CN109981910B - Service recommendation method and device - Google Patents
Service recommendation method and device Download PDFInfo
- Publication number
- CN109981910B CN109981910B CN201910131517.7A CN201910131517A CN109981910B CN 109981910 B CN109981910 B CN 109981910B CN 201910131517 A CN201910131517 A CN 201910131517A CN 109981910 B CN109981910 B CN 109981910B
- Authority
- CN
- China
- Prior art keywords
- service
- target
- voice response
- interactive voice
- response system
- 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.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 60
- 230000002452 interceptive effect Effects 0.000 claims abstract description 145
- 230000004044 response Effects 0.000 claims abstract description 145
- 238000013528 artificial neural network Methods 0.000 claims abstract description 28
- 238000012549 training Methods 0.000 claims abstract description 12
- 238000004891 communication Methods 0.000 claims description 75
- 239000000126 substance Substances 0.000 claims 4
- 238000013518 transcription Methods 0.000 abstract description 5
- 230000035897 transcription Effects 0.000 abstract description 5
- 238000013461 design Methods 0.000 description 17
- 238000010586 diagram Methods 0.000 description 8
- 238000005516 engineering process Methods 0.000 description 5
- 238000011161 development Methods 0.000 description 4
- 230000018109 developmental process Effects 0.000 description 4
- 230000008569 process Effects 0.000 description 4
- 238000012545 processing Methods 0.000 description 4
- 230000005540 biological transmission Effects 0.000 description 3
- 230000008878 coupling Effects 0.000 description 3
- 238000010168 coupling process Methods 0.000 description 3
- 238000005859 coupling reaction Methods 0.000 description 3
- 230000003287 optical effect Effects 0.000 description 3
- 239000002699 waste material Substances 0.000 description 3
- 230000000694 effects Effects 0.000 description 2
- 238000010295 mobile communication Methods 0.000 description 2
- RWSOTUBLDIXVET-UHFFFAOYSA-N Dihydrogen sulfide Chemical compound S RWSOTUBLDIXVET-UHFFFAOYSA-N 0.000 description 1
- 210000004556 brain Anatomy 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000003032 molecular docking Methods 0.000 description 1
- 230000002093 peripheral effect Effects 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 230000001360 synchronised effect Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
- G10L15/00—Speech recognition
- G10L15/08—Speech classification or search
-
- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
- G10L15/00—Speech recognition
- G10L15/08—Speech classification or search
- G10L15/18—Speech classification or search using natural language modelling
- G10L15/1822—Parsing for meaning understanding
-
- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
- G10L15/00—Speech recognition
- G10L15/22—Procedures used during a speech recognition process, e.g. man-machine dialogue
-
- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
- G10L15/00—Speech recognition
- G10L15/26—Speech to text systems
-
- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
- G10L25/00—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00
- G10L25/27—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 characterised by the analysis technique
- G10L25/30—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 characterised by the analysis technique using neural networks
-
- 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
- H04M3/5166—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
-
- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
- G10L15/00—Speech recognition
- G10L15/08—Speech classification or search
- G10L2015/088—Word spotting
-
- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
- G10L15/00—Speech recognition
- G10L15/22—Procedures used during a speech recognition process, e.g. man-machine dialogue
- G10L2015/225—Feedback of the input speech
Abstract
The embodiment of the invention provides a service recommendation method and equipment, wherein the method comprises the following steps: acquiring service handling voice of a user, and performing voice recognition on the service handling voice to obtain a target text; determining a target intention keyword corresponding to a target text according to a deep neural network, wherein the deep neural network is obtained by training according to the text and the intention keyword; judging whether the target intention keywords are matched with an automatic business handling system or not; and if so, determining a target interactive voice response system corresponding to the target intention keywords from the automatic business handling system, and recommending the business to the user by adopting the target interactive voice response system based on the target intention keywords. The method provided by the embodiment can provide real-time semantic transcription and semantic understanding for the online customer service, synchronously identify the service requirements of the clients, and synchronously recommend the online service in real time according to the automatic service handling system, so that the service which is most suitable for the current users can be recommended, and the users can enjoy thousands of informed services.
Description
Technical Field
The embodiment of the invention relates to the technical field of communication, in particular to a service recommendation method and device.
Background
With the development of mobile communication technology, mobile services have also been developed rapidly. Mobile terminals, especially mobile phones, are becoming more and more intelligent, and innovations and developments of mobile services are also being driven. A mobile service package is a service package for data transmission that is introduced by an operator according to the needs of different users. With the increase of mobile service types, operators need to recommend various mobile service packages to users in order to meet different requirements of users and promote the use of mobile services.
The existing online mobile service package recommendation method generally adopts a traditional method to recommend, namely under the condition that the service handled by a communication terminal applied by a user is known, service personnel can recommend service packages to the user according to the existing service.
However, the existing recommendation method has low recommendation success rate and wastes resources.
Disclosure of Invention
The embodiment of the invention provides a service recommendation method and equipment, which aim to solve the problems of low recommendation success rate and resource waste of the existing service recommendation method.
In a first aspect, an embodiment of the present invention provides a service recommendation method, including:
acquiring service handling voice of a user, and performing voice recognition on the service handling voice to obtain a target text corresponding to the service handling voice;
determining a target intention keyword corresponding to the target text according to a deep neural network, wherein the deep neural network is obtained by training according to the text and the intention keyword;
judging whether the target intention keywords are matched with an automatic business handling system or not;
and if the target intention keywords are matched with the automatic business handling system, determining a target interactive voice response system corresponding to the target intention keywords from the automatic business handling system, and recommending the business to the user based on the target intention keywords by adopting the target interactive voice response system.
In one possible design, the targeted interactive voice response system is a first interactive voice response system;
after the target interactive voice response system is adopted and the target intention keywords are used for recommending the service to the user, the method further comprises the following steps:
and if the business transaction refusing information of the user is obtained, adopting a manual business transaction system to perform business recommendation on the user based on the target intention keywords.
