CN106202301A - A kind of intelligent response system based on degree of depth study - Google Patents
A kind of intelligent response system based on degree of depth study Download PDFInfo
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Abstract
A kind of intelligent response system based on degree of depth study, it includes such as lower unit: information acquisition unit, for being obtained voice or the Word message of user's input by user terminal, when for voice messaging, it is identified voice messaging being converted to Word message and jumping to semantic acquiring unit, when for Word message, jumps directly to semantic acquiring unit；Semantic acquiring unit, for obtaining voice or the semanteme of Word message of user's input by degree of depth learning algorithm；Response matches unit, for utilizing Method of Fuzzy Matching and internal reasoning mechanism to select optimum answer from the knowledge base pre-set；Response display unit, shows user for described optimum answer.
Description
Technical field
The present invention relates to big data field of cloud computer technology, particularly to a kind of intelligent response system based on degree of depth study
System.
Background technology
Customer service system is as the effective promoting service of one and customer service model, increasingly by the weight of numerous enterprises and institutions
Depending on and use.In the pattern of common telephone customer system, user dials customer service hotline, and customer service system connects this hot line
After, it is supplied to, by voice, the service option that user is different, when user have selected corresponding service entry according to prompting, customer service system
This user is linked into corresponding service group by system, related personnel answer this hot line.In customer service system, IVR
(InteractiveVoiceResponse, interactive voice response) system is used widely, and it is with prerecording or TTS literary composition
This voice turning voice technology synthesis carries out automatic-answering back device, it is provided that a kind of function carrying out menu navigation for client.
CTI technology is to send out from traditional computer telephone integration (ComputerTelephony Integration) technology
Exhibition and come, be initially that computer technology is applied in telephone system, it is possible to automatically the signaling information in phone is carried out
Identifying processing, and connect by setting up relevant speech channel, and transmit predetermined recording file, calling etc. of transferring to user.And arrive
Now, CTI technology has developed into " computer telecommunication is integrated " technology (ComputerTelecommunication
Integration).More existing call center uses CTI technology, makes full use of internet, telecommunication path net and computer
The multiple function of net is integrated, and the complete integrated information service system being connected as a single entity with enterprise.It utilize existing respectively
Plant advanced Information Technology Methods, effectively provide high-quality, high efficiency, comprehensive service for client.
Specifically, CTI system generally comprise business application system, CTI telephone system and equipment of attending a banquet (as traffic equipment,
Traffic headset, computer of attending a banquet), cti server, CTI call center middleware (provide general call center system platform feature
And interface, linking CTI hardware and application software) etc..CTI telephone system includes multiple identical or different phone system of manufacturer
System.Business application system is different according to industry, is divided into different application management software, is such as order processing system or sends work
Repair reporting system.
In the specific implementation, business application system needs to provide business datum to CTI telephone system, in order to phone system of manufacturer
System can support its service application, and business application system cannot directly obtain business datum from manufacturer's telephone system.Right
In some period and some specific service entry, always can have many consumers and wait in line.These data are present in CTI phone
In system, but owing to business application system can not obtain these data, thus also cannot be supplied to user, cause the user cannot
Knowing and currently have how many people waiting in line, how long general needs waits.Not only waste time and the communication expense of user
With, waste and use the communication cost of producer that this customer service system is provided, and, if the waiting time long will result in
The most bad customer experience, causes customer churn.
Summary of the invention
Therefore, it is necessary to provide one can reduce period of reservation of number, it is not necessary to too much contact staff participates in, Yong Huneng
Enough intelligent response systems based on degree of depth study understanding information needed easily.
A kind of intelligent response system based on degree of depth study, it includes such as lower unit:
Information acquisition unit, for being obtained voice or the Word message of user's input by user terminal, is being believed for voice
During breath, it is identified voice messaging being converted to Word message and jumping to semantic acquiring unit, direct when for Word message
Jump to semantic acquiring unit；
Semantic acquiring unit, for obtaining voice or the semanteme of Word message of user's input by degree of deep learning algorithm；
Response matches unit, for utilizing Method of Fuzzy Matching and internal reasoning mechanism to select from the knowledge base pre-set
Select optimum answer；
Response display unit, shows user for described optimum answer.
