CN113225436B - Call control method, device, electronic equipment, storage medium and program product - Google Patents
Call control method, device, electronic equipment, storage medium and program product Download PDFInfo
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- CN113225436B CN113225436B CN202110592993.6A CN202110592993A CN113225436B CN 113225436 B CN113225436 B CN 113225436B CN 202110592993 A CN202110592993 A CN 202110592993A CN 113225436 B CN113225436 B CN 113225436B
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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
- H04M3/51—Centralised call answering arrangements requiring operator intervention, e.g. call or contact centers for telemarketing
- H04M3/5141—Details of processing calls and other types of contacts in an unified manner
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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
- H04M3/436—Arrangements for screening incoming calls, i.e. evaluating the characteristics of a call before deciding whether to answer it
- H04M3/4365—Arrangements for screening incoming calls, i.e. evaluating the characteristics of a call before deciding whether to answer it based on information specified by the calling party, e.g. priority or subject
Abstract
The embodiment of the disclosure discloses a call control method, a call control device, an electronic device, a storage medium and a program product, wherein the method comprises the following steps: acquiring a called object set, wherein the called object set comprises one or more called objects, the difference value between the call completion rate of the one or more called objects and a reference call completion rate is smaller than a preset call completion rate threshold value, and the reference call completion rate corresponds to the called object set; determining the number of called objects according to the reference call-through rate and the number of calling objects corresponding to the called object set; and taking out the called number of the target called object in the number of the called objects from the called object set to call. The technical scheme can acquire relatively stable call completion rate estimation data and carry out calling on the basis, and the technical scheme eliminates uncertain factors caused by uncertainty of whether the called user is called through or not to a great extent, thereby being beneficial to scheduling of calling work by a calling party and improving the working efficiency of the calling party.
Description
Technical Field
The present disclosure relates to the field of call control technologies, and in particular, to a call control method, an apparatus, an electronic device, a storage medium, and a program product.
Background
With the development of science and technology, users can seek services for various platforms through the channels of networks, telephones and the like, and service providers can often communicate with the users through the networks or the telephones, receive the consultation of the users, acquire the requirements of the users, solve the problems of the users and provide help for the users. However, in practical applications, due to poor communication network signals, busy users or other reasons, when a service provider calls a user, not all called users can be called, and although a call center is arranged in the prior art, only the called user called by the call center can be forwarded to a calling party to improve the working efficiency of the calling party, there is an uncertain factor caused by uncertainty of whether the called user can be called, which is not favorable for the scheduling of the calling party for the calling work and the improvement of the working efficiency of the calling party.
Disclosure of Invention
The embodiment of the disclosure provides a call control method, a call control device, an electronic device, a storage medium and a program product.
In a first aspect, a call control method is provided in an embodiment of the present disclosure.
Specifically, the call control method includes:
acquiring a called object set, wherein the called object set comprises one or more called objects, the difference value between the call completion rate of the one or more called objects and a reference call completion rate is smaller than a preset call completion rate threshold value, and the reference call completion rate corresponds to the called object set;
determining the number of called objects according to the reference call completing rate and the number of calling objects corresponding to the called object set;
and taking out the called number of the target called object in the number of the called objects from the called object set to call.
With reference to the first aspect, in a first implementation manner of the first aspect, the obtaining a called object set includes:
determining a reference call-through rate;
estimating the call-through rate of the called object;
and setting the called objects of which the difference value between the call completion rate and the reference call completion rate is smaller than the preset call completion rate threshold value as belonging to the same called object set.
With reference to the first aspect and the first implementation manner of the first aspect, in a second implementation manner of the first aspect, the obtaining a called object set includes:
estimating the call-through rate of the called object;
clustering the called objects according to the call completing rate to obtain one or more called object sets;
and setting the average call completion rate of all the called objects in the called object set as the reference call completion rate of the called object set.
With reference to the first aspect, the first implementation manner of the first aspect, and the second implementation manner of the first aspect, in a third implementation manner of the first aspect, the estimating a call completion rate of the called object includes:
acquiring characteristic data of the called object;
and inputting the characteristic data of the called object into a pre-trained call completion rate estimation model to obtain the estimated call completion rate of the called object.
With reference to the first aspect, the first implementation manner of the first aspect, the second implementation manner of the first aspect, and the third implementation manner of the first aspect, in a fourth implementation manner of the first aspect, the present disclosure further includes:
and training the call-through rate estimation model.
With reference to the first aspect, the first implementation manner of the first aspect, the second implementation manner of the first aspect, the third implementation manner of the first aspect, and the fourth implementation manner of the first aspect, in a fifth implementation manner of the first aspect, the training of the call-through rate estimation model includes:
determining an initial call-through rate estimation model;
acquiring a call completing rate training data set, wherein the call completing rate training data set comprises historical characteristic data of a called object and historical call completing rate data corresponding to the historical characteristic data;
and training the initial call-through rate estimation model by taking the historical characteristic data of the called object as input and the historical call-through rate data corresponding to the historical characteristic data as output to obtain the call-through rate estimation model.
With reference to the first aspect, the first implementation manner of the first aspect, the second implementation manner of the first aspect, the third implementation manner of the first aspect, the fourth implementation manner of the first aspect, and the fifth implementation manner of the first aspect, in a sixth implementation manner of the first aspect, the present disclosure further includes:
and adding the characteristic data of the called object and the estimated call-through rate corresponding to the characteristic data as new training data into a call-through rate training data set of the call-through rate estimation model, and training the call-through rate estimation model.
