CN107423393A - Data processing method and its system - Google Patents
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- CN107423393A CN107423393A CN201710609363.9A CN201710609363A CN107423393A CN 107423393 A CN107423393 A CN 107423393A CN 201710609363 A CN201710609363 A CN 201710609363A CN 107423393 A CN107423393 A CN 107423393A
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Abstract
Present disclose provides a kind of data processing method, including：Customer group data are obtained, customer group data represent potential user group interested in destination object classification, wherein, potential user group is by for identifying that user's usage mining Model Identification whether interested in destination object classification obtains；The user in potential user group is obtained under the default object offer pattern set for destination object classification, the associating web pages of destination object classification are carried out operating caused operation data；And usage mining model is verified based on operation data.The disclosure additionally provides a kind of data handling system and a kind of computer-readable recording medium.
Description
Technical field
This disclosure relates to data processing field, more particularly, to a kind of data processing method and its system.
Background technology
In the big data epoch, the function influence of big data the every aspect of people, how to handle these data and then enters
Row precision data, which excavates, seems significant.Wherein, data mining and machine learning are to be capable of the key of precision data excavation.Number
It is from substantial amounts of, incomplete, fuzzy, random real application data according to excavating with machine learning, extraction lies in it
In, people are ignorant in advance but the information and the process of knowledge that include.It should be noted that data mining and
The data source of machine learning must be real, substantial amounts of, and the data of extraction are user's information and knowledge interested, and are carried
The data taken are to be subjected to, be appreciated that and exercisable data, it is not required that the data extracted are all suitable for for all occasions,
But it can be only applicable to solve the problems, such as or evaluate special scenes discovery.
Precision data, which excavates, to be analyzed by significant factor, by the technologies such as data mining and machine learning, precise positioning
Specific potential valuable data, then the specific potential valuable data are carried out with the data analysis of special scenes.Precisely
The core technology of data mining is data mining and machine learning.The algorithm model of data mining needs regularly upgrade maintenance,
It can be only achieved the effect that more preferable precision data excavates.
But during disclosure design is realized, inventor has found that at least there are the following problems in the prior art：
Traditional algorithm model upgrade method is easily ensnared among experience guidance, and uncertain factor is high, leads to not
The upgrade maintenance for the algorithm model that effective guide data is excavated.
The content of the invention
In view of this, present disclose provides it is a kind of can effectively guide data mining mode upgrading data processing method and
Its system.
An aspect of this disclosure provides a kind of data processing method, including：Obtain customer group data, above-mentioned customer group
Data represent potential user group interested in destination object classification, wherein, above-mentioned potential user group is by being used for identifying
Family usage mining Model Identification whether interested in above-mentioned destination object classification obtains；Obtain in above-mentioned potential user group
User is under the default object offer pattern set for above-mentioned destination object classification, to the association net of above-mentioned destination object classification
Page carries out operating caused operation data；And above-mentioned usage mining model is verified based on aforesaid operations data.
In accordance with an embodiment of the present disclosure, obtaining potential user group interested in destination object classification includes：Obtain to upper
Destination object classification the first customer group interested is stated, wherein, above-mentioned first customer group is known by above-mentioned usage mining model
Do not obtain；The user obtained in above-mentioned first customer group carries out operating caused operation data for above-mentioned associating web pages, with
It is determined that for representing score value of the user in above-mentioned first customer group to the interest level of above-mentioned destination object classification；And root
Pattern is provided according to above-mentioned score value and above-mentioned default object, determines above-mentioned potential user group.
In accordance with an embodiment of the present disclosure, above-mentioned default object, which provides pattern, includes the first default object offer pattern and second
Default object provides pattern, obtains the user in above-mentioned potential user group in default pair set for above-mentioned destination object classification
As under offer pattern, the associating web pages of above-mentioned destination object classification are operated caused by operation data include：Obtain above-mentioned
User in potential user group under the above-mentioned first default object offer pattern, above-mentioned associating web pages are operated caused by the
One operation data；And user in above-mentioned potential user group is obtained under the above-mentioned second default object offer pattern, to above-mentioned
Associating web pages operated caused by second operand evidence.
In accordance with an embodiment of the present disclosure, above-mentioned default object, which provides pattern, includes the first default object offer pattern and second
Default object provides pattern, obtains the user in above-mentioned potential user group in default pair set for above-mentioned destination object classification
As under offer pattern, the associating web pages of above-mentioned destination object classification are operated caused by operation data include：Split above-mentioned
Potential user group, to obtain first object customer group and the second potential user group；Obtain the use in above-mentioned first object customer group
Family under the above-mentioned first default object offer pattern, above-mentioned associating web pages are operated caused by the 3rd operation data；And
The user of above-mentioned second potential user group is obtained under the above-mentioned second default object offer pattern, above-mentioned associating web pages are grasped
4th operation data caused by work.
In accordance with an embodiment of the present disclosure, above-mentioned potential user group is split, to obtain first object customer group and the second target
Customer group includes：The first pre-set user quantity under the above-mentioned first default object offer pattern is provided and preset above-mentioned second
The second pre-set user quantity under object offer pattern；Calculate above-mentioned first pre-set user quantity and above-mentioned second pre-set user number
Proportionality coefficient between amount；The user in above-mentioned potential user group is grouped at random, to obtain multiple user groupings；And
Determine that above-mentioned first object customer group and above-mentioned second target are used from above-mentioned multiple user groupings according to aforementioned proportion coefficient
Family group.
In accordance with an embodiment of the present disclosure, carrying out checking to above-mentioned usage mining model based on aforesaid operations data includes：Base
Verify that the step includes to above-mentioned usage mining model in above-mentioned 3rd operation data and above-mentioned 4th operation data：Root
Determine to provide in the above-mentioned first default object according to the number of users in above-mentioned 3rd operation data and above-mentioned first object customer group
The first operating rate that user is operated to above-mentioned associating web pages under pattern；According to above-mentioned 4th operation data and above-mentioned first mesh
Number of users in mark customer group determines that user grasps to above-mentioned associating web pages under the above-mentioned second default object offer pattern
The second operating rate made；And above-mentioned usage mining model is tested according to above-mentioned first operating rate and above-mentioned second operating rate
Card.
