CN108733696A - A kind of generation method and device of reference list - Google Patents
A kind of generation method and device of reference list Download PDFInfo
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- CN108733696A CN108733696A CN201710256415.9A CN201710256415A CN108733696A CN 108733696 A CN108733696 A CN 108733696A CN 201710256415 A CN201710256415 A CN 201710256415A CN 108733696 A CN108733696 A CN 108733696A
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Abstract
The embodiment of the present application discloses a kind of generation method and device of reference list.In the embodiment of the present application, when needing to treat reference user progress reference, according to waiting for the corresponding historical data of reference user, determine the corresponding each behavioural characteristic of the user, the probability occurred under each reference classification then in conjunction with predetermined each behavioural characteristic, determine the reference classification of user missing, further according to the reference classification of user missing, generate reference list, so that the user only needs to fill in the reference information in the reference classification of its missing, it is inconvenient caused by user to reduce, improve reference efficiency.
Description
Technical field
This application involves information technology field more particularly to a kind of generation methods and device of reference list.
Background technology
Field (reference field) is collected in credit, in order to which the service request (such as provide a loan, buy on credit) proposed to user carries out
Risk assessment, credit collection mechanism (credit information service) would generally acquire reference information of the user in each reference classification.
Wherein, reference classification refers to the classification of reference information, and reference classification is drawn according to certain standard by credit information service
Point, the criteria for classifying of different credit information services may be different.Reference information is to can be shown that the information of user credit ability.For example,
The reference information of user's corresponding " with post-secondary education ", may indicate that user credit ability, the reference classification of the reference information
It can be " educational background ", can also be " education experience ".
In many cases, credit information service can not collect the reference information of user, reference in each reference classification
Mechanism does not have the reference classification corresponding to the reference information of collected user, is exactly the reference classification of user's missing.At this point, sign
Letter mechanism often may require that user provides the reference information in the reference classification of its missing.
In practical application, the reference classification of different users missing is often also different, and still, credit information service would generally
A standardized reference list is provided to the user of missing reference classification, as shown in Figure 1, being enumerated on standardized reference list
All reference classifications, it is desirable that user is directed to each reference classification one by one, fills in corresponding reference information.However, reference machine
Structure has usually collected the reference information of user in some reference classifications, does not need to user actually and is directed to these again
Reference classification fills in a reference information, this wastes user's a large amount of time, and inconvenience is caused to user.
Invention content
The embodiment of the present application provides a kind of generation method and device of reference list, to solve the life of existing reference list
The problem of being caused inconvenience to the user at method.
In order to solve the above technical problems, what the embodiment of the present application was realized in：
A kind of generation method of reference list provided by the embodiments of the present application, including：
Obtain the historical data for waiting for reference user；
The corresponding each behavioural characteristic of reference user is waited for according to described in historical data determination；
Occurred under each reference classification according to determining each behavioural characteristic and predetermined each behavioural characteristic general
Rate, determine described in wait for reference user missing reference classification；
According to the reference classification for waiting for reference user missing, reference list is generated.
A kind of generating means of reference list provided by the embodiments of the present application, including：
Acquisition module obtains the historical data for waiting for reference user；
First determining module waits for the corresponding each behavioural characteristic of reference user according to described in historical data determination；
Second determining module, according to determining each behavioural characteristic and predetermined each behavioural characteristic in each reference class
The probability of appearance is not descended, and the reference classification of reference user missing is waited for described in determination；
Generation module generates reference list according to the reference classification for waiting for reference user missing.
By the above technical solution provided by the embodiments of the present application as it can be seen that in the embodiment of the present application, when needing to treat reference
When user carries out reference, according to the corresponding historical data of reference user is waited for, determines the corresponding each behavioural characteristic of the user, then tie
The probability that predetermined each behavioural characteristic occurs under each reference classification is closed, determines the reference classification of user missing,
Further according to the reference classification of user missing, reference list is generated so that the user only needs to fill in the reference class of its missing
Reference information on not, it is inconvenient caused by user to reduce, improve reference efficiency.
Description of the drawings
In order to illustrate the technical solutions in the embodiments of the present application or in the prior art more clearly, to embodiment or will show below
There is attached drawing needed in technology description to be briefly described, it should be apparent that, the accompanying drawings in the following description is only this
Some embodiments described in application, for those of ordinary skill in the art, in the premise of not making the creative labor property
Under, other drawings may also be obtained based on these drawings.
The existing reference list schematic diagrames of Fig. 1；
Fig. 2 is a kind of generation method flow chart of reference list provided by the embodiments of the present application；
Fig. 3 a are that the existing reference that credit information service uses provides the schematic diagram interacted with user；
Fig. 3 b are the schematic diagrames that credit investigation system provided by the embodiments of the present application is interacted with user；
Fig. 4 is a kind of generating means schematic diagram of reference list provided by the embodiments of the present application.
Specific implementation mode
The embodiment of the present application provides a kind of generation method and device of reference list.
In order to make those skilled in the art better understand the technical solutions in the application, below in conjunction with the application reality
The attached drawing in example is applied, technical solutions in the embodiments of the present application is clearly and completely described, it is clear that described implementation
Example is merely a part but not all of the embodiments of the present application.Based on the embodiment in the application, this field is common
The every other embodiment that technical staff is obtained without creative efforts should all belong to the application protection
Range.
Below in conjunction with attached drawing, the technical solution that each embodiment of the application provides is described in detail.
Fig. 2 is a kind of generation method flow chart of reference list provided by the embodiments of the present application, is included the following steps：
S201：Obtain the historical data for waiting for reference user.
The executive agent of this method can be credit investigation system or reference device, can also be performed for the visitor of reference work
Family end, the client can be installed in the existing credit investigation system that credit information service uses.For convenience of description, with this method
Executive agent be that following explanation is unfolded for credit investigation system.