In one possible design, the targeted interactive voice response system is a second interactive voice response system;
after the target interactive voice response system is adopted and the target intention keywords are used for recommending the service to the user, the method further comprises the following steps:
if the business transaction refusing information of the user is obtained, obtaining a judgment result of whether the target intention keyword is matched with a first interactive voice response system by a manual business transaction system;
and if the obtained judgment result is that the target intention keywords are matched with the first interactive voice response system, adopting the first interactive voice response system to recommend the service to the user based on the target intention keywords.
In one possible design, the recommending, with the first interactive voice response system, the business to the user based on the target intention keyword comprises:
judging whether the target intention keywords are preset intention keywords or not;
if the target intention keyword is the preset intention keyword, acquiring the times of service recommendation of the user based on the preset intention keyword by adopting the first interactive voice response system;
and if the times are lower than a preset time threshold value, performing service recommendation on the user based on the target intention keywords by adopting the first interactive voice response system.
In one possible design, the method further includes:
if the target intention keyword is not matched with the automatic service handling system, acquiring a judgment result of the manual service handling system whether the target intention keyword is matched with a first interactive voice response system;
and if the obtained judgment result is that the target intention keywords are matched with the first interactive voice response system, adopting the first interactive voice response system to recommend the service to the user based on the target intention keywords.
In a possible design, before acquiring the service transacting voice of the user, the method further includes:
receiving an incoming call of the user, and judging whether a communication terminal corresponding to the incoming call is stopped;
if the communication terminal is not stopped, judging whether the communication terminal is defaulting;
if the communication terminal is not defaulted, judging whether the telephone charge balance of the communication terminal is lower than a preset value;
if the telephone charge balance of the communication terminal is equal to or higher than the preset value, judging whether the communication terminal is matched with a preset flow packet service or not according to the service handled by the communication terminal;
and if the communication terminal is not matched with the preset flow packet service, generating a service handling prompt voice, and sending the service handling prompt voice to the communication terminal.
In a second aspect, an embodiment of the present invention provides a service recommendation device, including:
the voice acquisition module is used for acquiring service handling voice of a user, performing voice recognition on the service handling voice and acquiring a target text corresponding to the service handling voice;
the intention keyword determining module is used for determining a target intention keyword corresponding to the target text according to a deep neural network, and the deep neural network is obtained by training according to the text and the intention keyword;
the first intention keyword judgment module is used for judging whether the target intention keywords are matched with the automatic business handling system or not;
and the first service recommendation module is used for determining a target interactive voice response system corresponding to the target intention keyword from the automatic business handling system if the target intention keyword is matched with the automatic business handling system, and recommending the service to the user by adopting the target interactive voice response system based on the target intention keyword.
In one possible design, the targeted interactive voice response system is a first interactive voice response system;
the apparatus further comprises:
and the second service recommendation module is used for adopting the target interactive voice response system to perform service recommendation on the user based on the target intention keyword in the first service recommendation module, and adopting a manual service handling system to perform service recommendation on the user based on the target intention keyword if service handling refusal information of the user is obtained.
In one possible design, the targeted interactive voice response system is a second interactive voice response system;
the apparatus further comprises:
the second intention keyword judgment module is used for acquiring a judgment result of whether the target intention keyword is matched with the first interactive voice response system by the manual handling service system or not if business handling refusing information of the user is acquired after the first business recommendation module adopts the target interactive voice response system and carries out business recommendation on the user based on the target intention keyword;
and the third service recommendation module is used for recommending the service to the user based on the target intention keyword by adopting the first interactive voice response system if the acquired judgment result is that the target intention keyword is matched with the first interactive voice response system.
In one possible design, the third service recommendation module employs the first interactive voice response system to make service recommendations for the user based on the target intention keywords, and includes:
judging whether the target intention keywords are preset intention keywords or not;
if the target intention keyword is the preset intention keyword, acquiring the times of service recommendation of the user based on the preset intention keyword by adopting the first interactive voice response system;
and if the times are lower than a preset time threshold value, performing service recommendation on the user based on the target intention keywords by adopting the first interactive voice response system.
In one possible design, the above apparatus further includes:
the third intention keyword judgment module is used for acquiring a judgment result of whether the target intention keyword is matched with the first interactive voice response system or not by the manual business handling system if the target intention keyword is not matched with the automatic business handling system;
and the fourth service recommendation module is used for recommending the service to the user based on the target intention keyword by adopting the first interactive voice response system if the acquired judgment result is that the target intention keyword is matched with the first interactive voice response system.
In one possible design, the above apparatus further includes:
the system comprises a voice acquisition module, a shutdown judgment module and a voice processing module, wherein the voice acquisition module is used for acquiring business handling voice of a user, receiving an incoming call of the user and judging whether a communication terminal corresponding to the incoming call is shutdown or not;
the arrearage judging module is used for judging whether the communication terminal is arrearage or not if the communication terminal is not stopped;
the telephone charge balance judging module is used for judging whether the telephone charge balance of the communication terminal is lower than a preset value or not if the communication terminal does not arrear;
the traffic packet service judgment module is used for judging whether the communication terminal is matched with a preset traffic packet service according to the service handled by the communication terminal if the telephone charge balance of the communication terminal is equal to or higher than the preset value;
and the voice generating module is used for generating service handling prompt voice if the communication terminal is not matched with the preset flow packet service, and sending the service handling prompt voice to the communication terminal.
In a third aspect, an embodiment of the present invention provides a service recommendation device, including: at least one processor and memory;
the memory stores computer-executable instructions;
the at least one processor executing the computer-executable instructions stored by the memory causes the at least one processor to perform the business recommendation method as set forth in the first aspect above and in various possible designs of the first aspect.
In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, where computer-executable instructions are stored, and when a processor executes the computer-executable instructions, the service recommendation method according to the first aspect and various possible designs of the first aspect is implemented.
