CN109558530A - User's portrait automatic generation method and system based on data processing - Google Patents
User's portrait automatic generation method and system based on data processing Download PDFInfo
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- G—PHYSICS
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
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Abstract
This disclosure relates to a kind of user's portrait automatic generation method and system based on data processing, described method includes following steps: step 1 collects user information, and the user information includes the static information and behavioural information of user；Step 2, according to collected user information, generate the specific label of the user；Step 3, according to pre-defined rule, label generated is quantified, the attribute value of the user is calculated；Step 4, according to the attribute value of the calculated user, generate user's portrait.Beneficial effects of the present invention essentially consist in that: 1, it reduces user's operation and improves user experience；2, increase interest, the interaction between user can help to carry out the popularization of product and increase living day for product.
Description
Technical field
The present invention relates to based on Internet application service technology field more particularly to a kind of user's picture based on data processing
As automatic generation method and system.
Background technique
With the development that internet is explosive, all mass data is being generated, information how is quickly grabbed and is being generated daily
User's portrait, also at important project.
In traditional method, it needs to carry out user behavior manual sort, determine, and provided targetedly in the later period
Service or other processing reply.Under the scene of mass data, often dimension is more, data volume is big for data, is manually difficult user
The relevant indicator-specific statistics of behavior is comprehensive.Further, since people will appear situations such as fatigue, the method for this traditional manual identified is quasi-
True rate is not high.
After internet gradually steps into big data era, the behavior of user all will be visual in face of service provider.Clothes
Business quotient also start focus day benefit focus on how using big data come precision marketing, and then deeply excavate potential business valence
Value.Then, the concept of " user's portrait " is also just come into being.Big data enables service provider advantageously to obtain by internet
The more extensive feedback information of user, further precisely, rapidly to analyze user behavior habit, the important business such as consumption habit
Information provides enough data basis.Along with the understanding to people gradually deeply, user draw a portrait (UserProfile) it is general
Thought is come into being, and is used to take out the information overall picture of user by user tag, is considered as service provider using big data
Foundation.Typical user's portrait be by user information labeling, be exactly service provider by collect with analysis consumer's society attribute,
After the data of the main informations such as living habit, consumer behavior, the business overall picture of a user is ideally taken out, is considered as
It is the basic mode that service provider applies big data technology.
However, currently, mainly or passing through manual intervention and calculating to the foundation that the identification of user tag, user draw a portrait
The mode of machine simple process conversion is completed, and there are following deficiencies: 1, time-consuming very long；2, high labor cost；3, the result generated
It is not intuitive enough；4, data input has because of risk of errors caused by artificial.
In addition, excessively relying on the otherness for user's portrait result that background work personnel individual factor will lead to very
Greatly, and the timeliness of label is not accounted for, it is inaccurate will lead to finally obtained user's portrait.
In the prior art, the method classified to user behavior and predicted is more single, undesirable with reference to effect.By
It include online and offline behavior in user behavior, data source is complicated, and need exist for: exploitation can be directed to different numbers
According to source, comprehensive judgement and prediction user property and the scheme for generating user's portrait in conjunction with a variety of classification Predicting Techniques.
Summary of the invention
In view of the above problem of the prior art, inventor is made that the present invention, the present invention do not need user's uploading pictures,
System can substantially sketch out lucky point that personage draws a portrait and provides personage, in personage according to the big data analysis personage of acquisition
The wisdom value of personage is shown around portrait, financial resources value, ability value, physical strength value etc., user, which can also draw a portrait personage to analyze, to be divided
It enjoys and gives wechat good friend, good friend can open and check that the personage that other side shares dissects as a result, after authorization, while can inquire
The personage of oneself draws a portrait analysis as a result, APP is promoted and the day of increase APP is living to be conducive to.
According to an embodiment of the invention, a kind of user's portrait automatic generation method based on data processing is provided, it is special
Sign is to include the following steps:
Step 1 collects user information, and the user information includes the static information and behavioural information of user；
Step 2, according to collected user information, generate the specific label of the user；
Step 3, according to pre-defined rule, label generated is quantified, the attribute value of the user is calculated；
Step 4, according to the attribute value of the calculated user, generate user's portrait.