In the embodiment of the present application, the historical data can wait for that reference user generates in life (on line or under line)
Data.The historical data can be that staff obtains from each approach, can also be intelligent searching engine, crawlers
Or other intelligent programs that can obtain historical data are obtained from each approach.For example, the history number that Zhang San generates in life
According to can be Zhang San on January 5th, 2017 in 50,000 yuan of certain cash in banks, Zhang San is on January 6th, 2017 in gas station to automobile
Oiling 10L, Zhang San have participated in postgraduate qualifying examination tutorial class etc. in June, 2016, can be visited by staff certain bank,
Gas station, tutorial class obtain the historical data of Zhang San, can also be by intelligent program from the database of certain bank, the number of gas station
According to the historical data for obtaining Zhang San on library and the website of tutorial class.
S202：The corresponding each behavioural characteristic of reference user is waited for according to described in historical data determination.
In the embodiment of the present application, it waits for the behavioural characteristic of reference user, can wait for that reference user generated in life
Certain behaviors, such as automobile fuel filler behavior, luxury goods buying behavior, academic monograph Borrowing System.
The behavioural characteristic can be credit investigation system according to scheduled extracting rule, from the historical data for waiting for reference user
It extracts.
Wherein, the extracting rule can determine that the behavior that historical data is related to is special according to the keyword in historical data
Sign.I.e. by pre-setting the correspondence between each keyword and each behavioural characteristic so that credit investigation system can be according to history
(only the higher keyword of frequency of occurrence just can be shown that the behavior of user is practised to the keyword that frequency of occurrence is greater than the set value in data
It is used), corresponding behavioural characteristic is extracted, the corresponding behavioural characteristic of reference user is waited for as described.
Credit investigation system can also active obtaining user certain may be gone through with what the relevant behavior of credit facility generated by doing
History data, and further according to the historical data of acquisition, the custom sexual behaviour of the user is determined in these behaviors, as user
Behavioural characteristic.
It is generated between in January, 2017 in January, 2016 as an example it is assumed that obtaining Zhang San from Highway Control Center
Historical data, the keywords such as the higher oiling of extraction frequency of occurrence, charge station can be analyzed from the historical data of Zhang San, that
It can assert that the corresponding behavioural characteristic of Zhang San can be automobile fuel filler behavior and charge station's paying behaviors, be worth explanation
It is, if the automobile fuel filler behavior that Zhang San generates within a certain period of time is less (generating 5 automobile fuel filler behaviors within such as 1 year), then
With regard to illustrating that the behavior to refuel a car is not the custom sexual behaviour of Zhang San, then it cannot be assumed that the corresponding behavioural characteristic of Zhang San is vapour
Vehicle oiling behavior；Highway payment record, the oiling record that Zhang San can also be obtained, judge whether Zhang San often pays the fees or add
Oil, so that it is determined that the behavioural characteristic of Zhang San.
Analysis extracts the key of behavioural characteristic and is a series of pre-set behaviors of staff from historical data
The criteria for classifying of feature is as accurate as possible, and conditional sampling each other.So, credit investigation system is according to division behavioural characteristic
Behavioural characteristic of the standard from being extracted in the historical data for waiting for reference user, which can accurately reflect, waits for that reference user has
Reference classification.Certainly, staff can also adjust the standard for dividing behavioural characteristic at any time, further promote credit investigation system
Accuracy.
S203：Occurred under each reference classification according to determining each behavioural characteristic and predetermined each behavioural characteristic
Probability, determine described in wait for reference user missing reference classification.
According to statistical law, if the corresponding behavioural characteristic of two users is same or similar, then the two users have
Reference classification should also be same or similar.It, in the embodiment of the present application, can be in credit investigation system based on this statistical law
In preset the probability that occurs under each reference classification of each behavioural characteristic so that credit investigation system can inquire any one behavior
The probability that feature occurs under each reference classification.
In the embodiment of the present application, it can determine that each behavioural characteristic occurs under each reference classification in the following manner
Probability：
Data sample is obtained, the data sample includes the corresponding behavioural characteristic of multiple users of reference and described more
The reference classification that a user of reference is respectively provided with determines the behavior further according to the data sample for each behavioural characteristic
The probability that feature occurs under each reference classification respectively.
For example, data sample contains 10000 reference user and each reference classifications that reference user has
With corresponding each behavioural characteristic.Assuming that statistics obtains in this 10000 users, the user with reference classification y1 has 3000 people,
Then further statistics is obtained at this in 3000 people with y1, and the user of corresponding behavioural characteristic a1 has 300, then finally can
To obtain p (a1 | y1)=300/3000=1/10.Similar, each behavioural characteristic is general relative to the condition of each reference classification
Rate can be counted and be calculated.Behavioural characteristic is exactly behavioural characteristic in reference classification relative to the conditional probability of reference classification
The probability of lower appearance.
Various actions characteristic set x can also be counted from data sampleiProbability P (the x of appearancei), for example, 10000
Behavioural characteristic set x is corresponded in reference useriThe user of reference of=(a1, a3, a4) has 200 people, then can obtain P (xi)
=200/10000=2%, when it needs to be determined that some when reference user missing reference classification when, so that it may with from statistical result
It inquires this and waits for the corresponding P (x of reference useri).Further, it is also possible to count each reference classification yiProbability P (the y of appearancei), example
Such as, 10000 have reference classification y in reference useriThe user of reference of (such as vehicle production) has 2000 people, then can obtain P
(yi)=2000/10000=20%.
The user of reference for including in data sample is more, and data sample is bigger, and data sample is just closer to practical feelings
Condition, the probability that each behavioural characteristic obtained according to data sample occurs under each reference classification are more accurate.
