CN113079263B - Method, device, system and medium for intelligent customer service switching - Google Patents
Method, device, system and medium for intelligent customer service switching Download PDFInfo
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- CN113079263B CN113079263B CN202110283805.1A CN202110283805A CN113079263B CN 113079263 B CN113079263 B CN 113079263B CN 202110283805 A CN202110283805 A CN 202110283805A CN 113079263 B CN113079263 B CN 113079263B
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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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- 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
- H04M3/5166—Centralised call answering arrangements requiring operator intervention, e.g. call or contact centers for telemarketing in combination with interactive voice response systems or voice portals, e.g. as front-ends
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Abstract
The disclosure provides a method, a device, a system and a medium for intelligent customer service switching. The method comprises the following steps: receiving a consultation problem of a user; identifying user intention according to the consultation problem; replying the consultation problem based on the response knowledge points which are acquired from the response knowledge point library and are matched with the user intention; determining whether the current man-machine conversation content triggers a manual condition; if the current man-machine conversation content triggers a manual conversion condition, matching according to the mapping relation between the historical man-machine conversation content and the pre-established manual customer service group-dialogue information to obtain a response manual service group; and initiating a transfer request for designating the response manual customer service group to the manual customer service system. The method of the embodiment of the disclosure can be matched with the manual service group with proper skills according to the mapping relation during the transfer of the people.
Description
Technical Field
The disclosure relates to the technical field of internet, and more particularly, to a method, a device, a system and a medium for intelligent customer service switching.
Background
In the related art, a reply message of a customer service is automatically replied by a robot unless a customer specifies a service type that needs to be manually serviced in case of a manual switching requirement of the customer, so that the robot response system switches to the manual customer service according to the service type.
In implementing the concepts of the present disclosure, the inventors found that at least the following problems exist in the prior art: in some scenarios, since the customer does not know the service type corresponding to the own transfer requirement, the service type is usually designated randomly or is not designated practically, which may result in a situation that the skill of the manual service being transferred is not matched with the problem consulted by the customer or does not belong to the responsibility category, which results in a scenario that requires a second transfer, which may cause the resource waste of the manual service and the problem of the customer not being solved in time.
Disclosure of Invention
In view of this, the present disclosure provides a method, apparatus, system and medium for intelligent customer service switching.
A first aspect of the present disclosure provides a method of intelligent customer service switching. The method comprises the following steps: receiving a consultation problem of a user; identifying user intention according to the consultation problem; replying the consultation problem based on the response knowledge points which are acquired from the response knowledge point library and are matched with the user intention; determining whether the current man-machine conversation content triggers a manual condition; if the current man-machine conversation content triggers a manual conversion condition, matching according to the mapping relation between the historical man-machine conversation content and the pre-established manual customer service group-dialogue information to obtain a response manual service group; and initiating a transfer request for designating the response manual customer service group to the manual customer service system.
According to an embodiment of the present disclosure, the above-mentioned dialog information includes at least one of: the consultation questions of the user, the identified user intention, the identified user emotion, the response knowledge points and the response answers; and matching the skill of the artificial customer service group with at least one of the consultation questions of the user, the user intention, the user emotion, the response knowledge points and the response answers based on the mapping relation between the artificial customer service group and the dialogue information.
According to an embodiment of the present disclosure, the mapping relationship includes: a first mapping relation between the artificial customer service group and the response knowledge points, and a second mapping relation between the artificial customer service group and the response answers; the first mapping relation and the second mapping relation have a preset priority order. Matching according to the historical man-machine conversation content and the pre-established mapping relation of the artificial customer service group-dialogue information to obtain a response artificial customer service group, wherein the method comprises the following steps: matching the human-computer conversation content of one group of human-computer conversation content in the history human-computer conversation content based on the mapping relation with higher priority in the first mapping relation and the second mapping relation to obtain a response human-computer conversation group; and under the condition that the response manual skill cannot be obtained by matching the group of man-machine conversation contents based on the mapping relation with higher priority, matching the group of man-machine conversation contents by using the manual service group based on the mapping relation with lower priority.
According to the embodiment of the disclosure, the group of man-machine conversation contents are selected from the historical man-machine conversation contents in a time reverse order, and under the condition that the current group of man-machine conversation contents cannot be matched with the artificial customer service group, the next group of man-machine conversation contents are matched.
According to an embodiment of the present disclosure, the above method further includes: and pre-establishing a mapping relation between the manual customer service group and the dialogue information. The pre-establishing the mapping relation between the artificial customer service group and the dialogue information comprises the following steps: acquiring a historical reply answer, an identified user intention and an identified user emotion corresponding to a historical consultation problem of a user; acquiring all response knowledge points in a response knowledge point base; and matching the skills of the artificial customer service group with at least one of the historical consultation questions of the user, the identified user intention, the identified user emotion, all response knowledge points and the historical response answers to obtain a mapping relation of the artificial customer service group-dialogue information.
According to an embodiment of the present disclosure, the determining whether the current man-machine conversation content triggers a manual condition includes: if the times that the user intention identified by the consultation problem of the user in the current man-machine session is detected to be the same as the user intention identified in the historical man-machine session of the man-machine session interface exceeds a set value, triggering a manual condition; if the number of times that the consultation problem of the user is continuously repeated is recognized to exceed the preset value, triggering a manual condition; if the dissatisfaction of the user reaches the preset degree according to the consultation problem of the user in the current man-machine session, triggering a manual condition; and if the related expression of the transfer manual is contained in the consultation problem of the user in the current man-machine session, triggering the transfer manual condition.