According to an embodiment of the invention, the step 3 includes:
Step 3-1, each label of the user is quantified as multiple standard values；
Step 3-2, it is directed to some attribute of the user, to the standard value after the quantization of the part labels of the user
To summation is weighted, the attribute value of the attribute of the user is generated.
According to an embodiment of the invention, the inclusive distinguishing label of the label, academic label, consumption label, movement label, duty
Label, hobby label and the local label of activity are consulted in position label, shopping label, online,
Wherein, the user, which draws a portrait, shows the higher label of quantized value and attribute value.
According to an embodiment of the invention, calculating the attribute value as follows:
Wisdom value=educational background label × 80%+ shopping other classes of label × 15%+ label accounts for 5%；
Financial resources value=consumption label × 60%+ shopping other class labels of label × 30%+ account for × 5%；
Ability value=position label × 40%+ educational background label × 30%+ consumes other label × 10% of label × 20%+；
Physical strength value=movement label × 50%+ shopping other label × 30% of label × 20%+；
Wherein, each label in above-mentioned formula represents the standard value after its quantization.
According to an embodiment of the invention, the static information includes common data and in-house customer information, institute
It states including the ascribed characteristics of population, commercial attribute data,
Wherein, the ascribed characteristics of population includes: region, age, gender, culture, occupation, income, living habit, consumption habit.
According to an embodiment of the invention, the behavioural information includes behavior letter of the user on network or application program
Breath, website browsing behavioural information, customer transaction behavioural information including user.
According to an embodiment of the invention, the step 1 includes:
Step 1-1, static and behavioural information data are pre-processed, is obtained according in pretreated network access information
Behavioral data of the family in each default behavior classification is taken, the same category of behavioral data lattice having the same obtained are made
Formula.
According to an embodiment of the invention, after the step 4, in social platform, according to commenting between each user
Valence permission, each user can give a mark to the attribute of other users, and then, background system is according to marking situation, to user
Attribute value be modified.
According to an embodiment of the invention, additionally providing a kind of user used to perform the method portrait and automatically generating and be
System comprising:
User information collection module, for collecting user information, the user information includes the static information and row of user
For information；
User information analysis module generates the specific label of the user for analyzing user information；
User property computing module, for quantifying to every kind of label, then be weighted addition according to ad hoc rules,
Obtain the attribute value of user；
User's portrait generation module generates user's portrait for the label and attribute value according to user.
According to an embodiment of the invention, additionally providing a kind of user's picture used to perform the method based on data processing
As automatic creation system comprising:
Page snapshot handling module, the page snapshot of the present user interface for grabbing the application；
Unique attribute determining module, for passing through the attribute value for traversing all properties of extracted whole page assemblies,
Determine attribute with uniqueness in present user interface, wherein the component with uniqueness of each page assembly
The attribute value of attribute is different；
Component property preserving module, for storing the attribute of various components into the shared document, the shared text
It include the attribute table of page assembly in shelves, wherein the shared document can be accessed by tester, in each version iteration
In, tester can check and update the attribute of each page assembly, also, can be by the attribute of each page assembly only
One property, positions corresponding assembly in the shared document；
Test case constructs module, for being determined in user interface relevant to test case according to specific test case
Page assembly, and shared document relevant to the user interface is searched, further determining that in the user interface has uniquely
The component property of property, and the page assembly corresponding to it is determined by the attribute value of the component property with uniqueness, by
This building and/or update test case relevant to identified page assembly.
According to an embodiment of the invention, a kind of computer readable storage medium is additionally provided, the computer-readable storage
The program for the above method is stored on medium, when described program is executed by processor, the step of execution according to the method.