In the embodiment of the present application, it can be directed to and wait for the corresponding each behavioural characteristic of reference user, from predetermined every
In the probability that a behavioural characteristic occurs under each reference classification, inquiry obtains behavior feature to be occurred under each reference classification
Probability, obtaining after the probability that the corresponding each behavioural characteristic of reference user occurs under each reference classification, so that it may with
The reference classification of reference user missing is waited for described in determination.
Specifically, each reference classification can be directed to, according to waiting for the corresponding each behavioural characteristic of reference user in the sign
Believe the probability occurred under classification, waits for that reference user has the probability of the reference classification described in calculating；Reference user is waited for according to described
It is respectively provided with the probability of each reference classification, the reference classification that reference user has is waited for described in determination.And wait for reference user except described
Other reference classifications outside the reference classification having exactly wait for the reference classification of reference user missing.
Wherein it is possible to which to wait for that the corresponding each behavioural characteristic of reference user occurs under each reference classification general according to described
Rate waits for what the corresponding each behavioural characteristic of reference user occurred under each reference classification for each reference classification by described
The probability that probability and the reference classification occur substitutes into following formula：
Wherein, P (yi| x) it is exactly the probability for waiting for reference user and there is i-th of reference classification, yiIndicate i-th of reference
Classification, x indicate described in wait for the set of the corresponding each behavioural characteristic of reference user, ajThe corresponding jth of reference user is waited for described in expression
A behavioural characteristic, m indicate described in wait for the quantity of the corresponding behavioural characteristic of reference user, P (yi| wait for reference user described in x) indicating
Probability with i-th of reference classification, P (yi) indicate that the probability that i-th of reference classification occurs, each reference classification occur general
Rate is also according to data sample determination or preset, P (aj|yi) corresponding j-th of the row of reference user is waited for described in expression
It is characterized the probability occurred under i-th of reference classification, P (x) indicates the probability that x occurs.P(yi)、P(aj|yi) and P (x) all may be used
To be come out from statistical sample in advance.
Obtaining the probability P (y for waiting for reference user and there is i-th of reference classificationi| it, can be by 1-P (y after x)i| x) make
For the probability for waiting for reference user and lacking i-th of reference classification.
Above-mentioned formulaIt is derived by according to Bayes' theorem.According to
Bayes' theorem, A are relative to the calculation formula of the conditional probability of B：
So in order to determine the tool for waiting for reference user relative to the conditional probability for waiting for reference user according to each reference classification
Some reference classifications, then：
Wherein x can be the set for waiting for the corresponding each behavioural characteristic of reference user, yiIndicate i-th of reference classification.It is practical
On wait for that the corresponding each behavioural characteristic of reference user can be expressed as x=(a1, a2, a3... ... aj), then according to new probability formula：Therefore it according to this formula (1) and (2), can be derived by：
In fact, the core concept of the application technical solution claimed is to be based on Naive Bayes Classification Algorithm,
The historical data for treating reference user is classified, and is determined and is waited for the reference classification that reference user has, and then is determined and waited for that reference is used
The reference classification of family missing, to generate corresponding reference list.
Due to waiting for that the historical data of reference user is lengthy and jumbled unordered, reference information is too specific, and credit investigation system executes simplicity
Can not be process object with historical data and reference information when Bayesian Classification Arithmetic, it therefore, in the embodiment of the present application, can be with
According to waiting for that the historical data of reference user extracts a series of mutually incoherent behavioural characteristics, the behavioural habits of reference user will be waited for
It is abstracted as behavioural characteristic mutually incoherent one by one, and each behavioural characteristic can relative to the conditional probability of each reference classification
To be determined according to data sample, finally, each reference classification is respectively relative to wait for that the conditional probability of reference user is also counted
It calculates, so as to the compatible degree for quantifying more each reference classification Yu waiting for reference user.
In the embodiment of the present application, it is determining after reference user lacks the probability of each reference classification respectively, it can be to institute
It states and waits for that reference user lacks the probability of each reference classification by sorting from big to small, by the corresponding reference class of top n probability respectively
Not, it is determined as the reference classification for waiting for reference user missing, the N is the integer more than 0, can be that staff is based on business
What experience was set in credit investigation system in advance.It should be noted that treating reference user when using above-mentioned and lacking each reference classification
When probability carries out the mode that size sequence is compared, it may not need in above-mentioned formula
It is middle to substitute into the specific value of p (x), but p (x) is considered as constant, why the specific value of p (x) is to final comparison knot
Fruit has no influence.
The probability pair of particular value can also be will be greater than according to the probability for waiting for reference user and lacking each reference classification respectively
The reference classification answered is determined as the reference classification for waiting for reference user missing, wherein the particular value can be staff
It is set in credit investigation system in advance based on business experience.
For example, the corresponding each behavioural characteristic of Zhang San is that (oiling behavior, expressway tol lcollection behavior, Automobile product disappear
Take behavior, telephone recharge behavior, call behavior, the behavior of registration guidance of the postgraduate qualifying examination class, the behavior of purchase senior engineer's training materials),
It is vehicle production, operator's informaiton, educational background, common reserve fund, house property that credit information service, which needs the reference classification acquired,.So, credit investigation system can
To inquire the corresponding P (a of the corresponding each behavioural characteristic of Zhang Sanj| y), calculate the probability that Zhang San lacks each reference classification
It is followed successively by 40%, 35%, 32%, 82%, 97%, then can will be greater than 80% probability corresponding reference classification (common reserve fund, room
Production) it is determined as the reference classification of Zhang San's missing, the first two probability can also be taken to correspond to by this 5 probability by sorting from big to small
The reference classification that is lacked as Zhang San of reference classification (common reserve fund, house property).
S204：According to the reference classification for waiting for reference user missing, reference list is generated.
