CN110046233A - Problem distributing method and device - Google Patents
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- CN110046233A CN110046233A CN201910110664.6A CN201910110664A CN110046233A CN 110046233 A CN110046233 A CN 110046233A CN 201910110664 A CN201910110664 A CN 201910110664A CN 110046233 A CN110046233 A CN 110046233A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F16/33—Querying
- G06F16/332—Query formulation
- G06F16/3329—Natural language query formulation or dialogue systems
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F16/35—Clustering; Classification
- G06F16/353—Clustering; Classification into predefined classes
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
- G06Q10/06311—Scheduling, planning or task assignment for a person or group
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
- G06Q30/0281—Customer communication at a business location, e.g. providing product or service information, consulting
Abstract
The disclosure provides a kind of problem distributing method and device.The problem distributing method include: after the problem of receiving user, obtain described problem the problem of text, the user characteristic data of the user and user behavior track data are described；It is based on described problem using neural network model and describes text, the user characteristic data and user behavior track data progress Question Classification；And described problem is distributed to corresponding issue handling side based on described problem classification results.Using this method, customer problem can be distributed to suitable issue handling side to handle, enable a user to obtain more accurate problem answer, thus promote customer service effect.
Description
Technical field
The disclosure is usually directed to field of computer technology, more particularly, to the method and dress for distributing customer problem
It sets.
Background technique
In Internet enterprises, more particularly, to the Internet enterprises of commodity transaction, it will usually provide customer service system to answer
Client's such as asking questions about commercial quality, commodity transaction process, commodity after-sale service etc.It is seeked advice from by client
Problem would generally be related to different business or process, and different business or requirements of process are by special with the business or process knowledge
Door contact staff or customer service team (issue handling side) are replied, and otherwise will affect customer service effect, to need to provide one
Kind asking questions for client is distributed to the problem of suitable issue handling side and distributes mechanism.
The traditional method that problem distributes is to be classified according to user to requirement description.However, many users and not liking
The problem of going description problem against machine, or not knowing oneself emphasis, so that description is inaccurate the problem of user
With it is perfect, the accuracy rate for thus causing problem to distribute is bad, severely impacts answer effect.
Summary of the invention
In view of above-mentioned, present disclose provides a kind of problem distributing method and devices.Using the problem distributing method and device,
Customer problem is divided by describing text, user behavior track data and user characteristic data based on the problem of user
Class is enable to carry out Question Classification based on multi-modal multi-tag data, rather than describes text based on single problem
Customer problem, it is possible thereby to improve the accuracy rate of Question Classification prediction, and then can be distributed suitable issue handling side by this
It is handled, enables a user to access more accurate problem and reply, thus promoted and reply effect.
According to one aspect of the disclosure, a kind of problem distributing method is provided, comprising: the problem of receiving user
Afterwards, the problem of obtaining described problem describes text, the user characteristic data of the user and user behavior track data；Use mind
It is based on described problem through network model and describes text, the user characteristic data and the user behavior track data being asked
Topic classification；And described problem is distributed to corresponding issue handling side based on described problem classification results.
Optionally, in an example of above-mentioned aspect, be based on using neural network model described problem describe text,
It includes: that described problem is described text, institute that the user characteristic data and the user behavior track data, which carry out Question Classification,
It states user characteristic data and the user behavior track data is separately input at least one input of the neural network model
Layer carries out vectorization processing, to respectively obtain described problem describes text, the user characteristic data and the user behavior
The vector of track data indicates；Described problem is described into text, the user characteristic data and the user behavior track data
Vector indicate in the first intermediate hidden layers, the second intermediate hidden layers and the third that are separately input in the neural network model
Between hidden layer, text, the user characteristic data and the user behavior track data are described to respectively obtain described problem
Intermediate vector；Obtained described problem is described into text, the user characteristic data and the user behavior track data
Intermediate vector is input to the splicing layer in the neural network model and carries out splicing；And by the institute after splicing
The intermediate vector that the problem of stating describes text, the user characteristic data and the user behavior track data is input to the nerve
Classification layer in network model carries out classification processing, classification results the problem of to determine described problem.