Beneficial effects of the present invention essentially consist in that:
1, it reduces user's operation and improves user experience；
2, increase interest, the interaction between user can help to carry out the popularization of product and increase living day for product；
3, in view of the separate sources of data, the processing of differentiation is carried out, improves the fineness and accuracy of processing；
4, it is drawn a portrait using user as referring to information, greatly improve related service handles speed；
5, different disaggregated model cascade and/or parallel connection can be selected, so that client according to the difference in sample data source
Relation management is more accurate.
Detailed description of the invention
Fig. 1 is the concept for showing user's portrait automatic generation method based on data processing of embodiment according to the present invention
Schematic diagram；
Fig. 2 is the process for showing user's portrait automatic generation method based on data processing of embodiment according to the present invention
Schematic diagram；
Fig. 3 is the functional module according to user's portrait automatic creation system based on data processing of the embodiment of the present invention
Composition schematic diagram；
Fig. 4 is the schematic diagram according to the running environment of the system for being mounted with application program of the embodiment of the present invention.
Specific embodiment
In the following, being described in further detail in conjunction with attached drawing to the implementation of technical solution.
It will be appreciated by those of skill in the art that although the following description is related to many of embodiment for the present invention
Technical detail, but be only for not meaning that any restrictions for illustrating the example of the principle of the present invention.The present invention can be applicable in
In the occasion being different from except technical detail exemplified below, without departing from the principle and spirit of the invention.
It, may be to can be in description in the present specification in addition, tedious in order to avoid being limited to the description of this specification
The portion of techniques details obtained in prior art data has carried out the processing such as omission, simplification, accommodation, this technology for this field
It will be understood by for personnel, and this will not influence the open adequacy of this specification.
Hereinafter, description is used to carry out the embodiment of the present invention.Note that by description is provided with following order: 1, sending out
The summary (Fig. 1) of bright design；2, user's portrait automatic generation method (Fig. 2) based on data processing；3, based on data processing
User draws a portrait automatic creation system (Fig. 3)；4, the system (Fig. 4) for being mounted with application program of embodiment according to the present invention.
1, the summary of inventive concept
As shown in Figure 1, design of the invention mainly includes following aspect.
One, mass data is collected
By behavior record of the user on network or APP, collecting user in network uplink is data, user information, use
Family preference record, user the information such as transaction data.
Two, the analysis of user behavior attribute
It is handled by a large number of users information being collected into, the behavior of user, preference is guessed by machine learning
It surveys, the information of user behavior attribute is divided into label simultaneously also by Great possibility, then label is obtained into use by algorithm
The information such as wisdom value, financial resources value, ability value, physical strength value and the glamour value at family
Three, what user's solid was drawn a portrait delineates
According to the label by dividing to user behavior attributive analysis, according to tag extraction, we can be with after polymerization analysis
Sketch out the three-dimensional portrait of user, portrait generate after can in ambient display its calculated wisdom value, financial resources value, ability value, body
Force value and glamour value.
Four, the sharing drawn a portrait
User can also be shared with good friend by wechat after generating portrait, and good friend is by that can check the portrait of user after authorization
Value, and can give a mark to portrait value.Oneself it can also carry out generation portrait.Increase interacting between user and good friend.
In the following, in conjunction with the embodiments come illustrate foregoing invention design realization.
2, user's portrait automatic generation method based on data processing
Fig. 2 is to be illustrated according to the process of user's portrait automatic generation method based on data processing of the embodiment of the present invention
Figure.