Described in obtaining after the reference classification that reference user lacks, so that it may wait for what reference user had to generate not including
The reference list of reference classification.
It is worth noting that in the embodiment of the present application, the reference list can be the papery that credit investigation system prints
List can also be electronic spreadsheet, user interface etc., in short, the reference list can obtain the reference of user's offer
Information, the application are not limited the concrete form of reference list.
Fig. 3 a are the schematic diagrames that the existing credit investigation system that credit information service uses is interacted with user.Fig. 3 b are the application offers
The schematic diagram that is interacted with user of credit investigation system.
As shown in Figure 3a, user needs to fill in one by one accordingly for all reference classifications on standardized reference list
Reference information, convenience are relatively low.And it is as shown in Figure 3b, credit investigation system first determines that the user lacks according to the corresponding behavioural characteristic of user
Then the reference classification of mistake requires nothing more than user and fills in corresponding reference information in the reference classification of its missing.
It is gone through when needing to treat reference user progress reference according to waiting for that reference user is corresponding by method shown in Fig. 2
History data determine the corresponding each behavioural characteristic of the user, then in conjunction with predetermined each behavioural characteristic in each reference class
The probability for not descending appearance determines the reference classification of user missing, further according to the reference classification of user missing, generates reference table
It is single so that the user only needs to fill in the reference information in the reference classification of its missing, is made to user to reduce
At inconvenience, improve reference efficiency.
In the embodiment of the present application, each waiting for that reference user needs the reference list filled in is customized for it, each
Wait for that reference user needs the reference list filled in that may be different, this also achieves " thousand people, thousand face " of reference list.
The generation method of reference list provided by the embodiments of the present application is worked as without staff and needs to acquire new reference
Standardized reference list (reference classification is added in reference list) is updated when reference information in classification, but by the people that works
Member, which once matches credit investigation system, to be postponed, so that it may to wait for that reference user provides the reference list of customization by credit investigation system.
Further, the generation method of the application reference list claimed can be applied to big data reference neck
Domain, the historical data for the magnanimity that credit investigation system can be acquired according to big data platform, calculate each members of society has
The reference classification of reference classification and missing, to realize the big data reference to each member of the whole society.
In addition, in existing reference mode, need staff according to business experience from the numerous and jumbled historical data of user
The reference information of middle screening user, and then the reference classification of user's missing is analyzed, since the subjectivity of staff is strong, and people
Power is easy error when doing screening operation, with regard to the problem that the reference classification of usually determining user's missing is not accurate enough.And this Shen
Please the credit investigation system that provides of embodiment, on the one hand can mechanical executions reference work, on the other hand can be to each reference class
It does not wait for that the conditional probability of reference user calculates relative to described, therefore both can efficiently execute reference work, it can also be accurate
Really determine the reference classification for waiting for reference user missing.
In addition, the historical data for waiting for reference user got can come from the historical data of a data source, example
If the historical data may come from big data platform, embodiment as described above waits for the corresponding each row of reference user
Being characterized can be determined according to the historical data for coming from big data platform.
And as another embodiment provided by the embodiments of the present application, the historical data can also be to come from incessantly
The historical data of one data source.One data source represents a data acquiring way, and is gone through from what different data sources obtained
History data have often been also directed to different reference classifications.
For example, bank is a data source, the reference classification very maximum probability that the corresponding historical data of bank is directed toward is finance
Property, user can be analyzed from the corresponding historical data of bank to be had revenue and expenditure behavior, has lend-borrow action, the row such as the behavior that has money on deposit
It is characterized.For another example, it is a data source to learn letter grid database, learns the reference classification that the corresponding historical data of letter grid database is directed toward
Very maximum probability be educational background, can be analyzed from the corresponding historical data of the Ministry of Education user go to school behavior, behavior of suspending schooling, have
The behavioural characteristics such as the activities against discipline, the behavior of You Gua sections.
It, in the embodiment of the present application, can when the corresponding behavioural characteristic of reference user corresponding data source more than one
To be first directed to each data source, according to the behavioural characteristic determined by the historical data from the data source and predetermined every
The probability that a behavioural characteristic occurs under each reference classification, determine described in wait for the sign that reference user lacks relative to the data source
Believe classification, further according to the reference classification for waiting for reference user and being lacked relative to each data source, reference user is waited for described in determination
The reference classification of missing.
Specifically, according to the probability for waiting for reference user and lacking relative to the data source each reference classification, will be greater than
The corresponding reference classification of probability of particular value is determined as the reference classification for waiting for that reference user lacks and then waits levying to described
Credit household takes intersection, the exactly described reference class for waiting for reference user's true miss relative to the reference classification that each data source lacks
Not.
The reference classification that reference user has relative to each data source is waited for described in can also first determining, reference is waited for by described
Other reference classifications except all reference classifications that user has are determined as waiting for the reference classification of reference user missing.Also
It is to wait for that reference user has the probability of each reference classification relative to the data source according to, it will be not less than the probability pair of particular value
The reference classification answered waits for the reference classification that reference user has described in being determined as, and then, waits for reference user relative to each to described
The reference classification that data source has takes union, then, other reference classifications in addition to the union are exactly described to wait for that reference user is true
The reference classification just lacked.
For credit investigation system, actually according to the difference of data source, the corresponding each behavioural characteristic of reference user will be waited for
Set divides for several behavioural characteristic subclass corresponding with each data source.Wait for reference user with respect to Mr. Yu described in determination
The reference classification of a data source missing, actually according to each behavior in the corresponding behavioural characteristic subclass of the data source
Probability that feature occurs under each reference classification, determine described in wait for that reference user closes relative to behavior character subset and has
Reference classification then, then by the reference classification for waiting for reference user and relative to each data source having is determined as described waiting for reference
The reference classification that user has.Specific embodiment can refer to above, not repeat.