In the service recommendation method and device provided by this embodiment, the method performs voice recognition on the service handling voice by obtaining the service handling voice of the user, and obtains a target text corresponding to the service handling voice; determining a target intention keyword corresponding to a target text by using a deep neural network, wherein the deep neural network is obtained by training according to the text and the intention keyword; judging whether the target intention keywords are matched with an automatic business handling system or not; if the matching is carried out, a target interactive voice response system corresponding to the target intention keywords is determined from the automatic service handling system, the target interactive voice response system is utilized to carry out service recommendation on the user based on the target intention keywords, real-time semantic transcription and semantic understanding can be provided for the online customer service, the service appeal of the client is synchronously identified, the online service recommendation is synchronized in real time according to the existing automatic service handling system, the service which is most suitable for the user at present can be recommended, the service interacts with the user in real time, and the user can enjoy thousands of informed services.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
Fig. 1 is an application scenario diagram of a service recommendation method according to an embodiment of the present invention;
fig. 2 is a first flowchart of a service recommendation method according to an embodiment of the present invention;
fig. 3 is a flowchart illustrating a second service recommendation method according to an embodiment of the present invention;
fig. 4 is a first schematic structural diagram of a service recommendation device according to an embodiment of the present invention;
fig. 5 is a schematic structural diagram of a service recommendation device according to an embodiment of the present invention;
fig. 6 is a schematic diagram of a hardware structure of a service recommendation device according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The terms "first," "second," "third," "fourth," and the like in the description and in the claims, as well as in the drawings, if any, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are, for example, capable of operation in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
With the development of mobile communication technology, mobile services are also rapidly developed, and mobile terminals, especially mobile phones, are more and more intelligent, and meanwhile, innovation and development of mobile services are also driven. A mobile service package is a service package for data transmission that is introduced by an operator according to the needs of different users. With the increase of mobile service types, operators need to recommend various mobile service packages to users in order to meet different requirements of users and promote the use of mobile services. The existing online mobile service package recommendation method generally adopts a traditional method to recommend, namely under the condition that the service handled by a communication terminal applied by a user is known, service personnel can recommend service packages to the user according to the existing service. However, the existing recommendation method has low recommendation success rate and wastes resources.
Therefore, in view of the above problems, the present invention provides a service recommendation method, which obtains a service handling voice of a user, performs voice recognition on the service handling voice, and obtains a target text corresponding to the service handling voice; determining a target intention keyword corresponding to a target text by using a deep neural network, wherein the deep neural network is obtained by training according to the text and the intention keyword; judging whether the target intention keywords are matched with an automatic business handling system or not; if the matching is carried out, a target interactive voice response system corresponding to the target intention keywords is determined from the automatic service handling system, the target interactive voice response system is utilized to carry out service recommendation on the user based on the target intention keywords, real-time semantic transcription and semantic understanding can be provided for the online customer service, the service appeal of the client is synchronously identified, the online service recommendation is synchronously carried out in real time according to the existing automatic service handling system, the service which is most suitable for the user at present can be recommended, the service interacts with the user in real time, and the user can enjoy thousands of informed services.
Fig. 1 is an application scenario diagram of a service recommendation method provided by the present invention. As shown in fig. 1, a customer service system 101 may obtain a service handling voice of a user, perform voice recognition on the service handling voice to obtain a target text corresponding to the service handling voice, may determine a target intention keyword corresponding to the target text by using a deep neural network 102, the deep neural network is obtained by training according to the text and the intention keyword, may determine whether the target intention keyword matches with an automatic service handling system, and if the target intention keyword matches with the automatic service handling system, determine a target interactive voice response system corresponding to the target intention keyword from the automatic service handling system, and perform service recommendation on the user based on the target intention keyword by using the target interactive voice response system.
The customer service system can provide a dialogue platform for the user to dialogue with the user, and has the functions of service consultation, service recommendation, service handling and the like.
Fig. 2 is a first flowchart of a service recommendation method according to an embodiment of the present invention, where an execution subject of this embodiment may be a customer service system in the embodiment shown in fig. 1. As shown in fig. 2, the method may include:
s201, obtaining service handling voice of a user, performing voice recognition on the service handling voice, and obtaining a target text corresponding to the service handling voice.
Here, the customer service system may receive a service handling voice sent by a user through a communication terminal of the user, and then perform low-cost docking through a Media Resource Control Protocol (MRCP) or a Transmission Control Protocol (TCP), so as to convert a voice signal into a text stream for real-time output.
Optionally, before the obtaining of the service handling voice of the user, the customer service system may further:
receiving an incoming call of the user, and judging whether a communication terminal corresponding to the incoming call is stopped;
if the communication terminal is not stopped, judging whether the communication terminal is defaulting;
if the communication terminal is not defaulted, judging whether the telephone charge balance of the communication terminal is lower than a preset value;
if the telephone charge balance of the communication terminal is equal to or higher than the preset value, judging whether the communication terminal is matched with a preset flow packet service or not according to the service handled by the communication terminal;
and if the communication terminal is not matched with the preset flow packet service, generating a service handling prompt voice, and sending the service handling prompt voice to the communication terminal.
Specifically, if the communication terminal is stopped, the customer service system can judge whether the communication terminal is a mobile phone or a fixed phone; if the communication terminal is a mobile phone, the customer service system can judge whether the mobile phone is in arrearage shutdown or non-arrearage shutdown, if the mobile phone is in arrearage shutdown, the customer service system can generate a payment guiding voice and send the voice to the mobile phone, and if the mobile phone is in non-arrearage shutdown, the customer service system can generate a shutdown process voice and send the voice to the mobile phone; if the communication terminal is a fixed telephone, the customer service system can directly generate shutdown flow voice and send the voice to the fixed telephone.
If the communication terminal is arreared, the customer service system can generate an arrearage condition voice and send the voice to the communication terminal.
And if the telephone charge balance of the communication terminal is lower than a preset value, the customer service system can generate a suggested payment voice and send the voice to the communication terminal. And if the customer service system receives the payment request of the communication terminal, the customer service system generates payment guiding voice and sends the voice to the communication terminal. If the customer service system receives the payment refusing information of the communication terminal, the customer service system can execute the step of judging whether the communication terminal is matched with the preset flow packet service according to the service transacted by the communication terminal.