Another aspect of the disclosure provides a kind of data handling system, including：First acquisition module, used for obtaining
Family group's data, above-mentioned customer group data represent potential user group interested in destination object classification, wherein, above-mentioned targeted customer
Group is by for identifying that user's usage mining Model Identification whether interested in above-mentioned destination object classification obtains；Second
Acquisition module, carried for obtaining the user in above-mentioned potential user group in the default object set for above-mentioned destination object classification
For under pattern, carrying out operating caused operation data to the associating web pages of above-mentioned destination object classification；And authentication module, it is used for
Above-mentioned usage mining model is verified based on aforesaid operations data.
In accordance with an embodiment of the present disclosure, the first acquisition module includes：First acquisition unit, for obtaining to above-mentioned target pair
As classification the first customer group interested, wherein, above-mentioned first customer group is obtained by above-mentioned usage mining Model Identification；
Second acquisition unit, the user for obtaining in above-mentioned first customer group carry out operating caused operation for above-mentioned associating web pages
Data, to determine to be used to represent point of the user in above-mentioned first customer group to the interest level of above-mentioned destination object classification
Value；And first determining unit, for providing pattern according to above-mentioned score value and above-mentioned default object, determine above-mentioned targeted customer
Group.
In accordance with an embodiment of the present disclosure, above-mentioned default object, which provides pattern, includes the first default object offer pattern and second
Default object provides pattern, and above-mentioned second acquisition module includes：3rd acquiring unit, for obtaining in above-mentioned potential user group
User under the above-mentioned first default object offer pattern, above-mentioned associating web pages are operated caused by first operand evidence；With
And the 4th acquiring unit, it is right for obtaining the user in above-mentioned potential user group under the above-mentioned second default object offer pattern
Above-mentioned associating web pages operated caused by second operand evidence.
In accordance with an embodiment of the present disclosure, above-mentioned default object, which provides pattern, includes the first default object offer pattern and second
Default object provides pattern, and above-mentioned second acquisition module includes：Split cells, for splitting above-mentioned potential user group, to obtain
First object customer group and the second potential user group；5th acquiring unit, for obtaining the use in above-mentioned first object customer group
Family under the above-mentioned first default object offer pattern, above-mentioned associating web pages are operated caused by the 3rd operation data；And
6th acquiring unit is right for obtaining the user of above-mentioned second potential user group under the above-mentioned second default object offer pattern
Above-mentioned associating web pages operated caused by the 4th operation data.
In accordance with an embodiment of the present disclosure, above-mentioned split cells includes：Subelement is obtained, it is default above-mentioned first for obtaining
The first pre-set user quantity under object offer pattern and the second pre-set user under the above-mentioned second default object offer pattern
Quantity；Computation subunit, for calculating the ratio between above-mentioned first pre-set user quantity and above-mentioned second pre-set user quantity
Coefficient；Subelement is grouped, for being at random grouped the user in above-mentioned potential user group, to obtain multiple user groupings；
And first determination subelement, for determining above-mentioned first object from above-mentioned multiple user groupings according to aforementioned proportion coefficient
Customer group and above-mentioned second potential user group.
In accordance with an embodiment of the present disclosure, above-mentioned authentication module includes：Authentication unit, for based on above-mentioned 3rd operation data
Verify that the authentication unit includes to above-mentioned usage mining model with above-mentioned 4th operation data：Second determination subelement, use
Determined in the number of users in above-mentioned 3rd operation data and above-mentioned first object customer group in the above-mentioned first default object
The first operating rate that user is operated to above-mentioned associating web pages under offer pattern；3rd determination subelement, for according to above-mentioned
Number of users in 4th operation data and above-mentioned first object customer group is determined under the above-mentioned second default object offer pattern
The second operating rate that user is operated to above-mentioned associating web pages；And checking subelement, for according to above-mentioned first operating rate
Above-mentioned usage mining model is verified with above-mentioned second operating rate.
Another aspect of the present disclosure provides a kind of computer-readable recording medium, is stored thereon with executable instruction, should
Instruction makes processor realize above-mentioned data processing method when being executed by processor.
Another aspect of the present disclosure provides a kind of computer program, and above computer program includes the executable finger of computer
Order, above-mentioned instruction are used to realize above-mentioned data processing method when executed.
In accordance with an embodiment of the present disclosure, a kind of data processing method is employed, including：Obtain customer group data, above-mentioned use
Family group's data represent potential user group interested in destination object classification, wherein, above-mentioned potential user group is by for knowing
Other user usage mining Model Identification whether interested in above-mentioned destination object classification obtains；Obtain above-mentioned potential user group
In user under the default object offer pattern set for above-mentioned destination object classification, to the pass of above-mentioned destination object classification
Networking page carries out operating caused operation data；And above-mentioned usage mining model is verified based on aforesaid operations data.
Because the user in potential user group can produce operation data to destination object classification, the operation data is by usage mining model
Excavate what the user in obtained potential user group obtained to destination object class operation, in this case, used according to target
Operation data caused by user's reality in the group of family verifies can solve existing skill at least in part to usage mining model
The problem of traditional algorithm model upgrade method is easily ensnared among experience guidance in art, and uncertain factor is high, therefore can
To realize the technique effect of the upgrade maintenance of effective guide data mining algorithm model.
Brief description of the drawings
By the description to the embodiment of the present disclosure referring to the drawings, the above-mentioned and other purposes of the disclosure, feature and
Advantage will be apparent from, in the accompanying drawings：
Fig. 1, which is diagrammatically illustrated, can apply the data processing method of the disclosure and its exemplary system architecture of system；
Fig. 2 diagrammatically illustrates the flow chart of the data processing method according to the embodiment of the present disclosure；
Fig. 3 A diagrammatically illustrate to be entered according to the acquisition user of the embodiment of the present disclosure to the associating web pages of destination object classification
The flow chart of operation data caused by row operation；
Fig. 3 B diagrammatically illustrate another association for obtaining user to destination object classification according to the embodiment of the present disclosure
Webpage operated caused by operation data flow chart；
Fig. 4 diagrammatically illustrates the block diagram of data handling system in accordance with an embodiment of the present disclosure；And
Fig. 5 diagrammatically illustrates the block diagram of the computer system of the data processing method using the embodiment of the present disclosure.