With reference to the first aspect, the first implementation manner of the first aspect, the second implementation manner of the first aspect, the third implementation manner of the first aspect, the fourth implementation manner of the first aspect, the fifth implementation manner of the first aspect, and the sixth implementation manner of the first aspect, in a seventh implementation manner of the first aspect, the determining the number of called objects according to the reference call-through rate and the number of calling objects corresponding to the set of called objects includes:
and dividing the number of the calling objects by the reference call-through rate corresponding to the called object set to obtain the number of the called objects.
With reference to the first aspect, the first implementation manner of the first aspect, the second implementation manner of the first aspect, the third implementation manner of the first aspect, the fourth implementation manner of the first aspect, the fifth implementation manner of the first aspect, the sixth implementation manner of the first aspect, and the seventh implementation manner of the first aspect, in an eighth implementation manner of the first aspect, the disclosure further includes:
and switching the called target object to the calling object.
With reference to the first aspect, the first implementation manner of the first aspect, the second implementation manner of the first aspect, the third implementation manner of the first aspect, the fourth implementation manner of the first aspect, the fifth implementation manner of the first aspect, the sixth implementation manner of the first aspect, the seventh implementation manner of the first aspect, and the eighth implementation manner of the first aspect, in a ninth implementation manner of the first aspect, the present disclosure further includes:
when the calling number of the target called object is larger than the calling object number, determining a first difference number between the calling object number and the calling number of the target called object, and keeping the calling state of the target called object with the first difference number until one or more calling objects end the current call;
when the number of the calling of the target called object is smaller than the number of the calling objects, determining a second difference value number between the number of the calling objects and the number of the calling of the target called object, determining the number of candidate called objects according to the second difference value number and a reference calling rate corresponding to the called object set, and taking out the called number of the target called object with the number of the candidate called objects from the called object set to call.
In a second aspect, a call control device is provided in an embodiment of the present disclosure.
Specifically, the call control device includes:
the system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is configured to acquire a called object set, the called object set comprises one or more called objects, the difference value between the call completion rate of the one or more called objects and a reference call completion rate is smaller than a preset call completion rate threshold value, and the reference call completion rate corresponds to the called object set;
the determining module is configured to determine the number of the called objects according to the reference calling rate and the number of the calling objects corresponding to the called object set;
and the calling module is configured to take out the called numbers of the target called objects in the number of the called objects from the called object set to call.
With reference to the second aspect, in a first implementation manner of the second aspect, the obtaining module is configured to:
determining a reference call-through rate;
estimating the call-through rate of the called object;
and setting the called objects with the difference value between the call completion rate and the reference call completion rate smaller than the preset call completion rate threshold value as belonging to the same called object set.
With reference to the second aspect and the first implementation manner of the second aspect, in a second implementation manner of the second aspect, the obtaining module is configured to:
estimating the call-through rate of the called object;
clustering the called objects according to the call completing rate to obtain one or more called object sets;
and setting the average call completion rate of all the called objects in the called object set as the reference call completion rate of the called object set.
With reference to the second aspect, the first implementation manner of the second aspect, and the second implementation manner of the second aspect, in a third implementation manner of the second aspect, the estimating the call completion rate of the called object is configured to:
acquiring characteristic data of the called object;
and inputting the characteristic data of the called object into a pre-trained call-through rate estimation model to obtain the estimated call-through rate of the called object.
With reference to the second aspect, the first implementation manner of the second aspect, the second implementation manner of the second aspect, and the third implementation manner of the second aspect, in a fourth implementation manner of the second aspect, the present disclosure further includes:
a training module configured to train the call-through rate estimation model.
With reference to the second aspect, the first implementation manner of the second aspect, the second implementation manner of the second aspect, the third implementation manner of the second aspect, and the fourth implementation manner of the second aspect, in a fifth implementation manner of the second aspect, the training module is configured to:
determining an initial call-through rate estimation model;
acquiring a call completing rate training data set, wherein the call completing rate training data set comprises historical characteristic data of a called object and historical call completing rate data corresponding to the historical characteristic data;
and training the initial call-through rate estimation model by taking the historical characteristic data of the called object as input and the historical call-through rate data corresponding to the historical characteristic data as output to obtain the call-through rate estimation model.
With reference to the second aspect, the first implementation manner of the second aspect, the second implementation manner of the second aspect, the third implementation manner of the second aspect, the fourth implementation manner of the second aspect, and the fifth implementation manner of the second aspect, in a sixth implementation manner of the second aspect, the present disclosure further includes:
and the feedback module is configured to add the characteristic data of the called object and the estimated call completion rate corresponding to the characteristic data as new training data into a call completion rate training data set of the call completion rate estimation model, and train the call completion rate estimation model.
With reference to the second aspect, the first implementation manner of the second aspect, the second implementation manner of the second aspect, the third implementation manner of the second aspect, the fourth implementation manner of the second aspect, the fifth implementation manner of the second aspect, and the sixth implementation manner of the second aspect, in a seventh implementation manner of the second aspect, the determining module is configured to:
and dividing the number of the calling objects by the reference call-through rate corresponding to the called object set to obtain the number of the called objects.
With reference to the second aspect, the first implementation manner of the second aspect, the second implementation manner of the second aspect, the third implementation manner of the second aspect, the fourth implementation manner of the second aspect, the fifth implementation manner of the second aspect, the sixth implementation manner of the second aspect, and the seventh implementation manner of the second aspect, in an eighth implementation manner of the second aspect, the disclosure further includes:
and the switching module is configured to switch the called target object to the calling object.