As shown in Fig. 2, the embodiment provides a kind of user's portrait automatic generation method based on data processing,
It mainly comprises the steps that
Step S100, user information is collected, the user information includes the static information and behavioural information of user；
Step S200, user information is analyzed, generates the specific label of the user；
Wherein, the label may include gender label, academic label, consumption label, movement label, position label, shopping
Label, online consult label, hobby label and the local label of activity, etc.；
Step S300, according to ad hoc rules, every kind of label is quantified, then is weighted addition, obtains the category of user
Property value；
For example, academic label can be quantified as six class, highest class is 100 points, and minimum class is 16.67, other
Label is similar；
Label is obtained into the information such as the wisdom value of user, financial resources value, ability value, physical strength value by algorithm again,
The algorithm of each attribute value is as follows:
The label that wisdom value=educational background label accounts for 80%+ shopping other classes of label 15%+ accounts for 5%；
Financial resources value=consumption label accounts for 60%+ shopping other class labels of label 30%+ and accounts for 10%；
Ability value=position label, which accounts for 40%+ educational background label and accounts for 30%+ consumption label and account for 20%+ other class labels, to be accounted for
10%；
Physical strength value=movement label, which accounts for 50%+ shopping label and accounts for 20%+ other labels, accounts for 30%；
Step S400, according to the label of user and attribute value, user's portrait is generated；
Wherein, user's portrait includes the higher label of quantization score value and attribute value.
As an example, the static information refers to the information of user's relatively stable (being not easy to change over time), may include
Common data (big data) or in-house customer information (data of user's registration), it may for example comprise the ascribed characteristics of population, quotient
Industry attribute etc. data；
Wherein, the ascribed characteristics of population includes: region, age, gender, culture, occupation, income, living habit, consumption habit etc.；
Wherein, the static information can correspond directly to specific label, for example, the gender of user can correspond directly to label
The fertility record of " male " or " women ", user can correspond to label " mother ", etc..
Wherein, the behavioural information refers to the behavioural information on network or APP, the website browsing behavior letter including user
Breath, customer transaction behavioural information, etc.,
Wherein, user browsing behavior include user browsing enliven frequency, product hobby, use habit etc.；
Optionally, step S100 includes:
S101, (data cleansing, screening) is pre-processed to static and behavioural information data, according to pretreated network
Behavioral data of the user in each default behavior classification is obtained in access information, makes the same category of behavioral data obtained tool
There is identical format.
S102, the behavior classification that user is determined according to behavioural information, as follows:
Calculate attribute of the user behavior data in preset each dimension；
According to the source of user behavior data and the attribute corresponding with the source, corresponding classification is selected
Model；
According to selected disaggregated model, classify to user behavior data.
In step s101, it is the behavioral data for extracting each classification, which can be pre-processed.
Pretreatment to network access information includes that variable acquisition, range of variables processing, minimax rule are carried out to network access information
It then handles, missing values processing and format analysis processing etc.；
Variable acquisition for acquired out from network access information access time of user's each network access, login time,
Browse information, search information and purchase information etc., such as access time when one specific electric business website of access, login
Time, browsing information, search information and purchase information.Server is acquiring out access time, the login that user accesses every time
When the information such as time, browsing information, search information and purchase information, the corresponding system such as relevant accumulator or calculator can be called
Count out user's login times within a preset period of time, purchase number, browsing time and searching times, the purchase amount of money, etc..
The Interval Maps of delimitation are tool to be each variable delimitation section according to the rule of business by range of variables processing
There is operational indicator, to input as subsequent numerical value, to calculate the features such as user behavior entropy.For example, the above-mentioned number of user
Login times, the purchase amount of money can be divided into one in multiple sections respectively, and each section corresponds to specific value, for example,
User behavior relevant to number or the amount of money can correspond to the index (0 to 100) of standardization.
The rule process of minimax includes the processing for the numerical values recited for being included to network access information collected, with
Reduce the interference of behavior classification judgement of the abnormal data to user.Specifically, can in network access information collected
The age of user carries out the rule process of minimax.For example, being -1,0 or 999 years old etc. for the age, hence it is evident that do not meet just
The data of normal age of user, carry out minimax rule process to it.
Missing values processing refers to that the behavioral data in the default behavior classification for including in acquired network access information is not deposited
When, missing values processing can be carried out to it.It is such as marked as " 0 ", or using other information replacement etc..For example, user adopts
When directly accessing relevant shopping website with anonymous access or without logging into user name, the login letter for the user that server is recorded
Breath then lacks.Server can carry out missing values processing to the category information, can such as obtain the unique identification of the access terminal of user, will
The unique identification is associated as the login name with user.