According to the embodiment of the disclosure, if the current man-machine conversation content triggers a manual-to-manual condition, a manual-to-machine response message is generated; and under the condition that the response manual customer service group is matched, adding the identification of the response manual customer service group into the response message of the manual machine. The step of initiating a transfer request for designating the response manual customer service group to the manual customer service system includes: and converting the manual machine response message carrying the identification of the response manual customer service group into a message protocol format which can be identified by the manual customer service system, and then sending the message protocol format to the manual customer service system.
A second aspect of the present disclosure provides an intelligent customer service switching apparatus. The device comprises: the system comprises a receiving module, an intention recognition module, a reply module, a determination module, a manual customer service group matching module and a request sending module. The receiving module is used for receiving the consultation questions of the user. The intention recognition module is used for recognizing the intention of the user according to the consultation problem. And the reply module is used for replying the consultation problem based on the response knowledge points which are acquired from the response knowledge point library and are matched with the user intention. The determining module is used for determining whether the current man-machine conversation content triggers a manual condition. The artificial customer service group matching module is used for matching according to the mapping relation between the historical man-machine conversation content and the pre-established artificial customer service group-dialogue information to obtain a response artificial customer service group under the condition that the current man-machine conversation content triggers the manual conversion condition. The request sending module is used for initiating a transfer request for designating the response manual customer service group to the manual customer service system.
A third aspect of the present disclosure provides an intelligent customer service system. The intelligent customer service system comprises: one or more processors; and a storage device for storing one or more programs. Wherein the one or more programs, when executed by the one or more processors, cause the one or more processors to implement any of the methods described above.
A fourth aspect of the present disclosure provides a customer service system. The customer service system comprises: the intelligent customer service switching device or the intelligent customer service system and the artificial customer service system are described above. The artificial customer service system is used for receiving the transfer request initiated by the device or the intelligent customer service system and carrying out idle artificial customer service transfer in the response artificial customer service group appointed by the transfer request.
A fifth aspect of the present disclosure provides a computer-readable storage medium. The computer readable storage medium has stored thereon executable instructions that, when executed by a processor, cause the processor to implement any of the methods described above.
A sixth aspect of the present disclosure provides a computer program product. The computer program product comprises computer executable instructions which, when executed, are adapted to carry out any of the methods as described above.
According to the embodiment of the disclosure, based on the pre-established mapping relation of the artificial customer service group-dialogue information, the artificial customer service group with proper skills can be matched according to the mapping relation during transferring, so that the problems that the skills of the transferred artificial customer service are not matched with the problems consulted by the customer or the secondary transfer is required due to the fact that the customer does not know the service type corresponding to the transfer requirement of the customer or the customer does not belong to the responsibility category of the customer are avoided, and the problems that the resources of the artificial customer service are wasted and the problems of the customer are not solved in time can be at least partially solved.
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The above and other objects, features and advantages of the present disclosure will become more apparent from the following description of embodiments thereof with reference to the accompanying drawings in which:
FIG. 1 schematically illustrates a system architecture of a method suitable for implementing intelligent customer service switching in accordance with an embodiment of the present disclosure;
FIG. 2 schematically illustrates a flow chart of a method of intelligent customer service diversion in accordance with an embodiment of the present disclosure;
FIG. 3 schematically illustrates a detailed implementation flowchart of operation S25, according to an embodiment of the present disclosure;
FIG. 4 schematically illustrates a flow chart of a method of intelligent customer service diversion in accordance with another embodiment of the present disclosure;
FIG. 5 schematically illustrates a detailed implementation flowchart of operation S20, according to an embodiment of the present disclosure;
FIG. 6 schematically illustrates a flow chart of a method of intelligent customer service diversion in accordance with yet another embodiment of the present disclosure;
FIG. 7 schematically illustrates a block diagram of an apparatus for intelligent customer service switching in accordance with an embodiment of the present disclosure;
FIG. 8 schematically illustrates a block diagram of a smart customer service system, in accordance with an embodiment of the present disclosure; and
fig. 9 schematically shows a block diagram of a customer service system according to an embodiment of the present disclosure.
Detailed Description
Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. It should be understood that the description is only exemplary and is not intended to limit the scope of the present disclosure. In the following detailed description, for purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of the embodiments of the present disclosure. It may be evident, however, that one or more embodiments may be practiced without these specific details. In addition, in the following description, descriptions of well-known structures and techniques are omitted so as not to unnecessarily obscure the concepts of the present disclosure.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the disclosure. The terms "comprises," "comprising," and/or the like, as used herein, specify the presence of stated features, steps, operations, and/or components, but do not preclude the presence or addition of one or more other features, steps, operations, or components.
All terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art unless otherwise defined. It should be noted that the terms used herein should be construed to have meanings consistent with the context of the present specification and should not be construed in an idealized or overly formal manner.