The determining whether the communication terminal is matched with the preset traffic packet service may include: and judging whether the communication terminal meets the condition of handling the preset flow packet service according to the consumption condition in the preset time period of the communication terminal and the current service handling condition, wherein the condition can be set according to the actual condition. If the communication terminal meets the condition of handling the preset flow packet service, the customer service system can generate a flow packet handling guide voice and send the voice to the communication terminal, wherein the preset flow packet service can also be set according to the actual condition.
S202, determining a target intention keyword corresponding to the target text according to a deep neural network, wherein the deep neural network is obtained by training according to the text and the intention keyword.
The Deep Neural Network (DNN) is voice recognition software, and the working principle of the Deep Neural Network (DNN) is to simulate a human brain thinking mode, so that the voice recognition speed of the software is higher, and the recognition accuracy is higher.
Deep neural networks can be trained from a large number of text and intent keywords. Here, the trained deep neural network is used to identify the intention keyword corresponding to the target text, wherein the intention keyword may be a keyword related to a business that the user wants to transact.
S203, judging whether the target intention keywords are matched with an automatic business handling system.
Here, the customer service system determines whether the target intention keyword matches with an automatic transaction system, wherein the automatic transaction system may include a first Interactive Voice Response system, such as an intelligent Interactive Voice Response (IVR), and a second Interactive Voice Response system, such as a conventional IVR. The traditional IVR prompts a user to press keys, judges the user intention according to a key pressing system, then matches answers with a knowledge base, and returns the answers to the user in a voice mode. The intelligent IVR adopts an intelligent voice recognition technology, recognizes the user intention according to voice recognition, and then calls the knowledge base content to return to the user in a voice form. The core of intelligent IVR is the voice recognition technology. The voice recognition technology enables the system to understand the voice of the user and understand the intention of the user, and enables the system to return the information needed by the client more quickly and accurately.
Specifically, the determining whether the target intention keyword matches with the automatic transaction system may include: and judging whether the related information of the service transacted by the automatic transaction system contains the target intention keyword, if so, judging that the target intention keyword is matched with the automatic transaction system, and otherwise, judging that the target intention keyword is not matched with the automatic transaction system.
And S204, if the target intention keywords are matched with the automatic business handling system, determining a target interactive voice response system corresponding to the target intention keywords from the automatic business handling system, and recommending the business to the user by adopting the target interactive voice response system based on the target intention keywords.
Here, if the target intention keyword matches with the automatic transaction system, a target interactive voice response system corresponding to the target intention keyword is determined from the automatic transaction system, and service recommendation is performed on the user based on the target intention keyword by using the target interactive voice response system, wherein the target interactive voice response system may be the first interactive voice response system, such as an intelligent IVR, or a second interactive voice response system, such as a traditional IVR. Specifically, the method for determining the target interactive voice response system corresponding to the target intention keyword from the automatic business handling system may include: and judging which interactive voice response system transacted service related information in the automatic transaction service system contains the target intention keyword, and if the target interactive voice response system contains the target intention keyword, determining that the target intention keyword corresponds to the target interactive voice response system.
In addition, if the target intention keyword is not matched with the automatic business handling system, a manual business handling system is adopted, and business recommendation is carried out on the user based on the target intention keyword.
In the service recommendation method provided by this embodiment, the service handling voice of the user is acquired, and the voice recognition is performed on the service handling voice to acquire a target text corresponding to the service handling voice; determining a target intention keyword corresponding to a target text by using a deep neural network, wherein the deep neural network is obtained by training according to the text and the intention keyword; judging whether the target intention keywords are matched with an automatic business handling system or not; if the matching is carried out, a target interactive voice response system corresponding to the target intention keywords is determined from the automatic service handling system, the target interactive voice response system is utilized to carry out service recommendation on the user based on the target intention keywords, real-time semantic transcription and semantic understanding can be provided for the online customer service, the service appeal of the client is synchronously identified, the online service recommendation is synchronously carried out in real time according to the existing automatic service handling system, the service which is most suitable for the user at present can be recommended, the service interacts with the user in real time, and the user can enjoy thousands of informed services.
Fig. 3 is a second flowchart of a service recommendation method according to an embodiment of the present invention, and this embodiment describes details of a specific implementation process of this embodiment on the basis of the embodiment of fig. 2. As shown in fig. 3, the method may include:
s301, obtaining service handling voice of a user, performing voice recognition on the service handling voice, and obtaining a target text corresponding to the service handling voice.
S302, determining a target intention keyword corresponding to the target text according to a deep neural network, wherein the deep neural network is obtained by training according to the text and the intention keyword.
S303, judging whether the target intention keywords are matched with an automatic business handling system.
If the target intention keyword matches the automated transaction system, steps S304 to S309 are performed, and if the target intention keyword does not match the automated transaction system, steps S310 and S311 are performed.
S304, determining a target interactive voice response system corresponding to the target intention keyword from the automatic business handling system, and recommending the business to the user based on the target intention keyword by adopting the target interactive voice response system.
The specific implementation of S301 to S304 in this embodiment is similar to that of S201 to S204 in the above embodiment, and is not repeated here.
Specifically, after the target interactive voice response system is adopted and the service recommendation is performed on the user based on the target intention keyword, if the target interactive voice response system is the first interactive voice response system, step S305 is performed, and if the target interactive voice response system is the second interactive voice response system, steps S306 to S309 are performed.
S305, the target interactive voice response system is a first interactive voice response system, if the business transaction refusing information of the user is obtained, a manual business transaction system is adopted, and business recommendation is carried out on the user based on the target intention keywords.