Optionally, in an example of above-mentioned aspect, first intermediate hidden layers include shot and long term memory network
(Long Short-Term Memory, LSTM) layer, Recognition with Recurrent Neural Network (Recurrent Neural Network, RNN) layer,
Gating cycle unit (Gated Recurrent Unit, GRU) layer, deep neural network (Deep Neural Network,
DNN) at least one of layer and convolutional neural networks (CNN) layer, second intermediate hidden layers include DNN layers and described
Third intermediate hidden layers include LSTM layers, RNN layers or GRU layers.
Optionally, in an example of above-mentioned aspect, the classification layer is Softmax layers.
Optionally, in an example of above-mentioned aspect, the problem of obtaining described problem, to describe text included: to receive
After the problem of user, it is based at least partially on the user characteristic data and user behavior track data of the user, creation is at least
One question and answer problem；And it is based at least partially on the answer that the user is directed at least one the question and answer problem created, it obtains
The problem of taking described problem describes text.
According to another aspect of the present disclosure, a kind of problem is provided and distributes device, comprising: acquiring unit is configured as connecing
After the problem of receiving user, obtain described problem the problem of text, the user characteristic data of the user and user behavior are described
Track data；Question Classification unit is configured with neural network model to be based on described problem and describe text, the user
Characteristic and the user behavior track data carry out Question Classification；And problem dispatch unit, it is configured as based on described
Described problem is distributed to corresponding issue handling side by Question Classification result.
Optionally, in an example of above-mentioned aspect, the neural network model includes: at least one input layer, quilt
It is configured to describe text, the user characteristic data and user behavior track data progress vectorization to described problem respectively
Processing, to respectively obtain the vector that described problem describes text, the user characteristic data and the user behavior track data
It indicates；First intermediate hidden layers, the vector for being configured as being described text based on described problem are indicated, described problem description text is generated
This intermediate vector；Second intermediate hidden layers, being configured as the vector based on the user characteristic data indicates, generates the use
The intermediate vector of family characteristic；Third intermediate hidden layers are configured as the vector table based on the user behavior track data
Show, generates the intermediate vector of the user behavior track data；Splice layer, is configured as describing text to obtained described problem
Originally, the user characteristic data and the intermediate vector of the user behavior track data carry out splicing；And classification layer, quilt
It is configured to the described problem after splicing and describes text, the user characteristic data and the user behavior track
The intermediate vector of data carries out classification processing, classification results the problem of to determine described problem.
Optionally, in an example of above-mentioned aspect, first intermediate hidden layers include LSTM layers, RNN layers, GRU
At least one of layer, DNN layer and CNN layer, second intermediate hidden layers include that DNN layers and third centre are hiding
Layer includes LSTM layers, RNN layers or GRU layers.
Optionally, in an example of above-mentioned aspect, the classification layer is Softmax layers.
Optionally, in an example of above-mentioned aspect, described device further include: question and answer problem creating unit is configured
For the user characteristic data and user behavior track number for after the problem of receiving user, being based at least partially on the user
According to creating at least one question and answer problem, the acquiring unit is configured as: being based at least partially on the user for being created
At least one question and answer problem answer, obtain described problem the problem of text is described.
According to another aspect of the present disclosure, a kind of calculating equipment is provided, comprising: at least one processor, and with it is described
The memory of at least one processor coupling, the memory store instruction, when described instruction is by least one described processor
When execution, so that at least one described processor executes problem distributing method as described above.
According to another aspect of the present disclosure, a kind of non-transitory machinable medium is provided, is stored with executable
Instruction, described instruction make the machine execute problem distributing method as described above upon being performed.
Detailed description of the invention
By referring to following attached drawing, may be implemented to further understand the nature and advantages of present disclosure.?
In attached drawing, similar assembly or feature can have identical appended drawing reference.
Fig. 1 shows the flow chart of problem distributing method according to an embodiment of the present disclosure；
Fig. 2 shows an example schematic diagrams of problem according to an embodiment of the present disclosure；
Fig. 3 shows an exemplary schematic diagram of neural network model according to an embodiment of the present disclosure；
Fig. 4 shows the flow chart that problem according to an embodiment of the present disclosure describes text acquisition process；
Fig. 5 shows the example schematic diagram that problem according to an embodiment of the present disclosure describes text acquisition process；
Fig. 6 shows the structural block diagram that problem according to an embodiment of the present disclosure distributes device；
Fig. 7 shows the block diagram of the calculating equipment according to an embodiment of the present disclosure distributed for problem.