Embodiment
Hereinafter, it will be described with reference to the accompanying drawings embodiment of the disclosure.However, it should be understood that these descriptions are simply exemplary
, and it is not intended to limit the scope of the present disclosure.In addition, in the following description, the description to known features and technology is eliminated, with
Avoid unnecessarily obscuring the concept of the disclosure.
Term as used herein is not intended to limit the disclosure just for the sake of description specific embodiment.Used here as
Word " one ", " one (kind) " and "the" etc. should also include " multiple ", the meaning of " a variety of ", unless context clearly refers in addition
Go out.In addition, term " comprising " as used herein, "comprising" etc. indicate the presence of the feature, step, operation and/or part,
But it is not excluded that in the presence of or other one or more features of addition, step, operation or parts.
All terms (including technology and scientific terminology) as used herein have what those skilled in the art were generally understood
Implication, unless otherwise defined.It should be noted that term used herein should be interpreted that with consistent with the context of this specification
Implication, without should by idealization or it is excessively mechanical in a manner of explain.
Shown in the drawings of some block diagrams and/or flow chart.It should be understood that some sides in block diagram and/or flow chart
Frame or its combination can be realized by computer program instructions.These computer program instructions can be supplied to all-purpose computer,
The processor of special-purpose computer or other programmable data processing units, so as to which these instructions can be with when by the computing device
Create the device for realizing function/operation illustrated in these block diagrams and/or flow chart.
Therefore, the technology of the disclosure can be realized in the form of hardware and/or software (including firmware, microcode etc.).Separately
Outside, the technology of the disclosure can take the form of the computer program product on the computer-readable medium for being stored with instruction, should
Computer program product is available for instruction execution system use or combined command execution system to use.
Embodiment of the disclosure provides a kind of data processing method for being used to instruct usage mining model to upgrade and its is
System.This method includes obtaining customer group data and using the potential user group obtained to destination object class using usage mining model
Other Operations Analyst usage mining model.In customer group data procedures are obtained using usage mining model, potential user group is
Pass through what is obtained for identifying user's usage mining Model Identification whether interested in destination object classification.Mesh based on acquisition
Under the default object offer pattern that user in mark customer group is set to destination object classification, the association net to destination object classification
Page operated caused by operation data usage mining model is verified.
Fig. 1, which is diagrammatically illustrated, can apply the data processing method of the disclosure and its exemplary system architecture of system.
As shown in figure 1, system architecture 100 can include terminal device 101, terminal device 102, terminal device 103, network
104 and server 105.Network 104 to terminal device 101, terminal device 102, terminal device 103 and server 105 it
Between provide communication link medium.Network 104 can include various connection types, such as wired, wireless communication link or light
Fiber-optic cable etc..
User can pass through network 104 and server 105 with using terminal equipment 101, terminal device 102, terminal device 103
Interaction, to receive or send message etc..Terminal device 101, terminal device 102, can be provided with terminal device 103 it is various logical
Interrogate client application, such as the application of shopping class, web browser applications, searching class application, JICQ, mailbox client
(merely illustrative) such as end, social platform softwares.
Terminal device 101, terminal device 102, terminal device 103 can have display screen and supported web page browses
Various electronic equipments, including but not limited to smart mobile phone, tablet personal computer, pocket computer on knee and desktop computer etc..
Server 105 can be to provide the server of various services, such as user is set using terminal device 101, terminal
Standby 102, the shopping class website that terminal device 103 is browsed provides the back-stage management server (merely illustrative) supported.Manage on backstage
Reason server such as can ask the information query that receives analyze etc. processing at the data, and by result (such as
Target push information, product information -- merely illustrative) feed back to terminal device.
It should be noted that the data processing method that the embodiment of the present disclosure is provided can be performed by server 105, also may be used
With by being performed different from another server of server 105 or a server cluster.Correspondingly, for displayed web page
The device of coordinate click volume can be arranged in server 105, can also be set and another server beyond server 105
Or in a server cluster.
It should be understood that the number of the terminal device, network and server in Fig. 1 is only schematical.According to realizing need
Will, can have any number of terminal device, network and server.
Fig. 2 diagrammatically illustrates the flow chart of the data processing method according to the embodiment of the present disclosure.
As shown in Fig. 2 this method is included in operation S201~S203, wherein：
S201 is operated, obtains customer group data, customer group data represent targeted customer interested in destination object classification
Group, wherein, potential user group is by for identifying that user's usage mining model whether interested in destination object classification is known
Do not obtain.
S202 is operated, the user obtained in potential user group provides mould in the default object set for destination object classification
Under formula, the associating web pages of destination object classification are carried out operating caused operation data.
S203 is operated, usage mining model is verified based on operation data.
In accordance with an embodiment of the present disclosure, carried using usage mining model from substantial amounts of and random real application data
Implicit and/or people are taken to be not known whether potential user group data interested in destination object classification in advance.Wherein, mesh
Mark object type can be on a certain website business classification, it may for example comprise but be not limited on business site to daily necessities
Commodity classification, such as footwear, jacket, trousers.Or the business classification of financial management in the Internet product, such as stock type product, fund class product
And bond class product etc..The classification to different topics on question and answer class website is can also be, such as workplace, professional technique, philosophy art
Deng classification.It should be noted that the user in potential user group is user interested in destination object classification, but user is to mesh
Qualitative or quantitative point can be carried out to the operation data of destination object classification according to user by marking object type degree interested
Analyse the interest level of user.
In accordance with an embodiment of the present disclosure, the user in potential user group is in the default object set for destination object classification
Under offer pattern, the operation data to destination object classification can be produced.For example, when destination object classification is different moneys on certain website
During the shoes of formula, different activity patterns is used for the shoes of the different styles on the website, including but not limited to give a discount etc.
Promotion method, in such a scenario, when user has found that its shoes of interest is carrying out Discount Promotion, it may buy immediately
The shoes add shopping cart.By usage mining or the model of machine learning, user can be obtained destination object classification is produced
Raw operation data.Usage mining model can be verified according to practical operation data caused by destination object classification,
Judge whether the usage mining model is favourable to practical business.