Where expressions like at least one of "A, B and C, etc. are used, the expressions should generally be interpreted in accordance with the meaning as commonly understood by those skilled in the art (e.g.," a system having at least one of A, B and C "shall include, but not be limited to, a system having a alone, B alone, C alone, a and B together, a and C together, B and C together, and/or A, B, C together, etc.).
The embodiment of the disclosure provides an intelligent customer service switching method, an intelligent customer service switching device, an intelligent customer service system, a customer service system and a computer readable storage medium. The method can be applied to an intelligent customer service system. The method comprises the following steps: receiving a consultation problem of a user; identifying user intention according to the consultation problem; replying the consultation problem based on the response knowledge points which are acquired from the response knowledge point library and are matched with the user intention; determining whether the current man-machine conversation content triggers a manual condition; if the current man-machine conversation content triggers a manual conversion condition, matching according to the mapping relation between the historical man-machine conversation content and the pre-established manual customer service group-dialogue information to obtain a response manual service group; and initiating a transfer request for designating the response manual customer service group to the manual customer service system.
Fig. 1 schematically illustrates a system architecture of a method suitable for implementing intelligent customer service switching in accordance with an embodiment of the present disclosure. It should be noted that fig. 1 is only an example of a system architecture to which embodiments of the present disclosure may be applied to assist those skilled in the art in understanding the technical content of the present disclosure, but does not mean that embodiments of the present disclosure may not be used in other devices, systems, environments, or scenarios.
Referring to fig. 1, a system architecture 100 suitable for implementing a method of intelligent customer service switching includes: a user terminal device 101, an intelligent customer service system 102 and a manual customer service system 103.
The client device 101 has a customer service operation interface for connecting to customer service, and may also be provided with various communication client applications, such as shopping applications, web browser applications, search applications, instant messaging tools, mailbox clients, social platform software, etc. (only for example).
The intelligent customer service system 102 may be disposed in the customer premise equipment 101, or the intelligent customer service system 102 and the customer premise equipment 101 are two main bodies, which can be in communication connection. The intelligent customer service system 102 provides background data support and services for a customer service operation interface on the user side device 101.
The artificial customer service system 103 is in communication connection with the intelligent customer service system 102 and the user side equipment 101, and the intelligent customer service system 102 in the user side equipment 101 is used for sending an artificial transfer request to the artificial customer service system 103, and the artificial customer service distributed by the artificial customer service system 103 provides solutions to the problem of user consultation. Alternatively, the user equipment 101 sends the manual transfer request to the intelligent customer service system 102, and the intelligent customer service system 102 forwards the manual transfer request to the manual customer service system 103.
In an exemplary embodiment, referring to the single arrow in fig. 1, the user may input the consultation questions based on the customer service operation interface of the user side device 101, and the intelligent customer service system 102 replies to the consultation questions of the user.
In another exemplary embodiment, referring to the double-headed arrow in fig. 1, when a user-consulted question triggers a manual transfer condition, a manual transfer request is sent by the intelligent customer service system 102 to the manual customer service system 103, so that the manual customer service distributed by the manual customer service system 103 provides a solution to the user-consulted question.
The method for intelligent customer service switching provided in the embodiments of the present disclosure may be performed by the user device 101 or the intelligent customer service system 102. Accordingly, the intelligent customer service switching device may be disposed in the customer premise equipment 101 or the intelligent customer service system 102.
A first exemplary embodiment of the present disclosure provides a method of intelligent customer service switching.
Fig. 2 schematically illustrates a flow chart of a method of intelligent customer service diversion according to an embodiment of the present disclosure.
Referring to fig. 2, the method for intelligent customer service switching provided in the embodiment of the disclosure includes the following operations: s21, S22, S23, S24, S25 and S26.
In operation S21, a consultation problem of the user is received.
In operation S22, the user intention is identified according to the above-mentioned consultation problem.
In operation S23, the consultation question is replied based on the response knowledge points which are acquired from the response knowledge point library and match the user' S intention.
In operation S24, it is determined whether the current man-machine conversation content triggers a transfer manual condition.
In operation S25, if the current man-machine conversation content triggers a manual condition, the response manual service group is obtained according to the matching of the mapping relationship between the history man-machine conversation content and the pre-established manual service group-dialogue information.
In the above-mentioned mapping relationship between the artificial customer service group and the dialogue information, the dialogue information may include at least one of the following: the user's consultation questions, the identified user intent, the identified user emotion, the answer knowledge points and answer answers, etc. In the mapping relation, the skills of the artificial customer service group are matched with at least one of the consultation questions, the user intention, the user emotion, the response knowledge points and the response answers of the user, so that the artificial customer service in the artificial customer service group can provide targeted service for the user, continuity of dialogue information between the intelligent customer service system and the artificial customer service system is realized, and the skills of the artificial customer service can be better matched with the requirements of the user, so that the satisfaction degree of the user is improved. For example, matching human services can answer a class of questions well or be adept at handling poorly-engaging customers. In addition, the skills of the artificial customer service groups can be rated or scored, and the proper artificial customer service groups can be matched according to the requirements of users in the dialogue information, for example, the artificial customer service groups with higher comprehensive grading grades can be matched for service preferentially.
In operation S26, a transfer request designating the response artificial customer service group is initiated to the artificial customer service system.
The operations S21 to S26 may be performed by the user terminal device 101 or the intelligent customer service system 102.