Specific embodiment
Theme described herein is discussed referring now to example embodiment.It should be understood that discussing these embodiments only
It is in order to enable those skilled in the art can better understand that being not to claim to realize theme described herein
Protection scope, applicability or the exemplary limitation illustrated in book.It can be in the protection scope for not departing from present disclosure
In the case of, the function and arrangement of the element discussed are changed.Each example can according to need, omit, substitute or
Add various processes or component.For example, described method can be executed according to described order in a different order, with
And each step can be added, omits or combine.In addition, feature described in relatively some examples is in other examples
It can be combined.
As used in this article, term " includes " and its modification indicate open term, are meant that " including but not limited to ".
Term "based" indicates " being based at least partially on ".Term " one embodiment " and " embodiment " expression " at least one implementation
Example ".Term " another embodiment " expression " at least one other embodiment ".Term " first ", " second " etc. may refer to not
Same or identical object.Here may include other definition, either specific or implicit.Unless bright in context
It really indicates, otherwise the definition of a term is consistent throughout the specification.
Herein, term " issue handling side " refers to service provider (such as company or enterprise etc.) to handle user
Problem and the special problem processing mechanism set up, for example, each customer service technical ability group in the customer service system of service provider.It is logical
Often, service provider can set up multiple issue handling sides, some business of each issue handling side's special disposal is (for example, Alipay
Using packet, financing line etc.) or some process flow (account relevant treatment process) involved in customer problem, and at the problem
Various Knowledge Capability needed for reason side has the business or process and/or processing technical ability.In the disclosure, described problem processing side
It can be problem handler or issue handling group.
The embodiment according to distributing method the problem of the disclosure and device is described in detail below in conjunction with attached drawing.
Fig. 1 shows the flow chart of problem distributing method according to an embodiment of the present disclosure.The method is distributed by problem
Device executes, and is illustrated so that the problems in company's customer service system distributes device as an example below.
As shown in Figure 1, in block 110, the problem of receiving user.In the disclosure, user can for example pass through voice dialogue
Mode issue problem to customer service system, for example, by way of phone perhaps voice-enabled chat or key-press input can be passed through
Or the mode of screen input to issue problem to customer service system.Described problem can be a typical problem, be also possible to be directed to
One segment description text of problem.The format of described problem can be text formatting, phonetic matrix, picture format or other are suitable
Format.Fig. 2 shows an example schematic diagrams of problem according to an embodiment of the present disclosure.
After the problem of receiving user, in block 120, the problem of obtaining described problem, describes text, and from user's row
To obtain the user behavior track data of the user in track data database 130 and from user characteristic data database 140
The middle user characteristic data for obtaining the user.Here, it is the text description information for describing customer problem that problem, which describes text,.
In the case where the format of problem is not text formatting, described problem can be converted to using suitable format conversion regime
The problem of text formatting, describes text.Optionally, in addition, described problem, which describes text, can also be by being inputted to user
Obtained text description information after the problem of text formatting is pre-processed, the pretreatment for example can be the invalid letter of removal
Breath, the crucial participle of extraction etc..
User behavior track data database 130 can be through the internal network via service provider and/or such as
Internet, other service providers the external network of grid etc collect the historical behavior track data of user to create
's.For example, the historical behavior track data of user can be collected by the internal service network of service provider.The user
Historical behavior track data for example can be operation associated with service provided by service provider performed by user
Sequence data, for example, being directed to Alipay service, user's history action trail data may include that user browses Alipay APP times
Number, the operation behavior sequence of user on Alipay etc..Here, the user behavior track data has sequence signature
Data.User characteristic data refers to the data of the various information for describing user characteristics, such as age, height, feature, consumption
Preference, gender, income, occupation, user's this month whether also blowing etc..User characteristic data database 140, which can be, to be passed through
Via the extranets of the grid etc of the internal network and/or such as internet, other service providers of service provider
Network collects the characteristic of user to create.For example, user can be collected by the internal service network of service provider
Characteristic.Here, the user characteristic data is that have the data of discrete features.User behavior track data database
130 and user characteristic data database 140 can store and distributed in device in problem, the problem that can also be distributed in distribute device it
In other equipment in outer one or more equipment, such as in customer service system, and distribute between device with problem via having
Line is wirelessly communicated.
Then, in block 150, text, user characteristic data are described based on acquired problem using neural network model
Question Classification is carried out with user behavior track data.How using neural network model Question Classification is carried out, will tied below
Fig. 3 is closed to be described.