In intelligent response system based on degree of depth study of the present invention, described semantic acquiring unit includes:
Server is set up the compound mode weights of each lemma in Word message beyond the clouds, and weights are saved in weights
In data base；
Server is set up based on big data translation word stocks beyond the clouds；
Cloud server receives the Word message sent, and extracts language sight from Word message, and to Word message
Carry out participle and obtain each lemma；
Cloud server is according to carrying out each lemma after translation translated by the translation word stocks of degree of deep learning algorithm
Lemma, and according to the language sight extracted, the lemma after translation is engaged in the dialogue restructuring；
Cloud server is sent to user terminal to the dialogue after restructuring；
Judge user terminal cognition and correction whether to the dialogue after restructuring, if any, then cloud server obtains user
By user terminal, recombinant forms is entered by the cognition of dialogue after restructuring and correction, cognition and amendment operation according to user
Row is revised, and according to the weights revised in power of amendment Value Data storehouse and jump to response matches unit；Otherwise jump to response
Join unit.
In intelligent response system based on degree of depth study of the present invention,
Described response matches unit includes:
The knowledge base knowledge content of answering system organized and build according to the specification of AIML language；Knowledge base is used
In carrying out Ontology Query, therefrom obtaining the field ontology library of the upper the next information of described effective word；For utilizing fuzzy matching
Method and internal reasoning mechanism select optimum answer from knowledge base.
In intelligent response system based on degree of depth study of the present invention, to response system in described response matches unit
The knowledge base that the knowledge content of system carries out organizing and building according to the specification of AIML language includes:
Obtain dialog history initiate information and the answer of history response and for response answer satisfaction value of feedback,
Feedback to response answer；
Information of initiating dialog history is analyzed obtaining dialog history and initiates the emotional status of information, the length degree of dialogue
And the order arrangement preference of each statement composition in information；
Answer according to history response and for the satisfaction value of feedback of response answer, feedback to response answer, will
The answer of history response carries out satisfaction and is arranged in order from high to low, retains ranking history response before default ranking value
Answer；
It is analyzed the answer of the ranking of reservation history response before default ranking value obtaining answering of history response
The order arrangement preference of each statement composition in case emotional status, the length degree of dialogue and information；
Set up the suitable of each statement composition in emotional status in dialog history initiation information, the length degree of dialogue and information
Answer emotional status, the length of dialogue in the answer of the ranking of sequence arrangement preference and reservation history response before default ranking value
The multi-to-multi mapping relations of the order arrangement preference of each statement composition in short degree and information, and multi-to-multi mapping relations are set
Mapping relations weights；
And dialog history is initiated information and the answer of history response and for response answer satisfaction value of feedback,
The feedback information of response answer is organized and according to AIML (Artificial Intelligence Markup
Language；Artificial intelligence markup language) language specification build knowledge base.
In intelligent response system based on degree of depth study of the present invention, described semantic acquiring unit passes through the degree of depth
The semanteme of voice or Word message that learning algorithm obtains user's input also includes:
Whether the semanteme judging voice that user inputs or Word message is to obtain answer information；As for obtaining answer letter
Breath, then the model answer that pre-sets in extracting directly knowledge base also jumps to response display unit, as chat message,
Then jump to response matches unit.
In intelligent response system based on degree of depth study of the present invention,
Described semantic acquiring unit obtains answer information, after the model answer pre-set in extracting directly knowledge base
Also include according to the order of each statement composition in emotional status, the length degree of dialogue and information in dialog history initiation information
Answer emotional status, the length of dialogue in the answer of the ranking of arrangement preference and reservation history response before default ranking value
The multi-to-multi mapping relations of the order arrangement preference of each statement composition in degree and information, and multi-to-multi mapping relations are set
Mapping relations weights, carry out expression way restructuring, and jump to response display unit model answer information.