According to the intelligent customer service switching method, based on the pre-established mapping relation between the artificial customer service group and the dialogue information, the artificial customer service group with proper skills can be matched according to the mapping relation during switching, and the matched artificial customer service group can provide good services on at least one aspect of soothing the emotion of a user, solving the problem of user consultation and the like, so that the problems that the skill of the switched artificial customer service is not matched with the problem consulted by the user or the problem of secondary switching is not required due to the fact that a customer does not know the service type corresponding to the switching requirement of the customer, and the problems that the resource waste of the artificial customer service is wasted and the problem of the customer is not solved in time can be at least partially solved.
According to an embodiment of the present disclosure, the mapping relationship includes: the first mapping relation between the artificial customer service group and the response knowledge points, and the second mapping relation between the artificial customer service group and the response answers. The first mapping relation and the second mapping relation have a preset priority order.
According to an embodiment of the present disclosure, determining whether the current man-machine conversation content triggers a transfer manual condition includes: if the times that the user intention identified by the consultation problem of the user in the current man-machine session is detected to be the same as the user intention identified in the historical man-machine session of the man-machine session interface exceeds a set value, triggering a manual condition; if the number of times of recognizing that the consultation problem of the user is continuously repeated exceeds a preset value, triggering a transfer-to-work condition; if the dissatisfaction of the user reaches the preset degree according to the consultation problem of the user in the current man-machine session, triggering a manual condition; and if the related expression of the transfer manual is contained in the consultation problem of the user in the current man-machine session, triggering the transfer manual condition. The manual condition is triggered as long as one of the conditions is satisfied.
Fig. 3 schematically shows a detailed implementation flowchart of operation S25 according to an embodiment of the present disclosure.
According to an embodiment of the present disclosure, referring to fig. 3, an operation S25 of obtaining a response artificial customer service group according to matching of a mapping relationship between a history man-machine conversation content and pre-established artificial customer service group-dialogue information includes the following sub-operations: s251 and S252.
In sub-operation S251, matching of the artificial customer service group is performed on a group of man-machine conversation contents in the history man-machine conversation contents based on the mapping relationship with higher priority in the first mapping relationship and the second mapping relationship, so as to obtain a response artificial customer service group.
In sub-operation S252, in the case that the group of man-machine conversation contents is not matched based on the mapping relationship with higher priority to obtain the response artificial customer service group, the group of man-machine conversation contents is matched based on the mapping relationship with lower priority to obtain the response artificial customer service group.
In this way, the matching of the artificial customer service group is preferentially performed on the group of man-machine conversation contents based on the mapping relation with higher priority, and the response artificial customer service group with higher matching degree is preferentially obtained. And under the condition that the response to the artificial customer service group cannot be obtained by matching, matching the artificial customer service group for the man-machine conversation content of the group based on the mapping relation with lower priority, and effectively ensuring the matching of the artificial customer service group.
In an embodiment, according to the actual evaluation effect, compared with the answer knowledge points, the answer is matched to the user intention to a higher degree, so as to reflect the actual requirement of the user, and therefore, the priority order of the second mapping relationship of the artificial customer service group-answer is set to be higher than the first mapping relationship of the artificial customer service group-answer knowledge points.
The matching of the artificial customer service group can be carried out on the group of man-machine conversation contents based on the second mapping relation of the artificial customer service group-answer reply; and if the matching is performed to obtain the artificial customer service group, the artificial customer service group obtained by the matching is the response artificial customer service group. And if the artificial customer service group cannot be obtained by matching, matching the artificial customer service group with the man-machine conversation content of the group based on the first mapping relation of the artificial customer service group and the response knowledge points.
According to the embodiment of the disclosure, the group of man-machine conversation contents are selected from the historical man-machine conversation contents in a time reverse order, and under the condition that the current group of man-machine conversation contents cannot be matched with the artificial customer service group, the next group of man-machine conversation contents are matched.
The historical human-computer conversation content is in a question-answer form, and the matching is carried out according to the latest time priority by setting a mode of selecting the historical human-computer conversation content in a reverse order to match, so that the actual demands of users can be reflected with high probability. In addition, in the second mapping relationship, the skills of the artificial customer service group may be matched with at least one of the emotion of the user and the intention of the user in addition to the answer, that is, in the second mapping relationship, the skills of the artificial customer service group are matched with the answer and the emotion of the user at the same time, or matched with the answer, the emotion of the user and the intention of the user at the same time. The manual skill set is good at replying to answers to questions/intentions that are involved in the answer, and at the same time is good at handling the user's emotion.
Fig. 4 schematically illustrates a flow chart of a method of intelligent customer service diversion according to another embodiment of the present disclosure.
According to an embodiment of the present disclosure, referring to fig. 4, the method for intelligent customer service switching provided in the embodiment of the present disclosure includes operations S20 in addition to operations S21 to S26 described above: and pre-establishing a mapping relation between the manual customer service group and the dialogue information.
Fig. 5 schematically shows a detailed implementation flowchart of operation S20 according to an embodiment of the present disclosure.
Referring to fig. 5, an operation S20 of pre-establishing a mapping relationship between an artificial customer service group and dialogue information provided by an embodiment of the present disclosure includes the following sub-operations: s201, S202, S203, and S204.