After Question Classification executed as described above, in block 160, based on Question Classification as a result, described problem is distributed to corresponding
Issue handling side.For example, problem is distributed to handling with the matched customer service group of Question Classification result in customer service system.
Fig. 3 shows an exemplary schematic diagram of neural network model 300 according to an embodiment of the present disclosure.Such as Fig. 3
Shown, neural network model 300 includes at least one input layer 340, the first intermediate hidden layers 350-1,350-2,350-3, the
Two intermediate hidden layers 360, third intermediate hidden layers 370, splicing layer 380 and classification layer 390.
Text 310, the user characteristic data 320 of user and user behavior track are described the problem of getting customer problem
After data 330, acquired problem is described into text 310, user characteristic data 320 and user behavior track data 330 and is distinguished
Input at least one input layer 340.At least one input layer 340 may include one or more input layers, as shown in figure 3,
Problem, which describes text 310, user characteristic data 320 and user behavior track data 330, can respectively correspond an input layer.?
The other examples of the disclosure are also possible to problem and describe text 310, user characteristic data 320 and user behavior track data 330
In at least two correspond at least one input layer 340 in an input layer.Input layer 340 describes text to problem respectively
310, user characteristic data 320 and user behavior track data 330 carry out vectorization processing, with obtain problem describe text 310,
The vector of user characteristic data 320 and user behavior track data 330 indicates.In the disclosure, input layer 340 can be used embedding
Enter layer to realize.
In the vector for as above obtaining problem and describing text 310, user characteristic data 320 and user behavior track data 330
After expression, the vector expression that problem describes text 310 is supplied to the first intermediate hidden layers 350-1,350-2,350-3, will be used
The vector expression of family characteristic 320 is supplied to the second intermediate hidden layers 360, and by user behavior track data 330 to
Amount indicates to be supplied to third intermediate hidden layers 370.
First intermediate hidden layers 350-1,350-2,350-3 is indicated based on the vector that problem describes text 310, generates problem
The intermediate vector of text 310 is described.Second intermediate hidden layers 360 are indicated based on the vector of user characteristic data 320, generate user
The intermediate vector of characteristic 320.Third intermediate hidden layers 370 are indicated based on the vector of user behavior track data 330, are generated
The intermediate vector of user behavior track data 330.Then, the first intermediate hidden layers 350-1,350-2,350-3, the second centre are hidden
It hides layer 360 and third intermediate hidden layers 370 and problem generated is described into text 310, user characteristic data 320 and user behavior
The intermediate vector of track data 330 is supplied to splicing layer 380.
In the disclosure, the first intermediate hidden layers 350 can use in LSTM layers, RNN layers, GRU layers, DNN layers and CNN layers
At least one realize.For example, as shown in Figure 3, the first intermediate hidden layers 350 can use LSTM layers 350-1, DNN layers
350-2 and RNN layers of 350-3 is realized.Second intermediate hidden layers 360 can use DNN layers of realization.Third intermediate hidden layers 370
It can use LSTM layers, RNN layers or GRU layers realization.Preferably, third intermediate hidden layers 370 utilize LSTM layers of realization.
Splicing layer 380 is configured as describing obtained problem text 310, user characteristic data 320 and user behavior
The intermediate vector of track data 330 carries out splicing, and the problem after splicing is then described text 310, user
Characteristic 320 and the intermediate vector of user behavior track data 330 are supplied to classification layer 390.Splicing layer 380 for example can benefit
It is realized with full articulamentum and dropout function.
The centre that text 310, user characteristic data 320 and user behavior track data 330 are as above described to problem to
After amount carries out splicing, layer 390 of classifying describes text 310, user characteristic data 320 based on the problem after splicing
Classification processing is carried out with the intermediate vector of user behavior track data 330, classification results the problem of to determine problem.In this public affairs
In opening, classification layer 390 can use Softmax layers of realization.
Optionally, in addition, when carrying out executive problem classification processing using neural network model, it may be incorporated into attention
(Attention) mechanism.How Attention mechanism is introduced in neural network model, be well known in the present art, herein
It is not described in detail.
In the disclosure, neural network model is to utilize classification mark treated the problem by each issue handling side
Text and corresponding user behavior track data and user characteristic data is described to train.