For example, Zhang San corresponding behavioural characteristic subclass x1, x2, x3 from three data sources are respectively that x1 (adds
Oily behavior, expressway tol lcollection behavior, the consumer behavior of Automobile product), x2 (telephone recharge behavior, call behavior), x3 (examine by registration
Grind tutorial class's behavior, the behavior of purchase senior engineer's training materials), it is vehicle production, fortune that credit information service, which needs the reference classification acquired,
Seek quotient's information, educational background, common reserve fund, house property.So, for x1, can inquire P (oiling behavior | vehicle produces), P (oiling behavior |
Operator's informaiton), P (oiling behavior | educational background), P (oiling behavior | common reserve fund), P (oiling behavior | house property), similar can also
Inquire the conditional probability of expressway tol lcollection behavior, the consumer behavior of Automobile product relative to each reference classification.
So that conditional probability P (y | x1) of each reference classification relative to x1 can be calculated.Assuming that calculated vehicle
Production, operator's informaiton, educational background, common reserve fund, the corresponding P of house property (y | x1) are followed successively by 95%, 68%, 55%, 40%, 81%, that
It can take 95% corresponding reference classification (vehicle production) that can also take and be more than as the reference classification that Zhang San has relative to x1
The 80% corresponding reference classification of probability (vehicle production, house property), the reference classification having relative to x1 as Zhang San.Similarly,
It can determine the reference classification that Zhang San has relative to x2, x3.So, the reference classification of Zhang San's missing is exactly to remove Zhang San's phase
Other reference classifications outside the reference classification being respectively provided with for x1, x2, x3.
In existing reference mode, when staff obtains the historical data of user from multiple data sources, from some
The historical data that data source gets user can only illustrate that the user is likely to have the corresponding reference classification of the data source, but work
Making personnel can not determine whether the user of the historical data with the data source with other seems unrelated sign with the data source
Believe classification.For example, if statistical law shows that there is well educated people very maximum probability to have vehicle production, but in existing reference side
In formula, staff often it is subjective can not intuitive judgment come learn by oneself letter grid database some wait for the history number of reference user
According to can illustrate this wait for reference user whether have vehicle production.
And in the embodiment of the present application, by waiting for the corresponding each behavioural characteristic of reference user relative to each reference classification
Conditional probability, it may be determined that go out the reference classification that a few thing personnel can not intuitively analyze with business experience, as user
The reference classification having.Based on Naive Bayes Classification Algorithm, exist using to each behavioural characteristic that data sample statistics obtain
The probability occurred under each reference classification can carry out quantifiable depth excavation, compared with subject to the corresponding historical data of user
It is so true that determine the reference classification that user lacks.Thus, which the reference classification that the reference list generated includes can greatly subtract
It is few, it is not necessary to waste user's excessive time.
For example, the historical data of Zhang San is to refuel altogether 20 times in January, 2016 in January, 2017, in January, 2016 to 8
The moon, purchase was paid the fees 5 times to 2 months in Tibetan high speed in Beijing automobile cushion, in January, 2017 three times altogether.So, staff is according to Zhang San
Historical data can only judge the reference classification that Zhang San has for vehicle produce.But credit investigation system can be according to the history of Zhang San
Data determine that the corresponding behavioural characteristic of Zhang San is (oiling behavior, expressway tol lcollection behavior, the consumer behavior of Automobile product), in addition to
It is except 95% that P (vehicle produce | Zhang San), which can be calculated, it is also possible to which it is 75% to calculate P (educational background | Zhang San), shows there is above-mentioned three
The people of a behavioural characteristic is not only likely to the people of vehicle production, and also greater probability is that have the people of educational background.Thus, which Zhang San has
Reference classification can be vehicle production and educational background, credit investigation system need not just enumerate this academic reference classification on reference list
?.And in existing reference mode, by manually classifying as a result, the academic reference for being not determined to Zhang San and having
Classification.
Finally, it is emphasized that, it will be understood by those skilled in the art that determining the probability for lacking each reference classification
It is equivalent technological means with the determining probability with each reference classification, waits for that reference user lacks using the determination of any technological means
Reference classification, all should be within the protection domain required by the application.
Based on the call method of interactive controls shown in Fig. 2, the embodiment of the present application also correspondence provides a kind of reference list
Generating means, as shown in figure 4, including：
Acquisition module 401 obtains the historical data for waiting for reference user；
First determining module 402 waits for the corresponding each behavioural characteristic of reference user according to described in historical data determination；
Second determining module 403, according to determining each behavioural characteristic and predetermined each behavioural characteristic in each sign
Believe the probability occurred under classification, the reference classification of reference user missing is waited for described in determination；
Generation module 404 generates reference list according to the reference classification for waiting for reference user missing.
The probability that each behavioural characteristic occurs under each reference classification is predefined, is specifically included：Obtain data sample；
The data sample includes that the corresponding behavioural characteristic of multiple users of reference and the multiple user of reference are respectively provided with
Reference classification；Determine behavior feature respectively under each reference classification for each behavioural characteristic according to the data sample
The probability of appearance.
Second determining module 403 occurs from predetermined each behavioural characteristic under each reference classification general
In rate, inquires and wait for the probability that the corresponding each behavioural characteristic of reference user occurs under each reference classification described in obtaining；For
Each reference classification, according to the probability for waiting for the corresponding each behavioural characteristic of reference user and occurring under the reference classification, meter
Wait for that reference user lacks the probability of the reference classification described in calculation；Wait for that reference user lacks the general of each reference classification respectively according to described
Rate, determine described in wait for reference user missing reference classification.
