate a service success rate of a whole outbound task, adjust a dialing sequence of an outbound call according to a best success rate, and achieve an optimal benefit of the outbound service on the premise of improving user experience.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The above-mentioned embodiments are intended to illustrate the objects, technical solutions and advantages of the present invention in further detail, and it should be understood that the above-mentioned embodiments are only exemplary embodiments of the present invention, and are not intended to limit the scope of the present invention, and any modifications, equivalent substitutions, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (10)
1. A method for controlling an outbound call system, comprising:
obtaining an outbound service list of an outbound system, wherein the outbound service list comprises: a plurality of users to be called;
determining outbound time preference information of each user to be called in the outbound service list at different time points by using a pre-trained machine learning model;
and controlling the outbound system to execute the outbound service task according to the outbound time preference information of each user to be called at different time points.
2. The method of claim 1, wherein determining outbound time preference information of each subscriber to be called in the outbound service list at different time points by using a pre-trained machine learning model comprises:
acquiring an outbound service time period of the outbound system;
dividing the outbound service time period into a plurality of time intervals according to a preset time interval;
and determining the outbound time preference information of each user to be called in the outbound service list in each time interval by using a pre-trained machine learning model.
3. The method of claim 1, wherein the outbound time preference information comprises: a willingness value; the method for controlling the outbound system to execute the outbound service task according to the outbound time preference information of each user to be called at different time points comprises the following steps:
acquiring the willingness value of each user to be called at the time point of waiting for calling, and determining a first alternative user and a second alternative user called by an outbound system at the time point of waiting for calling according to the willingness value of each user to be called at the time point of waiting for calling, wherein the first alternative user is the user to be called with the largest willingness value, and the second alternative user is the user to be called of which the willingness value is only smaller than that of the first alternative user;
if a first difference value between the maximum will value of the first alternative user at each time point and the will value of the first alternative user at the time point of waiting for calling is smaller than or equal to a second difference value between the will value of the first alternative user at the time point of waiting for calling and the will value of the second alternative user at the time point of waiting for calling, controlling an outbound system to call the first alternative user at the time point of waiting for calling;
and if a first difference value between the maximum will value of the first alternative user at each time point and the will value of the first alternative user at the time point of waiting for calling is larger than a second difference value between the will value of the first alternative user at the time point of waiting for calling and the will value of the second alternative user at the time point of waiting for calling, controlling an outbound system to call the second alternative user at the time point of waiting for calling.
4. The method of any of claims 1 to 3, wherein the machine learning model is a LightGBM model.
5. A control apparatus for an outbound system, comprising:
an outbound service list obtaining module, configured to obtain an outbound service list of an outbound system, where the outbound service list includes: a plurality of users to be called;
the outbound time preference information prediction module is used for determining the outbound time preference information of each user to be called in the outbound service list at different time points by utilizing a pre-trained machine learning model;
and the outbound system control module is used for controlling the outbound system to execute the outbound service task according to the outbound time preference information of each user to be called at different time points.
6. The apparatus of claim 5, wherein the outbound time preference information prediction module is further to: acquiring an outbound service time period of the outbound system; dividing the outbound service time period into a plurality of time intervals according to a preset time interval; and determining the outbound time preference information of each user to be called in the outbound service list in each time interval by using a pre-trained machine learning model.
7. The apparatus of claim 5, wherein the outbound time preference information comprises: a willingness value; wherein, the outbound system control module comprises:
the system comprises a user screening module, a calling module and a calling module, wherein the user screening module is used for acquiring the willingness value of each user to be called at the time point of waiting calling, and determining a first alternative user and a second alternative user called by an outbound system at the time point of waiting calling according to the willingness value of each user to be called at the time point of waiting calling, the first alternative user is the user to be called with the largest willingness value, and the second alternative user is the user to be called of which the willingness value is only smaller than that of the first alternative user;
the system comprises a user screening module, a calling module and a calling module, wherein the user screening module is used for acquiring the willingness value of each user to be called at the time point of waiting calling, and determining a first alternative user and a second alternative user called by an outbound system at the time point of waiting calling according to the willingness value of each user to be called at the time point of waiting calling, the first alternative user is the user to be called with the largest willingness value, and the second alternative user is the user to be called of which the willingness value is only smaller than that of the first alternative user;
a first execution module, configured to control an outbound system to call the first alternative user at the time point to be called if a first difference between a maximum will value of the first alternative user at each time point and a will value of the first alternative user at the time point to be called is less than or equal to a second difference between a will value of the first alternative user at the time point to be called and a will value of the second alternative user at the time point to be called;
and the second execution module is used for controlling the outbound system to call the second alternative user at the time point to be called if a first difference value between the maximum will value of the first alternative user at each time point and the will value of the first alternative user at the time point to be called is greater than a second difference value between the will value of the first alternative user at the time point to be called and the will value of the second alternative user at the time point to be called.
8. The apparatus of any of claims 5 to 7, wherein the machine learning model is a LightGBM model.
9. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements a method of controlling a callout system according to any one of claims 1 to 4 when executing the computer program.
10. A computer-readable storage medium characterized in that the computer-readable storage medium stores a computer program for executing the control method of the outbound system of any one of claims 1 to 4.
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| CN114125154A (en) * | 2021-11-12 | 2022-03-01 | 杭州摸象大数据科技有限公司 | Outbound policy parameter adjusting method and device, computer equipment and storage medium |
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| CN109698875A (en) * | 2018-08-27 | 2019-04-30 | 平安科技（深圳）有限公司 | Calling-out method, system, equipment and computer readable storage medium |
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| CN110166632A (en) * | 2019-04-15 | 2019-08-23 | 中国平安人寿保险股份有限公司 | Intelligent outgoing call processing method, device, computer equipment and storage medium |
| CN111343345A (en) * | 2020-02-28 | 2020-06-26 | 携程计算机技术（上海）有限公司 | Management method, system, electronic equipment and medium for outgoing call of hotel order |
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| CN112446556A (en) * | 2021-01-27 | 2021-03-05 | 电子科技大学 | Communication network user calling object prediction method based on expression learning and behavior characteristics |
| CN113163063A (en) * | 2021-04-30 | 2021-07-23 | 重庆度小满优扬科技有限公司 | Intelligent outbound call system and method |
| CN113938566A (en) * | 2021-10-21 | 2022-01-14 | 北京淇瑀信息科技有限公司 | Task execution method and device and electronic equipment |
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