With reference to the second aspect, the first implementation manner of the second aspect, the second implementation manner of the second aspect, the third implementation manner of the second aspect, the fourth implementation manner of the second aspect, the fifth implementation manner of the second aspect, the sixth implementation manner of the second aspect, the seventh implementation manner of the second aspect, and the eighth implementation manner of the second aspect, in a ninth implementation manner of the second aspect, the call module is further configured to:
when the calling number of the target called object is larger than the calling object number, determining a first difference number between the calling object number and the calling number of the target called object, and keeping the calling state of the target called object with the first difference number until one or more calling objects end the current call;
when the number of the calling of the target called object is smaller than the number of the calling objects, determining a second difference value number between the number of the calling objects and the number of the calling of the target called object, determining the number of candidate called objects according to the second difference value number and a reference calling rate corresponding to the called object set, and taking out the called number of the target called object with the number of the candidate called objects from the called object set to call.
In a third aspect, the disclosed embodiments provide an electronic device, including a memory for storing one or more computer instructions that support a call control apparatus to perform the above-mentioned call control method, and a processor configured to execute the computer instructions stored in the memory. The call control apparatus may further comprise a communication interface for the call control apparatus to communicate with other devices or a communication network.
In a fourth aspect, the disclosed embodiments provide a computer-readable storage medium for storing computer instructions for a call control apparatus, which includes computer instructions for executing the above-mentioned call control method to the call control apparatus.
In a fifth aspect, the disclosed embodiments provide a computer program product comprising computer programs/instructions which, when executed by a processor, implement the steps of the above-described call control method.
The technical scheme provided by the embodiment of the disclosure can have the following beneficial effects:
according to the technical scheme, the call completion rate of the user is estimated, the user is classified based on the call completion rate, a user group with relatively consistent call completion rate is obtained, and finally the called party can be determined by combining the call completion rate of the user group and the number of calling parties. The technical scheme can acquire relatively stable call completion rate estimation data and carry out calling on the basis, and can eliminate uncertain factors caused by uncertainty of whether the called user is called up or not to a great extent, reduce the number of idle calling objects and the waiting time of the idle calling objects, and be beneficial to scheduling calling work by the calling party and improving the working efficiency of the calling party.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of embodiments of the disclosure.
Drawings
Other features, objects, and advantages of embodiments of the disclosure will become more apparent from the following detailed description of non-limiting embodiments when taken in conjunction with the accompanying drawings. In the drawings:
fig. 1 illustrates a flow chart of a call control method according to an embodiment of the present disclosure;
fig. 2 shows a block diagram of a call control device according to an embodiment of the present disclosure;
FIG. 3 shows a block diagram of an electronic device according to an embodiment of the present disclosure;
fig. 4 is a schematic block diagram of a computer system suitable for implementing a call control method according to an embodiment of the present disclosure.
Detailed Description
Hereinafter, exemplary embodiments of the present disclosure will be described in detail with reference to the accompanying drawings so that those skilled in the art can easily implement them. Furthermore, parts that are not relevant to the description of the exemplary embodiments have been omitted from the drawings for the sake of clarity.
In the embodiments of the present disclosure, it is to be understood that terms such as "including" or "having", etc., are intended to indicate the presence of the features, numerals, steps, actions, components, parts, or combinations thereof disclosed in the specification, and are not intended to exclude the possibility that one or more other features, numerals, steps, actions, components, parts, or combinations thereof are present or added.
It should be further noted that the embodiments and features of the embodiments in the present disclosure may be combined with each other without conflict. Embodiments of the present disclosure will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.
According to the technical scheme provided by the embodiment of the disclosure, the call completion rate of the user is estimated, the user is classified based on the call completion rate, a user group with relatively consistent call completion rate is obtained, and finally the called party can be determined by combining the call completion rate of the user group and the number of calling parties. The technical scheme can acquire relatively stable call completion rate estimation data and call on the basis, and can eliminate uncertain factors caused by uncertainty of whether the called user is called up to a great extent, reduce the number of idle calling objects and the waiting time of the idle calling objects, and be beneficial to scheduling call work of the calling party and improving the working efficiency of the calling party.
Fig. 1 shows a flowchart of a call control method according to an embodiment of the present disclosure, as shown in fig. 1, the call control method includes the following steps S101-S103:
in step S101, a called object set is obtained, where the called object set includes one or more called objects, a difference between a call completion rate of the one or more called objects and a reference call completion rate is smaller than a preset call completion rate threshold, and the reference call completion rate corresponds to the called object set;
in step S102, determining the number of called objects according to the reference call completion rate and the number of calling objects corresponding to the set of called objects;
in step S103, the called number of the target called object is extracted from the called object set, and the call is made.
As mentioned above, with the development of science and technology, users seek services for various platforms through networks, phones, and other channels, and service providers often communicate with users through networks or phones to receive user's consultation, obtain user's needs, solve user's problems, and provide help for users. However, in practical applications, due to poor communication network signals, busy users or other reasons, when a service provider calls a user, not all called users can connect the call, and although a call center is arranged in the prior art, only the called user called by the call center is forwarded to a calling party, so as to improve the working efficiency of the calling party, there are uncertain factors caused by uncertainty of whether the called user is called, which is not favorable for the scheduling of the calling party for the call work and the improvement of the working efficiency of the calling party.
In view of the above problems, in this embodiment, a call control method is provided, in which a call completion rate of a user is estimated, the user is classified based on the call completion rate, a user group with a relatively consistent call completion rate is obtained, and finally, a called party can be determined by combining the call completion rate of the user group and the number of calling parties. The technical scheme can acquire relatively stable call completion rate estimation data and call on the basis, and can eliminate uncertain factors caused by uncertainty of whether the called user is called up to a great extent, reduce the number of idle calling objects and the waiting time of the idle calling objects, and be beneficial to scheduling call work of the calling party and improving the working efficiency of the calling party.