Second determining module 403, using formulaIt is waited for described in calculating
Reference user has i-th of reference classification yiProbability P (yi|x)；According to the P (yi| wait for that reference user lacks described in x) determining
The probability of i-th of reference classification；
Wherein, the set of the corresponding each behavioural characteristic of reference user, a are waited for described in x expressionsjReference user couple is waited for described in expression
J-th of the behavioural characteristic answered, m indicate described in wait for the quantity of the corresponding behavioural characteristic of reference user, P (yi| it waits levying described in x) indicating
Credit household has the probability of i-th of reference classification, P (yi) indicate that the probability that i-th of reference classification occurs, each reference classification go out
Existing probability is determined according to the data sample, P (aj|yi) corresponding j-th of the behavioural characteristic of reference user is waited for described in expression
The probability occurred under i-th of reference classification, P (x) indicate the probability that x occurs.
Second determining module 403 will be greater than according to the probability for waiting for reference user and lacking each reference classification respectively
The corresponding reference classification of probability of particular value is determined as the reference classification for waiting for reference user missing；Or wait for reference to described
User lacks the probability of each reference classification by sorting from big to small respectively, and the corresponding reference classification of top n probability determines
For the reference classification for waiting for reference user missing, the N is the integer more than 0.
The acquisition module 401, obtained respectively from least two data sources described in wait for the historical data of reference user；
First determining module 402 is determined for each data source according to the historical data obtained from the data source
It is described to wait for the corresponding behavioural characteristic of reference user；
Second determining module 403 is determined for each data source according to by the historical data from the data source
Behavioural characteristic and the probability that occurs under each reference classification of predetermined each behavioural characteristic, determine described in wait for that reference is used
The reference classification that family is lacked relative to the data source；According to the reference class for waiting for reference user and being lacked relative to each data source
Not, the reference classification of reference user missing is waited for described in determining.
In the 1990s, the improvement of a technology can be distinguished clearly be on hardware improvement (for example,
Improvement to circuit structures such as diode, transistor, switches) or software on improvement (improvement for method flow).So
And with the development of technology, the improvement of current many method flows can be considered as directly improving for hardware circuit.
Designer nearly all obtains corresponding hardware circuit by the way that improved method flow to be programmed into hardware circuit.Cause
This, it cannot be said that the improvement of a method flow cannot be realized with hardware entities module.For example, programmable logic device
(Programmable Logic Device, PLD) (such as field programmable gate array (Field Programmable Gate
Array, FPGA)) it is exactly such a integrated circuit, logic function determines device programming by user.By designer
Voluntarily programming comes a digital display circuit " integrated " on a piece of PLD, designs and makes without asking chip maker
Dedicated IC chip.Moreover, nowadays, substitution manually makes IC chip, this programming is also used instead mostly " patrols
Volume compiler (logic compiler) " software realizes that software compiler used is similar when it writes with program development,
And the source code before compiling also write by handy specific programming language, this is referred to as hardware description language
(Hardware Description Language, HDL), and HDL is also not only a kind of, but there are many kind, such as ABEL
(Advanced Boolean Expression Language)、AHDL(Altera Hardware Description
Language)、Confluence、CUPL(Cornell University Programming Language)、HDCal、JHDL
(Java Hardware Description Language)、Lava、Lola、MyHDL、PALASM、RHDL(Ruby
Hardware Description Language) etc., VHDL (Very-High-Speed are most generally used at present
Integrated Circuit Hardware Description Language) and Verilog.Those skilled in the art also answer
This understands, it is only necessary to method flow slightly programming in logic and is programmed into integrated circuit with above-mentioned several hardware description languages,
The hardware circuit for realizing the logical method flow can be readily available.
Controller can be implemented in any suitable manner, for example, controller can take such as microprocessor or processing
The computer for the computer readable program code (such as software or firmware) that device and storage can be executed by (micro-) processor can
Read medium, logic gate, switch, application-specific integrated circuit (Application Specific Integrated Circuit,
ASIC), the form of programmable logic controller (PLC) and embedded microcontroller, the example of controller includes but not limited to following microcontroller
Device：ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20 and Silicone Labs C8051F320, are deposited
Memory controller is also implemented as a part for the control logic of memory.It is also known in the art that in addition to
Pure computer readable program code mode is realized other than controller, can be made completely by the way that method and step is carried out programming in logic
Controller is obtained in the form of logic gate, switch, application-specific integrated circuit, programmable logic controller (PLC) and embedded microcontroller etc. to come in fact
Existing identical function.Therefore this controller is considered a kind of hardware component, and to including for realizing various in it
The device of function can also be considered as the structure in hardware component.Or even, it can will be regarded for realizing the device of various functions
For either the software module of implementation method can be the structure in hardware component again.
System, device, module or the unit that above-described embodiment illustrates can specifically realize by computer chip or entity,
Or it is realized by the product with certain function.It is a kind of typically to realize that equipment is computer.Specifically, computer for example may be used
Think personal computer, laptop computer, cellular phone, camera phone, smart phone, personal digital assistant, media play
It is any in device, navigation equipment, electronic mail equipment, game console, tablet computer, wearable device or these equipment
The combination of equipment.
For convenience of description, it is divided into various units when description apparatus above with function to describe respectively.Certainly, implementing this
The function of each unit is realized can in the same or multiple software and or hardware when application.
It should be understood by those skilled in the art that, the embodiment of the present invention can be provided as method, system or computer program
Product.Therefore, complete hardware embodiment, complete software embodiment or reality combining software and hardware aspects can be used in the present invention
Apply the form of example.Moreover, the present invention can be used in one or more wherein include computer usable program code computer
The computer program production implemented in usable storage medium (including but not limited to magnetic disk storage, CD-ROM, optical memory etc.)
The form of product.