Here, the first interactive voice response system may be an intelligent IVR. If a first interactive voice response system is adopted, after the user is recommended based on the target intention keywords, business information which is refused to be handled by the user is obtained, namely the recommended business is not the business which the user wants to handle, at the moment, a manual business handling system can be adopted, business recommendation is carried out on the user based on the target intention keywords, namely, business recommendation is carried out on the user by manual customer service based on the target intention keywords and communication with the user, the business which is most suitable for the user at present can be recommended, and the business requirements of the user are met.
S306, the target interactive voice response system is a second interactive voice response system, and if the business transaction refusing information of the user is obtained, a judgment result of whether the target intention keyword is matched with the first interactive voice response system by the manual business transaction system is obtained.
The second interactive voice response system may be a conventional IVR. If the second interactive voice response system is adopted, after the user is recommended to the service based on the target intention keyword, the information of refusing to handle the service of the user is obtained, at the moment, the judgment result of whether the target intention keyword is matched with the first interactive voice response system or not by the manual service handling system can be obtained, namely whether the target intention keyword is matched with the first interactive voice response system or not is judged by the manual service handling system, the judgment result is uploaded to the service handling system, the service handling system obtains the judgment result, and subsequent processing is carried out according to the judgment result.
S307, if the obtained judgment result is that the target intention keyword is matched with the first interactive voice response system, judging whether the target intention keyword is a preset intention keyword.
If the target intention keyword is matched with the first interactive voice response system, the customer service system judges whether the target intention keyword is a preset intention keyword, wherein the preset intention keyword can be set according to the actual situation.
In addition, if the obtained judgment result is that the target intention keyword is not matched with the first interactive voice response system, a manual business handling system is adopted, and business recommendation is carried out on the user based on the target intention keyword.
S308, if the target intention keyword is the preset intention keyword, acquiring the times of service recommendation of the user based on the preset intention keyword by adopting the first interactive voice response system.
If the target intention keyword is a preset intention keyword, the customer service system obtains the times of service recommendation to the user based on the preset intention keyword by adopting a first interactive voice response system, wherein the customer service system can record the current call or a preset time period, and the times of service recommendation to the user based on the preset intention keyword by adopting the first interactive voice response system.
S309, if the times are lower than a preset time threshold, performing service recommendation on the user based on the target intention keywords by using the first interactive voice response system.
If the acquired times are lower than a preset time threshold, wherein the preset time threshold can be set according to actual conditions, the customer service system can adopt the first interactive voice response system to recommend services to the user based on the target intention keywords. Otherwise, the customer service system can adopt a manual service handling system to recommend the service to the user based on the target intention keywords.
And if the target intention keyword is a non-preset intention keyword, acquiring the number of times of service recommendation of the user based on the non-preset intention keyword by using the first interactive voice response system, wherein the non-preset intention keyword can also be set according to the actual situation. If the acquired times are lower than a preset time threshold, wherein the preset time threshold can also be set according to the actual situation, the customer service system can adopt the first interactive voice response system to recommend the service to the user based on the target intention keywords. Otherwise, the customer service system can adopt a manual service handling system to recommend the service to the user based on the target intention keywords.
S310, obtaining a judgment result of whether the target intention keywords are matched with the first interactive voice response system or not by the manual business handling system.
S311, if the obtained judgment result is that the target intention keywords are matched with the first interactive voice response system, adopting the first interactive voice response system to recommend the service to the user based on the target intention keywords.
Specifically, with the first interactive voice response system, the recommending a service to the user based on the target intention keyword may be as follows: judging whether the target intention keywords are preset intention keywords or not; if the target intention keyword is the preset intention keyword, acquiring the times of service recommendation of the user based on the preset intention keyword by adopting the first interactive voice response system; and if the times are lower than a preset time threshold value, performing service recommendation on the user based on the target intention keywords by adopting the first interactive voice response system.
In addition, if the obtained judgment result is that the target intention keyword is not matched with the first interactive voice response system, the customer service system can adopt a manual business handling system to recommend the business to the user based on the target intention keyword.
The service recommendation method provided by the embodiment can provide real-time semantic transcription and semantic understanding for online customer service, synchronously identify the service requirements of clients, and synchronously perform online service recommendation in real time according to the existing automatic service handling system, so that the service which is most suitable for the user at present can be recommended and interacts with the user in real time, and the user can enjoy thousands of informed services.
Fig. 4 is a first schematic structural diagram of a service recommendation device according to an embodiment of the present invention. As shown in fig. 4, the service recommendation apparatus 40 includes: a voice obtaining module 401, an intention keyword determining module 402, a first intention keyword judging module 403, and a first service recommending module 404.
The voice acquiring module 401 is configured to acquire a service handling voice of a user, perform voice recognition on the service handling voice, and acquire a target text corresponding to the service handling voice.
An intention keyword determining module 402, configured to determine a target intention keyword corresponding to the target text according to a deep neural network, where the deep neural network is obtained by training according to the text and the intention keyword.
A first intention keyword judgment module 403, configured to judge whether the target intention keyword matches with an automatic transaction system.
A first service recommendation module 404, configured to determine, if the target intention keyword matches the automatic service handling system, a target interactive voice response system corresponding to the target intention keyword from the automatic service handling system, and perform service recommendation on the user based on the target intention keyword by using the target interactive voice response system.
The device provided in this embodiment may be used to implement the technical solution of the above method embodiment, and the implementation principle and technical effect are similar, which are not described herein again.
Fig. 5 is a schematic structural diagram of a service recommendation device according to an embodiment of the present invention. As shown in fig. 5, this embodiment further includes, on the basis of the embodiment in fig. 4: a second service recommendation module 405, a second intention keyword judgment module 406, a third service recommendation module 407, a third intention keyword judgment module 408, a fourth service recommendation module 409, a shutdown judgment module 410, an arrearage judgment module 411, a telephone charge balance judgment module 412, a traffic packet service judgment module 413 and a voice generation module 414.
In one possible design, the targeted interactive voice response system is a first interactive voice response system.