In an embodiment of the present disclosure, the call control method may be applied to a call controller such as a computer, an electronic device, or a server that performs call control.
In an embodiment of the present disclosure, the calling object refers to an object that initiates a call to a called object according to a called number of the called object, and the called object refers to an object that receives a call initiated by the calling object. For example, in a scenario where a user is called by a manual service, the manual service is the calling object, and the user is the called object.
In an embodiment of the present disclosure, the called object set refers to a set composed of one or more called objects with similar call completion rates, that is, the called object set includes one or more called objects, further, at least identification information of one or more called objects and called numbers corresponding to the one or more called objects are stored in the called object set, and the call completion rates of the one or more called objects are similar, for example, a difference between the call completion rate of the one or more called objects and a preset reference call completion rate is smaller than a preset call completion rate threshold. The reference call-through rate corresponds to the called object set, that is, one called object set is provided with one reference call-through rate, and different called object sets are provided with different reference call-through rates. The call completion rate refers to the ratio of the call completion times to the total call times within a preset time period for a certain called object; the reference call-through rate can be preset, such as 10%, 20%, 30% and the like; the call completing rate threshold value can be set according to the requirements of practical application, and the specific value of the call completing rate threshold value is not particularly limited by the disclosure.
In the above embodiment, first, one or more called object sets corresponding to different reference call-through rates are determined; then, for each called object set, determining the number of called objects according to the reference call completing rate and the number of calling objects corresponding to the called object set; and finally, taking out the called numbers of the target called objects in the number of the called objects from the called object set to carry out calling.
In an embodiment of the present disclosure, the step S101 of acquiring the called object set may include the following steps:
determining a reference call-through rate;
estimating the call-through rate of the called object;
and setting the called objects of which the difference value between the call completion rate and the reference call completion rate is smaller than the preset call completion rate threshold value as belonging to the same called object set.
In order to make the call completion rates of the called objects in the same called object set similar, improve the scheduling of the calling party for the calling work and improve the work efficiency of the calling party, in this embodiment, when acquiring the called object set, a reference call rate of a certain called object set may be determined first, then estimating the call-through rate of the called object, placing the called object with the difference value between the call-through rate and the reference call-through rate smaller than the preset call-through rate threshold value into the called object set, so as to obtain a set consisting of one or more called objects with similar call-through rates to the reference call-through rate, and then determining the called object for executing the call based on the set of called objects with similar call-through rates, therefore, the situation that the calling object waits or the calling object is unevenly distributed due to large calling rate difference of the called object can be reduced to the maximum extent.
In another embodiment of the present disclosure, the call completion rate of the called object may be estimated, and then the called objects are clustered according to the call completion rate of each called object, so as to obtain a set consisting of one or more called objects with similar call completion rates, at this time, the average call completion rate of all the called objects in each set of the called objects may be set as the reference call completion rate of the set of the called objects, that is, in another embodiment of the present disclosure, the step S101, that is, the step of acquiring the set of the called objects, may include the following steps:
estimating the call-through rate of the called object;
clustering the called objects according to the call completing rate to obtain one or more called object sets;
and setting the average call completion rate of all the called objects in the called object set as the reference call completion rate of the called object set.
In an embodiment of the present disclosure, the step of estimating the call-through rate of the called party may include the steps of:
acquiring characteristic data of the called object;
and inputting the characteristic data of the called object into a pre-trained call completion rate estimation model to obtain the estimated call completion rate of the called object.
In this embodiment, a call-through rate estimation model trained in advance is used to estimate the call-through rate of a called object, that is, feature data of the called object is acquired first, wherein the feature data may include one or more of the following data: call time, call time period, call purpose, calling number type, etc., wherein the call purpose may be marketing, after-sales, consultation, etc., and the calling number type may be 800 phone, 400 phone, local city phone, foreign phone, etc.; and then inputting the obtained characteristic data of the called object into a pre-trained call completion rate estimation model to obtain the estimated call completion rate of the called object.
In an embodiment of the present disclosure, the method may further include the steps of:
and training the call-through rate estimation model.
In this embodiment, the step of training the call-through rate estimation model may include the steps of:
determining an initial call-through rate estimation model;
acquiring a call completion rate training data set, wherein the call completion rate training data set comprises historical characteristic data of a called object and historical call completion rate data corresponding to the historical characteristic data;
and training the initial call-through rate estimation model by taking the historical characteristic data of the called object as input and the historical call-through rate data corresponding to the historical characteristic data as output to obtain the call-through rate estimation model.
In the embodiment, when the call completion rate estimation model is trained, firstly, an initial call completion rate estimation model is determined, wherein the initial call completion rate estimation model can be selected according to the requirements of practical application; then obtaining historical characteristic data of a called object and historical call-through rate data corresponding to the historical characteristic data of the called object; and then taking the historical characteristic data of the called object as input, taking the historical call-through rate data corresponding to the historical characteristic data of the called object as output to train the initial call-through rate estimation model, and obtaining the call-through rate estimation model when the training result is converged.
In an embodiment of the present disclosure, the method may further include the steps of:
and adding the characteristic data of the called object and the estimated call-through rate corresponding to the characteristic data as new training data into a call-through rate training data set of the call-through rate estimation model, and training the call-through rate estimation model.