Problem distributing method according to an embodiment of the present disclosure is described above with reference to Fig. 1 to Fig. 3.It is distributed using the problem
Method, by based on the problem of user describe text, user behavior track data and user characteristic data come to customer problem into
Row classification, is enable to be carried out Question Classification based on multi-modal multi-tag data, rather than is retouched based on single problem
Text is stated, it is possible thereby to improve the accuracy rate of Question Classification prediction, and then customer problem can be distributed at suitable problem
Reason side is handled, and is enabled a user to access more accurate problem and is replied, and is thus promoted and is replied effect.
In addition, describing text, user behavior track data and user characteristics for problem in above problem distributing method
Data describe text, user behavior track data and the respective data characteristics of user characteristic data based on problem, are respectively adopted pair
The suitable hidden layer answered is handled, so that describing text, user behavior track data and user characteristics for problem
The intermediate vector treatment effeciency of data is higher, thus the further accuracy rate of Upgrade Problem classification.
In the disclosure, under application scenes, user does not simultaneously like and goes description problem against customer service system, or simultaneously
Thus the problem of not knowing oneself emphasis causes so that the problem of customer service system is received description is inaccurate and perfect
Problem acquired in customer service system, which describes text, can not accurately reflect that the consulting of user is intended to, so that can not be to asking
Topic is accurately classified and the problem is distributed suitable issue handling side to answer.
In order to obtain more effective informations of customer problem, text acquisition process is described for problem, present disclose provides
One kind is by creating at least one question and answer problem based on user behavior track data and user characteristic data, and based on user's
It replies to obtain and describe text acquisition scheme the problem of more effective informations about customer problem.
Fig. 4 shows that problem according to an embodiment of the present disclosure describes the flow chart of text acquisition process and Fig. 5 is shown
Problem according to an embodiment of the present disclosure describes example schematic diagram of text acquisition process.
As shown in figure 4, in block 410, the problem of receiving user, for example, user can only put through a phone, Huo Zheyong
Family sends and describes about the problem of problem, for example, problem provided by user is described as, " I loses cell-phone number, then mends again
Do, then log in Alipay again, with it is pervious be not just the same Alipay account ", as shown in Figure 5.Here, if institute
The description of the problem of reception is non-textual format, then also needs to be implemented the conversion operation from non-textual format to text formatting, with
The problem of obtaining text formatting description.
After the problem of receiving user, in block 420, it is based at least partially on the user behavior track data and use of user
Family characteristic creates a question and answer problem and is pushed to user.For example, " being intended to give original Alipay account for change? ", such as
Shown in Fig. 5.In addition, being based at least partially on the user behavior track of user when describing the problem of received comprising problem
Data and user characteristic data, creating a question and answer problem and being pushed to user may include: to be based at least partially on to be received
To the problem of the problem of description, the user behavior track data of user and user characteristic data, create a question and answer problem and push away
Give user.
After receiving the positive reply of user, process proceeds to block 480.If receiving the negative reply of user,
In block 440, it is based at least partially on the user behavior track data and user characteristic data of user, creates another question and answer problem simultaneously
It is pushed to user.For example, " being to worry that original Alipay account looks for the fund security of that? ", as shown in Figure 5.In this public affairs
In another example opened, it is based at least partially on the user behavior track data and user characteristic data of user, creates another ask
It may include: the user behavior track data for being based at least partially on user, user characteristic data that question and answer, which inscribes and is pushed to user,
And user is directed to the answer of a upper problem, creates another question and answer problem and is pushed to user.Wherein, the answer of the user can
To include positive reply or the negative reply of user.In some cases, replying for the user can also include user's
Supplementary question description.
After receiving the positive reply of user, process proceeds to block 480.If receiving the negative reply of user,
In block 460, it is based at least partially on the user behavior track data and user characteristic data of user, creates another question and answer problem
And it is pushed to user.Equally, in another example of the disclosure, be based at least partially on user user behavior track data and
User characteristic data, creating another question and answer problem and being pushed to user may include: the user's row for being based at least partially on user
It is directed to the answer of a upper problem for track data, user characteristic data and user, creates another question and answer problem and is pushed to use
Family.Wherein, the answer of the user may include positive reply or the negative reply of user.In some cases, the use
Replying for family can also be described including the supplementary question of user.So circulation executes above-mentioned question answering process, until obtaining answering certainly
It is multiple, or creating predetermined number question and answer problem and obtaining stopping after user replies.Preferably, the question and answer created are asked
The number of topic is no more than three.