In operation S201, a historical answer corresponding to the historical consultation question of the user, a corresponding user intention, and an identified user emotion are obtained.
In operation S202, all the answer knowledge points in the answer knowledge point library are acquired.
In operation S203, a mapping relationship between the artificial customer service group and the dialogue information is obtained based on the matching of the skills of the artificial customer service group with at least one of the historical consultation questions of the user, the identified user intention, the identified user emotion, all the response knowledge points and the historical response answers.
For example, the first mapping relation between the artificial customer service group and the response knowledge points is established according to the skill of the artificial customer service group and all the response knowledge points in the response knowledge point base.
And establishing a second mapping relation between the artificial customer service group and the answer according to the skill of the artificial customer service group and the historical answer. In the second mapping relationship, the skills of the artificial customer service group can be matched with at least one of the emotion of the user and the intention of the user at the same time besides the matching with the answer.
The first mapping relationship and the second mapping relationship established above are stored, for example, in a database of the intelligent customer service system 102, and are called when needed. For example, the first mapping and the second mapping are stored in a distributed database.
In addition, the stored first mapping relationship and second mapping relationship may be updated, where the updating includes: add, delete, modify, etc. The above-described updating may be performed directly in the database. The timing of the update includes: at least one of the response knowledge points in the response knowledge point library, the history response answers corresponding to the history consultation questions, or the skill level of the manual customer service group is changed, and in this case, the mapping relationship is updated.
Fig. 6 schematically illustrates a flow chart of a method of intelligent customer service diversion according to yet another embodiment of the present disclosure.
According to an embodiment of the present disclosure, referring to fig. 6, the method for intelligent customer service switching provided by the embodiment of the present disclosure includes the following operations in addition to the operations S21, S22, S23, S24, and S25 described above: s31, S32 and S33.
In operation S31, if the current man-machine session content triggers a transfer manual condition, a transfer manual machine response message is generated.
In operation S32, if the answer manual service group is matched, the identification of the answer manual service group is added to the machine answer message.
In operation S33, the above-mentioned response message from the machine to the man is converted into a message protocol format recognizable by the man-made service system, and then sent to the man-made service system.
The operation S31 is performed after the operation S24, the operation S32 is performed after the operation S25, and the operation S33 is a specific embodiment of the operation S26.
A second exemplary embodiment of the present disclosure provides an apparatus for intelligent customer service switching.
Fig. 7 schematically illustrates a block diagram of an apparatus for intelligent customer service switching in accordance with an embodiment of the present disclosure.
Referring to fig. 7, an apparatus 400 provided in an embodiment of the present disclosure includes: a receiving module 40l, an intention recognition module 402, a reply module 403, a determination module 404, a manual customer service group matching module 405, and a request sending module 406.
The receiving module 401 is configured to receive a consultation problem of a user.
The intention recognition module 402 is used to recognize the intention of the user according to the above-mentioned consultation questions.
The reply module 403 is configured to reply to the consultation problem based on the answer knowledge points that are acquired from the answer knowledge point library and match the user intention.
The determining module 404 is configured to determine whether the current man-machine session content triggers a transfer manual condition.
According to an embodiment of the present disclosure, determining whether the current man-machine conversation content triggers a transfer manual condition includes: if the times that the user intention identified by the consultation problem of the user in the current man-machine session is detected to be the same as the user intention identified in the historical man-machine session of the man-machine session interface exceeds a set value, triggering a manual condition; if the number of times that the consultation problem of the user is continuously repeated is recognized to exceed the preset value, triggering a manual condition; if the dissatisfaction of the user reaches the preset degree according to the consultation problem of the user in the current man-machine session, triggering a manual condition; and if the related expression of the transfer manual is contained in the consultation problem of the user in the current man-machine session, triggering the transfer manual condition. The manual condition is triggered as long as one of the conditions is satisfied.
The artificial customer service group matching module 405 is configured to obtain a response artificial customer service group according to matching between the historical human-machine conversation content and the mapping relationship between the pre-established artificial customer service group and the dialogue information under the condition that the current human-machine conversation content triggers the conversion artificial condition.
The artificial group matching module 405 includes functional sub-modules for implementing operations S251 and S252 described above.
According to the embodiment of the disclosure, the group of man-machine conversation contents are selected from the historical man-machine conversation contents in a time reverse order, and under the condition that the current group of man-machine conversation contents cannot be matched with the artificial customer service group, the next group of man-machine conversation contents are matched.
The request sending module 406 is configured to initiate a transfer request to the artificial customer service system, where the transfer request is specified to answer the artificial customer service group.
Any number of modules, sub-modules, units, sub-units, or at least some of the functionality of any number of the sub-units according to embodiments of the present disclosure may be implemented in one module. Any one or more of the modules, sub-modules, units, sub-units according to embodiments of the present disclosure may be implemented as split into multiple modules. Any one or more of the modules, sub-modules, units, sub-units according to embodiments of the present disclosure may be implemented at least in part as a hardware circuit, such as a Field Programmable Gate Array (FPGA), a Programmable Logic Array (PLA), a system-on-chip, a system-on-substrate, a system-on-package, an Application Specific Integrated Circuit (ASIC), or in any other reasonable manner of hardware or firmware that integrates or encapsulates the circuit, or in any one of or a suitable combination of three of software, hardware, and firmware. Alternatively, one or more of the modules, sub-modules, units, sub-units according to embodiments of the present disclosure may be at least partially implemented as computer program modules, which when executed, may perform the corresponding functions.