In order to improve the completeness of a call completion rate training data set which is training data of the call completion rate estimation model and ensure the comprehensiveness of the training result of the call completion rate estimation learning, in the embodiment, a feedback mechanism is adopted to carry out the call completion rate estimation, that is, after the call completion rate estimation result is obtained by using the call completion rate estimation model based on the feature data of the called party obtained at present, and adding the characteristic data of the called object and the obtained corresponding call-through rate estimation result data as new training data into a call-through rate training data set of the call-through rate estimation model, the call-through rate estimation model may subsequently be trained based on a new set of call-through rate training data, the training data is enriched, the accuracy of call completion rate estimation is improved, and the call completion rate estimation model with more completeness is obtained to participate in the output of the next call completion rate estimation result.
In an embodiment of the present disclosure, the step S102 of determining the number of called objects according to the reference call completion rate and the number of calling objects corresponding to the set of called objects may include the following steps:
and dividing the number of the calling objects by the reference call-through rate corresponding to the called object set to obtain the number of the called objects.
In this embodiment, when the number of called objects is determined according to the reference call-through rate and the number of calling objects corresponding to the called object set, the number of calling objects may be divided by the reference call-through rate corresponding to the called object set to obtain the number of called objects. For example, if the number of calling objects is 20 and the reference call rate corresponding to a certain set of called objects is 20%, the number of called objects obtained by dividing the number of calling objects by the reference call rate 20 corresponding to a certain set of called objects is 20/20% ("100").
In an embodiment of the present disclosure, the method may further include the steps of:
and switching the called target object to the calling object.
In this embodiment, in order to save the call waiting time of the calling party and improve the working efficiency of the calling party, a call controller, such as a call center, first calls the selected target called party, and then forwards the call to the calling party after the target called party connects the call.
In an embodiment of the present disclosure, the method may further include the steps of:
when the calling number of the target called object is larger than the calling object number, determining a first difference number between the calling object number and the calling number of the target called object, and keeping the calling state of the target called object with the first difference number until one or more calling objects end the current call;
when the calling number of the target called object is smaller than the calling number, determining a second difference value number between the calling number and the calling number of the target called object, determining the number of candidate called objects according to the second difference value number and the reference calling rate corresponding to the called object set, and taking out the called number of the target called object with the number of candidate called objects from the called object set to call.
Considering that there is a certain difference between the estimated call completion rate and the actual call completion rate, therefore, a situation may occur that the actual call completion number of the target called object is greater than or less than the number of the calling objects, specifically, when the actual call completion number of the target called object is greater than the number of the calling objects, that is, the number of the calling objects is not enough to receive the called target called object at this time, the call completion state of the excessive called target called object may be maintained until one or more calling objects receiving other called target called objects end their calls, and the excessive called target called objects may be answered; when the actual call number of the target called object is smaller than the number of the calling objects, that is, there are one or more calling objects in idle state and no called object can be received, a certain number of called objects can be continuously taken out from the called object set for calling according to the method described above, and at this time, the taken-out number of the called objects still needs to be determined according to the reference call rate corresponding to the called object set and the number of the currently idle calling objects.
The following are embodiments of the disclosed apparatus that may be used to perform embodiments of the disclosed methods.
Fig. 2 shows a block diagram of a call control device according to an embodiment of the present disclosure, which may be implemented as part or all of an electronic device by software, hardware, or a combination of both. As shown in fig. 2, the call control apparatus includes:
an obtaining module 201, configured to obtain a called object set, where the called object set includes one or more called objects, a difference between a call completion rate of the one or more called objects and a reference call completion rate is smaller than a preset call completion rate threshold, and the reference call completion rate corresponds to the called object set;
a determining module 202, configured to determine the number of called objects according to the reference call completion rate and the number of calling objects corresponding to the set of called objects;
and the calling module 203 is configured to take the called number of the target called object in the number of the called objects from the called object set to call.
As mentioned above, with the development of science and technology, users seek services for various platforms through networks, phones, and other channels, and service providers often communicate with users through networks or phones to receive user's consultation, obtain user's needs, solve user's problems, and provide help for users. However, in practical applications, due to poor communication network signals, busy users or other reasons, when a service provider calls a user, not all called users can connect the call, and although a call center is arranged in the prior art, only the called user called by the call center is forwarded to a calling party, so as to improve the working efficiency of the calling party, there are uncertain factors caused by uncertainty of whether the called user is called, which is not favorable for the scheduling of the calling party for the call work and the improvement of the working efficiency of the calling party.
In view of the above problems, in this embodiment, a call control device is provided, which estimates a call completion rate of a user, classifies the user based on the call completion rate to obtain a user group with a relatively consistent call completion rate, and finally determines a called party by combining the call completion rate of the user group and the number of calling parties. The technical scheme can acquire relatively stable call completion rate estimation data and carry out calling on the basis, and the technical scheme eliminates uncertain factors caused by uncertainty of whether the called user is called through or not to a great extent, thereby being beneficial to scheduling of calling work by a calling party and improving the working efficiency of the calling party.
In one embodiment of the present disclosure, the call control device may be implemented as a call controller such as a computer, an electronic device, or a server that performs call control.
In an embodiment of the present disclosure, the calling object refers to an object that initiates a call to a called object according to a called number of the called object, and the called object refers to an object that receives the call initiated by the calling object. For example, in the scenario of manual customer service calling the user, the manual customer service is the calling object, and the user is the called object.
