CN111526253A - Call control method, device, computer equipment and storage medium - Google Patents
Call control method, device, computer equipment and storage medium Download PDFInfo
- Publication number
- CN111526253A CN111526253A CN202010155739.5A CN202010155739A CN111526253A CN 111526253 A CN111526253 A CN 111526253A CN 202010155739 A CN202010155739 A CN 202010155739A CN 111526253 A CN111526253 A CN 111526253A
- Authority
- CN
- China
- Prior art keywords
- user
- candidate
- reference user
- target
- customer service
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Classifications
-
- 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
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/95—Retrieval from the web
- G06F16/953—Querying, e.g. by the use of web search engines
- G06F16/9535—Search customisation based on user profiles and personalisation
-
- 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
Landscapes
- Engineering & Computer Science (AREA)
- Databases & Information Systems (AREA)
- Business, Economics & Management (AREA)
- Marketing (AREA)
- Signal Processing (AREA)
- Theoretical Computer Science (AREA)
- Data Mining & Analysis (AREA)
- Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The application relates to a call control method, a call control device, computer equipment and a storage medium. The method comprises the following steps: obtaining a plurality of reference user portraits; the reference user representation includes a plurality of user tags corresponding to the reference user; the reference user is a user of the counter robot customer service; the user tag is used for indicating the attribute or behavior of the user; screening out a target user from a plurality of candidate users which are not called according to the reference user image; and calling the target user by adopting manual customer service. By adopting the method, the conversation effect can be improved, and the user satisfaction can be improved.
Description
Technical Field
The present application relates to the field of customer service system technologies, and in particular, to a call control method, an apparatus, a computer device, and a storage medium.
Background
With the development of science and technology, robot customer service based on artificial intelligence appears, and the robot customer service is gradually applied to many fields. For example, in the field of sales, a robot customer service is usually used to make a call and a product sales, and when a call object has a special requirement, the call object is converted into a manual customer service.
At present, a robot service is adopted to make a call, and generally all users led into a call platform are called in sequence. However, this calling method does not work well in terms of actual sales, and sometimes reduces the satisfaction of the user.
Disclosure of Invention
In view of the above, it is necessary to provide a call control method, apparatus, computer device and storage medium capable of improving user satisfaction in view of the above technical problems.
A method of call control, the method comprising:
obtaining a plurality of reference user portraits; the reference user representation includes a plurality of user tags corresponding to the reference user; the reference user is a user of the counter robot customer service; the user tag is used for indicating the attribute or behavior of the user;
screening out a target user from a plurality of candidate users which are not called according to the reference user image;
and calling the target user by adopting manual customer service.
In one embodiment, the screening out the target user from the plurality of candidate users not called according to the reference user image includes:
acquiring a candidate user image corresponding to a candidate user; the candidate user image comprises a plurality of user labels corresponding to the candidate users;
comparing the candidate user portrait with each reference user portrait to obtain a comparison result;
and if the comparison result is that the reference user image matched with the candidate user image exists, determining the candidate user as the target user.
In one embodiment, the comparing the candidate user image with each reference user image to obtain a comparison result includes:
comparing the user label in the candidate user picture with the user label in the reference user picture, and taking the same user label as a target user label;
calculating the ratio of the number of the labels of the target user to the number of the labels in the reference user image;
if the calculated ratio is greater than the preset ratio, it is determined that the candidate user profile matches the reference user profile.
In one embodiment, prior to the obtaining the plurality of reference user representations, further comprising:
determining a reference user of the counter robot customer service;
and constructing a reference user portrait according to the user behavior information and the user attribute information corresponding to the reference user.
In one embodiment, the determining the reference user of the countering robot service includes:
acquiring a plurality of call records;
if the call record meets the preset conditions, determining the user corresponding to the call record as a reference user;
the preset conditions comprise that the call duration corresponding to the call record is less than the preset duration, and the hanging-up node of the call record is at least one of the preset nodes.
In one embodiment, the constructing a reference user portrait according to the user behavior information and the user attribute information corresponding to the reference user includes:
generating a first user label according to user attribute information corresponding to a reference user;
generating a second user label according to the user behavior information corresponding to the reference user;
a reference user representation is constructed from the first user tag and the second user tag.
In one embodiment, the user attribute information includes at least one of an age, a gender and an occupation of the user, and the user behavior information includes at least one of a type of purchased products, a number of times of purchased products, an online shopping frequency and a purchase preference of the user.