The present invention be with reference to according to the method for the embodiment of the present invention, the flow of equipment (system) and computer program product
Figure and/or block diagram describe.It should be understood that can be realized by computer program instructions every first-class in flowchart and/or the block diagram
The combination of flow and/or box in journey and/or box and flowchart and/or the block diagram.These computer programs can be provided
Instruct the processor of all-purpose computer, special purpose computer, Embedded Processor or other programmable data processing devices to produce
A raw machine so that the instruction executed by computer or the processor of other programmable data processing devices is generated for real
The device for the function of being specified in present one flow of flow chart or one box of multiple flows and/or block diagram or multiple boxes.
These computer program instructions, which may also be stored in, can guide computer or other programmable data processing devices with spy
Determine in the computer-readable memory that mode works so that instruction generation stored in the computer readable memory includes referring to
Enable the manufacture of device, the command device realize in one flow of flow chart or multiple flows and/or one box of block diagram or
The function of being specified in multiple boxes.
These computer program instructions also can be loaded onto a computer or other programmable data processing device so that count
Series of operation steps are executed on calculation machine or other programmable devices to generate computer implemented processing, in computer or
The instruction executed on other programmable devices is provided for realizing in one flow of flow chart or multiple flows and/or block diagram one
The step of function of being specified in a box or multiple boxes.
In a typical configuration, computing device includes one or more processors (CPU), input/output interface, net
Network interface and memory.
Memory may include computer-readable medium in volatile memory, random access memory (RAM) and/or
The forms such as Nonvolatile memory, such as read-only memory (ROM) or flash memory (flash RAM).Memory is computer-readable medium
Example.
Computer-readable medium includes permanent and non-permanent, removable and non-removable media can be by any method
Or technology realizes information storage.Information can be computer-readable instruction, data structure, the module of program or other data.
The example of the storage medium of computer includes, but are not limited to phase transition internal memory (PRAM), static RAM (SRAM), moves
State random access memory (DRAM), other kinds of random access memory (RAM), read-only memory (ROM), electric erasable
Programmable read only memory (EEPROM), fast flash memory bank or other memory techniques, read-only disc read only memory (CD-ROM) (CD-ROM),
Digital versatile disc (DVD) or other optical storages, magnetic tape cassette, tape magnetic disk storage or other magnetic storage apparatus
Or any other non-transmission medium, it can be used for storage and can be accessed by a computing device information.As defined in this article, it calculates
Machine readable medium does not include temporary computer readable media (transitory media), such as data-signal and carrier wave of modulation.
It should also be noted that, the terms "include", "comprise" or its any other variant are intended to nonexcludability
Including so that process, method, commodity or equipment including a series of elements include not only those elements, but also wrap
Include other elements that are not explicitly listed, or further include for this process, method, commodity or equipment intrinsic want
Element.In the absence of more restrictions, the element limited by sentence "including a ...", it is not excluded that wanted including described
There is also other identical elements in the process of element, method, commodity or equipment.
It will be understood by those skilled in the art that embodiments herein can be provided as method, system or computer program product.
Therefore, complete hardware embodiment, complete software embodiment or embodiment combining software and hardware aspects can be used in the application
Form.It is deposited moreover, the application can be used to can be used in the computer that one or more wherein includes computer usable program code
The shape for the computer program product implemented on storage media (including but not limited to magnetic disk storage, CD-ROM, optical memory etc.)
Formula.
The application can describe in the general context of computer-executable instructions executed by a computer, such as program
Module.Usually, program module includes routines performing specific tasks or implementing specific abstract data types, program, object, group
Part, data structure etc..The application can also be put into practice in a distributed computing environment, in these distributed computing environments, by
Task is executed by the connected remote processing devices of communication network.In a distributed computing environment, program module can be with
In the local and remote computer storage media including storage device.
Each embodiment in this specification is described in a progressive manner, identical similar portion between each embodiment
Point just to refer each other, and each embodiment focuses on the differences from other embodiments.Especially for system reality
For applying example, since it is substantially similar to the method embodiment, so description is fairly simple, related place is referring to embodiment of the method
Part explanation.
Above is only an example of the present application, it is not intended to limit this application.For those skilled in the art
For, the application can have various modifications and variations.It is all within spirit herein and principle made by any modification, equivalent
Replace, improve etc., it should be included within the scope of claims hereof.
Claims (12)
1. a kind of generation method of reference list, which is characterized in that including：
Obtain the historical data for waiting for reference user；
The corresponding each behavioural characteristic of reference user is waited for according to described in historical data determination；
According to the probability that determining each behavioural characteristic and predetermined each behavioural characteristic occur under each reference classification, really
The fixed reference classification for waiting for reference user missing；
According to the reference classification for waiting for reference user missing, reference list is generated.
2. according to the method described in claim 1, it is characterized in that, predefining each behavioural characteristic under each reference classification
The probability of appearance, specifically includes：
Obtain data sample；The data sample include the corresponding behavioural characteristic of multiple users of reference and it is the multiple
The reference classification that reference user is respectively provided with；
According to the data sample, for each behavioural characteristic, determine what behavior feature occurred under each reference classification respectively
Probability.
3. according to the method described in claim 2, it is characterized in that, according to determining each behavioural characteristic and predetermined each
The probability that behavioural characteristic occurs under each reference classification, determine described in wait for reference user missing reference classification, specifically include：
From the probability that predetermined each behavioural characteristic occurs under each reference classification, inquires and wait for that reference is used described in obtaining
The probability that the corresponding each behavioural characteristic in family occurs under each reference classification；
For each reference classification, wait for what the corresponding each behavioural characteristic of reference user occurred under the reference classification according to described
Probability waits for that reference user lacks the probability of the reference classification described in calculating；
According to the probability for waiting for reference user and lacking each reference classification respectively, the reference class of reference user missing is waited for described in determination
Not.