For example, any of the receiving module 401, the intention identifying module 402, the replying module 403, the determining module 404, the manual group matching module 405, and the request transmitting module 406 may be combined in one module to be implemented, or any one of the modules may be split into a plurality of modules. Alternatively, at least some of the functionality of one or more of the modules may be combined with at least some of the functionality of other modules and implemented in one module. According to embodiments of the present disclosure, at least one of the receiving module 401, the intent identifying module 402, the replying module 403, the determining module 404, the manual group matching module 405, and the request sending module 406 may be implemented at least in part as hardware circuitry, such as a Field Programmable Gate Array (FPGA), a Programmable Logic Array (PLA), a system on a chip, a system on a substrate, a system on a package, an Application Specific Integrated Circuit (ASIC), or in hardware or firmware in any other reasonable way of integrating or packaging the circuitry, or in any one of or a suitable combination of three of software, hardware, and firmware. Alternatively, at least one of the receiving module 401, the intention recognition module 402, the reply module 403, the determining module 404, the artificial group matching module 405, and the request transmitting module 406 may be at least partially implemented as a computer program module, which when executed may perform the corresponding functions.
A third exemplary embodiment of the present disclosure provides an intelligent customer service system. The intelligent customer service system comprises: one or more processors; and a storage device for storing one or more programs. Wherein the one or more programs, when executed by the one or more processors, cause the one or more processors to implement any of the methods described above.
Fig. 8 schematically illustrates a block diagram of a smart customer service system in accordance with an embodiment of the present disclosure.
Referring to fig. 8, an intelligent customer service system 500 according to an embodiment of the present disclosure includes a processor 501, which may perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM) 502 or a program loaded from a storage section 508 into a Random Access Memory (RAM) 503. The processor 501 may include, for example, a general purpose microprocessor (e.g., a CPU), an instruction set processor and/or an associated chipset and/or a special purpose microprocessor (e.g., an Application Specific Integrated Circuit (ASIC)), or the like. The processor 501 may also include on-board memory for caching purposes. The processor 501 may comprise a single processing unit or a plurality of processing units for performing different actions of the method flows according to embodiments of the disclosure.
In the RAM 503, various programs and data required for the operation of the intelligent customer service system 500 are stored. The processor 501, ROM502, and RAM 503 are connected to each other by a bus 504. The processor 501 performs various operations of the method flow according to the embodiments of the present disclosure by executing programs in the ROM502 and/or the RAM 503. Note that the program may be stored in one or more memories other than the ROM502 and the RAM 503. The processor 501 may also perform various operations of the method flow according to embodiments of the present disclosure by executing programs stored in the one or more memories.
According to embodiments of the present disclosure, the intelligent customer service system 500 may also include an input/output (I/O) interface 505, the input/output (I/O) interface 505 also being connected to the bus 504. The intelligent customer service system 500 may also include one or more of the following components connected to the I/O interface 505: an input section 506 including a keyboard, a mouse, and the like; an output portion 507 including a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker, and the like; a storage portion 508 including a hard disk and the like; and a communication section 509 including a network interface card such as a Local Area Network (LAN) card, a modem, or the like. The communication section 509 performs communication processing via a network such as the internet. The drive 510 is also connected to the I/O interface 505 as needed. A removable medium 511 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 510 as needed so that a computer program read therefrom is mounted into the storage section 508 as needed.
A fourth exemplary embodiment of the present disclosure provides a customer service system. The customer service system comprises: the intelligent customer service switching device or the intelligent customer service system and the artificial customer service system are described above. The artificial customer service system is used for receiving the transfer request initiated by the device or the intelligent customer service system and carrying out idle artificial customer service transfer in the response artificial customer service group appointed by the transfer request.
Fig. 9 schematically shows a block diagram of a customer service system according to an embodiment of the present disclosure.
The customer service system 600 described above is taken as an example in fig. 9 to include an intelligent customer service system 601 and an artificial customer service system 602. In this embodiment, the artificial customer service system 602 is configured to receive a transfer request initiated by the intelligent customer service system, and perform idle artificial customer service transfer in a response artificial customer service group specified by the transfer request.
A fifth exemplary embodiment of the present disclosure provides a computer-readable storage medium. The computer readable storage medium has stored thereon executable instructions that, when executed by a processor, cause the processor to implement any of the methods described above.
The computer-readable storage medium may be embodied in the apparatus/device/system described in the above embodiments; or may exist alone without being assembled into the apparatus/device/system. The computer-readable storage medium carries one or more programs which, when executed, implement methods in accordance with embodiments of the present disclosure.
According to embodiments of the present disclosure, the computer-readable storage medium may be a non-volatile computer-readable storage medium, which may include, for example, but is not limited to: a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this disclosure, a computer-readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. For example, according to embodiments of the present disclosure, the computer-readable storage medium may include ROM 502 and/or RAM 503 and/or one or more memories other than ROM 502 and RAM 503 described above.