A call control device, the device comprising:
a reference user profile acquisition module for acquiring a plurality of reference user profiles; the reference user representation includes a plurality of user tags corresponding to the reference user; the reference user is a user of the counter robot customer service; the user tag is used for indicating the attribute or behavior of the user;
the target user screening module is used for screening a target user from a plurality of candidate users which are not called according to the reference user image;
and the calling module is used for calling the target user by adopting manual customer service.
In one embodiment, the target user screening module is configured to obtain a candidate user image corresponding to a candidate user; the candidate user image comprises a plurality of user labels corresponding to the candidate users; comparing the candidate user portrait with each reference user portrait to obtain a comparison result; and if the comparison result is that the reference user image matched with the candidate user image exists, determining the candidate user as the target user.
In one embodiment, the target user screening module is configured to compare user tags in the candidate user images with user tags in the reference user images, and use the same user tags as target user tags; calculating the ratio of the number of the labels of the target user to the number of the labels in the reference user image; if the calculated ratio is greater than the preset ratio, it is determined that the candidate user profile matches the reference user profile.
In one embodiment, the method further comprises the following steps:
the reference user determining module is used for determining a reference user of the counter robot customer service;
and the reference user portrait constructing module is used for constructing a reference user portrait according to the user behavior information and the user attribute information corresponding to the reference user.
In one embodiment, the reference subscriber determining module is configured to obtain a plurality of call records; if the call record meets the preset conditions, determining the user corresponding to the call record as a reference user;
the preset conditions comprise that the call duration corresponding to the call record is less than the preset duration, and the hanging-up node of the call record is at least one of the preset nodes.
In one embodiment, the reference user profile constructing module is configured to generate a first user tag according to user attribute information corresponding to a reference user; generating a second user label according to the user behavior information corresponding to the reference user; a reference user representation is constructed from the first user tag and the second user tag.
In one embodiment, the user attribute information includes at least one of an age, a gender and an occupation of the user, and the user behavior information includes at least one of a type of purchased products, a number of times of purchased products, an online shopping frequency and a purchase preference of the user.
A computer device comprising a memory and a processor, the memory storing a computer program, the processor implementing the following steps when executing the computer program:
obtaining a plurality of reference user portraits; the reference user representation includes a plurality of user tags corresponding to the reference user; the reference user is a user of the counter robot customer service; the user tag is used for indicating the attribute or behavior of the user;
screening out a target user from a plurality of candidate users which are not called according to the reference user image;
and calling the target user by adopting manual customer service.
A computer-readable storage medium, on which a computer program is stored which, when executed by a processor, carries out the steps of:
obtaining a plurality of reference user portraits; the reference user representation includes a plurality of user tags corresponding to the reference user; the reference user is a user of the counter robot customer service; the user tag is used for indicating the attribute or behavior of the user;
screening out a target user from a plurality of candidate users which are not called according to the reference user image;
and calling the target user by adopting manual customer service.
The call control method, the call control device, the computer equipment and the storage medium acquire a plurality of reference user pictures, and screen out target users from a plurality of candidate users which are not called according to the reference user pictures; and calling the target user by adopting manual customer service. According to the method and the device, the target user of the countering robot customer service is screened out from the candidate users which are not called according to the reference user figure, and the target user is called by adopting the artificial customer service, so that the probability that the user of the countering robot customer service hangs up the telephone or does not cooperate with the call can be reduced, the call effect can be further improved, and the user satisfaction degree is improved.
Drawings
FIG. 1 is a diagram of an exemplary call control method;
FIG. 2 is a flow diagram illustrating a call control method according to one embodiment;
FIG. 3 is a schematic flow chart diagram illustrating the step of filtering target users in one embodiment;
FIG. 4 is a flow chart illustrating a call control method according to another embodiment;
FIG. 5 is a block diagram showing the structure of a call control device according to an embodiment;
FIG. 6 is a diagram illustrating an internal structure of a computer device according to an embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
The call control method provided by the application can be applied to the application environment shown in fig. 1. The application environment includes a terminal 102 and a server 104, and the terminal 102 and the server 104 communicate through a network. The terminal 102 may be, but not limited to, various personal computers, notebook computers, smart phones, tablet computers, and portable wearable devices, and the server 104 may be implemented by an independent server or a server cluster formed by a plurality of servers.