In an embodiment of the present disclosure, the called object set refers to a set composed of one or more called objects with similar call completion rates, that is, the called object set includes one or more called objects, further, at least identification information of one or more called objects and called numbers corresponding to the one or more called objects are stored in the called object set, and the call completion rates of the one or more called objects are similar, for example, a difference between the call completion rate of the one or more called objects and a preset reference call completion rate is smaller than a preset call completion rate threshold. The reference call-through rate corresponds to the called object set, that is, one called object set corresponds to one reference call-through rate, and different called object sets correspond to different reference call-through rates. The call completion rate refers to the ratio of the call completion times to the total call times within a preset time period for a certain called object; the reference call-through rate can be preset, such as 10%, 20%, 30% and the like; the call completing rate threshold value can be set according to the requirements of practical application, and the specific value of the call completing rate threshold value is not particularly limited by the disclosure.
In the above embodiment, first, one or more called object sets corresponding to different reference call rates are determined; then, for each called object set, determining the number of called objects according to the reference call-through rate and the number of calling objects corresponding to the called object set; and finally, the called number of the target called object with the number of the called objects is taken out from the called object set to carry out calling.
In an embodiment of the present disclosure, the obtaining module 201 may be configured to:
determining a reference call-through rate;
estimating the call-through rate of the called object;
and setting the called objects of which the difference value between the call completion rate and the reference call completion rate is smaller than the preset call completion rate threshold value as belonging to the same called object set.
In order to make the call completion rates of the called objects in the same called object set similar, improve the scheduling of the calling party for the calling work and improve the work efficiency of the calling party, in this embodiment, when acquiring the called object set, a reference call rate of a certain called object set may be determined first, then estimating the call-through rate of the called object, placing the called object of which the difference value between the call-through rate and the reference call-through rate is less than the preset call-through rate threshold value into the called object set, this results in a set of one or more called objects having a call completion rate similar to the reference call completion rate, and subsequently a called object for performing a call can be determined based on the set of called objects having similar call completion rates, therefore, the situation that the calling object waits or the calling object is unevenly distributed due to large calling rate difference of the called object can be reduced to the maximum extent.
In another embodiment of the present disclosure, the call completion rate of the called object may be estimated first, and then the called objects are clustered according to the call completion rate of each called object, so as to obtain a set consisting of one or more called objects with similar call completion rates, at this time, the average call completion rate of all the called objects in each set of called objects may be set as the reference call completion rate of the set of called objects, that is, in another embodiment of the present disclosure, the obtaining module 201 may be configured to:
estimating the call-through rate of the called object;
clustering the called objects according to the call completing rate to obtain one or more called object sets;
and setting the average call completion rate of all the called objects in the called object set as the reference call completion rate of the called object set.
In an embodiment of the present disclosure, the estimating the call-through rate of the called object may be configured to:
acquiring characteristic data of the called object;
and inputting the characteristic data of the called object into a pre-trained call-through rate estimation model to obtain the estimated call-through rate of the called object.
In this embodiment, a call-through rate estimation model trained in advance is used to estimate the call-through rate of a called object, that is, feature data of the called object is acquired first, wherein the feature data may include one or more of the following data: call time, call time period, call purpose, calling number type, etc., wherein the call purpose may be marketing, after-sales, consultation, etc., and the calling number type may be 800 phone, 400 phone, local city phone, foreign phone, etc.; and inputting the obtained characteristic data of the called object into a pre-trained call-through rate estimation model to obtain the estimated call-through rate of the called object.
In an embodiment of the present disclosure, the apparatus may further include:
a training module configured to train the call-through rate estimation model.
In this embodiment, the training module may be configured to:
determining an initial call-through rate estimation model;
acquiring a call completion rate training data set, wherein the call completion rate training data set comprises historical characteristic data of a called object and historical call completion rate data corresponding to the historical characteristic data;
and training the initial call-through rate estimation model by taking the historical characteristic data of the called object as input and the historical call-through rate data corresponding to the historical characteristic data as output to obtain the call-through rate estimation model.
In the embodiment, when the call completion rate estimation model is trained, an initial call completion rate estimation model is determined at first, wherein the initial call completion rate estimation model can be selected according to the requirements of practical application; then obtaining historical characteristic data of a called object and historical call-through rate data corresponding to the historical characteristic data of the called object; and then, taking the historical characteristic data of the called object as input, taking the historical call-through rate data corresponding to the historical characteristic data of the called object as output to train the initial call-through rate estimation model, and obtaining the call-through rate estimation model when the training result is converged.
In an embodiment of the present disclosure, the apparatus may further include:
and the feedback module is configured to add the characteristic data of the called object and the estimated call completion rate corresponding to the characteristic data as new training data into a call completion rate training data set of the call completion rate estimation model, and train the call completion rate estimation model.
In order to improve the completeness of a call completing rate training data set which is the training data of the call completing rate estimation model and ensure the comprehensiveness of the learning training result of the call completing rate estimation, in the embodiment, a feedback mechanism is adopted to carry out the call completing rate estimation, that is, after the call completion rate estimation result is obtained by using the call completion rate estimation model based on the feature data of the called party obtained at present, and adding the characteristic data of the called object and the obtained corresponding call-through rate estimation result data as new training data into a call-through rate training data set of the call-through rate estimation model, the call-through rate estimation model may subsequently be trained based on a new set of call-through rate training data, the training data is enriched, the accuracy of call completing rate estimation is improved, and the more complete call completing rate estimation model is obtained to participate in the output of the next call completing rate estimation result.
In an embodiment of the present disclosure, the determining module 202 may be configured to:
and dividing the number of the calling objects by the reference call-through rate corresponding to the called object set to obtain the number of the called objects.