The second service recommendation module 405 is configured to, after the first service recommendation module 404 adopts the target interactive voice response system to recommend a service to the user based on the target intention keyword, if service information of the user refusing to handle is obtained, adopt a manual service handling system to recommend a service to the user based on the target intention keyword.
In one possible design, the targeted interactive voice response system is a second interactive voice response system.
The second intention keyword determination module 406 is configured to, after the first service recommendation module 404 adopts the target interactive voice response system and performs service recommendation on the user based on the target intention keyword, obtain a determination result of whether the target intention keyword is matched with the first interactive voice response system by the manual service handling system if the service information of the user refusing to handle is obtained.
And a third service recommendation module 407, configured to, if the obtained determination result is that the target intention keyword matches the first interactive voice response system, perform service recommendation on the user based on the target intention keyword by using the first interactive voice response system.
In one possible design, the third service recommendation module 407 employs the first interactive voice response system to make service recommendations for the user based on the target intention keywords, including:
judging whether the target intention keywords are preset intention keywords or not;
if the target intention keyword is the preset intention keyword, acquiring the times of service recommendation of the user based on the preset intention keyword by adopting the first interactive voice response system;
and if the times are lower than a preset time threshold value, performing service recommendation on the user based on the target intention keywords by adopting the first interactive voice response system.
In a possible design, the third intention keyword determining module 408 is configured to, if the target intention keyword does not match the automatic business handling system, obtain a determination result of the manual business handling system whether the target intention keyword matches the first interactive voice response system.
The fourth service recommendation module 409 is configured to, if the obtained determination result is that the target intention keyword matches the first interactive voice response system, perform service recommendation on the user based on the target intention keyword by using the first interactive voice response system.
In a possible design, the stop determining module 410 is configured to receive an incoming call of the user and determine whether a communication terminal corresponding to the incoming call is stopped before the voice acquiring module acquires a service handling voice of the user.
The arrearage judging module 411 is configured to judge whether the communication terminal is arrearage if the communication terminal is not stopped.
The telephone charge balance judging module 412 is configured to judge whether the telephone charge balance of the communication terminal is lower than a preset value if the communication terminal does not arrear.
The traffic packet service determining module 413 is configured to determine whether the communication terminal is matched with a preset traffic packet service according to a service handled by the communication terminal if the telephone charge balance of the communication terminal is equal to or higher than the preset value.
The voice generating module 414 is configured to generate a service handling prompt voice if the communication terminal is not matched with the preset traffic packet service, and send the service handling prompt voice to the communication terminal.
The device provided in this embodiment may be used to implement the technical solution of the above method embodiment, and the implementation principle and technical effect are similar, which are not described herein again.
Fig. 6 is a schematic diagram of a hardware structure of a service recommendation device according to an embodiment of the present invention. As shown in fig. 6, the service recommendation device 60 of the present embodiment includes: a processor 601 and a memory 602; wherein
A memory 602 for storing computer-executable instructions;
the processor 601 is configured to execute the computer-executable instructions stored in the memory to implement the steps performed by the service recommendation method in the foregoing embodiments. Reference may be made in particular to the description relating to the method embodiments described above.
Alternatively, the memory 602 may be separate or integrated with the processor 601.
When the memory 602 is separately provided, the service recommendation device further includes a bus 603 for connecting the memory 602 and the processor 601.
An embodiment of the present invention further provides a computer-readable storage medium, where a computer execution instruction is stored in the computer-readable storage medium, and when a processor executes the computer execution instruction, the service recommendation method is implemented as described above.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described device embodiments are merely illustrative, and for example, the division of the modules is only one logical division, and other divisions may be realized in practice, for example, a plurality of modules may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or modules, and may be in an electrical, mechanical or other form.
The modules described as separate parts may or may not be physically separate, and parts displayed as modules may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment.
In addition, functional modules in the embodiments of the present invention may be integrated into one processing unit, or each module may exist alone physically, or two or more modules are integrated into one unit. The unit formed by the modules can be realized in a hardware form, and can also be realized in a form of hardware and a software functional unit.
The integrated module implemented in the form of a software functional module may be stored in a computer-readable storage medium. The software functional module is stored in a storage medium and includes several instructions for enabling a computer device (which may be a personal computer, a server, or a network device) or a processor (processor) to execute some steps of the methods according to the embodiments of the present application.
It should be understood that the Processor may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of a method disclosed in connection with the present invention may be embodied directly in a hardware processor, or in a combination of the hardware and software modules within the processor.
The memory may comprise a high-speed RAM memory, and may further comprise a non-volatile storage NVM, such as at least one disk memory, and may also be a usb disk, a removable hard disk, a read-only memory, a magnetic or optical disk, etc.
The bus may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, an Extended ISA (EISA) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, the buses in the figures of the present application are not limited to only one bus or one type of bus.
The storage medium may be implemented by any type or combination of volatile or non-volatile memory devices, such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic or optical disks. A storage media may be any available media that can be accessed by a general purpose or special purpose computer.
An exemplary storage medium is coupled to the processor such the processor can read information from, and write information to, the storage medium. Of course, the storage medium may also be integral to the processor. The processor and the storage medium may reside in an Application Specific Integrated Circuits (ASIC). Of course, the processor and the storage medium may reside as discrete components in an electronic device or host device.
Those of ordinary skill in the art will understand that: all or a portion of the steps of implementing the above-described method embodiments may be performed by hardware associated with program instructions. The program may be stored in a computer-readable storage medium. When executed, the program performs steps comprising the method embodiments described above; and the aforementioned storage medium includes: various media that can store program codes, such as ROM, RAM, magnetic or optical disks.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.