In one embodiment, as shown in fig. 2, a call control method is provided, which is described by taking the application of the method to the server in fig. 1 as an example, and includes the following steps:
In the embodiment of the application, as part of users dislike the robot service, when the robot service is used for calling, the users may hang up when the robot service is confirmed, or the users do not cooperate in the communication process. Therefore, for the users of the type, calling by using the robot customer service cannot achieve good conversation effect, and even the satisfaction degree of the users is affected.
Before calling, the user of the countering machine customer service serves as a reference user, and a reference user portrait is constructed by adopting a plurality of user tags corresponding to the reference user, so that the reference user portrait is obtained. Wherein the user tag indicates an attribute or behavior of the user. For example, user tags indicating user attributes may include "student", "office worker", user tags indicating user behavior may include "purchased X product", "not purchased X product", then reference user profiles may be "student" of "not purchased X product", and "office worker" of "purchased X product". The user label is not limited in detail in the embodiment of the application, and can be set according to actual conditions.
In the embodiment of the application, after the reference user portrait is obtained, whether the candidate user is the target user is determined according to whether the candidate user accords with the reference user portrait. Specifically, if the candidate user is matched with the reference user portrait, which indicates that the candidate user has a high possibility of countering the robot customer service, the candidate user is taken as the target user. If the candidate user does not conform to the reference user portrait, the probability that the candidate user will dislike the robot is low.
For example, there are 100 candidate users that are not called, and if candidate user 1 matches the reference user profile, candidate user 1 is the target user; if candidate user 2 does not conform to the reference user profile, candidate user 2 is not the target user.
And step 203, calling the target user by adopting a manual customer service.
In the embodiment of the application, after the target users are screened out, the target users are called by manual customer service instead of robot customer service. Specifically, a call is made to a target user, and a manual customer service is adopted to perform voice interaction with the target user. Or calling the target user selected by the manual customer service. The embodiment of the present application does not limit this in detail, and can be set according to actual situations.
In the call control method, a plurality of reference user images are obtained, and a target user is screened out from a plurality of candidate users which are not called according to the reference user images; and calling the target user by adopting manual customer service. According to the method and the device, the target user of the countering robot customer service is screened out from the candidate users which are not called according to the reference user figure, and the target user is called by adopting the artificial customer service, so that the probability that the user of the countering robot customer service hangs up the telephone or does not cooperate with the call can be reduced, the call effect can be further improved, and the user satisfaction degree is improved.
In one embodiment, as shown in FIG. 3, the present embodiment relates to an optional process of screening target users from a plurality of candidate users based on a reference user profile. Based on the above embodiment, step 202 may include the following steps:
In the embodiment of the application, when the target user is screened, the candidate user images corresponding to the candidate users pre-stored in the server can be obtained. Or the user information associated with the user identifier of the candidate user can be acquired first, and then the candidate user picture can be constructed according to the acquired user information. The user identifier of the candidate user may be a phone number of the candidate user, and the user information associated with the phone number of the candidate user may be gender, age, occupation, purchase record, and the like. The embodiment of the application does not limit the user identification and the user information in detail, and can be set according to actual conditions.
Step 302 compares the candidate user image with each reference user image to obtain a comparison result.
In this embodiment, since the candidate user portrait and the reference user portrait each include a plurality of user tags, comparing the candidate user portrait with each reference user portrait may include: comparing the user label in the candidate user picture with the user label in the reference user picture, and taking the same user label as a target user label; calculating the ratio of the number of the labels of the target user to the number of the labels in the reference user image; if the calculated ratio is greater than the preset ratio, it is determined that the candidate user profile matches the reference user profile. If the calculated ratio is less than or equal to the predetermined ratio, it is determined that the candidate user image does not match the reference user image.
For example, candidate user representations include user tags a1, B1, C1, D1, E1, and G1, reference user representation includes user tags a1, B1, C1, D1, E1, and F1, and comparing the user tags in the candidate user representation with the user tags in the reference user representation yields the same user tags a1, B1, C1, D1, and E1, and the user tags a1, B1, C1, D1, and E1 are used as target user tags. Wherein the number of tags of the target user tag is 5, the number of tags in the reference user portrait is 6, the calculated ratio is 0.83, which is greater than the preset ratio 0.8, and it is determined that the candidate user portrait matches the reference user portrait. The preset ratio is not limited in detail in the embodiment of the application, and can be set according to actual conditions.
According to the comparison method, the candidate user image is sequentially compared with a plurality of reference user images to obtain the comparison result of whether the reference user image matched with the candidate user image exists or not. For example, if a candidate user image is compared with 100 reference user images in sequence, where the candidate user image matches the reference user image 15, then the comparison results in the presence of a reference user image matching the candidate user image. If the candidate user image does not match 100 reference user images, then the comparison is made such that there is no reference user image matching the candidate user image.