In this embodiment, when the number of called objects is determined according to the reference call completion rate and the number of calling objects corresponding to the called object set, the number of calling objects may be divided by the reference call completion rate corresponding to the called object set to obtain the number of called objects. For example, if the number of calling objects is 20 and the reference call rate corresponding to a certain set of called objects is 20%, the number of called objects obtained by dividing the number of calling objects by the reference call rate 20 corresponding to a certain set of called objects is 20/20% ("100").
In an embodiment of the present disclosure, the apparatus may further include:
and the switching module is configured to switch the called target object to the calling object.
In this embodiment, in order to save the call waiting time of the calling party and improve the work efficiency of the calling party, a call controller, such as a call center, first calls the selected target called party, and then transfers the call to the calling party after the target called party connects the call.
In an embodiment of the present disclosure, the calling module 203 may be further configured to:
when the calling number of the target called object is larger than the calling object number, determining a first difference number between the calling object number and the calling number of the target called object, and keeping the calling state of the target called object with the first difference number until one or more calling objects end the current call;
when the calling number of the target called object is smaller than the calling number, determining a second difference value number between the calling number and the calling number of the target called object, determining the number of candidate called objects according to the second difference value number and the reference calling rate corresponding to the called object set, and taking out the called number of the target called object with the number of candidate called objects from the called object set to call.
Considering that there is a certain difference between the estimated call completion rate and the actual call completion rate, therefore, a situation may occur that the actual call completion number of the target called object is greater than or less than the number of the calling objects, specifically, when the actual call completion number of the target called object is greater than the number of the calling objects, that is, the number of the calling objects is not enough to receive the called target called objects, the call completion state of the excessive called target called objects can be maintained until one or more calling objects receiving other called target called objects end their calls, and the excessive called target called objects can be answered; when the actual call number of the target called object is smaller than the number of the calling objects, that is, there are one or more calling objects in idle state and no called object can be received, a certain number of called objects can be continuously taken out from the called object set for calling according to the method described above, and at this time, the taken-out number of the called objects still needs to be determined according to the reference call rate corresponding to the called object set and the number of the currently idle calling objects.
The present disclosure also discloses an electronic device, fig. 3 shows a block diagram of an electronic device according to an embodiment of the present disclosure, and as shown in fig. 3, the electronic device 300 includes a memory 301 and a processor 302; wherein the content of the first and second substances,
the memory 301 is used to store one or more computer instructions, which are executed by the processor 302 to implement the above-described method steps.
FIG. 4 is a block diagram of a computer system suitable for use in implementing call control in accordance with an embodiment of the present disclosure.
As shown in fig. 4, the computer system 400 includes a processing unit 401 that can execute various processes in the above-described embodiments according to a program stored in a Read Only Memory (ROM)402 or a program loaded from a storage section 408 into a Random Access Memory (RAM) 403. In the RAM403, various programs and data necessary for the operation of the system 400 are also stored. The processing unit 401, ROM402, and RAM403 are connected to each other by a bus 404. An input/output (I/O) interface 405 is also connected to bus 404.
The following components are connected to the I/O interface 405: an input portion 406 including a keyboard, a mouse, and the like; an output section 407 including a display device such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker; a storage section 408 including a hard disk and the like; and a communication section 409 including a network interface card such as a LAN card, a modem, or the like. The communication section 409 performs communication processing via a network such as the internet. A driver 410 is also connected to the I/O interface 405 as needed. A removable medium 411 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 410 as needed, so that a computer program read out therefrom is mounted in the storage section 408 as needed. The processing unit 401 may be implemented as a CPU, a GPU, a TPU, an FPGA, an NPU, or other processing units.
In particular, the above described methods may be implemented as computer software programs, according to embodiments of the present disclosure. For example, embodiments of the present disclosure include a computer program product comprising a computer program tangibly embodied on a medium readable thereby, the computer program comprising program code for performing the call control method. In such an embodiment, the computer program may be downloaded and installed from a network through the communication section 409 and/or installed from the removable medium 411.
Embodiments of the present disclosure also disclose a computer program product comprising a computer program/instructions which, when executed by a processor, implement any of the above method steps.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units or modules described in the embodiments of the present disclosure may be implemented by software or hardware. The units or modules described may also be provided in a processor, and the names of the units or modules do not in some cases constitute a limitation on the units or modules themselves.
As another aspect, the disclosed embodiment also provides a computer-readable storage medium, which may be the computer-readable storage medium included in the apparatus in the foregoing embodiment; or it may be a separate computer readable storage medium not incorporated into the device. The computer readable storage medium stores one or more programs for use by one or more processors in performing the methods described in the embodiments of the present disclosure.
The foregoing description is only exemplary of the preferred embodiments of the disclosure and is illustrative of the principles of the technology employed. It will be appreciated by those skilled in the art that the scope of the invention in the embodiments of the present disclosure is not limited to the specific combinations of the above-mentioned features, and that other embodiments can be made by any combination of the above-mentioned features or their equivalents without departing from the spirit of the invention. For example, the above features and (but not limited to) the features with similar functions disclosed in the embodiments of the present disclosure are mutually replaced to form the technical solution.
Claims (22)
1. A call control method, comprising:
acquiring a called object set, wherein the called object set comprises one or more called objects, the difference value between the call completion rate of the one or more called objects and a reference call completion rate is smaller than a preset call completion rate threshold value, and the reference call completion rate corresponds to the called object set;
determining the number of called objects according to the reference call completing rate and the number of calling objects corresponding to the called object set;
and taking out the called number of the target called object in the number of the called objects from the called object set to call.
2. The method of claim 1, wherein the obtaining a set of called objects comprises:
determining a reference call-through rate;
estimating the call-through rate of the called object;
and setting the called objects of which the difference value between the call completion rate and the reference call completion rate is smaller than the preset call completion rate threshold value as belonging to the same called object set.