The intelligent response system based on degree of depth study that implementing the present invention provides compared with prior art has following useful
Effect: obtained voice or the semanteme of Word message of user's input by degree of deep learning algorithm；And utilize response matches unit to use
Method of Fuzzy Matching and internal reasoning mechanism select optimum answer from the knowledge base pre-set, it is possible to make answering system pair
Higher in the matching degree of user's response.By judging user terminal cognition and correction whether to the dialogue after restructuring, if any, then
Cloud server obtains user by user terminal for the cognition of dialogue after restructuring and correction, according to the cognition of user with repair
Change operation recombinant forms is modified, and according to the weights revised in power of amendment Value Data storehouse and jump to response matches list
Unit so that the dialogue after restructuring more can meet the language performance feature of each user self.Send out by setting up dialog history
In the information of rising, in emotional status, the length degree of dialogue and information, the order of each statement composition arranges the ranking of preference and reservation
Each statement in answer emotional status, the length degree of dialogue and information in the answer of the history response before default ranking value
The multi-to-multi mapping relations of the order arrangement preference of composition, and the mapping relations weights of multi-to-multi mapping relations are set, it is possible to make
The optimum answer that must reply not only semantically can meet the demand of user, and expression-form, emotional status, the length of dialogue
Short degree can meet the individual demand of user.
Accompanying drawing explanation
Fig. 1 is the intelligent response system architecture diagram based on degree of depth study of the embodiment of the present invention.
Detailed description of the invention
As it is shown in figure 1, a kind of intelligent response system based on degree of depth study, it includes such as lower unit:
Information acquisition unit, for being obtained voice or the Word message of user's input by user terminal, is being believed for voice
During breath, it is identified voice messaging being converted to Word message and jumping to semantic acquiring unit, direct when for Word message
Jump to semantic acquiring unit.
Semantic acquiring unit, for obtaining voice or the semanteme of Word message of user's input by degree of deep learning algorithm；
Response matches unit, for utilizing Method of Fuzzy Matching and internal reasoning mechanism to select from the knowledge base pre-set
Select optimum answer；
Response display unit, shows user for described optimum answer.
Alternatively, in the intelligent response system based on degree of depth study described in the embodiment of the present invention, described semantic acquisition
Unit includes:
Server is set up the compound mode weights of each lemma in Word message beyond the clouds, and weights are saved in weights
In data base；
Server is set up based on big data translation word stocks beyond the clouds；.
Cloud server receives the Word message sent, and extracts language sight from Word message, and to Word message
Carry out participle and obtain each lemma；
Cloud server is according to carrying out each lemma after translation translated by the translation word stocks of degree of deep learning algorithm
Lemma, and according to the language sight extracted, the lemma after translation is engaged in the dialogue restructuring；
Cloud server is sent to user terminal to the dialogue after restructuring；
Judge user terminal cognition and correction whether to the dialogue after restructuring, if any, then cloud server obtains user
By user terminal, recombinant forms is entered by the cognition of dialogue after restructuring and correction, cognition and amendment operation according to user
Row is revised, and according to the weights revised in power of amendment Value Data storehouse and jump to response matches unit；Otherwise jump to response
Join unit.
Alternatively, in the intelligent response system based on degree of depth study described in the embodiment of the present invention,
Described response matches unit includes:
The knowledge base knowledge content of answering system organized and build according to the specification of AIML language；Knowledge base is used
In carrying out Ontology Query, therefrom obtaining the field ontology library of the upper the next information of described effective word；For utilizing fuzzy matching
Method and internal reasoning mechanism select optimum answer from knowledge base.