4. according to the method described in claim 3, it is characterized in that, waiting for that reference user lacks the general of the reference classification described in calculating
Rate specifically includes：
Using formulaWait for that reference user has i-th of reference classification described in calculating
yiProbability P (yi|x)；
According to the P (yi| wait for that reference user lacks the probability of i-th of reference classification described in x) determining；
Wherein, the set of the corresponding each behavioural characteristic of reference user, a are waited for described in x expressionsjWait for that reference user is corresponding described in expression
J-th of behavioural characteristic, m indicate described in wait for the quantity of the corresponding behavioural characteristic of reference user, P (yi| wait for that reference is used described in x) indicating
Family has the probability of i-th of reference classification, P (yi) indicate the probability that i-th of reference classification occurs, what each reference classification occurred
Probability is determined according to the data sample, P (aj|yi) wait for corresponding j-th of the behavioural characteristic of reference user described in expression
The probability occurred under i reference classification, P (x) indicate the probability that x occurs.
5. method according to claim 3 or 4, which is characterized in that wait for that reference user lacks each reference respectively according to described
The probability of classification, determine described in wait for reference user missing reference classification, specifically include：
According to the probability for waiting for reference user and lacking each reference classification respectively, the corresponding reference class of probability of particular value will be greater than
Not, it is determined as the reference classification for waiting for reference user missing；Or
Wait for that reference user lacks the probability of each reference classification by sorting from big to small respectively to described, top n probability is right respectively
The reference classification answered, is determined as the reference classification for waiting for reference user missing, and the N is the integer more than 0.
6. according to the method described in claim 1, waiting for the historical data of reference user it is characterized in that, obtaining, specifically include：
The historical data of reference user is waited for described in being obtained respectively from least two data sources；
The corresponding each behavioural characteristic of reference user is waited for according to described in historical data determination, is specifically included：
For each data source, according to the historical data obtained from the data source, the corresponding behavior of reference user is waited for described in determination
Feature；
According to the probability that determining each behavioural characteristic and each behavioural characteristic occur under each reference classification, wait levying described in determination
The reference classification of credit household's missing, specifically includes：
For each data source, according to the behavioural characteristic determined by the historical data from the data source and predetermined every
The probability that a behavioural characteristic occurs under each reference classification, determine described in wait for the sign that reference user lacks relative to the data source
Believe classification；
According to the reference classification for waiting for reference user and being lacked relative to each data source, reference user missing is waited for described in determination
Reference classification.
7. a kind of generating means of reference list, which is characterized in that including：
Acquisition module obtains the historical data for waiting for reference user；
First determining module waits for the corresponding each behavioural characteristic of reference user according to described in historical data determination；
Second determining module, according to determining each behavioural characteristic and predetermined each behavioural characteristic under each reference classification
The probability of appearance, determine described in wait for reference user missing reference classification；
Generation module generates reference list according to the reference classification for waiting for reference user missing.
8. device according to claim 7, which is characterized in that predefine each behavioural characteristic under each reference classification
The probability of appearance, specifically includes：
Obtain data sample；The data sample include the corresponding behavioural characteristic of multiple users of reference and it is the multiple
The reference classification that reference user is respectively provided with；
According to the data sample, for each behavioural characteristic, determine what behavior feature occurred under each reference classification respectively
Probability.
9. device according to claim 8, which is characterized in that second determining module, from predetermined each row
It is characterized in the probability occurred under each reference classification, inquires and wait for that the corresponding each behavioural characteristic of reference user exists described in obtaining
The probability occurred under each reference classification；For each reference classification, wait for that the corresponding each behavior of reference user is special according to described
The probability occurred under the reference classification is levied, waits for that reference user lacks the probability of the reference classification described in calculating；It is waited for according to described
Reference user lacks the probability of each reference classification respectively, and the reference classification of reference user missing is waited for described in determination.
10. device according to claim 9, which is characterized in that second determining module, using formulaWait for that reference user has i-th of reference classification y described in calculatingiProbability P (yi|
x)；According to the P (yi| wait for that reference user lacks the probability of i-th of reference classification described in x) determining；
Wherein, the set of the corresponding each behavioural characteristic of reference user, a are waited for described in x expressionsjWait for that reference user is corresponding described in expression
J-th of behavioural characteristic, m indicate described in wait for the quantity of the corresponding behavioural characteristic of reference user, P (yi| wait for that reference is used described in x) indicating
Family has the probability of i-th of reference classification, P (yi) indicate the probability that i-th of reference classification occurs, what each reference classification occurred
Probability is determined according to the data sample, P (aj|yi) wait for corresponding j-th of the behavioural characteristic of reference user described in expression
The probability occurred under i reference classification, P (x) indicate the probability that x occurs.
11. device according to claim 9 or 10, which is characterized in that second determining module waits for reference according to described
User lacks the probability of each reference classification respectively, will be greater than the corresponding reference classification of probability of particular value, is determined as described waiting levying
The reference classification of credit household's missing；Or wait for that reference user lacks the probability of each reference classification by arranging from big to small respectively to described
The corresponding reference classification of top n probability is determined as the reference classification for waiting for reference user missing, the N is big by sequence
In 0 integer.
12. device according to claim 7, which is characterized in that
The acquisition module, obtained respectively from least two data sources described in wait for the historical data of reference user；
First determining module, according to the historical data obtained from the data source, waits levying for each data source described in determination
The corresponding behavioural characteristic of credit household；
Second determining module, for each data source, according to the behavior determined by the historical data from the data source
The probability that feature and predetermined each behavioural characteristic occur under each reference classification, determine described in wait for that reference user is opposite
In the reference classification of data source missing；According to the reference classification for waiting for reference user and being lacked relative to each data source, really
The fixed reference classification for waiting for reference user missing.
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