In accordance with an embodiment of the present disclosure, because the user in potential user group can produce operand to destination object classification
It is user in the potential user group for excavating to obtain by usage mining model to destination object class operation according to, the operation data
Obtain, in this case, operation data caused by user's reality in potential user group is entered to usage mining model
Row checking, can solve at least in part algorithm model upgrade method traditional in the prior art be easily ensnared into experience instruct work as
In, the problem of uncertain factor is high, therefore the technology of the upgrade maintenance of effective guide data mining algorithm model can be realized
Effect.
In accordance with an embodiment of the present disclosure, obtaining potential user group interested in destination object classification includes：Obtain to mesh
Object type the first customer group interested is marked, wherein, the first customer group identifies to obtain by user's mining model；Obtain
User in first customer group carries out operating caused operation data for associating web pages, to determine to be used for represent the first customer group
In user to the score value of the interest level of destination object classification；And pattern is provided according to score value and default object, it is determined that
Potential user group.
By the model of data mining or machine learning, target interested in destination object classification can be got and used
Family group, but for different practical business activities, each practical business activity is required for the number of users of specific magnitude, because
This, can obtain the user data of specific magnitude according to the requirement of business activity.
In accordance with an embodiment of the present disclosure, can be obtained using usage mining Model Identification interested in destination object classification
First customer group, user in the first customer group of acquisition for associating web pages operated caused by operation data determine
User in first customer group is to the score value of the interest level of destination object classification, for example, user is carried out a little to a certain commodity
The operation data hit, browse or bought, score value of the user to the interest level of the commodity is determined for, it is determined that score value
Afterwards, pattern can be provided according to score value and default object, determines potential user group.Wherein, preset object provide pattern can with but
It is not limited to such as other practical businesses activity such as advertising campaign, drainage activity.The difference of pattern is provided according to default object, it is required
Number of users is also different, and target can be determined to the score value of destination object classification by providing pattern and each user according to default object
Customer group.
According to the embodiment of the present disclosure, the algorithm model that data mining or machine learning use can have supervision algorithm mould
Type and unsupervised algorithm model, for having the conventional algorithm of monitor model, such as logistic regression, Bayes's scheduling algorithm, normal conditions
Down finally can output probable value as score S.It can use to the score value of the interest level of the commodity to determine user
Logistic regression, Bayes's scheduling algorithm, these algorithms are by algorithm input feature vector collection+sample labeling, finally directly producing probability
Value is used as score S, obtains the potential score S of user, score is higher, and the interest level of user is higher.For unsupervised model by
In can not the score of input output model in itself, according to the embodiment of the present disclosure, following several method selection one of which can be used to obtain
.
(1) service priority order arrangement is carried out for participating in the feature of unsupervised model algorithm, then to clustering algorithm
Data set according to arrangement priority carry out feature ordering, then to the partial value carry out score value processing, simplest side
Method can directly assign the sequence number of sequence.
Wherein, the priority of feature is the measure to class of business emphasis, for example, the value point to user
Group, it is characterized in operation data of the user to destination object, such as order volume and pageview, the preferential pageview of order volume of user.Industry
Emphasis of being engaged in is different, and priority is also different, for example, drainage activity is compared with advertising campaign, pageview is in drainage activity
Priority is higher than pageview or purchase volume in advertising campaign.
(2) for the algorithm model of data intensity can be calculated, data intensity can be calculated to judge score
Just.Such as kmeans, we can calculate each point to the distance of cluster centre point.If apart from smaller, score is higher.Can
With the reciprocal directly as score S of distance.
Wherein, Kmeans algorithms are realized as follows
1) determine that k values, that is, data are finally divided into several clusters by data distribution or business bore, while take out at random
K data point of sample is as central point.
2) to all data points, it is calculated to the distance at k center, the data point is grouped into closest central point institute
It is being grouped.
3) according in the group average value a little as new central point.
4) judge the otherness of the central point and a upper central point, if difference is big, return to 2), 3) step progress
Continue iteration, if difference very little, stops iteration, the cluster centre is Optimal cluster centers.
5) K final cluster centre point is returned, while each point is encoded.
To the certain customers colony, inverted order arrangement is carried out according to user's score of step 2).Then top n user is selected to make
For the user in potential user group.
For practical business activity, because each practical business activity can all have cost budgeting and activity specification, so
And the single cost for limiting attraction user that the meeting of activity specification is strict, so the quantity of user group is limited to a certain extent
System.Assuming that practical business active user Population is N0, user's reference coefficient n (0 ＜ n ＜ 0.2), for active user amount
It is required that particularly severe scene, the Stringency of scene depends on business activity species, or artificial regulation, practical business activity
Value final user group's quantity N is N0/(1-n).It should be noted that obtained by machine learning or mining model algorithm
The potential user group M taken, normal conditions potential user group M are necessarily more than N.If potential user group M is less than practical business activity
User group quantity N, then directly using the potential user group M of acquisition as the targeted customer eventually for evaluation usage mining model
Group.
, can be with the case of practical business active user Population is more than 10,000 in addition, according to the embodiment of the present disclosure
N is set as 0.05, for that less than 10,000, can set n as 0.1-0.05, but n is less than 0.2 under normal circumstances, otherwise can shadow
Ring the precision of model evaluation.
In accordance with an embodiment of the present disclosure, due to considering different practical business activity species and user to different business pair
As the interest level of classification, to obtain the quantity of targeted customer and targeted customer, according to the targeted customer to destination object
Practical operation data caused by classification can be verified to usage mining model, more conform to actual conditions, reach accurate
Verify the whether effective effect of usage mining model.
Below with reference to Fig. 3 A and Fig. 3 B, the method shown in Fig. 2 is described further in conjunction with specific embodiments.
Fig. 3 A diagrammatically illustrate to be entered according to the acquisition user of the embodiment of the present disclosure to the associating web pages of destination object classification
The flow chart of operation data caused by row operation.
Wherein, in accordance with an embodiment of the present disclosure, preset object and pattern is provided includes the first default object and pattern and the are provided
Two default objects provide pattern, and the user obtained in potential user group provides in the default object set for destination object classification
Under pattern, the associating web pages of destination object classification are operated caused by operation data method as shown in Figure 3A, this method
Including operating S301 and S302, wherein：
S301 is operated, the user in potential user group is obtained under the first default object offer pattern, associating web pages is entered
First operand evidence caused by row operation.