A sixth exemplary embodiment of the present disclosure provides a computer program product. The computer program product comprises computer executable instructions which, when executed, are adapted to carry out any of the methods as described above.
The computer program product of the embodiments of the present disclosure includes a computer program loaded on a computer-readable storage medium, the computer program containing program code for executing the method shown in the flowchart. In such an embodiment, the computer program may be downloaded and installed from a network via the communication portion 509, and/or installed from the removable media 511. The above-described functions defined in the system of the embodiments of the present disclosure are performed when the computer program is executed by the processor 501. The systems, devices, apparatus, modules, units, etc. described above may be implemented by computer program modules according to embodiments of the disclosure.
The above-described functions defined in the system/apparatus of the embodiments of the present disclosure are performed when the computer program is executed by the processor 501. The systems, apparatus, modules, units, etc. described above may be implemented by computer program modules according to embodiments of the disclosure.
In one embodiment, the computer program may be based on a tangible storage medium such as an optical storage device, a magnetic storage device, or the like. In another embodiment, the computer program may also be transmitted, distributed, and downloaded and installed in the form of a signal on a network medium, and/or installed from a removable medium 511 via the communication portion 509. The computer program may include program code that may be transmitted using any appropriate network medium, including but not limited to: wireless, wired, etc., or any suitable combination of the foregoing.
According to embodiments of the present disclosure, program code for performing computer programs provided by embodiments of the present disclosure may be written in any combination of one or more programming languages, and in particular, such computer programs may be implemented in high-level procedural and/or object-oriented programming languages, and/or assembly/machine languages. Programming languages include, but are not limited to, such as Java, c++, python, "C" or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, partly on a remote computing device, or entirely on the remote computing device or server. In the case of remote computing devices, the remote computing device may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computing device (e.g., connected via the Internet using an Internet service provider).
The flowcharts 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 be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams 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.
Those skilled in the art will appreciate that the features recited in the various embodiments of the disclosure and/or in the claims may be combined in various combinations and/or combinations, even if such combinations or combinations are not explicitly recited in the disclosure. In particular, the features recited in the various embodiments of the present disclosure and/or the claims may be variously combined and/or combined without departing from the spirit and teachings of the present disclosure. All such combinations and/or combinations fall within the scope of the present disclosure.
The embodiments of the present disclosure are described above. However, these examples are for illustrative purposes only and are not intended to limit the scope of the present disclosure. Although the embodiments are described above separately, this does not mean that the measures in the embodiments cannot be used advantageously in combination. The scope of the disclosure is defined by the appended claims and equivalents thereof. Various alternatives and modifications can be made by those skilled in the art without departing from the scope of the disclosure, and such alternatives and modifications are intended to fall within the scope of the disclosure.
Claims (9)
1. A method of intelligent customer service switching, the method comprising:
receiving a consultation problem of a user;
identifying user intent based on the consultation questions;
replying the consultation problem based on the response knowledge points which are acquired from the response knowledge point library and are matched with the user intention;
determining whether the current man-machine conversation content triggers a manual transfer condition comprises the following steps: if the times that the user intention identified by the consultation problem of the user in the current man-machine session is detected to be the same as the user intention identified in the historical man-machine session of the man-machine session interface exceeds a set value, triggering a manual condition; if the number of times that the consultation problem of the user is continuously repeated is recognized to exceed the preset value, triggering a manual condition; if the dissatisfaction of the user reaches the preset degree according to the consultation problem of the user in the current man-machine session, triggering a manual condition; triggering a manual conversion condition if the related manual conversion expression is contained in the consultation problem of the user in the current man-machine session;
If the current man-machine conversation content triggers a manual conversion condition, a response manual service group is obtained according to matching of the historical man-machine conversation content and a mapping relation of the pre-established manual service group-dialogue information, wherein the mapping relation comprises the following steps: a first mapping relation between the artificial customer service group and the response knowledge points, and a second mapping relation between the artificial customer service group and the response answers; the priority order of the second mapping relation is higher than that of the first mapping relation; and
initiating a transfer request for designating the response manual customer service group to a manual customer service system;
wherein, the matching of the mapping relation between the historical man-machine conversation content and the pre-established manual customer service group-dialogue information to obtain the response manual customer service group comprises the following steps:
matching a group of man-machine conversation contents in the history man-machine conversation contents by using the mapping relation with higher priority in the first mapping relation and the second mapping relation to obtain a response man-machine conversation content;
and under the condition that the response manual skill cannot be obtained by matching the group of man-machine conversation contents based on the mapping relation with higher priority, matching the group of man-machine conversation contents by using the manual service group based on the mapping relation with lower priority.
2. The method of claim 1, wherein the dialog information includes at least one of: the consultation questions of the user, the identified user intention, the identified user emotion, the response knowledge points and the response answers; and in the mapping relation of the artificial customer service group and the dialogue information, matching is carried out based on the skill of the artificial customer service group and at least one of the consultation questions of the user, the user intention, the user emotion, the response knowledge points and the response answers.
3. The method of claim 2, wherein the set of human-machine conversation content is selected from the historical human-machine conversation content in a reverse order of time, and matching of a next set of human-machine conversation content is performed if the current set of human-machine conversation content does not match a human-machine service group.