In block 480, it is based at least partially on the answer that the user is directed at least one the question and answer problem created, is obtained
The problem of problem, describes text.Here, the answer of user may include the positive or negative answer for problem.Alternatively, at this
In disclosed other examples, the answer of user can also include other additional notes, such as " fund security " in Fig. 5 etc..?
In another example of the disclosure, in the case where including problem description the problem of user is issued, it is based at least partially on described
For user for the problem that the answer of at least one the question and answer problem created, it may include: at least portion that the problem of acquisition, which describes text,
Description the problem of dividing the problem of ground is based on the user and the user are directed to answering at least one the question and answer problem created
Again, the problem of obtaining problem describes text.
In addition, can be considered as " affirmative " if user does not reply at least one the question and answer problem created and answer
Multiple perhaps " negative " replies and replies according to " affirmative " or " negative " reply to execute subsequent operation.Specifically it is considered as and " agrees
It is fixed " still " negating " answer is replied, it can come as the case may be by default.
Text acquisition process is described using problem shown in Fig. 4, can not like in user against customer service system and describe
Problem or the problem of do not know oneself in the case where emphasis, especially user by the way of such as phone or dialogue chat come
The problem of voice inputs the situation of problem description, and acquisition includes more effective informations about customer problem describes text.
Fig. 6 shows the structural block diagram that problem according to an embodiment of the present disclosure distributes device 600.
As shown in fig. 6, it includes that acquiring unit 610, Question Classification unit 620 and problem distribute list that problem, which distributes device 600,
Member 630.
The problem of acquiring unit 610 is configured as the problem of receiving user description after, obtain described problem the problem of
The user characteristic data and user behavior track data of text, user are described.The operation of acquiring unit 610 can refer to be joined above
According to the operation of the block 120 of Fig. 1, Fig. 4 and Fig. 5 description.
Question Classification unit 620 is configured with neural network model to be based on problem and describe text, user characteristics number
Question Classification is carried out according to user behavior track data.The operation of Question Classification unit 620 can with reference to above with reference to Fig. 1 and
The operation of the block 150 of Fig. 3 description.
Problem dispatch unit 630 is configured as that described problem being distributed at corresponding problem based on Question Classification result
Reason side.The operation of problem dispatch unit 630 can be with reference to the operation above with reference to Fig. 1 block 160 described.
Optionally, in addition, it can also include question and answer problem creating unit 640 that problem, which distributes device 600,.Problem creating unit
640 were configured as after the problem of receiving user, and user behavior track data and the user for being based at least partially on user are special
Data are levied, at least one question and answer problem is created.Correspondingly, acquiring unit 610 is configured as being based at least partially on the user
For the problem that the answer of at least one the question and answer problem created, obtains described problem and describe text.
Above with reference to Fig. 1 to Fig. 6, it is described to according to the embodiment of distributing method the problem of the disclosure and device.
Problem above is distributed device and can also be realized using the combination of software or hardware and software using hardware realization.
Fig. 7 shows the block diagram of the calculating equipment 700 according to an embodiment of the present disclosure distributed for problem.Such as Fig. 7
Shown, calculating equipment 700 may include at least one processor 710, memory 720, memory 730 and communication interface 740, and
At least one processor 710, memory 720, memory 730 and communication interface 740 link together via bus 760.At least one
A processor 710 execute store or encode in memory at least one computer-readable instruction (that is, it is above-mentioned in a software form
The element of realization).
In one embodiment, computer executable instructions are stored in memory, make at least one when implemented
Processor 710: the problem of the problem of receiving user after description, the problem of obtaining described problem, describes text, the user
User characteristic data and user behavior track data；It is based on described problem using neural network model and describes text, described
User characteristic data and the user behavior track data carry out Question Classification；And based on described problem classification results come by institute
The problem of stating is distributed to corresponding issue handling side.
It should be understood that the computer executable instructions stored in memory make at least one processor when implemented
710 carry out the above various operations and functions described in conjunction with Fig. 1-6 in each embodiment of the disclosure.
In the disclosure, calculating equipment 700 can include but is not limited to: personal computer, server computer, work
It stands, desktop computer, laptop computer, notebook computer, mobile computing device, smart phone, tablet computer, bee
Cellular telephone, personal digital assistant (PDA), hand-held device, messaging devices, wearable calculating equipment, consumer-elcetronics devices etc.