In the embodiment of the application, if the reference user portrait matched with the candidate user portrait shows that the candidate user and the reference user are the same type of user, namely the candidate user is also a user of the counter-sense robot customer service, the candidate user is determined as the target user. If there is no reference user representation matching the candidate user representation, indicating that the candidate user is not the same class of user as the reference user, then the candidate user is not the target user.
Selecting a target user from a plurality of candidate users according to the reference user portrait; acquiring a candidate user image corresponding to a candidate user; comparing the candidate user portrait with each reference user portrait to obtain a comparison result; and if the comparison result is that the reference user image matched with the candidate user image exists, determining the candidate user as the target user. According to the embodiment of the application, whether the candidate user is a user of the counter robot customer service is determined by comparing the user labels in the user portrait, and the calculation mode is simple and easy to implement and is high in speed.
In one embodiment, as shown in fig. 4, the present embodiment relates to an alternative procedure of a call control method. On the basis of the above embodiment, the method comprises the following steps:
In this embodiment of the present application, determining the reference user may include: acquiring a plurality of call records; and if the call record meets the preset conditions, determining the user corresponding to the call record as a reference user.
Specifically, a plurality of call records pre-stored in the server are obtained, and call information such as call duration, hang-up node and the like can be obtained according to the call records. And if the call information meets the preset conditions, determining the user corresponding to the call record as a reference user. The preset conditions comprise that the call duration corresponding to the call record is less than the preset duration, and the hanging-up node of the call record is at least one of the preset nodes.
For example, when the call record 1 is acquired, the call duration is 8 seconds, the preset duration is 15 seconds, it is determined that the call duration of the call record 1 is less than the preset duration, and the call record 1 meets the preset condition. At this time, the user corresponding to the call record 1 is determined as the reference user. For another example, when the call record 2 is acquired, the hang-up node is a hello node, the preset node is also a hello node, the hang-up node is determined to be the preset node, and the call record 2 meets the preset condition. At this time, the user corresponding to the call record 2 is determined as the reference user. The method and the device do not limit the preset duration and the preset nodes in detail, and can be set according to actual conditions.
Constructing a reference user portrait according to user behavior information and user attribute information corresponding to a reference user, which may include: generating a first user label according to user attribute information corresponding to a reference user; generating a second user label according to the user behavior information corresponding to the reference user; a reference user representation is constructed from the first user tag and the second user tag.
The user attribute information comprises at least one of age, gender and occupation of the user, and the user behavior information comprises at least one of purchased product type, purchased product frequency, online shopping frequency and purchased preference of the user.
For example, a first user label of user 1 is generated as "student" based on user 1's age of 15 years, gender of male, occupation of student; the first user label of user 2 is generated as "office worker" based on user 2's age of 25 years, gender of male, occupation of programmer. Generating a second user label of the user 1 as 'X product not purchased' according to the purchased product type of the user 1; according to the purchased product type of the user 2, a second user label of the user 2 is generated as "purchased X product". A "student" with a reference user portrait of the user 1 as "not purchasing X products" can be constructed according to the first user tag and the second user tag of the user 1; from the first user tag and the second user tag of user 2, a reference user representation of user 2 as "office worker" of "purchased X products" may be constructed.
In the embodiment of the present application, the candidate user portrait may be constructed in the same manner as the reference user portrait, and is not redundant here.
In one embodiment, comparing the candidate user representation with each reference user representation to obtain a comparison result comprises: comparing the user label in the candidate user picture with the user label in the reference user picture to obtain the same target user label; calculating the ratio of the number of the labels of the target user to the number of the labels in the reference user image; if the calculated ratio is greater than the preset ratio, it is determined that the candidate user profile matches the reference user profile.
In step 404, if the comparison result is that there is a reference user image matching the candidate user image, it is determined that the candidate user is the target user.
In the call control method, a reference user of the counter robot customer service is determined according to preset conditions, such as call duration and hang-up nodes; and then, constructing a reference user portrait according to the user behavior information and the user attribute information corresponding to the reference user. Then, acquiring a candidate user image, comparing the candidate user image with a reference user image, and screening a target user from the candidate users not called; and finally, adopting manual customer service calling for the target user. Through the embodiment of the application, the probability that the user of the counter robot customer service hangs up the phone or does not cooperate with the call can be reduced, the call effect can be further improved, and the user satisfaction degree is improved. Furthermore, the waste of communication line resources can be avoided, and the resources are saved.