Alternatively, in the intelligent response system based on degree of depth study described in the embodiment of the present invention, described response matches
The knowledge base that in unit, the knowledge content to answering system is organized and built according to the specification of AIML language includes:
Obtain dialog history initiate information and the answer of history response and for response answer satisfaction value of feedback,
Feedback to response answer；
Information of initiating dialog history is analyzed obtaining dialog history and initiates the emotional status of information, the length degree of dialogue
And the order arrangement preference of each statement composition in information；
Answer according to history response and for the satisfaction value of feedback of response answer, feedback to response answer, will
The answer of history response carries out satisfaction and is arranged in order from high to low, retains ranking history response before default ranking value
Answer；
It is analyzed the answer of the ranking of reservation history response before default ranking value obtaining answering of history response
The order arrangement preference of each statement composition in case emotional status, the length degree of dialogue and information；
Set up the suitable of each statement composition in emotional status in dialog history initiation information, the length degree of dialogue and information
Answer emotional status, the length of dialogue in the answer of the ranking of sequence arrangement preference and reservation history response before default ranking value
The multi-to-multi mapping relations of the order arrangement preference of each statement composition in short degree and information, and multi-to-multi mapping relations are set
Mapping relations weights；
And dialog history is initiated information and the answer of history response and for response answer satisfaction value of feedback,
The feedback information of response answer is organized and builds knowledge base according to the specification of AIML language.
Alternatively, in the intelligent response system based on degree of depth study described in the embodiment of the present invention, described semantic acquisition
The semanteme of the voice or Word message that obtain user's input by degree of deep learning algorithm in unit also includes:
Whether the semanteme judging voice that user inputs or Word message is to obtain answer information；As for obtaining answer letter
Breath, then the model answer that pre-sets in extracting directly knowledge base also jumps to response display unit, as chat message,
Then jump to response matches unit.
Alternatively, in the intelligent response system based on degree of depth study described in the embodiment of the present invention,
Described semantic acquiring unit obtains answer information, after the model answer pre-set in extracting directly knowledge base
Also include according to the order of each statement composition in emotional status, the length degree of dialogue and information in dialog history initiation information
Answer emotional status, the length of dialogue in the answer of the ranking of arrangement preference and reservation history response before default ranking value
The multi-to-multi mapping relations of the order arrangement preference of each statement composition in degree and information, and multi-to-multi mapping relations are set
Mapping relations weights, carry out expression way restructuring, and jump to response display unit model answer information.
Implement the embodiment of the present invention provide based on the degree of depth study intelligent response system compared with prior art have with
Lower beneficial effect: obtained voice or the semanteme of Word message of user's input by degree of deep learning algorithm；And utilize response matches
Unit Method of Fuzzy Matching and internal reasoning mechanism select optimum answer from the knowledge base pre-set, it is possible to make response
System is higher for the matching degree of user's response.By judging user terminal cognition and correction whether to the dialogue after restructuring,
If any, then cloud server obtains user by user terminal for the cognition of dialogue after restructuring and correction, according to user's
Recombinant forms is modified by cognitive and amendment operation, and according to the weights revised in power of amendment Value Data storehouse and jump to response
Matching unit so that the dialogue after restructuring more can meet the language performance feature of each user self.By setting up history
In dialogue initiation information, in emotional status, the length degree of dialogue and information, the order of each statement composition arranges preference and reservation
Ranking history response before default ranking value answer in each in answer emotional status, the length degree of dialogue and information
The multi-to-multi mapping relations of the order arrangement preference of individual statement composition, and the mapping relations weights of multi-to-multi mapping relations are set,
Enable to the optimum answer of response and not only semantically can meet the demand of user, and expression-form, emotional status, right
The length degree of words can meet the individual demand of user.
It is understood that for the person of ordinary skill of the art, can conceive according to the technology of the present invention and do
Go out other various corresponding changes and deformation, and all these change all should belong to the protection model of the claims in the present invention with deformation
Enclose.
Claims (6)
1. an intelligent response system based on degree of depth study, it is characterised in that it includes such as lower unit:
Information acquisition unit, for being obtained voice or the Word message of user's input by user terminal, when for voice messaging,
It is identified voice messaging being converted to Word message and jumping to semantic acquiring unit, jumps directly to when for Word message
Semantic acquiring unit；
Semantic acquiring unit, for obtaining voice or the semanteme of Word message of user's input by degree of deep learning algorithm；
Response matches unit, for utilizing Method of Fuzzy Matching and internal reasoning mechanism to select from the knowledge base pre-set
Good answer；
Response display unit, shows user for described optimum answer.