Deng.
According to one embodiment, a kind of program product of such as non-transitory machine readable media is provided.Non-transitory
Machine readable media can have instruction (that is, above-mentioned element realized in a software form), which when executed by a machine, makes
It obtains machine and executes the above various operations and functions described in conjunction with Fig. 1-6 in each embodiment of the disclosure.Specifically, Ke Yiti
For being furnished with the system or device of readable storage medium storing program for executing, store on the readable storage medium storing program for executing any in realization above-described embodiment
The software program code of the function of embodiment, and read and execute the computer of the system or device or processor and be stored in
Instruction in the readable storage medium storing program for executing.
According to one embodiment, a kind of program product of such as non-transitory machine readable media is provided.Non-transitory
Machine readable media can have instruction (that is, above-mentioned element realized in a software form), which when executed by a machine, makes
It obtains machine and executes the above various operations and functions described in conjunction with Fig. 1-6 in each embodiment of the disclosure.Specifically, Ke Yiti
For being furnished with the system or device of readable storage medium storing program for executing, store on the readable storage medium storing program for executing any in realization above-described embodiment
The software program code of the function of embodiment, and read and execute the computer of the system or device or processor and be stored in
Instruction in the readable storage medium storing program for executing.
In this case, it is real that any one of above-described embodiment can be achieved in the program code itself read from readable medium
The function of example is applied, therefore the readable storage medium storing program for executing of machine readable code and storage machine readable code constitutes of the invention one
Point.
The embodiment of readable storage medium storing program for executing include floppy disk, hard disk, magneto-optic disk, CD (such as CD-ROM, CD-R, CD-RW,
DVD-ROM, DVD-RAM, DVD-RW, DVD-RW), tape, non-volatile memory card and ROM.It selectively, can be by communication network
Network download program code from server computer or on cloud.
It will be appreciated by those skilled in the art that each embodiment disclosed above can be in the situation without departing from invention essence
Under make various changes and modifications.Therefore, protection scope of the present invention should be defined by the appended claims.
It should be noted that step and unit not all in above-mentioned each process and each system construction drawing is all necessary
, certain step or units can be ignored according to the actual needs.Each step execution sequence be not it is fixed, can be according to need
It is determined.Apparatus structure described in the various embodiments described above can be physical structure, be also possible to logical construction, that is, have
A little units may be realized by same physical entity, be realized alternatively, some units may divide by multiple physical entities, alternatively, can be with
It is realized jointly by certain components in multiple autonomous devices.
In the above various embodiments, hardware cell or module mechanically or can be realized electrically.For example, one
Hardware cell, module or processor may include permanent dedicated circuit or logic (such as special processor, FPGA or
ASIC) corresponding operating is completed.Hardware cell or processor can also include programmable logic or circuit (such as general processor or
Other programmable processors), interim setting can be carried out by software to complete corresponding operating.Concrete implementation mode is (mechanical
Mode or dedicated permanent circuit or the circuit being temporarily arranged) it can be determined based on cost and temporal consideration.
The specific embodiment illustrated above in conjunction with attached drawing describes exemplary embodiment, it is not intended that may be implemented
Or fall into all embodiments of the protection scope of claims." exemplary " meaning of the term used in entire this specification
Taste " be used as example, example or illustration ", be not meant to than other embodiments " preferably " or " there is advantage ".For offer pair
The purpose of the understanding of described technology, specific embodiment include detail.However, it is possible in these no details
In the case of implement these technologies.In some instances, public in order to avoid the concept to described embodiment causes indigestion
The construction and device known is shown in block diagram form.
The foregoing description of present disclosure is provided so that any those of ordinary skill in this field can be realized or make
Use present disclosure.To those skilled in the art, the various modifications carried out to present disclosure are apparent
, also, can also answer generic principles defined herein in the case where not departing from the protection scope of present disclosure
For other modifications.Therefore, present disclosure is not limited to examples described herein and design, but disclosed herein with meeting
Principle and novel features widest scope it is consistent.
Claims (12)
1. a kind of problem distributing method, comprising:
After the problem of receiving user, obtain described problem the problem of describe text, the user user characteristic data and
User behavior track data；
It is based on described problem using neural network model and describes text, the user characteristic data and the user behavior track
Data carry out Question Classification；And
Described problem is distributed to corresponding issue handling side based on described problem classification results.