It should be understood that although the various steps in the flowcharts of fig. 2-4 are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least some of the steps in fig. 2-4 may include multiple steps or multiple stages, which are not necessarily performed at the same time, but may be performed at different times, which are not necessarily performed in sequence, but may be performed in turn or alternately with other steps or at least some of the other steps or stages.
In one embodiment, as shown in fig. 5, there is provided a call control apparatus including:
a reference user profile acquisition module 501 for acquiring a plurality of reference user profiles; the reference user representation includes a plurality of user tags corresponding to the reference user; the reference user is a user of the counter robot customer service; the user tag is used for indicating the attribute or behavior of the user;
a target user screening module 502, configured to screen a target user from a plurality of candidate users that are not called according to the reference user image;
and the calling module 503 is configured to call the target user by using a manual customer service.
In one embodiment, the target user screening module is configured to obtain a candidate user image corresponding to a candidate user; the candidate user image comprises a plurality of user labels corresponding to the candidate users; comparing the candidate user portrait with each reference user portrait to obtain a comparison result; and if the comparison result is that the reference user image matched with the candidate user image exists, determining the candidate user as the target user.
In one embodiment, the target user screening module is configured to compare user tags in the candidate user images with user tags in the reference user images, and use the same user tags as target user tags; calculating the ratio of the number of the labels of the target user to the number of the labels in the reference user image; if the calculated ratio is greater than the preset ratio, it is determined that the candidate user profile matches the reference user profile.
In one embodiment, the method further comprises the following steps:
the reference user determining module is used for determining a reference user of the counter robot customer service;
and the reference user portrait constructing module is used for constructing a reference user portrait according to the user behavior information and the user attribute information corresponding to the reference user.
In one embodiment, the reference subscriber determining module is configured to obtain a plurality of call records; if the call record meets the preset conditions, determining the user corresponding to the call record as a reference user;
the preset conditions comprise that the call duration corresponding to the call record is less than the preset duration, and the hanging-up node of the call record is at least one of the preset nodes.
In one embodiment, the reference user profile constructing module is configured to generate a first user tag according to user attribute information corresponding to a reference user; generating a second user label according to the user behavior information corresponding to the reference user; a reference user representation is constructed from the first user tag and the second user tag.
In one embodiment, the user attribute information includes at least one of an age, a gender and an occupation of the user, and the user behavior information includes at least one of a type of purchased products, a number of times of purchased products, an online shopping frequency and a purchase preference of the user.
For the specific definition of the call control device, reference may be made to the above definition of the call control method, which is not described herein again. The modules in the call control device can be implemented wholly or partially by software, hardware and a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as shown in fig. 6. The computer device includes a processor, a memory, and a network interface connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The database of the computer device is used for storing call control data. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a call control method.
Those skilled in the art will appreciate that the architecture shown in fig. 6 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
In one embodiment, a computer device is provided, comprising a memory and a processor, the memory having a computer program stored therein, the processor implementing the following steps when executing the computer program:
obtaining a plurality of reference user portraits; the reference user representation includes a plurality of user tags corresponding to the reference user; the reference user is a user of the counter robot customer service; the user tag is used for indicating the attribute or behavior of the user;
screening out a target user from a plurality of candidate users which are not called according to the reference user image;
and calling the target user by adopting manual customer service.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
acquiring a candidate user image corresponding to a candidate user; the candidate user image comprises a plurality of user labels corresponding to the candidate users;
comparing the candidate user portrait with each reference user portrait to obtain a comparison result;
and if the comparison result is that the reference user image matched with the candidate user image exists, determining the candidate user as the target user.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
comparing the user label in the candidate user picture with the user label in the reference user picture, and taking the same user label as a target user label;
calculating the ratio of the number of the labels of the target user to the number of the labels in the reference user image;
if the calculated ratio is greater than the preset ratio, it is determined that the candidate user profile matches the reference user profile.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
determining a reference user of the counter robot customer service;
and constructing a reference user portrait according to the user behavior information and the user attribute information corresponding to the reference user.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
acquiring a plurality of call records;
if the call record meets the preset conditions, determining the user corresponding to the call record as a reference user;
the preset conditions comprise that the call duration corresponding to the call record is less than the preset duration, and the hanging-up node of the call record is at least one of the preset nodes.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
generating a first user label according to user attribute information corresponding to a reference user;
generating a second user label according to the user behavior information corresponding to the reference user;
a reference user representation is constructed from the first user tag and the second user tag.