S302 is operated, the user in potential user group is obtained under the second default object offer pattern, associating web pages is entered
Second operand evidence caused by row operation.
, can be by the user in potential user group respectively different pre- after the user data in obtaining potential user group
If under object offer pattern, the user obtained in potential user group carries out operating caused operation data to associating web pages.For example,
It can be promotion pattern and drainage pattern that default object, which provides pattern, obtain multiple users respectively in promotion pattern and drainage pattern
When to the operation data of clothes, such as click on, browse data, based on the operation datas under different default object offer patterns to user
Mining model is verified.It should be noted that default object, which provides pattern, includes but is not limited to the first default object offer mould
Formula and the second default object provide pattern, can also include the 3rd default object and provide pattern, and then enter according to associating web pages
First operand evidence, second operand evidence and the 3rd operation data are verified to usage mining model caused by row operation, are led to
Aforesaid way is crossed, considers caused operation data under various modes, can effectively instruct whether usage mining model is applicable
Usage mining under various modes.
Fig. 3 B diagrammatically illustrate another association for obtaining user to destination object classification according to the embodiment of the present disclosure
Webpage operated caused by operation data flow chart.
Wherein, in accordance with an embodiment of the present disclosure, preset object and pattern is provided includes the first default object and pattern and the are provided
Two default objects provide pattern, and the user obtained in potential user group provides in the default object set for destination object classification
Under pattern, the associating web pages of destination object classification are operated caused by operation data method as shown in Figure 3 B, this method
It is included in operation S401~S403, wherein：
S401 is operated, potential user group is split, to obtain first object customer group and the second potential user group.
S402 is operated, the user in first object customer group is obtained under the first default object offer pattern, to associating net
Page operated caused by the 3rd operation data.
S403 is operated, the user of the second potential user group is obtained under the second default object offer pattern, to associating web pages
4th operation data caused by being operated.
In accordance with an embodiment of the present disclosure, the potential user group of acquisition is split, obtains different potential user groups, when
When default object offer pattern includes first default object offer pattern and the second default object offer pattern, to different targets
Customer group, the user in first object customer group can be obtained under the first default object offer pattern, associating web pages are carried out
3rd operation data caused by operation, and the user of the second potential user group is obtained under the second default object offer pattern,
4th operation data caused by being operated to associating web pages.Wherein, the first default object provides pattern and the second default object
Offer pattern can be the different manners for same target, for example, default for same part commodity on certain website, first
It can be discounting activity that object, which provides pattern, and it can be that (attract clients access for drainage activity that the second default object, which provides pattern,
Amount).For another example for same part commodity on certain website, it can be discounting activity that the first default object, which provides pattern, and second is default
It can be the pattern sold by normal price that object, which provides pattern,.According to different potential user groups at different default pair
As the operation data under offer pattern is verified to usage mining model.
By disclosed embodiment, split at random by the potential user group for obtaining usage mining Model Identification,
Then Contrast on effect analysis movable under different business pattern is carried out respectively, and quantification of targets finally is carried out to the operation data of acquisition
Analysis, obtain the business support effect of the usage mining model.
In accordance with an embodiment of the present disclosure, potential user group is split, to obtain first object customer group and the second targeted customer
Group includes：The first pre-set user quantity under the first default object offer pattern is provided and provides pattern in the second default object
Under the second pre-set user quantity；Calculate the proportionality coefficient between the first pre-set user quantity and the second pre-set user quantity；With
User in potential user group is grouped by machine, to obtain multiple user groupings；And according to proportionality coefficient from multiple users
First object customer group and the second potential user group are determined in packet.
The mode for splitting potential user group has a lot, can split potential user group using random manner.According to this
Open embodiment, the pattern that can be provided according to different default objects determines the number of users under different mode, so that it is determined that not
With the ratio of number of users under pattern., can be with setting ratio in the case of practical business active user Population is more than 10,000
Coefficient is 0.05, can be using setting ratio coefficient as 0.1-0.05 for less than 10,000, but proportionality coefficient is small under normal circumstances
In 0.2, the precision of model evaluation otherwise can be influenceed.According to the scale parameter between different target customer group, using corresponding letter
It is several that potential user group is split.After different proportionality coefficients is obtained, the target that usage mining model obtains can be used
Family group is split, and obtains the potential user group of different grouping.
By the above-mentioned means, splitting potential user group using random manner, can obtain under different object offer patterns
Customer group, then after user operates under different object offer patterns to associating web pages, to the behaviour under different mode
It is compared as data, it is whether valuable that the user that accurate analysis usage mining model excavates to obtain can be reached.
In accordance with an embodiment of the present disclosure, carrying out checking to usage mining model based on operation data includes：Based on the 3rd behaviour
Make data and the 4th operation data is verified to usage mining model, the step includes：According to the 3rd operation data and first
Number of users in potential user group determine that under the first default object offer pattern user operated to associating web pages the
One operating rate；Number of users in the 4th operation data and first object customer group determines to provide mould in the second default object
The second operating rate that user is operated to associating web pages under formula；And user is dug according to the first operating rate and the second operating rate
Pick model is verified.
In accordance with an embodiment of the present disclosure, for example, the number of users in first object customer group is N1, first object customer group
In user's associating web pages are operated under the first default object offer pattern the 3rd operation data be x1, then first grasp
Make rate f1For x1/N1.Number of users in second potential user group is N2, the user in the second potential user group is default second
The 4th operation data operated under object offer pattern to associating web pages is x2, then the second operating rate f2For x2/N2.According to
First operating rate f1With the second operating rate f2Usage mining model is verified, can use F=(f1-f2)/f2, according to
The F values being calculated are verified to usage mining model.It should be noted that the effect of business activity needs to combine specific field
The service definition of scape.Such as boosting consumption, can be described well by order volume, for activity drainage,
The click volume of targeted customer can be very good to describe.Wherein, order volume and click volume can serve as user at Bu Tong default pair
As the operation data operated under offer pattern to associating web pages.
By the above-mentioned means, the animation effect under different business pattern can be carried out to quantify to divide according to different operating rates
Analysis, and then assess the quality of usage mining model.So as to instruct whether usage mining model needs to be upgraded, to support business
The needs of activity.
Fig. 4 diagrammatically illustrates the block diagram of data processing equipment in accordance with an embodiment of the present disclosure.
As shown in figure 4, data processing equipment 500 includes the first acquisition module 510, the second acquisition module 520 and checking mould
Block 530.
Second acquisition module 510 is used to obtain customer group data, and customer group data represent interested in destination object classification
Potential user group, wherein, potential user group is by the user whether interested in destination object classification for identifying user
Mining model identifies what is obtained.
The user that second acquisition module 520 is used to obtain in potential user group presets what is set for destination object classification
Under object offer pattern, the associating web pages of destination object classification are carried out operating caused operation data.
Authentication module 530 is used to verify usage mining model based on operation data.
In accordance with an embodiment of the present disclosure, because the user in potential user group can produce operand to destination object classification
It is user in the potential user group for excavating to obtain by usage mining model to destination object class operation according to, the operation data
Obtain, in this case, operation data caused by user's reality in potential user group is entered to usage mining model
Row checking, can solve at least in part algorithm model upgrade method traditional in the prior art be easily ensnared into experience instruct work as
In, the problem of uncertain factor is high, therefore the technology of the upgrade maintenance of effective guide data mining algorithm model can be realized
Effect.
In accordance with an embodiment of the present disclosure, the first acquisition module includes：First acquisition unit, for obtaining to destination object class
First customer group not interested, wherein, the first customer group identifies to obtain by user's mining model；Second obtains list
Member, carry out operating caused operation data for associating web pages for obtaining the user in the first customer group, to determine to be used for table
Show the score value of user in the first customer group to the interest level of destination object classification；And first determining unit, for root
Pattern is provided according to score value and default object, determines potential user group.
In accordance with an embodiment of the present disclosure, it is default including the first default object offer pattern and second to preset object offer pattern
Object provides pattern, and the second acquisition module includes：3rd acquiring unit, it is pre- first for obtaining the user in potential user group
If under object offer pattern, associating web pages are operated caused by first operand evidence；And the 4th acquiring unit, for obtaining
User in potential user group is taken under the second default object offer pattern, associating web pages are operated caused by second operate
Data.
In accordance with an embodiment of the present disclosure, it is default including the first default object offer pattern and second to preset object offer pattern
Object provides pattern, and the second acquisition module includes：Split cells, for splitting potential user group, to obtain first object user
Group and the second potential user group；5th acquiring unit, for obtaining the user in first object customer group in the first default object
Under offer pattern, associating web pages are operated caused by the 3rd operation data；And the 6th acquiring unit, for obtaining second
The user of potential user group under the second default object offer pattern, associating web pages are operated caused by the 4th operand
According to.
In accordance with an embodiment of the present disclosure, split cells includes：Subelement is obtained, is provided for obtaining in the first default object
The first pre-set user quantity under pattern and the second pre-set user quantity under the second default object offer pattern；It is single to calculate son
Member, for calculating the proportionality coefficient between the first pre-set user quantity and the second pre-set user quantity；Be grouped subelement, for
User in potential user group is grouped by machine, to obtain multiple user groupings；And first determination subelement, for basis
Proportionality coefficient determines first object customer group and the second potential user group from multiple user groupings.
In accordance with an embodiment of the present disclosure, authentication module includes：Authentication unit, for being grasped based on the 3rd operation data and the 4th
Make data to verify usage mining model, the authentication unit includes：Second determination subelement, for according to the 3rd operand
Determine that user is carried out to associating web pages under the first default object offer pattern according to the number of users in first object customer group
First operating rate of operation；3rd determination subelement, for the user in the 4th operation data and first object customer group
Quantity determines the second operating rate that user is operated to associating web pages under the second default object offer pattern；And checking
Unit, for being verified according to the first operating rate and the second operating rate to usage mining model.
It should be noted that data handling system part and data processing side in the embodiment of the present disclosure in the embodiment of the present disclosure
Method part is corresponding, and the description of data handling system part will not be repeated here with specific reference to data processing method part.
Fig. 5 diagrammatically illustrates the block diagram of the computer system of the data processing method using the embodiment of the present disclosure.
Fig. 5 diagrammatically illustrates the structural representation suitable for being used for the computer system 600 for realizing the embodiment of the present disclosure.
As shown in figure 5, computer system 600 includes CPU (CPU) 601, it can be read-only according to being stored in
Program in memory (ROM) 602 or be loaded into program in random access storage device (RAM) 603 from storage part 608 and
Perform various appropriate actions and processing.In RAM603, be also stored with computer system 600 operate required various programs and
Data.CPU 601 can realize the various operations according to the embodiment of the present disclosure by execute program instructions.
In accordance with an embodiment of the present disclosure, CPU 601, ROM 602 and RAM 603 can be connected with each other by bus 604.
Input/output interface (I/O interfaces 605) can also be connected to bus 604.I/O interfaces 605 are connected to lower component：Including key
The importation 606 of disk, mouse etc.；Including cathode-ray tube (CRT), liquid crystal display (LCD) etc. and loudspeaker etc.
Output par, c 607；Storage part 608 including hard disk etc.；And the network including LAN card, modem etc. connects
The communications portion 609 of mouth card.Communications portion 609 performs communication process via the network of such as internet.Driver 610 also according to
Need to be connected to I/O interfaces 605.Detachable media 611, such as disk, CD, magneto-optic disk, semiconductor memory etc., according to
Need to be arranged on driver 610, in order to which the computer program read from it is mounted into storage part as needed
608。
Especially, in accordance with an embodiment of the present disclosure, it may be implemented as computer above with reference to the process of flow chart description
Software program.For example, embodiment of the disclosure includes a kind of computer program product, it includes being carried on computer-readable medium
On computer program, the computer program include be used for execution flow chart shown in method program code.In such reality
To apply in example, the computer program can be downloaded and installed by communications portion 609 from network, and/or from detachable media
611 are mounted.When the computer program is performed by CPU 601, the above-mentioned function of being limited in the system of the disclosure is performed.
It should be noted that the computer-readable medium shown in the disclosure can be computer-readable signal media or meter
Calculation machine readable storage medium storing program for executing either the two any combination.Computer-readable recording medium for example can be --- but not
Be limited to --- electricity, magnetic, optical, electromagnetic, system, device or the device of infrared ray or semiconductor, or it is any more than combination.Meter
The more specifically example of calculation machine readable storage medium storing program for executing can include but is not limited to：Electrical connection with one or more wires, just
Take formula computer disk, hard disk, random access storage device (RAM), read-only storage (ROM), erasable type and may be programmed read-only storage
Device (EPROM or flash memory), optical fiber, portable compact disc read-only storage (CD-ROM), light storage device, magnetic memory device,
Or above-mentioned any appropriate combination.In the disclosure, computer-readable recording medium can any include or store journey
The tangible medium of sequence, the program can be commanded the either device use or in connection of execution system, device.And at this
In open, computer-readable signal media can be included in a base band or the data-signal as carrier wave part propagation,
Wherein carry computer-readable program code.The data-signal of this propagation can take various forms, including but unlimited
In electromagnetic signal, optical signal or above-mentioned any appropriate combination.Computer-readable signal media can also be that computer can
Any computer-readable medium beyond storage medium is read, the computer-readable medium, which can send, propagates or transmit, to be used for
By instruction execution system, device either device use or program in connection.Included on computer-readable medium
Program code can be transmitted with any appropriate medium, be included but is not limited to：Wirelessly, electric wire, optical cable, RF etc., or it is above-mentioned
Any appropriate combination.
Flow chart and block diagram in accompanying drawing, it is illustrated that according to the system of the various embodiments of the disclosure, method and computer journey
Architectural framework in the cards, function and the operation of sequence product.At this point, each square frame in flow chart or block diagram can generation
The part of one module of table, program segment or code, a part for above-mentioned module, program segment or code include one or more
For realizing the executable instruction of defined logic function.It should also be noted that some as replace realization in, institute in square frame
The function of mark can also be with different from the order marked in accompanying drawing generation.For example, two square frames succeedingly represented are actual
On can perform substantially in parallel, they can also be performed in the opposite order sometimes, and this is depending on involved function.Also
It is noted that the combination of each square frame and block diagram in block diagram or flow chart or the square frame in flow chart, can use and perform rule
Fixed function or the special hardware based system of operation are realized, or can use the group of specialized hardware and computer instruction
Close to realize.
Being described in unit involved in the embodiment of the present disclosure can be realized by way of software, can also be by hard
The mode of part is realized.Described unit can also be set within a processor, for example, can be described as：A kind of processor bag
Include transmitting element, acquiring unit, determining unit and first processing units.Wherein, the title of these units is under certain conditions simultaneously
The restriction in itself to the unit is not formed, for example, transmitting element is also described as " sending picture to the service end connected
Obtain the unit of request ".
As on the other hand, a kind of computer-readable recording medium is additionally provided in accordance with an embodiment of the present disclosure.Above-mentioned meter
Calculation machine readable storage medium storing program for executing carries one or more program, when one or more program is performed, it is possible to achieve root
According to the data processing method of the embodiment of the present disclosure, including：Customer group data are obtained, customer group data are represented to destination object classification
Potential user group interested, wherein, potential user group is by for identifying whether user is interested in destination object classification
Usage mining Model Identification obtain；The user in potential user group is obtained in default pair set for destination object classification
As under offer pattern, carrying out operating caused operation data to the associating web pages of destination object classification；And based on operation data
Usage mining model is verified.Obtaining potential user group interested in destination object classification includes：Obtain to target pair
As classification the first customer group interested, wherein, the first customer group identifies to obtain by user's mining model；Obtain first
User in customer group carries out operating caused operation data for associating web pages, to determine to be used for represent in the first customer group
Score value of the user to the interest level of destination object classification；And pattern is provided according to score value and default object, determine target
Customer group.Default object provides pattern and provides pattern, acquisition mesh including the first default object offer pattern and the second default object
The user in customer group is marked under the default object offer pattern set for destination object classification, to the pass of destination object classification
Networking page operated caused by operation data include：The user obtained in potential user group provides pattern in the first default object
Under, associating web pages are operated caused by first operand evidence；And the user obtained in potential user group is default second
Under object offer pattern, associating web pages are operated caused by second operand evidence.Default object, which provides pattern, includes first
Default object provides pattern and the second default object provides pattern, obtains the user in potential user group for destination object class
Under the default object offer pattern not set, the associating web pages of destination object classification are operated caused by operation data bag
Include：Potential user group is split, to obtain first object customer group and the second potential user group；Obtain in first object customer group
User under the first default object offer pattern, associating web pages are operated caused by the 3rd operation data；And obtain the
The user of two potential user groups under the second default object offer pattern, associating web pages are operated caused by the 4th operand
According to.Potential user group is split, is included with obtaining first object customer group and the second potential user group：Obtain in the first default object
The first pre-set user quantity under offer pattern and the second pre-set user quantity under the second default object offer pattern；Calculate
Proportionality coefficient between first pre-set user quantity and the second pre-set user quantity；The user in potential user group is carried out at random
Packet, to obtain multiple user groupings；And first object customer group is determined from multiple user groupings according to proportionality coefficient
With the second potential user group.Carrying out checking to usage mining model based on operation data includes：Based on the 3rd operation data and
Four operation datas verify that the step includes to usage mining model：According to the 3rd operation data and first object customer group
In number of users determine user is operated to associating web pages under the first default object offer pattern the first operating rate；Root
The user couple under the second default object offer pattern is determined according to the number of users in the 4th operation data and first object customer group
The second operating rate that associating web pages are operated；And usage mining model is carried out according to the first operating rate and the second operating rate
Checking.
Embodiment of the disclosure is described above.But the purpose that these embodiments are merely to illustrate that, and
It is not intended to limit the scope of the present disclosure.Although respectively describing each embodiment more than, but it is not intended that each reality
Use can not be advantageously combined by applying the measure in example.The scope of the present disclosure is defined by the appended claims and the equivalents thereof.Do not take off
From the scope of the present disclosure, those skilled in the art can make a variety of alternatives and modifications, and these alternatives and modifications should all fall at this
Within scope of disclosure.
Claims (13)
1. a kind of data processing method, including：
Customer group data are obtained, the customer group data represent potential user group interested in destination object classification, wherein, institute
It is by the usage mining Model Identification whether interested in the destination object classification for identifying user to state potential user group
Obtain；
The user in the potential user group is obtained under the default object offer pattern set for the destination object classification,
The associating web pages of the destination object classification are carried out operating caused operation data；And
The usage mining model is verified based on the operation data.
2. according to the method for claim 1, wherein, obtaining potential user group interested in destination object classification includes：
The first customer group interested in the destination object classification is obtained, wherein, first customer group is by the use
Family mining model identifies what is obtained；
The user obtained in first customer group carries out operating caused operation data for the associating web pages, to determine to use
In representing score value of the user in first customer group to the interest level of the destination object classification；And
Pattern is provided according to the score value and the default object, determines the potential user group.
3. according to the method for claim 1, wherein, the default object, which provides pattern, includes the first default object offer mould
Formula and the second default object provide pattern, and the user obtained in the potential user group is set for the destination object classification
Default object offer pattern under, the associating web pages of the destination object classification are operated caused by operation data include：
The user in the potential user group is obtained under the described first default object offer pattern, the associating web pages are carried out
First operand evidence caused by operation；And
The user in the potential user group is obtained under the described second default object offer pattern, the associating web pages are carried out
Second operand evidence caused by operation.
4. according to the method for claim 1, wherein, the default object, which provides pattern, includes the first default object offer mould
Formula and the second default object provide pattern, and the user obtained in the potential user group is set for the destination object classification
Default object offer pattern under, the associating web pages of the destination object classification are operated caused by operation data include：
The potential user group is split, to obtain first object customer group and the second potential user group；
The user in the first object customer group is obtained under the described first default object offer pattern, to the associating web pages
3rd operation data caused by being operated；And
The user of second potential user group is obtained under the described second default object offer pattern, the associating web pages are entered
4th operation data caused by row operation.
5. according to the method for claim 4, wherein, split the potential user group, with obtain first object customer group and
Second potential user group includes：
The first pre-set user quantity under the described first default object offer pattern is provided and carried in the described second default object
For the second pre-set user quantity under pattern；
Calculate the proportionality coefficient between the first pre-set user quantity and the second pre-set user quantity；
The user in the potential user group is grouped at random, to obtain multiple user groupings；And
The first object customer group and second mesh are determined from the multiple user grouping according to the proportionality coefficient
Mark customer group.
6. according to the method for claim 5, wherein, the usage mining model is verified based on the operation data
Including：The usage mining model is verified based on the 3rd operation data and the 4th operation data, the step
Including：
Number of users in the 3rd operation data and the first object customer group is determined at described first default pair
As the first operating rate that user is operated to the associating web pages under offer pattern；
Number of users in the 4th operation data and the first object customer group is determined at described second default pair
As the second operating rate that user is operated to the associating web pages under offer pattern；And
The usage mining model is verified according to first operating rate and second operating rate.
7. a kind of data handling system, including：
First acquisition module, for obtaining customer group data, the customer group data represent interested in destination object classification
Potential user group, wherein, the potential user group is by for identifying whether user is interested in the destination object classification
Usage mining Model Identification obtain；
Second acquisition module, for obtain the user in the potential user group set for the destination object classification it is pre-
If under object offer pattern, the associating web pages of the destination object classification are carried out operating caused operation data；And
Authentication module, for being verified based on the operation data to the usage mining model.
8. system according to claim 7, wherein, the first acquisition module includes：
First acquisition unit, for obtaining the first customer group interested in the destination object classification, wherein, described first uses
Family group is obtained by the usage mining Model Identification；
Second acquisition unit, operated for obtaining the user in first customer group for the associating web pages caused by
Operation data, to determine to be used for represent user in first customer group to the interest level of the destination object classification
Score value；And
First determining unit, for providing pattern according to the score value and the default object, determine the potential user group.
9. system according to claim 7, wherein, the default object, which provides pattern, includes the first default object offer mould
Formula and the second default object provide pattern, and second acquisition module includes：
3rd acquiring unit, for obtaining the user in the potential user group under the described first default object offer pattern,
First operand evidence caused by being operated to the associating web pages；And
4th acquiring unit, for obtaining the user in the potential user group under the described second default object offer pattern,
Second operand evidence caused by being operated to the associating web pages.
10. system according to claim 7, wherein, the default object, which provides pattern, includes the first default object offer
Pattern and the second default object provide pattern, and second acquisition module includes：
Split cells, for splitting the potential user group, to obtain first object customer group and the second potential user group；
5th acquiring unit, pattern is provided in the described first default object for obtaining the user in the first object customer group
Under, the associating web pages are operated caused by the 3rd operation data；And
6th acquiring unit, the user for obtaining second potential user group provide pattern in the described second default object
Under, the associating web pages are operated caused by the 4th operation data.
11. system according to claim 10, wherein, the split cells includes：
Subelement is obtained, for obtaining the first pre-set user quantity under the described first default object offer pattern and described
The second pre-set user quantity under second default object offer pattern；
Computation subunit, for calculating the ratio system between the first pre-set user quantity and the second pre-set user quantity
Number；
Subelement is grouped, for being at random grouped the user in the potential user group, to obtain multiple user groupings；With
And
First determination subelement, for determining the first object from the multiple user grouping according to the proportionality coefficient
Customer group and second potential user group.
12. system according to claim 11, wherein, the authentication module includes：Authentication unit, for based on described
Three operation datas and the 4th operation data verify that the authentication unit includes to the usage mining model：
Second determination subelement, it is true for the number of users in the 3rd operation data and the first object customer group
It is scheduled on the first operating rate that user is operated to the associating web pages under the described first default object offer pattern；
3rd determination subelement, it is true for the number of users in the 4th operation data and the first object customer group
It is scheduled on the second operating rate that user is operated to the associating web pages under the described second default object offer pattern；And
Subelement is verified, for being tested according to first operating rate and second operating rate the usage mining model
Card.
13. a kind of computer-readable recording medium, is stored thereon with executable instruction, the instruction makes processing when being executed by processor
Device realizes the data processing method any one of claim 1 to 6.
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