2. problem distributing method as described in claim 1, wherein be based on described problem description text using neural network model
Originally, the user characteristic data and user behavior track data progress Question Classification include:
Described problem is described into text, the user characteristic data and the user behavior track data and is separately input to the mind
At least one input layer through network model carries out vectorization processing, to respectively obtain described problem describes text, the use
The vector of family characteristic and the user behavior track data indicates；
The vector that described problem describes text, the user characteristic data and the user behavior track data is indicated defeated respectively
Enter to the first intermediate hidden layers, the second intermediate hidden layers and the third intermediate hidden layers in the neural network model, with respectively
Obtain the intermediate vector that described problem describes text, the user characteristic data and the user behavior track data；
By obtained described problem describe the centre of text, the user characteristic data and the user behavior track data to
It measures the splicing layer being input in the neural network model and carries out splicing；And
Described problem after splicing is described into text, the user characteristic data and the user behavior track data
Intermediate vector be input to the classification layer in the neural network model to carry out classification processing, the problem of to determine described problem
Classification results.
3. problem distributing method as claimed in claim 2, wherein first intermediate hidden layers include LSTM layers, RNN layers,
At least one of GRU layers, DNN layers and CNN layers, second intermediate hidden layers include hidden among DNN layers and the third
Hiding layer includes LSTM layers, RNN layers or GRU layers.
4. problem distributing method as claimed in claim 2, wherein the classification layer is Softmax layers.
5. problem distributing method as described in claim 1, wherein the problem of obtaining described problem describes text and include:
After the problem of receiving user, it is based at least partially on the user characteristic data and user behavior track number of the user
According to creating at least one question and answer problem；And
It is based at least partially on the answer that the user is directed at least one the question and answer problem created, obtains asking for described problem
Topic description text.
6. a kind of problem distributes device, comprising:
The problem of acquiring unit was configured as after the problem of receiving user, obtained described problem describes text, the user
User characteristic data and user behavior track data；
Question Classification unit is configured with neural network model to be based on described problem and describe text, the user characteristics
Data and the user behavior track data carry out Question Classification；And
Problem dispatch unit is configured as that described problem is distributed to corresponding issue handling based on described problem classification results
Side.
7. problem as claimed in claim 6 distributes device, wherein the neural network model includes:
At least one input layer is configured to describe described problem text, the user characteristic data and the user
Action trail data carry out vectorization processing, describe text, the user characteristic data and described to respectively obtain described problem
The vector of user behavior track data indicates；
First intermediate hidden layers, the vector for being configured as being described text based on described problem are indicated, described problem description text is generated
This intermediate vector；
Second intermediate hidden layers, being configured as the vector based on the user characteristic data indicates, generates the user characteristics number
According to intermediate vector；
Third intermediate hidden layers, being configured as the vector based on the user behavior track data indicates, generates user's row
For the intermediate vector of track data；
Splice layer, is configured as describing obtained described problem text, the user characteristic data and the user behavior
The intermediate vector of track data carries out splicing；And
Classification layer, is configured as describing text, the user characteristic data and institute based on the described problem after splicing
The intermediate vector of user behavior track data is stated to carry out classification processing, classification results the problem of to determine described problem.
8. problem as claimed in claim 7 distributes device, wherein first intermediate hidden layers include LSTM layers, RNN layers,
At least one of GRU layers, DNN layers and CNN layers, second intermediate hidden layers include hidden among DNN layers and the third
Hiding layer includes LSTM layers, RNN layers or GRU layers.
9. problem as claimed in claim 7 distributes device, wherein the classification layer is Softmax layers.
10. problem as claimed in claim 6 distributes device, further includes:
Question and answer problem creating unit, was configured as after the problem of receiving user, was based at least partially on the use of the user
Family characteristic and user behavior track data create at least one question and answer problem,
Wherein, the acquiring unit is configured as: being based at least partially on the user and is directed at least one question and answer created
The problem of answer of problem, acquisition described problem, describes text.
11. a kind of calculating equipment, comprising:
At least one processor, and
The memory coupled at least one described processor, the memory store instruction, when described instruction by it is described at least
When one processor executes, so that at least one described processor executes the method as described in any in claims 1 to 5.
12. a kind of non-transitory machinable medium, is stored with executable instruction, described instruction makes upon being performed
The machine executes the method as described in any in claims 1 to 5.
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