In one embodiment, the user attribute information includes at least one of an age, a gender and an occupation of the user, and the user behavior information includes at least one of a type of purchased products, a number of purchased products, an online shopping frequency and a purchase preference of the user.
In one embodiment, a computer-readable storage medium is provided, having a computer program stored thereon, which when executed by a processor, performs the steps of:
obtaining a plurality of reference user portraits; the reference user representation includes a plurality of user tags corresponding to the reference user; the reference user is a user of the counter robot customer service; the user tag is used for indicating the attribute or behavior of the user;
screening out a target user from a plurality of candidate users which are not called according to the reference user image;
and calling the target user by adopting manual customer service.
In one embodiment, the computer program when executed by the processor further performs the steps of:
acquiring a candidate user image corresponding to a candidate user; the candidate user image comprises a plurality of user labels corresponding to the candidate users;
comparing the candidate user portrait with each reference user portrait to obtain a comparison result;
and if the comparison result is that the reference user image matched with the candidate user image exists, determining the candidate user as the target user.
In one embodiment, the computer program when executed by the processor further performs the steps of:
comparing the user label in the candidate user picture with the user label in the reference user picture, and taking the same user label as a target user label;
calculating the ratio of the number of the labels of the target user to the number of the labels in the reference user image;
if the calculated ratio is greater than the preset ratio, it is determined that the candidate user profile matches the reference user profile.
In one embodiment, the computer program when executed by the processor further performs the steps of:
determining a reference user of the counter robot customer service;
and constructing a reference user portrait according to the user behavior information and the user attribute information corresponding to the reference user.
In one embodiment, the computer program when executed by the processor further performs the steps of:
acquiring a plurality of call records;
if the call record meets the preset conditions, determining the user corresponding to the call record as a reference user;
the preset conditions comprise that the call duration corresponding to the call record is less than the preset duration, and the hanging-up node of the call record is at least one of the preset nodes.
In one embodiment, the computer program when executed by the processor further performs the steps of:
generating a first user label according to user attribute information corresponding to a reference user;
generating a second user label according to the user behavior information corresponding to the reference user;
a reference user representation is constructed from the first user tag and the second user tag.
In one embodiment, the user attribute information includes at least one of an age, a gender and an occupation of the user, and the user behavior information includes at least one of a type of purchased products, a number of purchased products, an online shopping frequency and a purchase preference of the user.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware related to instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database or other medium used in the embodiments provided herein can include at least one of non-volatile and volatile memory. Non-volatile memory may include Read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical storage, or the like. Volatile Memory can include Random Access Memory (RAM) or external cache Memory. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM), among others.
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above examples only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (10)
1. A method for call control, the method comprising:
obtaining a plurality of reference user portraits; the reference user representation comprises a plurality of user tags corresponding to reference users; the reference user is a user of the counter robot customer service; the user tag is used for indicating the attribute or the behavior of the user;
screening out target users from a plurality of candidate users which are not called according to the reference user image;
and calling the target user by adopting manual customer service.
2. The method of claim 1, wherein the screening target users from a plurality of candidate users not called according to the reference user image comprises:
acquiring a candidate user image corresponding to the candidate user; the candidate user image comprises a plurality of user labels corresponding to the candidate users;
comparing the candidate user portrait with each reference user portrait to obtain a comparison result;
and if the comparison result is that a reference user image matched with the candidate user image exists, determining that the candidate user is the target user.
3. The method of claim 2, wherein comparing the candidate user representation to each of the reference user representations to obtain a comparison comprises:
comparing the user label in the candidate user picture with the user label in the reference user picture, and taking the same user label as a target user label;
calculating the ratio of the number of the labels of the target user to the number of the labels in the reference user portrait;
if the calculated ratio is greater than a preset ratio, it is determined that the candidate user profile matches the reference user profile.
4. The method of claim 1, prior to said obtaining a plurality of reference user representations, further comprising:
determining the reference user of the countering robot customer service;
and constructing the reference user picture according to the user behavior information and the user attribute information corresponding to the reference user.
5. The method of claim 4, wherein the determining the reference user of countering robot customer service comprises:
acquiring a plurality of call records;
if the call record meets the preset condition, determining the user corresponding to the call record as the reference user;
the preset condition comprises that the call duration corresponding to the call record is less than the preset duration, and the hang-up node of the call record is at least one of the preset nodes.