Claims (8)
1. A method for recommending services, comprising:
acquiring service handling voice of a user, and performing voice recognition on the service handling voice to obtain a target text corresponding to the service handling voice;
determining a target intention keyword corresponding to the target text according to a deep neural network, wherein the deep neural network is obtained by training according to the text and the intention keyword;
judging whether the target intention keywords are matched with an automatic business handling system or not;
if the target intention keywords are matched with the automatic business handling system, determining a target interactive voice response system corresponding to the target intention keywords from the automatic business handling system, and recommending the business to the user based on the target intention keywords by adopting the target interactive voice response system; the automatic business handling system comprises a first interactive voice response system and a second interactive voice response system;
wherein the content of the first and second substances,
if the target interactive voice response system is a second interactive voice response system;
after the recommending the user for the service based on the target intention keyword by adopting the second interactive voice response system, the method further comprises the following steps:
if the business transaction refusing information of the user is obtained, obtaining a judgment result of whether the target intention keyword is matched with a first interactive voice response system by a manual business transaction system;
if the obtained judgment result is that the target intention keywords are matched with the first interactive voice response system, adopting the first interactive voice response system to recommend the service to the user based on the target intention keywords;
wherein the content of the first and second substances,
the method for recommending the service to the user based on the target intention keywords by adopting the first interactive voice response system comprises the following steps:
judging whether the target intention keywords are preset intention keywords or not;
if the target intention keyword is the preset intention keyword, acquiring the times of service recommendation of the user based on the preset intention keyword by adopting the first interactive voice response system;
if the times are lower than a preset time threshold value, performing service recommendation on the user based on the target intention keywords by adopting the first interactive voice response system;
wherein, the judging whether the target intention keyword is matched with an automatic transaction system comprises: and judging whether the related information of the service transacted by the automatic transaction system contains the target intention keyword, and if so, judging that the target intention keyword is matched with the automatic transaction system.
2. The method of claim 1, wherein if the targeted interactive voice response system is a first interactive voice response system;
after the recommending the user for the service based on the target intention keyword by adopting the first interactive voice response system, the method further comprises the following steps: and if the business transaction refusing information of the user is obtained, adopting a manual business transaction system to perform business recommendation on the user based on the target intention keywords.
3. The method of claim 1, further comprising:
if the target intention keyword is not matched with the automatic service handling system, acquiring a judgment result of the manual service handling system whether the target intention keyword is matched with a first interactive voice response system;
and if the obtained judgment result is that the target intention keywords are matched with the first interactive voice response system, adopting the first interactive voice response system to recommend the service to the user based on the target intention keywords.
4. The method of claim 1, prior to the obtaining the service transacting voice of the user, further comprising:
receiving an incoming call of the user, and judging whether a communication terminal corresponding to the incoming call is stopped;
if the communication terminal is not stopped, judging whether the communication terminal is defaulting;
if the communication terminal is not defaulted, judging whether the telephone charge balance of the communication terminal is lower than a preset value;
if the telephone charge balance of the communication terminal is equal to or higher than the preset value, judging whether the communication terminal is matched with a preset flow packet service or not according to the service handled by the communication terminal;
and if the communication terminal is not matched with the preset flow packet service, generating a service handling prompt voice, and sending the service handling prompt voice to the communication terminal.
5. A service recommendation device, comprising:
the voice acquisition module is used for acquiring service handling voice of a user, performing voice recognition on the service handling voice and acquiring a target text corresponding to the service handling voice;
the intention keyword determining module is used for determining a target intention keyword corresponding to the target text according to a deep neural network, and the deep neural network is obtained by training according to the text and the intention keyword;
the first intention keyword judgment module is used for judging whether the target intention keywords are matched with the automatic business handling system or not;
the first service recommendation module is used for determining a target interactive voice response system corresponding to the target intention keyword from the automatic business handling system if the target intention keyword is matched with the automatic business handling system, and performing service recommendation on the user based on the target intention keyword by adopting the target interactive voice response system; the automatic business handling system comprises a first interactive voice response system and a second interactive voice response system;
wherein the content of the first and second substances,
if the target interactive voice response system is a second interactive voice response system;
the apparatus further comprises:
the second intention keyword judgment module is used for acquiring a judgment result of whether the target intention keyword is matched with the first interactive voice response system by the manual handling service system or not if business handling refusing information of the user is acquired after the first business recommendation module adopts the second interactive voice response system to recommend the business to the user based on the target intention keyword;
the third service recommendation module is used for recommending the service to the user based on the target intention keyword by adopting the first interactive voice response system if the acquired judgment result is that the target intention keyword is matched with the first interactive voice response system;
wherein the content of the first and second substances,
the third service recommendation module adopts the first interactive voice response system to recommend services to the user based on the target intention keywords, and comprises:
judging whether the target intention keywords are preset intention keywords or not;
if the target intention keyword is the preset intention keyword, acquiring the times of service recommendation of the user based on the preset intention keyword by adopting the first interactive voice response system;
if the times are lower than a preset time threshold value, performing service recommendation on the user based on the target intention keywords by adopting the first interactive voice response system;
wherein, the judging whether the target intention keyword is matched with an automatic transaction system comprises: and judging whether the related information of the service transacted by the automatic transaction system contains the target intention keyword, and if so, judging that the target intention keyword is matched with the automatic transaction system.
6. The apparatus of claim 5, wherein if the targeted interactive voice response system is a first interactive voice response system;
the apparatus further comprises:
and the second service recommendation module is used for adopting the first interactive voice response system to recommend the service to the user based on the target intention keyword, and adopting a manual service handling system to recommend the service to the user based on the target intention keyword if the service handling refusal information of the user is obtained.
7. A service recommendation device, comprising: at least one processor and memory;
the memory stores computer-executable instructions;
the at least one processor executing the computer-executable instructions stored by the memory causes the at least one processor to perform the service recommendation method of any of claims 1-4.