3. The method of claim 1, wherein the obtaining a set of called objects comprises:
estimating the call-through rate of the called object;
clustering the called objects according to the call completing rate to obtain one or more called object sets;
and setting the average call completion rate of all the called objects in the called object set as the reference call completion rate of the called object set.
4. The method according to claim 2 or 3, the estimating a call-through rate of the called subject, comprising:
acquiring characteristic data of the called object;
and inputting the characteristic data of the called object into a pre-trained call completion rate estimation model to obtain the estimated call completion rate of the called object.
5. The method of claim 4, further comprising:
and training the call-through rate estimation model.
6. The method of claim 5, the training the call-through rate estimation model, comprising:
determining an initial call-through rate estimation model;
acquiring a call completion rate training data set, wherein the call completion rate training data set comprises historical characteristic data of a called object and historical call completion rate data corresponding to the historical characteristic data;
and training the initial call-through rate estimation model by taking the historical characteristic data of the called object as input and the historical call-through rate data corresponding to the historical characteristic data as output to obtain the call-through rate estimation model.
7. The method of any of claims 4-6, further comprising:
and adding the characteristic data of the called object and the estimated call-through rate corresponding to the characteristic data as new training data into a call-through rate training data set of the call-through rate estimation model, and training the call-through rate estimation model.
8. The method according to any one of claims 1 to 7, wherein the determining the number of the called objects according to the reference call completion rate and the number of the calling objects corresponding to the set of the called objects comprises:
and dividing the number of the calling objects by the reference call-through rate corresponding to the called object set to obtain the number of the called objects.
9. The method of any of claims 1-8, further comprising:
and switching the called target object to the calling object.
10. The method of claim 9, further comprising:
when the number of the calling parties of the target called object is larger than the number of the calling objects, determining a first difference number between the number of the calling objects and the number of the calling parties of the target called object, and keeping the calling state of the target called object with the first difference number until one or more calling objects end the current call;
when the number of the calling of the target called object is smaller than the number of the calling objects, determining a second difference value number between the number of the calling objects and the number of the calling of the target called object, determining the number of candidate called objects according to the second difference value number and a reference calling rate corresponding to the called object set, and taking out the called number of the target called object with the number of the candidate called objects from the called object set to call.
11. A call control device comprising:
the system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is configured to acquire a called object set, the called object set comprises one or more called objects, the difference value between the call completion rate of the one or more called objects and a reference call completion rate is smaller than a preset call completion rate threshold value, and the reference call completion rate corresponds to the called object set;
the determining module is configured to determine the number of the called objects according to the reference calling rate and the number of the calling objects corresponding to the called object set;
and the calling module is configured to take the called number of the target called object with the number of the called objects from the called object set to call.
12. The apparatus of claim 11, the acquisition module configured to:
determining a reference call-through rate;
estimating the call-through rate of the called object;
and setting the called objects with the difference value between the call completion rate and the reference call completion rate smaller than the preset call completion rate threshold value as belonging to the same called object set.
13. The apparatus of claim 11, the acquisition module configured to:
estimating the call-through rate of the called object;
clustering the called objects according to the call completing rate to obtain one or more called object sets;
and setting the average call completion rate of all the called objects in the called object set as the reference call completion rate of the called object set.
14. The apparatus according to claim 12 or 13, said estimating a call-through rate of the called subject configured to:
acquiring characteristic data of the called object;
and inputting the characteristic data of the called object into a pre-trained call completion rate estimation model to obtain the estimated call completion rate of the called object.
15. The apparatus of claim 14, further comprising:
a training module configured to train the call-through rate estimation model.
16. The apparatus of claim 15, the training module configured to:
determining an initial call-through rate estimation model;
acquiring a call completing rate training data set, wherein the call completing rate training data set comprises historical characteristic data of a called object and historical call completing rate data corresponding to the historical characteristic data;
and training the initial call-through rate estimation model by taking the historical characteristic data of the called object as input and the historical call-through rate data corresponding to the historical characteristic data as output to obtain the call-through rate estimation model.
17. The apparatus of any of claims 14-16, further comprising:
and the feedback module is configured to add the characteristic data of the called object and the estimated call completion rate corresponding to the characteristic data as new training data into a call completion rate training data set of the call completion rate estimation model, and train the call completion rate estimation model.
18. The apparatus of any of claims 11-17, the determination module configured to:
and dividing the number of the calling objects by the reference call-through rate corresponding to the called object set to obtain the number of the called objects.
19. The apparatus of any of claims 11-18, further comprising:
and the switching module is configured to switch the target called object of the call-through to the calling object.
20. The apparatus of claim 19, the call module further configured to:
when the calling number of the target called object is larger than the calling object number, determining a first difference number between the calling object number and the calling number of the target called object, and keeping the calling state of the target called object with the first difference number until one or more calling objects end the current call;
when the calling number of the target called object is smaller than the calling number, determining a second difference value number between the calling number and the calling number of the target called object, determining the number of candidate called objects according to the second difference value number and the reference calling rate corresponding to the called object set, and taking out the called number of the target called object with the number of candidate called objects from the called object set to call.
21. An electronic device comprising a memory and a processor; wherein, the first and the second end of the pipe are connected with each other,
the memory is configured to store one or more computer instructions, wherein the one or more computer instructions are executed by the processor to implement the steps of the method of any one of claims 1-10.
22. A computer readable storage medium having computer instructions stored thereon, wherein the computer instructions, when executed by a processor, implement the steps of the method of any one of claims 1-10.
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