6. The method according to claim 4, wherein the constructing the reference user image according to the user behavior information and the user attribute information corresponding to the reference user comprises:
generating a first user label according to the user attribute information corresponding to the reference user;
generating a second user label according to the user behavior information corresponding to the reference user;
and constructing the reference user picture according to the first user label and the second user label.
7. The method according to any one of claims 4 to 6, wherein the user attribute information includes at least one of age, gender and occupation of the user, and the user behavior information includes at least one of type of purchased products, number of purchased products, frequency of online purchases and user purchase preference of the user.
8. A call control apparatus, characterized in that the apparatus comprises:
a reference user profile acquisition module for acquiring a plurality of reference user profiles; the reference user representation comprises a plurality of user tags corresponding to reference users; the reference user is a user of the counter robot customer service; the user tag is used for indicating the attribute or the behavior of the user;
the target user screening module is used for screening a target user from a plurality of candidate users which are not called according to the reference user image;
and the calling module is used for calling the target user by adopting manual customer service.
9. A computer device comprising a memory and a processor, the memory storing a computer program, wherein the processor implements the steps of the method of any one of claims 1 to 7 when executing the computer program.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010155739.5A CN111526253B (en) | 2020-03-09 | 2020-03-09 | Call control method, device, computer equipment and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010155739.5A CN111526253B (en) | 2020-03-09 | 2020-03-09 | Call control method, device, computer equipment and storage medium |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN111526253A true CN111526253A (en) | 2020-08-11 |
| CN111526253B CN111526253B (en) | 2022-02-08 |
Family
ID=71910546
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010155739.5A Active CN111526253B (en) | 2020-03-09 | 2020-03-09 | Call control method, device, computer equipment and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111526253B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114205468A (en) * | 2020-09-17 | 2022-03-18 | 北京有限元科技有限公司 | Telephone traffic distribution method and device based on intelligent prediction and computing equipment |
Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107590159A (en) * | 2016-07-08 | 2018-01-16 | 阿里巴巴集团控股有限公司 | The method and apparatus that robot customer service turns artificial customer service |
| CN107977460A (en) * | 2017-12-20 | 2018-05-01 | 姜涵予 | Communication way based on listener clustering determines method and device |
| CN108022107A (en) * | 2016-10-31 | 2018-05-11 | 上海赛特斯信息科技股份有限公司 | The method that intelligent customer service robot communicates with client |
| CN108304435A (en) * | 2017-09-08 | 2018-07-20 | 腾讯科技（深圳）有限公司 | Information recommendation method, device, computer equipment and storage medium |
| CN108519991A (en) * | 2018-02-28 | 2018-09-11 | 北京奇艺世纪科技有限公司 | A kind of method and apparatus of main broadcaster's account recommendation |
| CN109087175A (en) * | 2018-08-15 | 2018-12-25 | 深圳追科技有限公司 | The method, apparatus and system of customer service session switching |
| CN109636501A (en) * | 2018-10-30 | 2019-04-16 | 深圳壹账通智能科技有限公司 | Product data processing method, device, computer equipment and computer readable storage medium |
| CN109636302A (en) * | 2018-10-23 | 2019-04-16 | 平安科技（深圳）有限公司 | Outgoing call rule configuration method, calling-out method, device and communication equipment |
| CN109767237A (en) * | 2018-12-05 | 2019-05-17 | 深圳供电局有限公司 | Method and system for intelligent access of customer service |
| CN109934619A (en) * | 2019-02-13 | 2019-06-25 | 北京三快在线科技有限公司 | User's portrait tag modeling method, apparatus, electronic equipment and readable storage medium storing program for executing |
| CN110472023A (en) * | 2019-07-10 | 2019-11-19 | 深圳追一科技有限公司 | Customer service switching method, device, computer equipment and storage medium |
| CN110634018A (en) * | 2019-08-30 | 2019-12-31 | 阿里巴巴集团控股有限公司 | Feature depiction method, recognition method and related device for lost user |
| US20200020015A1 (en) * | 2018-07-10 | 2020-01-16 | International Business Machines Corporation | Ecommerce product-recommendation engine with recipient-based gift selection |
-
2020
- 2020-03-09 CN CN202010155739.5A patent/CN111526253B/en active Active