8. A computer-readable storage medium having stored thereon computer-executable instructions which, when executed by a processor, implement the service recommendation method of any one of claims 1 to 4.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910131517.7A CN109981910B (en) | 2019-02-22 | 2019-02-22 | Service recommendation method and device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910131517.7A CN109981910B (en) | 2019-02-22 | 2019-02-22 | Service recommendation method and device |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN109981910A CN109981910A (en) | 2019-07-05 |
| CN109981910B true CN109981910B (en) | 2021-08-10 |
Family
ID=67077232
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910131517.7A Active CN109981910B (en) | 2019-02-22 | 2019-02-22 | Service recommendation method and device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109981910B (en) |
Families Citing this family (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110569806A (en) * | 2019-09-11 | 2019-12-13 | 上海软中信息系统咨询有限公司 | Man-machine interaction system |
| CN110677399B (en) * | 2019-09-20 | 2022-04-15 | 中国联合网络通信集团有限公司 | Authentication method and device |
| CN110619878B (en) * | 2019-10-17 | 2022-04-12 | 思必驰科技股份有限公司 | Voice interaction method and device for office system |
| CN111429157A (en) * | 2020-03-27 | 2020-07-17 | 上海东普信息科技有限公司 | Method, device and equipment for evaluating and processing complaint work order and storage medium |
| CN111710336B (en) * | 2020-06-05 | 2023-05-26 | 平安科技（深圳）有限公司 | Voice intention recognition method, device, computer equipment and storage medium |
| CN111813989B (en) * | 2020-07-02 | 2023-07-18 | 中国联合网络通信集团有限公司 | Information processing method, apparatus and storage medium |
| CN112199474A (en) * | 2020-10-19 | 2021-01-08 | 康佳集团股份有限公司 | Voice customer service method and system |
| CN112885348B (en) * | 2021-01-25 | 2024-03-08 | 广州中汇信息科技有限公司 | AI-combined intelligent voice electric marketing method |
| CN112927033A (en) * | 2021-01-27 | 2021-06-08 | 上海商汤智能科技有限公司 | Data processing method and device, electronic equipment and storage medium |
| CN113364920B (en) * | 2021-06-09 | 2023-01-20 | 中国银行股份有限公司 | Incoming line request processing method and device and electronic equipment |
| CN113468306A (en) * | 2021-06-30 | 2021-10-01 | 西安乾阳电子科技有限公司 | Voice conversation method, device, electronic equipment and storage medium |
| CN114095360B (en) * | 2021-11-12 | 2024-02-13 | 中国联合网络通信集团有限公司 | Communication service opening method and device |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103903097A (en) * | 2014-04-04 | 2014-07-02 | 中国联合网络通信集团有限公司 | Business handling data processing method and device |
| CN104751843A (en) * | 2013-12-25 | 2015-07-01 | 上海博泰悦臻网络技术服务有限公司 | Voice service switching method and voice service switching system |
Family Cites Families (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20030125958A1 (en) * | 2001-06-19 | 2003-07-03 | Ahmet Alpdemir | Voice-interactive marketplace providing time and money saving benefits and real-time promotion publishing and feedback |
| US7187761B2 (en) * | 2002-11-07 | 2007-03-06 | Blake Bookstaff | Method and system for providing advertising to telephone callers |
| US20090113312A1 (en) * | 2006-09-08 | 2009-04-30 | American Well Systems | Connecting Providers of Legal Services |
| CN102722539A (en) * | 2012-05-23 | 2012-10-10 | 华为技术有限公司 | Query method and device based on voice recognition |
| CN105469797A (en) * | 2015-12-31 | 2016-04-06 | 广东翼卡车联网服务有限公司 | Method and system for controlling switching-over from intelligent voice identification to manual services |
| CN107645613A (en) * | 2016-07-20 | 2018-01-30 | 平安科技（深圳）有限公司 | The method and apparatus of service diverting search |
| CN107666544B (en) * | 2017-06-15 | 2020-06-02 | 平安科技（深圳）有限公司 | Method, device and equipment for managing IVR incoming line |
| CN109348077A (en) * | 2018-11-23 | 2019-02-15 | 杭州简丽信息技术有限公司 | A kind of telephone system and application method manually switched with robot |
-
2019
- 2019-02-22 CN CN201910131517.7A patent/CN109981910B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104751843A (en) * | 2013-12-25 | 2015-07-01 | 上海博泰悦臻网络技术服务有限公司 | Voice service switching method and voice service switching system |
| CN103903097A (en) * | 2014-04-04 | 2014-07-02 | 中国联合网络通信集团有限公司 | Business handling data processing method and device |
Also Published As
| Publication number | Publication date |
|---|---|
| CN109981910A (en) | 2019-07-05 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109981910B (en) | Service recommendation method and device | |
| CN109514586B (en) | Method and system for realizing intelligent customer service robot | |
| CN107391359B (en) | Service testing method and device | |
| CN111932144B (en) | Customer service agent distribution method and device, server and storage medium | |
| WO2018086489A1 (en) | Method and device for processing incoming call, and terminal | |
| KR20190005930A (en) | Automatic reply method, apparatus, facility and computer readable storage medium | |
| CN109218390B (en) | User screening method and device | |
| CN110597952A (en) | Information processing method, server, and computer storage medium | |
| CN103679452A (en) | Payment authentication method, device thereof and system thereof | |
| CN106157023A (en) | A kind of method of payment and user terminal | |
| CN111583931A (en) | Service data processing method and device | |
| CN109949830B (en) | User intention identification method and device | |
| CN112183098B (en) | Session processing method and device, storage medium and electronic device | |
| CN111654582A (en) | Intelligent outbound method and device | |
| CN113383362A (en) | User identification method and related product | |
| CN115470318A (en) | Customer service problem processing method and device | |
| CN110489519B (en) | Session method based on session prediction model and related products | |
| CN115017289A (en) | Method and device for serving customers based on knowledge base | |
| CN112150252A (en) | Credit-based service processing method and device | |
| CN108257600B (en) | Voice processing method and device | |
| CN111126071A (en) | Method and device for determining questioning text data and data processing method of customer service group | |
| CN110516049A (en) | Service creation method, service creation device, computer equipment and computer readable storage medium | |
| CN113505272A (en) | Behavior habit based control method and device, electronic equipment and storage medium | |
| CN110929014B (en) | Information processing method, information processing device, electronic equipment and storage medium | |
| CN110047473B (en) | Man-machine cooperative interaction method and system |
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 |