4. The method of claim 1, further comprising: pre-establishing a mapping relation between the manual customer service group and the dialogue information;
the pre-establishing the mapping relation between the artificial customer service group and the dialogue information comprises the following steps:
acquiring a historical reply answer, an identified user intention and an identified user emotion corresponding to a historical consultation problem of a user;
acquiring all response knowledge points in a response knowledge point base; and
And matching the skills of the artificial customer service group with at least one of the historical consultation questions of the user, the identified user intention, the identified user emotion, all response knowledge points and the historical response answers to obtain a mapping relation of the artificial customer service group-dialogue information.
5. The method of claim 1, wherein,
if the current man-machine conversation content triggers a man-machine conversion condition, a man-machine conversion response message is generated;
under the condition that the response manual customer service group is matched, adding the identification of the response manual customer service group into the response message of the machine for transferring the manual work;
the step of initiating a transfer request for designating the response manual customer service group to the manual customer service system comprises the following steps:
and converting the manual machine response message carrying the identification of the response manual customer service group into a message protocol format which can be identified by the manual customer service system, and then sending the message protocol format to the manual customer service system.
6. An intelligent customer service switching device, comprising:
the receiving module is used for receiving the consultation problem of the user;
the intention recognition module is used for recognizing the intention of the user according to the consultation problem;
the reply module is used for replying the consultation problem based on the response knowledge points which are acquired from the response knowledge point library and are matched with the user intention;
The determining module is used for determining whether the current man-machine conversation content triggers a manual condition or not, and comprises the following steps: if the times that the user intention identified by the consultation problem of the user in the current man-machine session is detected to be the same as the user intention identified in the historical man-machine session of the man-machine session interface exceeds a set value, triggering a manual condition; if the number of times that the consultation problem of the user is continuously repeated is recognized to exceed the preset value, triggering a manual condition; if the dissatisfaction of the user reaches the preset degree according to the consultation problem of the user in the current man-machine session, triggering a manual condition; triggering a manual conversion condition if the related manual conversion expression is contained in the consultation problem of the user in the current man-machine session;
the artificial customer service group matching module is used for matching according to the mapping relation between the historical man-machine conversation content and the pre-established artificial customer service group-dialogue information to obtain a response artificial customer service group under the condition that the current man-machine conversation content triggers a manual conversion condition, wherein the mapping relation comprises the following steps: a first mapping relation between the artificial customer service group and the response knowledge point, and a second mapping relation between the artificial customer service group and the response answer, wherein the priority order of the second mapping relation is higher than that of the first mapping relation; the step of obtaining the response artificial customer service group according to the matching of the historical man-machine conversation content and the mapping relation of the pre-established artificial customer service group-dialogue information comprises the following steps: matching a group of man-machine conversation contents in the history man-machine conversation contents by using the mapping relation with higher priority in the first mapping relation and the second mapping relation to obtain a response man-machine conversation content; under the condition that the response manual skill cannot be obtained by matching the group of man-machine conversation contents based on the mapping relation with higher priority, matching the group of man-machine conversation contents with a manual customer service group based on the mapping relation with lower priority; and
And the request sending module is used for initiating a transfer request for designating the response manual customer service group to the manual customer service system.
7. An intelligent customer service system, comprising:
one or more processors; and
storage means for storing one or more programs,
wherein the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the method of any of claims 1-5.
8. A customer service system, comprising:
the apparatus of claim 6 or the intelligent customer service system of claim 7; and
and the artificial customer service system is used for receiving a transfer request initiated by the device or the intelligent customer service system and carrying out idle artificial customer service transfer in a response artificial customer service group appointed by the transfer request.
9. A computer readable storage medium having stored thereon executable instructions which when executed by a processor cause the processor to implement the method of any of claims 1-5.
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| CN113342962A (en) * | 2021-07-07 | 2021-09-03 | 上海华客信息科技有限公司 | Customer service method, system, device and storage medium |
| CN113472958A (en) * | 2021-07-13 | 2021-10-01 | 上海华客信息科技有限公司 | Method, system, electronic device and storage medium for receiving branch telephone in centralized mode |
| CN113724036A (en) * | 2021-07-29 | 2021-11-30 | 阿里巴巴（中国）有限公司 | Method and electronic equipment for providing question consultation service |
| CN113704432A (en) * | 2021-08-31 | 2021-11-26 | 广州方舟信息科技有限公司 | Artificial intelligence customer service system construction method and device based on Internet hospital |
| CN114173008A (en) * | 2021-11-12 | 2022-03-11 | 杭州摸象大数据科技有限公司 | Customer service switching calling method, customer service switching calling device, computer equipment and storage medium |
| CN114117157B (en) * | 2021-11-19 | 2024-04-09 | 招联消费金融股份有限公司 | Session processing method, apparatus, computer device and storage medium |
| CN114925192A (en) * | 2022-07-21 | 2022-08-19 | 北京聆心智能科技有限公司 | Man-machine collaborative dialogue method, device, equipment and storage medium |
| CN116739235B (en) * | 2023-05-06 | 2024-03-22 | 广州圈量网络信息科技有限公司 | Intelligent community service management system based on big data |
| CN117456653A (en) * | 2023-10-25 | 2024-01-26 | 威海万伟达信息科技有限公司 | Queuing and calling system and queuing and calling method for government affair service hall |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
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