2. the intelligent response system learnt based on the degree of depth as claimed in claim 1, it is characterised in that described semantic acquiring unit
Including:
Server is set up the compound mode weights of each lemma in Word message beyond the clouds, and weights are saved in weight data
In storehouse；
Server is set up based on big data translation word stocks beyond the clouds；
Cloud server receives the Word message sent, and extracts language sight from Word message, and carries out Word message
Participle obtains each lemma；
Cloud server is according to the word after being translated each lemma by the translation word stocks of degree of deep learning algorithm
Unit, and according to the language sight extracted, the lemma after translation is engaged in the dialogue restructuring；
Cloud server is sent to user terminal to the dialogue after restructuring；
Judge user terminal cognition and correction whether to the dialogue after restructuring, if any, then cloud server obtains user and passes through
Recombinant forms is repaiied by user terminal for the cognition of dialogue after restructuring and correction, cognition and amendment operation according to user
Just, and according to the weights revised in power of amendment Value Data storehouse and jump to response matches unit；Otherwise jump to response matches list
Unit.
3. the intelligent response system learnt based on the degree of depth as claimed in claim 2, it is characterised in that
Described response matches unit includes:
The knowledge base knowledge content of answering system organized and build according to the specification of AIML language；Knowledge base be used for into
Row Ontology Query, therefrom obtain the field ontology library of the upper the next information of described effective word；For the method utilizing fuzzy matching
And internal reasoning mechanism selects optimum answer from knowledge base.
4. the intelligent response system learnt based on the degree of depth as claimed in claim 3, it is characterised in that described response matches unit
In the knowledge base the knowledge content of answering system being organized and builds according to the specification of AIML language include:
Obtain dialog history and initiate information and the answer of history response and for the satisfaction value of feedback of response answer, correspondence
The feedback of answer；
To dialog history initiate information be analyzed obtain dialog history initiate the emotional status of information, the length degree of dialogue and
The order arrangement preference of each statement composition in information；
Answer according to history response and for the satisfaction value of feedback of response answer, feedback to response answer, by history
The answer of response carries out satisfaction and is arranged in order from high to low, retains answering of ranking history response before default ranking value
Case；
The answer of the ranking of reservation history response before default ranking value is analyzed obtaining the answer feelings of history response
The order arrangement preference of each statement composition in thread situation, the length degree of dialogue and information；
Set up the order row of each statement composition in emotional status in dialog history initiation information, the length degree of dialogue and information
Answer emotional status, the length degree of dialogue in the answer of the ranking of row preference and reservation history response before default ranking value
And the multi-to-multi mapping relations of the order arrangement preference of each statement composition in information, and reflecting of multi-to-multi mapping relations is set
Penetrate relation weights；
And dialog history is initiated information and the answer of history response and for the satisfaction value of feedback of response answer, correspondence
The feedback information of answer carries out organizing and building knowledge base according to the specification of AIML language.
5. the intelligent response system learnt based on the degree of depth as claimed in claim 4, it is characterised in that described semantic acquiring unit
In obtain the voice of user's input by degree of deep learning algorithm or the semanteme of Word message also includes:
Whether the semanteme judging voice that user inputs or Word message is to obtain answer information；As for obtaining answer information, then
The model answer that pre-sets in extracting directly knowledge base also jumps to response display unit, as chat message, then jump
Forward response matches unit to.
6. the intelligent response system learnt based on the degree of depth as claimed in claim 5, it is characterised in that
Described semantic acquiring unit obtains answer information, also wraps after the model answer pre-set in extracting directly knowledge base
Include according to the order arrangement of each statement composition in emotional status, the length degree of dialogue and information in dialog history initiation information
Answer emotional status in the answer of the ranking of preference and reservation history response before default ranking value, dialogue length degree with
And the multi-to-multi mapping relations of the order arrangement preference of each statement composition in information, and the mapping of multi-to-multi mapping relations is set
Relation weights, carry out expression way restructuring, and jump to response display unit model answer information.
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