Patent Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107590159A (en) * | 2016-07-08 | 2018-01-16 | 阿里巴巴集团控股有限公司 | The method and apparatus that robot customer service turns artificial customer service |
| CN108022107A (en) * | 2016-10-31 | 2018-05-11 | 上海赛特斯信息科技股份有限公司 | The method that intelligent customer service robot communicates with client |
| CN108304435A (en) * | 2017-09-08 | 2018-07-20 | 腾讯科技（深圳）有限公司 | Information recommendation method, device, computer equipment and storage medium |
| CN107977460A (en) * | 2017-12-20 | 2018-05-01 | 姜涵予 | Communication way based on listener clustering determines method and device |
| CN108519991A (en) * | 2018-02-28 | 2018-09-11 | 北京奇艺世纪科技有限公司 | A kind of method and apparatus of main broadcaster's account recommendation |
| US20200020015A1 (en) * | 2018-07-10 | 2020-01-16 | International Business Machines Corporation | Ecommerce product-recommendation engine with recipient-based gift selection |
| CN109087175A (en) * | 2018-08-15 | 2018-12-25 | 深圳追科技有限公司 | The method, apparatus and system of customer service session switching |
| CN109636302A (en) * | 2018-10-23 | 2019-04-16 | 平安科技（深圳）有限公司 | Outgoing call rule configuration method, calling-out method, device and communication equipment |
| CN109636501A (en) * | 2018-10-30 | 2019-04-16 | 深圳壹账通智能科技有限公司 | Product data processing method, device, computer equipment and computer readable storage medium |
| CN109767237A (en) * | 2018-12-05 | 2019-05-17 | 深圳供电局有限公司 | Method and system for intelligent access of customer service |
| CN109934619A (en) * | 2019-02-13 | 2019-06-25 | 北京三快在线科技有限公司 | User's portrait tag modeling method, apparatus, electronic equipment and readable storage medium storing program for executing |
| CN110472023A (en) * | 2019-07-10 | 2019-11-19 | 深圳追一科技有限公司 | Customer service switching method, device, computer equipment and storage medium |
| CN110634018A (en) * | 2019-08-30 | 2019-12-31 | 阿里巴巴集团控股有限公司 | Feature depiction method, recognition method and related device for lost user |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114205468A (en) * | 2020-09-17 | 2022-03-18 | 北京有限元科技有限公司 | Telephone traffic distribution method and device based on intelligent prediction and computing equipment |
Also Published As
| Publication number | Publication date |
|---|---|
| CN111526253B (en) | 2022-02-08 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111340237B (en) | Data processing and model running method, device and computer equipment | |
| WO2019061991A1 (en) | Multi-element universal model platform modeling method, electronic device, and computer readable storage medium | |
| CN108230346B (en) | Method and device for segmenting semantic features of image and electronic equipment | |
| JP2020515983A (en) | Target person search method and device, device, program product and medium | |
| CN111325352B (en) | Model updating method, device, equipment and medium based on longitudinal federal learning | |
| CN111614843A (en) | Call configuration determining method and device, computer equipment and storage medium | |
| CN110880100A (en) | Business approval processing method, device and system | |
| CN112256318B (en) | Construction method and equipment for dependent product | |
| CN111526253B (en) | Call control method, device, computer equipment and storage medium | |
| CN111857803A (en) | Page updating method, device, server and storage medium | |
| CN113468886B (en) | Work order processing method and device and computer equipment | |
| CN110020910B (en) | Object recommendation method and device | |
| CN109785867B (en) | Double-recording flow configuration method and device, computer equipment and storage medium | |
| CN112068812A (en) | Micro-service generation method and device, computer equipment and storage medium | |
| CN113992784B (en) | Audio and video call method, device, computer equipment and storage medium | |
| CN115424001A (en) | Scene similarity estimation method and device, computer equipment and storage medium | |
| CN112818235B (en) | Method and device for identifying illegal user based on association characteristics and computer equipment | |
| CN112862008A (en) | Training method of preference prediction model and prediction method of user preference | |
| CN111176630A (en) | Method and device for changing identity information of person on duty | |
| CN113918131B (en) | Face recognition method and system | |
| CN113450124B (en) | Outbound method and device based on user behavior, electronic equipment and medium | |
| CN117289840A (en) | Menu determination method, device, equipment, medium and product based on portrait tag | |
| CN116962335A (en) | Prompt message sending method and device, computer equipment and storage medium | |
| CN115237409A (en) | Method, device, equipment and storage medium for controlling node operation authority | |
| CN114238756A (en) | Message recommendation method, device, equipment and medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |