CN109471657A - Gray scale dissemination method, device, computer equipment and computer storage medium - Google Patents
Gray scale dissemination method, device, computer equipment and computer storage medium Download PDFInfo
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- CN109471657A CN109471657A CN201811044243.XA CN201811044243A CN109471657A CN 109471657 A CN109471657 A CN 109471657A CN 201811044243 A CN201811044243 A CN 201811044243A CN 109471657 A CN109471657 A CN 109471657A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
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- G06F8/70—Software maintenance or management
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Abstract
This application discloses a kind of gray scale dissemination method, device, computer equipment and computer storage mediums, it is related to using distribution technology field, more targeted user can be gone out according to grayscale version functional screening and carry out grayscale version publication, realize the purpose of gray scale grading product version.The described method includes: generating the user's set for carrying various feature tags by index of the big data counting user data under various dimensional characteristics；Grayscale version to be released and the corresponding version characteristic of the grayscale version are obtained, gray scale issue rules are determined according to the corresponding version characteristic of the grayscale version；The user's set for meeting gray scale issue rules is filtered out from the user's set for carrying various feature tags；To it is described filter out meet default issue rules user gather carry out grayscale version publication.
Description
Technical field
The present invention relates to apply distribution technology field, particularly with regard to gray scale dissemination method, device, computer equipment and
Computer storage medium.
Background technique
Gray scale publication refers to that between black and white, a kind of published method that can be seamlessly transitted, it can be formal in product
Before publication, user is allowed to participate in product test, reinforcement is interacted with user's, and obtains the suggestion feedback of user in time, into
And product function is improved, Improving The Quality of Products.
Currently, most of gray scale distribution platforms can dispose two using ring during carrying out gray scale publication in the market
Border, such as two application environments of A, B, A is as production environment, and B is as gray scale environment, in carrying out gray scale issuing process, need by
User under build environment is gradually switched to gray scale environment, thus the new function of fast verification product.Under normal conditions, it will use
During family is switched to gray scale environment from production environment, both for white list user or by flow randomly select user into
The publication of row gray scale.However, demand of the different user to application function is different, such as the user that often manages money matters is to financing class application
The demand of function is higher, and demand of the User to study class application function is higher, if only for white list user or
Person randomly selects user by flow and is issued at random, and the purpose of gray scale par version is often not achieved, so that gray scale publication
User experience is poor.
Summary of the invention
The embodiment of the invention provides gray scale dissemination method, device, computer equipment and computer storage mediums, solve
It is unable to reach the purpose of gray scale evaluation product version in the related technology.
According to a first aspect of the embodiments of the present invention, a kind of gray scale dissemination method is provided, which comprises
By index of the big data counting user data under various dimensional characteristics, the use for carrying various feature tags is generated
Family set；
Grayscale version to be released and the corresponding version characteristic of the grayscale version are obtained, according to the grayscale version pair
The version characteristic answered determines gray scale issue rules；
The user's collection for meeting the gray scale issue rules is filtered out from the user's set for carrying various feature tags
It closes；
To it is described filter out meet default issue rules user gather carry out grayscale version publication.
Further, the index by big data counting user data under various dimensional characteristics is generated and is carried respectively
The user of kind feature tag, which gathers, includes:
Gone out by big data counting user data abstraction and is used to describe index of the user data under various dimensional characteristics, structure
Build the user's portrait for carrying various feature tags；
The user's portrait for carrying same characteristic features label is sorted out, various features label respectively corresponding use is generated
Family set.
Further, go out to be used to describe user data in various dimensions by big data counting user data abstraction described
Index under feature, before building carries user's portrait of various feature tags, the method also includes:
The data for describing user are grabbed from multiple data sources；
The data for being used to describe user are divided into multiple reliability ratings according to the corresponding confidence level of every kind of data, often
The corresponding weighted value of a reliability rating；
Weighted value is set for each reliability rating, the data for describing user are weighted according to the weighted value and are asked
And processing, obtain user data.
Further, acquisition grayscale version to be released and the corresponding version characteristic of the grayscale version, according to
The corresponding version characteristic of the grayscale version determines that gray scale issue rules include:
Grayscale version to be released and the corresponding version characteristic of the grayscale version are obtained, according to the grayscale version pair
The version feature answered is determined for compliance at least one feature tag of grayscale version publication；
Logical operation is carried out at least one described feature tag, generates gray scale issue rules.
Further, the logic of propositions rule for meeting grayscale version publication are provided between at least one described feature tag
Then, described that logical operation is carried out at least one described feature tag, it generates gray scale issue rules and specifically includes:
Logical operation is carried out at least one described feature tag according to the logic of propositions rule between the feature tag,
Generate gray scale issue rules.
Further, described filter out from the user's set for carrying various feature tags meets gray scale issue rules
User set include:
Filtered out respectively from the user's set for carrying various feature tags meet that the grayscale version issues to
Multiple users set of a few feature tag；
According to the logic of propositions rule between the feature tag to described at least one spy for meeting grayscale version publication
The multiple users for levying label, which gather, carries out logical operation, obtains the user's set for meeting the gray scale issue rules.
Further, it is described to it is described filter out meet default issue rules user gather carry out grayscale version publication
Later, the method also includes:
The feedback quantity that grayscale version issues corresponding user's set is received, gray scale publication rule are adjusted according to the feedback quantity
Then.
According to a second aspect of the embodiments of the present invention, a kind of gray scale distributing device is provided, described device includes:
Statistic unit, for by big data analysis user data, generating the user's set for carrying various feature tags；
Acquiring unit, for obtaining grayscale version to be released and the corresponding version characteristic of the grayscale version, according to
The corresponding version characteristic of the grayscale version determines gray scale issue rules；
Screening unit meets gray scale issue rules for filtering out from the user's set for carrying various feature tags
User set；
Release unit, for it is described filter out meet default issue rules user gather carry out grayscale version publication.
Further, the statistic unit includes:
Module is constructed, it is special in various dimensions for going out to be used to describe user data by big data counting user data abstraction
Index under sign, building carry user's portrait of various feature tags；
It is each to generate various features label for sorting out to the user's portrait for carrying same characteristic features label for classifying module
Gather from corresponding user.
Further, the statistic unit further include:
Handling module, for going out to be used to describe user data various by big data counting user data abstraction described
Index under dimensional characteristics, before building carries user's portrait of various feature tags, crawl is for retouching from multiple data sources
State the data of user；
Division module is more for being divided into the data for being used to describe user according to the corresponding confidence level of every kind of data
A reliability rating, the corresponding weighted value of each reliability rating；
Processing module, for weighted value to be arranged for each reliability rating, according to the weighted value to for describing user's
Data are weighted summation process, obtain user data.
Further, the acquiring unit includes:
Determining module, for obtaining grayscale version to be released and the corresponding version characteristic of the grayscale version, according to
The corresponding version feature of the grayscale version, is determined for compliance at least one feature tag of grayscale version publication；
Generation module generates gray scale issue rules for carrying out logical operation at least one described feature tag.
Further, the logic of propositions rule for meeting grayscale version publication are provided between at least one described feature tag
Then,
Generation module, specifically for according to the logic of propositions rule between the feature tag at least one described feature
Label carries out logical operation, generates gray scale issue rules.
Further, the screening unit includes:
Screening module meets grayscale version for filtering out respectively from the user's set for carrying various feature tags
Multiple users set of at least one feature tag of publication；
Operation module, for meeting grayscale version publication to described according to the logic of propositions rule between the feature tag
Multiple users of at least one feature tag gather and carry out logical operation, obtain meeting user's set of gray scale issue rules.
Further, described device further include:
Adjustment unit, for it is described to it is described filter out meet default issue rules user gather carry out grayscale version
After publication, the feedback quantity that grayscale version issues corresponding user's set is received, gray scale publication is adjusted according to the feedback quantity
Rule.
According to a third aspect of the embodiments of the present invention, a kind of computer equipment, including memory and processor are provided, it is described
Computer program is stored in memory, the processor realizes above-mentioned gray scale dissemination method when executing the computer program
Step.
According to a fourth aspect of the embodiments of the present invention, a kind of computer storage medium is provided, computer journey is stored thereon with
The step of sequence, the computer program realizes above-mentioned gray scale dissemination method when being executed by processor.
Through the invention, it is various to generate carrying for the index according to big data counting user data under various dimensional characteristics
The user of feature tag gathers, and determines gray scale issue rules according to the corresponding version characteristic of grayscale version, further each from carrying
The user's set for meeting gray scale issue rules is filtered out in user's set of kind feature tag, due to meeting gray scale issue rules
User's collection is combined into the user's set filtered out for the corresponding version characteristic of grayscale version and grayscale version to be released, more
It is bonded the application demand of grayscale version, further carries out the user's set for meeting gray scale issue rules as gray scale issue object
Grayscale version publication is realized the purpose of gray scale evaluation product version, is improved so that there is more applicable user to gather for gray scale publication
The user experience of gray scale publication.
Detailed description of the invention
The drawings described herein are used to provide a further understanding of the present invention, constitutes part of this application, this hair
Bright illustrative embodiments and their description are used to explain the present invention, and are not constituted improper limitations of the present invention.In the accompanying drawings:
Fig. 1 is a kind of flow chart of gray scale dissemination method according to an embodiment of the present invention；
Fig. 2 is the flow chart of another gray scale dissemination method according to an embodiment of the present invention；
Fig. 3 is a kind of structural block diagram of gray scale distributing device according to an embodiment of the present invention；
Fig. 4 is the structural block diagram of another gray scale distributing device according to an embodiment of the present invention；
Fig. 5 is the block diagram of gray scale distributing device 400 according to an embodiment of the present invention.
Specific embodiment
Hereinafter, the present invention will be described in detail with reference to the accompanying drawings and in combination with Examples.It should be noted that not conflicting
In the case of, the features in the embodiments and the embodiments of the present application can be combined with each other.
A kind of gray scale dissemination method is provided in the present embodiment, and Fig. 1 is a kind of gray scale hair according to an embodiment of the present invention
The flow chart of cloth method, as shown in Figure 1, this method comprises the following steps:
Step S101 is generated by index of the big data counting user data under various dimensional characteristics and is carried various spies
The user's set for levying label.
Wherein, user data is to be grabbed from multiple data sources for describing the data of user, can specifically include dynamic
Information data and static information data, static information data are the relatively stable attribute information of user, such as address name, property
Not, the customer attribute informations such as occupation, multidate information data are the continually changing behavioural information of user, as user opens webpage, clear
Look at microblogging, the purchase user behaviors information such as commodity.
Since record has information overall picture of the user under various dimensional characteristics in user data, pass through big data counting user
Index of the data under various dimensional characteristics, using the index under every kind of dimensional characteristics as a feature tag, as age label,
Gender label buys product number label, to fancy grade label of certain movement etc., available various feature tags.
Every kind of feature tag defines understanding and describes the angle of user, and the user with same characteristic features label is in spy
Determine attribute having the same or behavior in dimension, such as user A and user B age attribute having the same, user A and user
B bought identical books etc..The embodiment of the present invention is carried by summarizing the user with same characteristic features label
Respectively corresponding user gathers various feature tags, the user with same alike result or behavior can be gathered together,
In order to analyze the user with same alike result or behavior.
Step S102 obtains grayscale version to be released and the corresponding version characteristic of the grayscale version, according to described
The corresponding version characteristic of grayscale version determines gray scale issue rules.
Wherein, grayscale version to be released has optimization characteristics compared to original version, for example, having in data reality excellent
Change characteristic or there are optimization characteristics in data processing speed, which is the corresponding version characteristic of grayscale version.
Likewise, gray scale issue rules are the requirement for meeting grayscale version characteristic, such as grayscale version is to payment function
Optimization, then gray scale issue rules are the requirement for meeting payment function characteristic, and grayscale version is the optimization of purchase condition, then gray scale
Issue rules are the requirement for buying condition characteristic, here to gray scale issue rules without limiting.
Step S103 is filtered out from the user's set for carrying various feature tags and is met the gray scale issue rules
User set.
Gray scale publication is internet product in order to avoid strategy used by system upgrade risk, and each system upgrade is always
With risk, the compatible risk of new and old edition and user's use habit sudden change and the risk etc. for causing customer churn are led to
Gray scale publication is crossed in advance gradually to expand certain customers if user does not have feedback opinion to grayscale version using grayscale version
The user scope of grayscale version, until all users are switched to grayscale version, if user has feedback opinion to grayscale version,
Then grayscale version is adjusted according to field feedback, to guarantee the normal operation of grayscale version.
Both for blacklist, perhaps white list user carries out gray scale publication blacklist or white list for existing gray scale publication
User be usually intra-company research staff perhaps by the user that flow is randomly selected and blacklist or white list user are opposite
Than more random, it is not necessarily suitable grayscale version, if carrying out gray scale publication to blacklist or white list user, it is likely that
Less than feedback information required for grayscale version, the purpose of gray scale evaluation product version is also just lost in this way.For the present invention
Embodiment, gray scale issue rules are the rule for grayscale version featured configuration, and the user for meeting gray scale issue rules collects contract
Sample is also applied for grayscale version characteristic, further filters out from the user's set for carrying various feature tags and meets gray scale publication
User's set of rule, gathers for the user for meeting gray scale issue rules and carries out gray scale publication.
Step S104, to it is described filter out meet default issue rules user gather carry out grayscale version publication.
For the embodiment of the present invention, the user's set black name compared to the prior art for meeting default issue rules is filtered out
List or white list user are more suitable for grayscale version, gather for the user for meeting gray scale issue rules and carry out grayscale version hair
Cloth enables to gray scale publication to be matched to specific user crowd, realizes the purpose of gray scale evaluation product version.
Through the invention, it is various to generate carrying for the index according to big data counting user data under various dimensional characteristics
The user of feature tag gathers, and determines gray scale issue rules according to the corresponding version characteristic of grayscale version, further each from carrying
The user's set for meeting gray scale issue rules is filtered out in user's set of kind feature tag, due to meeting gray scale issue rules
User's collection is combined into the user's set filtered out for the corresponding version characteristic of grayscale version and grayscale version to be released, more
It is bonded the application demand of grayscale version, further carries out the user's set for meeting gray scale issue rules as gray scale issue object
Grayscale version publication is realized the purpose of gray scale evaluation product version, is improved so that there is more applicable user to gather for gray scale publication
The user experience of gray scale publication.
Fig. 2 is the flow chart of another gray scale dissemination method according to an embodiment of the present invention, as shown in Fig. 2, this method packet
Include following steps:
Step S201 grabs the data for describing user from multiple data sources.
Wherein, multiple data sources can be daily record data, the user information data etc. crawled from website, for example, from sub- horse
The daily record data and user information data that inferior website crawls, the daily record data can specifically include for describing user in website
The data of operation behavior, such as user browse webpage behavior, user's payment behavior, and user information data can specifically include description
The data generated when user's registration website, such as User ID, user name, gender user basic information.
It should be noted that the data for describing user grabbed here are the bases of comprehensive understanding user, and
The user data grabbed from different data sources has different emphasis, for example, media or reading class website based on content,
User is often grabbed to the data of the interest characteristics of browsing content, such as cuisines class, house property class, financing class, class is to do shopping
Main electric business website often grabs the data of user's online shopping interest and consuming capacity index, and the data of the crawl of centering here are not
It is defined, can specifically be determined according to grayscale version institute's application field, such as grayscale version correspond to shopping class application, it can be with
It grabs emphatically for describing the data of user in all kinds of shopping websites, grayscale version corresponds to financing class application, can grab emphatically
It takes in all kinds of financing classes website for describing the data of user.
The data for being used to describe user are divided into multiple letters according to the corresponding confidence level of every kind of data by step S202
Appoint grade, the corresponding weighted value of each reliability rating.
Due in order to improve the accuracy of data, from each number during grabbing the data for describing user
It is grabbed according to source, and the data reliability that each data source grabs is different, is not accurately, if directly using a certain
The data of data source crawl, then may influence the accuracy of user data, here previously according to the corresponding confidence level of every kind of data
The data for being used to describe user are divided into multiple reliability ratings, and the corresponding weighted value of each reliability rating, grade are got over
Height illustrates that the confidence level of the data is higher, and corresponding weighted value is bigger.
Weighted value is arranged for each reliability rating, according to the weighted value to the data for describing user in step S203
It is weighted summation process, obtains user data.
The data for being used to describe user can be specifically divided into the data of multiple reliability ratings, each reliability rating is corresponding
Weighted value agreement be generally a probability value between 0-1, high priority data higher for reliability rating as user data,
Data lower for reliability rating can be ignored, and can be weighted ask to data according to the weight label of setting here
And processing, user data is obtained, the higher data of reliability rating can also be directlyed adopt certainly as user data, using real-time
The lower data of reliability rating are as user data after update, here without limiting.
It should be noted that usual situation static information data are the data filled in of user, corresponding confidence level often compared with
Height, can be directly as user data, and multidate information data are that user adds up behavior and the data that generate, can with the time or
User behavior changes, and corresponding confidence level is often lower, is used as user data after needing real-time update.
Step S204 goes out to be used to describe user data under various dimensional characteristics by big data counting user data abstraction
Index, building carries user's portrait of various feature tags.
Wherein, user's portrait refers to according to information such as the attribute of user, user preference, living habit, user behaviors and takes out
As the labeling user model come out.Popular theory is exactly to label to user, and features tab is by Users'Data Analysis
And the highly refined signature identification come.It can use some high level overviews, readily comprehensible feature by features tab to retouch
User is stated, people can be allowed to be easier to understand user, and can be convenient computer disposal.
It should be noted that every kind of feature tag defines understanding and describes the angle of user, due to user data
It is corresponding with different data sources, so that the mode for obtaining feature tag corresponding label content is different, static information data
The corresponding label substance of lower feature tag is often fixed, such as gender, age, phone, the number that can be filled in by user
According to obtaining, if user does not fill in can judge probability by establishing model, feature tag is corresponding under multidate information data
Label substance is often variation, for example, buying the number of certain commodity, maximum consumption or Brang Preference etc., can pass through use
Family row characteristic is calculated.
The corresponding label substance of feature tag may indicate that user is interesting to the features tab, inclined under multidate information data
Good, demand etc., can be every kind of feature mark to further describe the corresponding label substance of feature tag under multidate information data
Weight is arranged in corresponding label substance in label, for example, the weight of user A preference red wine is 0.7, user A is interested to basketball
Weight is 0.2 etc..
Step S205 sorts out the user's portrait for carrying same characteristic features label, generates various features label and respectively divide
Not corresponding user's set.
It is the data model that user is described from different dimensions due to user's portrait, by the use that will carry identical features tab
Family portrait is sorted out, and various features label respectively corresponding user's set is generated, can be by the use with identical dimensional characteristic
Family is collected, for example, the user with same age features tab gathers, the user with identical living habit features tab
Set, user's set with identical consumer behavior etc..
It should be noted that respectively corresponding user's set can be directed to single features to various features label here
The identical user's set of label, for example, it is identical only for age characteristics label, it is identical only for sex character label, it uses
Family set can also be for the identical user's set of multiple label characteristics, for example, for age characteristics label and sex character mark
Sign it is identical, specific aim distinguishing label with hobby label it is identical, here without specifically limiting.
Step S206 obtains grayscale version to be released and the corresponding version characteristic of the grayscale version, according to described
The corresponding version feature of grayscale version is determined for compliance at least one feature tag of grayscale version publication.
Since grayscale version has certain optimization characteristics compared to original version, which is equivalent to version spy
Property, it can be embodied on multiple features tabs, such as grayscale version has done certain optimization in the push function of purchase commodity, so that
Push ranking more meets user demand, then the features tab for meeting grayscale version publication includes at least the characteristic mark of purchase commodity
Label can also meet the features tab of grayscale version publication for the user property that purchase commodity are applicable in, addition certainly, such as suitable
The female user for being 20-30 for the age.
It should be noted that the corresponding version feature of grayscale version can be embodied on multiple features tabs, if met
There is denominator between multiple features tabs of grayscale version publication, then can choose more specific features tab, for example, branch
Paying commodity function and paying between certain a kind of commodity function has denominator, then selects the characteristic mark for paying certain class I goods
Label.
Step S207 carries out logical operation at least one described feature tag, generates gray scale issue rules.
Wherein, logical operation can be the logical operations such as intersection, union, non-, and meet the characteristic mark of grayscale version publication
The logic of propositions rule for meeting grayscale version publication is provided between label, as the corresponding optimization characteristics of grayscale version are suitable for 30 years old
Above female user, then the logic of propositions rule for meeting grayscale version publication are to need to gender woman features tab and age
30 features tab takes intersection, if the corresponding optimization characteristics of grayscale version are applicable in features tab and the purchase of hobby sport certainly
The features tab of sports goods is bought, then the logic of propositions rule for meeting grayscale version publication is the characteristic mark needed to hobby sport
The features tab of label and purchase sports goods takes union, further according to the logic of propositions rule between features tab at least
One features tab carries out logical operation, generates gray scale issue rules.
The embodiment of the present invention can be generated and be more in line with by carrying out logical operation at least one feature tag
The gray scale issue rules of the optimization characteristics of grayscale version.
Step S208 is filtered out from the various features label respectively corresponding user's set and is met the gray scale
The user of issue rules gathers.
It specifically can be from a variety of spies since each features tab is corresponding with user's set for the embodiment of the present invention
Sign label respectively filters out at least one feature tag for meeting grayscale version publication in corresponding user set respectively
Multiple user's set, then according to the logic of propositions rule between feature tag at least one spy for meeting grayscale version publication
The multiple users for levying label, which gather, carries out logical operation, obtains the user's set for meeting gray scale issue rules.
Step S209, to it is described filter out meet default issue rules user gather carry out grayscale version publication.
It should be noted that due to gray scale issue corresponding number of users be it is gradually widened, gray scale publication initial stage simultaneously
It is non-be directly to it is all filter out meet default issue rules user gather carry out grayscale version publication, but be arranged to part
The user's set progress grayscale version publication for meeting default issue rules is filtered out, as user is to the feedback information of grayscale version
Continuous adjustment grayscale version and the user's set for gradually expanding grayscale version, until meeting default publication to all filter out out
The user of rule, which gathers, carries out grayscale version publication, if grayscale version feedback effects are relatively good certainly, grayscale version is issued not
It can be limited to comply with user's set of default issue rules, be eventually gradually expanded to all user's set.
Step S210 receives the feedback quantity that grayscale version issues corresponding user's set, is adjusted according to the feedback quantity
Gray scale issue rules.
Since in gray scale issuing process, user has corresponding feedback information to grayscale version, such as think grayscale version also
There are which shortage places, or think that grayscale version effect is relatively good etc., can specifically set in grayscale version issuing process
Grayscale version evaluation plate is set, such as perhaps message form is obtained by receiving marking or the message of user for setting marking
Grayscale version corresponds to the feedback quantity of user's set.
For the embodiment of the present invention, if grayscale version feedback quantity is more, illustrate that user is concerned about journey to grayscale version
Degree is higher, and the purpose of gray scale evaluation product version may be implemented in the corresponding user's set of gray scale issue rules, without sending out gray scale
Cloth rule is excessively adjusted, if grayscale version feeds back negligible amounts, illustrates that user is not relevant for grayscale version, gray scale
The corresponding user's set of issue rules can not achieve the purpose of gray scale evaluation product version, further according to field feedback
Adjustment has damaged gray scale issue rules, so that gray scale issue rules can filter out the user's collection for more meeting grayscale version characteristic
It closes.
Through the embodiment of the present invention, the index according to big data counting user data under various dimensional characteristics, generation are taken
With various feature tags user set, gray scale issue rules are determined according to the corresponding version characteristic of grayscale version, further from
The user's set for filtering out in user's set of various feature tags and meeting gray scale issue rules is carried, due to meeting gray scale publication
User's collection of rule is combined into the user's collection filtered out for the corresponding version characteristic of grayscale version and grayscale version to be released
It closes, is more bonded the application demand of grayscale version, further issue the user's set for meeting gray scale issue rules as gray scale
Object carries out grayscale version publication, so that there is more applicable user to gather for gray scale publication, realizes gray scale evaluation product version
Purpose improves the user experience of gray scale publication.
Fig. 3 is a kind of structural block diagram of gray scale distributing device according to an embodiment of the present invention.Referring to Fig. 3, which includes
Statistic unit 31, acquiring unit 32, screening unit 3,3 and release unit 34.
Statistic unit 31 can be used for the index by big data counting user data under various dimensional characteristics, generate
Carry user's set of various feature tags；
Acquiring unit 32, can be used for obtaining grayscale version to be released and the corresponding version of the grayscale version is special
Property, gray scale issue rules are determined according to the corresponding version characteristic of the grayscale version；
Screening unit 33 can be used for from the user's set for carrying various feature tags filtering out meeting gray scale hair
The user of cloth rule gathers；
Release unit 34, can be used for it is described filter out meet default issue rules user gather carry out grayscale version
Publication.
Through the embodiment of the present invention, the index according to big data counting user data under various dimensional characteristics, generation are taken
With various feature tags user set, gray scale issue rules are determined according to the corresponding version characteristic of grayscale version, further from
The user's set for filtering out in user's set of various feature tags and meeting gray scale issue rules is carried, due to meeting gray scale publication
User's collection of rule is combined into the user's collection filtered out for the corresponding version characteristic of grayscale version and grayscale version to be released
It closes, is more bonded the application demand of grayscale version, further issue the user's set for meeting gray scale issue rules as gray scale
Object carries out grayscale version publication, so that there is more applicable user to gather for gray scale publication, realizes gray scale evaluation product version
Purpose improves the user experience of gray scale publication.
As the further explanation of gray scale distributing device shown in Fig. 3, Fig. 4 is another gray scale according to embodiments of the present invention
The structural schematic diagram of distributing device, as shown in figure 4, the device further include:
Adjustment unit 35, can be used for it is described to it is described filter out meet default issue rules user gather carry out ash
It spends after version publication, receives the feedback quantity that grayscale version issues corresponding user's set, ash is adjusted according to the feedback quantity
Spend issue rules.
Further, the statistic unit 31 includes:
Module 311 is constructed, can be used for taking out by big data analysis user data various for describing user data
The feature tag of dimension, building carry user's portrait of various feature tags；
Classifying module 312 can be used for sorting out the user's portrait for carrying same characteristic features label, it is various to generate carrying
The user of feature tag gathers.
Further, the statistic unit 31 further include:
Handling module 313 can be used for taking out by big data analysis user data for describing number of users described
According to the feature tag of various dimensions, before building carries user's portrait of various feature tags, it is used for from the crawl of various data sources
The data of user are described；
Division module 314 can be used for the data for being used to describe user according to the corresponding confidence level of every kind of data
It is divided into multiple reliability ratings, the corresponding weighted value of each reliability rating；
Processing module 315 can be used for that weighted value is arranged for each reliability rating, according to the weighted value to for describing
The data of user are weighted summation process, obtain user data.
Further, the acquiring unit 32 includes:
Determining module 321, can be used for obtaining grayscale version to be released and the corresponding version of the grayscale version is special
Property, according to the corresponding version feature of the grayscale version, it is determined for compliance at least one feature tag of grayscale version publication；
Generation module 322 can be used for carrying out logical operation at least one described feature tag, generate gray scale publication rule
Then；
Further, the logic of propositions rule for meeting grayscale version publication are provided between at least one described feature tag
Then,
The generation module 322 specifically can be used for according to the logic of propositions rule between the feature tag to described
At least one feature tag carries out logical operation, generates gray scale issue rules.
Further, the screening unit 33 includes:
Screening module 331 can be used for from the user's set for carrying various feature tags filtering out respectively meeting
Multiple users set of at least one feature tag of grayscale version publication；
Operation module 332 can be used for meeting gray scale to described according to the logic of propositions rule between the feature tag
Multiple users of at least one feature tag of version publication, which gather, carries out logical operation, obtains the use for meeting gray scale issue rules
Family set.
Fig. 5 is a kind of block diagram of gray scale distributing device 400 shown according to an exemplary embodiment.For example, device 400 can
To be mobile phone, computer, digital broadcasting terminal, messaging device, game console, tablet device, Medical Devices are good for
Body equipment, personal digital assistant etc..
Referring to Fig. 5, device 400 may include following one or more components: processing component 402, memory 404, power supply
Component 406, multimedia component 408, audio component 410, the interface 412 of I/O (Input/Output, input/output), sensor
Component 414 and communication component 416.
The integrated operation of the usual control device 400 of processing component 402, such as with display, telephone call, data communication, phase
Machine operation and record operate associated operation.Processing component 402 may include that one or more processors 420 refer to execute
It enables, to perform all or part of the steps of the methods described above.In addition, processing component 402 may include one or more modules, just
Interaction between processing component 402 and other assemblies.For example, processing component 402 may include multi-media module, it is more to facilitate
Interaction between media component 408 and processing component 402.
Memory 404 is configured as storing various types of data to support the operation in device 400.These data are shown
Example includes the instruction of any application or method for operating on device 400, contact data, and telephone book data disappears
Breath, picture, video etc..Memory 404 can be by any kind of volatibility or non-volatile memory device or their group
It closes and realizes, such as SRAM (Static Random Access Memory, static random access memory), EEPROM
(Electrically-Erasable Programmable Read-Only Memory, the read-only storage of electrically erasable
Device), EPROM (Erasable Programmable Read Only Memory, Erasable Programmable Read Only Memory EPROM), PROM
(Programmable Read-Only Memory, programmable read only memory), and ROM (Read-Only Memory, it is read-only to deposit
Reservoir), magnetic memory, flash memory, disk or CD.
Power supply module 406 provides electric power for the various assemblies of device 400.Power supply module 406 may include power management system
System, one or more power supplys and other with for device 400 generate, manage, and distribute the associated component of electric power.
Multimedia component 408 includes the screen of one output interface of offer between described device 400 and user.One
In a little embodiments, screen may include LCD (Liquid Crystal Display, liquid crystal display) and TP (Touch
Panel, touch panel).If screen includes touch panel, screen may be implemented as touch screen, from the user to receive
Input signal.Touch panel includes one or more touch sensors to sense the gesture on touch, slide, and touch panel.Institute
The boundary of a touch or slide action can not only be sensed by stating touch sensor, but also be detected and the touch or slide phase
The duration and pressure of pass.In some embodiments, multimedia component 408 includes that a front camera and/or postposition are taken the photograph
As head.When device 400 is in operation mode, such as in a shooting mode or a video mode, front camera and/or rear camera can
With the multi-medium data outside reception.Each front camera and rear camera can be a fixed optical lens system
Or there are focusing and optical zoom capabilities.
Audio component 410 is configured as output and/or input audio signal.For example, audio component 410 includes a MIC
(Microphone, microphone), when device 400 is in operation mode, such as call mode, recording mode, and voice recognition mode
When, microphone is configured as receiving external audio signal.The received audio signal can be further stored in memory 404
Or it is sent via communication component 416.In some embodiments, audio component 410 further includes a loudspeaker, for exporting audio
Signal.
I/O interface 412 provides interface between processing component 402 and peripheral interface module, and above-mentioned peripheral interface module can
To be keyboard, click wheel, button etc..These buttons may include, but are not limited to: home button, volume button, start button and lock
Determine button.
Sensor module 414 includes one or more sensors, and the state for providing various aspects for device 400 is commented
Estimate.For example, sensor module 414 can detecte the state that opens/closes of equipment 400, the relative positioning of component, such as component
For the display and keypad of device 400, sensor module 414 can be with the position of 400 1 components of detection device 400 or device
Set change, the existence or non-existence that user contacts with device 400, the temperature in 400 orientation of device or acceleration/deceleration and device 400
Variation.Sensor module 414 may include proximity sensor, be configured to detect without any physical contact near
The presence of object.Sensor module 414 can also include optical sensor, such as CMOS (Complementary Metal Oxide
Semiconductor, complementary metal oxide) or CCD (Charge-coupled Device, charge coupled cell) image biography
Sensor, for being used in imaging applications.In some embodiments, which can also include acceleration sensing
Device, gyro sensor, Magnetic Sensor, pressure sensor or temperature sensor.
Communication component 416 is configured to facilitate the communication of wired or wireless way between device 400 and other equipment.Device
400 can access the wireless network based on communication standard, such as WiFi, 2G or 3G or their combination.In an exemplary implementation
In example, communication component 416 receives broadcast singal or broadcast related information from external broadcasting management system via broadcast channel.
In one exemplary embodiment, the communication component 416 further includes that (Near Field Communication, near field are logical by NFC
Letter) module, to promote short range communication.For example, RFID (Radio Frequency can be based in NFC module
Identification, radio frequency identification) technology, IrDA (Infra-red Data Association, Infrared Data Association) skill
Art, UWB (Ultra Wideband, ultra wide band) technology, BT (Bluetooth, bluetooth) technology and other technologies are realized.
In the exemplary embodiment, device 400 can be by one or more ASIC (Application Specific
Integrated Circuit, application specific integrated circuit), DSP (Digital signal Processor, at digital signal
Manage device), DSPD (Digital signal ProcessorDevice, digital signal processing appts), PLD (Programmable
Logic Device, programmable logic device), FPGA) (Field Programmable Gate Array, field programmable gate
Array), controller, microcontroller, microprocessor or other electronic components realize, for executing above-mentioned gray scale dissemination method.
In the exemplary embodiment, a kind of non-transitorycomputer readable storage medium including instruction, example are additionally provided
It such as include the memory 404 of instruction, above-metioned instruction can be executed by the processor 420 of device 400 to complete the above method.For example,
The non-transitorycomputer readable storage medium can be ROM, RAM (Random Access Memory, random access memory
Device), CD-ROM (Compact Disc Read-OnlyMemory, compact disc read-only memory), tape, floppy disk and optical data storage
Equipment etc..
A kind of non-transitorycomputer readable storage medium, when the instruction in the storage medium is by gray scale distributing device
When processor executes, so that gray scale distributing device is able to carry out above-mentioned gray scale dissemination method.
Obviously, those skilled in the art should be understood that each module of the above invention or each step can be with general
Computing device realize that they can be concentrated on a single computing device, or be distributed in multiple computing devices and formed
Network on, optionally, they can be realized with the program code that computing device can perform, it is thus possible to which they are stored
It is performed by computing device in the storage device, and in some cases, it can be to be different from shown in sequence execution herein
Out or description the step of, perhaps they are fabricated to each integrated circuit modules or by them multiple modules or
Step is fabricated to single integrated circuit module to realize.In this way, the present invention is not limited to any specific hardware and softwares to combine.
The foregoing is only a preferred embodiment of the present invention, is not intended to restrict the invention, for the skill of this field
For art personnel, the invention may be variously modified and varied.All within the spirits and principles of the present invention, made any to repair
Change, equivalent replacement, improvement etc., should all include within protection scope of the present invention.
Claims (10)
1. a kind of gray scale dissemination method, which is characterized in that the described method includes:
By index of the big data counting user data under various dimensional characteristics, the user's collection for carrying various feature tags is generated
It closes；
Grayscale version to be released and the corresponding version characteristic of the grayscale version are obtained, it is corresponding according to the grayscale version
Version characteristic determines gray scale issue rules；
The user's set for meeting the gray scale issue rules is filtered out from the user's set for carrying various feature tags；
To it is described filter out meet default issue rules user gather carry out grayscale version publication.
2. the method according to claim 1, wherein it is described by big data counting user data in various dimensions
Index under feature, the user's set for generating the various feature tags of carrying include:
Go out to be used to describe index of the user data under various dimensional characteristics by big data counting user data abstraction, building is taken
User's portrait with various feature tags；
The user's portrait for carrying same characteristic features label is sorted out, various features label respectively corresponding user's collection is generated
It closes.
3. according to the method described in claim 2, it is characterized in that, going out to use by big data counting user data abstraction described
It is described before building carries user's portrait of various feature tags in index of the description user data under various dimensional characteristics
Method further include:
The data for describing user are grabbed from multiple data sources；
The data for being used to describe user are divided into multiple reliability ratings, Mei Gexin according to the corresponding confidence level of every kind of data
Appoint the corresponding weighted value of grade；
Weighted value is set for each reliability rating, the data for describing user are weighted at summation according to the weighted value
Reason, obtains user data.
4. the method according to claim 1, wherein described obtain grayscale version and the gray scale to be released
The corresponding version characteristic of version determines that gray scale issue rules include: according to the corresponding version characteristic of the grayscale version
Grayscale version to be released and the corresponding version characteristic of the grayscale version are obtained, it is corresponding according to the grayscale version
Version feature is determined for compliance at least one feature tag of grayscale version publication；
Logical operation is carried out at least one described feature tag, generates gray scale issue rules.
5. according to the method described in claim 4, meeting ash it is characterized in that, being provided between at least one described feature tag
The logic of propositions rule of version publication is spent, it is described that logical operation is carried out at least one described feature tag, generate gray scale publication
Rule specifically includes:
Logical operation is carried out at least one described feature tag according to the logic of propositions rule between the feature tag, is generated
Gray scale issue rules.
6. according to the method described in claim 5, it is characterized in that, described from the user's set for carrying various feature tags
In filter out meet the gray scale issue rules user set include:
Filtered out from the various features label respectively corresponding user set meet that the grayscale version issues to
Multiple users set of a few feature tag；
According to the logic of propositions rule between the feature tag to described at least one feature mark for meeting grayscale version publication
Multiple users of label, which gather, carries out logical operation, obtains the user's set for meeting the gray scale issue rules.
7. method according to claim 1 to 6, which is characterized in that it is described to it is described filter out meet it is default
After the user of issue rules gathers progress grayscale version publication, the method also includes:
The feedback quantity that grayscale version issues corresponding user's set is received, gray scale issue rules are adjusted according to the feedback quantity.
8. a kind of gray scale distributing device, which is characterized in that described device includes:
Statistic unit, for by big data analysis user data, generating the user's set for carrying various feature tags；
Acquiring unit, for obtaining grayscale version to be released and the corresponding version characteristic of the grayscale version, according to described
The corresponding version characteristic of grayscale version determines gray scale issue rules；
Screening unit, for filtering out the use for meeting gray scale issue rules from the user's set for carrying various feature tags
Family set；
Release unit, for it is described filter out meet default issue rules user gather carry out grayscale version publication.
9. a kind of computer equipment, including memory and processor, it is stored with computer program in the memory, feature exists
In the step of processor realizes any one of claims 1 to 7 the method when executing the computer program.
10. a kind of computer storage medium, is stored thereon with computer program, which is characterized in that the computer program is located
The step of reason device realizes method described in any one of claims 1 to 7 when executing.
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| CN110111199A (en) * | 2019-04-23 | 2019-08-09 | 上海淇玥信息技术有限公司 | A kind of resource-niche methods of exhibiting, device, system and the recording medium of credit product |
| CN110120971A (en) * | 2019-04-17 | 2019-08-13 | 北京奇艺世纪科技有限公司 | A kind of gray scale dissemination method, device and electronic equipment |
| CN110135975A (en) * | 2019-04-23 | 2019-08-16 | 上海淇玥信息技术有限公司 | A kind of customized information sending method, device, system and the recording medium of credit product |
| CN110135896A (en) * | 2019-04-23 | 2019-08-16 | 上海淇玥信息技术有限公司 | A kind of marketing message method for pushing, device, system and the recording medium of financial product |
| CN110245070A (en) * | 2019-05-07 | 2019-09-17 | 平安科技（深圳）有限公司 | Test user's screening technique, device, computer equipment and storage medium |
| CN110493336A (en) * | 2019-08-15 | 2019-11-22 | 问问智能信息科技有限公司 | The method and apparatus at target user end are determined in a kind of gray scale issuing process |
| CN110597535A (en) * | 2019-08-27 | 2019-12-20 | 贝壳技术有限公司 | Gray scale publishing method and device and storage medium |
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| CN111723003A (en) * | 2020-05-18 | 2020-09-29 | 五八有限公司 | Gray scale testing method and device, electronic equipment and storage medium |
| CN111858311A (en) * | 2020-06-22 | 2020-10-30 | 上海趣致网络科技股份有限公司 | Version updating method and device of vending machine and electronic equipment |
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| CN114070936A (en) * | 2020-07-31 | 2022-02-18 | 北京中关村科金技术有限公司 | Interactive voice response method, device and system |
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| CN110135975A (en) * | 2019-04-23 | 2019-08-16 | 上海淇玥信息技术有限公司 | A kind of customized information sending method, device, system and the recording medium of credit product |
| CN110135896A (en) * | 2019-04-23 | 2019-08-16 | 上海淇玥信息技术有限公司 | A kind of marketing message method for pushing, device, system and the recording medium of financial product |
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| CN110245070A (en) * | 2019-05-07 | 2019-09-17 | 平安科技（深圳）有限公司 | Test user's screening technique, device, computer equipment and storage medium |
| CN110493336B (en) * | 2019-08-15 | 2021-11-16 | 问问智能信息科技有限公司 | Method and device for determining target user side in gray scale release process |
| CN110493336A (en) * | 2019-08-15 | 2019-11-22 | 问问智能信息科技有限公司 | The method and apparatus at target user end are determined in a kind of gray scale issuing process |
| CN110597535A (en) * | 2019-08-27 | 2019-12-20 | 贝壳技术有限公司 | Gray scale publishing method and device and storage medium |
| CN110688134A (en) * | 2019-08-29 | 2020-01-14 | 阿里巴巴集团控股有限公司 | Method and device for gray scale publishing |
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| CN110928555A (en) * | 2019-11-21 | 2020-03-27 | 广州品唯软件有限公司 | Gray scale release control method and device, computer equipment and storage medium |
| CN110928555B (en) * | 2019-11-21 | 2023-04-18 | 广州品唯软件有限公司 | Gray scale release control method and device, computer equipment and storage medium |
| CN110908688A (en) * | 2019-11-26 | 2020-03-24 | 中国银行股份有限公司 | Application gray level publishing method and device |
| CN111723003A (en) * | 2020-05-18 | 2020-09-29 | 五八有限公司 | Gray scale testing method and device, electronic equipment and storage medium |
| CN111858311A (en) * | 2020-06-22 | 2020-10-30 | 上海趣致网络科技股份有限公司 | Version updating method and device of vending machine and electronic equipment |
| CN114070936A (en) * | 2020-07-31 | 2022-02-18 | 北京中关村科金技术有限公司 | Interactive voice response method, device and system |
| CN112965742A (en) * | 2021-02-10 | 2021-06-15 | 中国工商银行股份有限公司 | Application version release method and system based on user map |
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