Format analysis processing includes the processing to the format for the temporal information for including in network access information, its format is made to keep phase
Together.For example, for temporal informations such as the login times of the user recorded, for example the temporal information being recorded includes
The forms such as 20091011 and on October 11st, 2009-10-11 and 2009 can be wholly converted into unified format, such as
20091011。
As an example, setting some user behaviors as substantially stationary label according to existing information in the market.It has set
Label rule be exemplified below:
Gender label: gender label is simply divided into male's label and women label very much, according to the behavioural information for obtaining user
It goes to determine that he is male's label or women label；
Academic label: academic label is divided into the different shelves in junior middle school and following, senior middle school, training, undergraduate course, master, doctor or more
It is secondary；
Consumption label: consumption is divided into top-grade consumption, middle-grade consumption, the different class of low-grade consumption；
Movement label: movement is divided into the different class such as stroll, running, body-building；
Shopping label: shopping label according to purchase object distinguish, be divided into books class, clothes packet class, daily class,
Body-building and sports equipment class etc.；
Other labels are also similar to do this differentiation.
It is directed to above-mentioned label, as an example, step S200 includes:
S201, the classification according to user behavior generate the user tag under corresponding scene.
For example, user shows user to specific content/business corresponding to the website access of specific website/network address
Interesting, preference, demand etc..It is possible thereby to generate user's scene (example corresponding to the website (for example, shopping website)
Such as, do shopping scene) under user tag (for example, " sports fan "), thus, can be under scene of doing shopping for same user
It generates and shows a series of corresponding labels, and generated under other scenes (for example, social scene) and show additional series pair
Label is answered, so that the user of subsequent generation be made to draw a portrait there are Multi-attributes difference can be presented according to scene for same user
User portrait.
In addition, the behavior a bit more complicated to user, cannot according to the differentiation set, can will to these behaviors into
The mode of row Great possibility analysis is sorted out.For example, if the user behavior obtained is user i.e. in high-grade shopping square
In expensive dining room have a meal and buy famous brand packet, also consumed on the same day in low-grade street restaurant, then bad this user of judgements category
At this moment which kind of in consumption label must go to handle, maximum probability calculation formula is as follows according to Great possibility:
P (A)=m/n.Wherein, " (A) " indicates event." m " indicates the sum that event (A) occurs." n " is that total event occurs
Sum.
If P is greater than 50% or more, that is, being set as A event is Great possibility, i.e., such event is divided into the label
Statistical phenomeon range in, that is, the quantized value of the label depend on associated particular event a situation arises.
Optionally, after step S400, in social platform, user's portrait generated can be disclosed or be sent to
Other users, wherein each user can check specific user's portrait according to mutual browse right；
As an example, after step S400 can include:
Step S500, according to the evaluation permission between each user, user can give a mark to the attribute value of other users,
Then, background system can be according to marking situation, to be modified to the attribute value of user；For example, by beating other users
Score value takes certain weight (such as weight that 10~30% are taken according to the quantity of marking user), is weighted with current attribute value
Summation, generates the attribute value of update, to further update user's portrait, wherein the system that background system refers to operation this method,
That is, the system for generating user's portrait.
3, user's portrait automatic creation system based on data processing
Fig. 3 is the functional module according to user's portrait automatic creation system based on data processing of the embodiment of the present invention
Schematic diagram.As shown in the drawing, according to an embodiment of the invention, provide it is a kind of based on data processing user portrait automatically generate
System mainly includes user information collection module, user information analysis module, user property computing module, user's portrait life
At module.
Wherein, for the user information collection module for collecting user information, the user information includes the static state of user
Information and behavioural information；
The user information analysis module generates the specific label of the user for analyzing user information；
Wherein, the label may include gender label, academic label, consumption label, movement label, position label, shopping
Label, online consult label, hobby label and the local label of activity, etc.；
The user property computing module is used to quantify every kind of label, then be weighted phase according to ad hoc rules
Add, obtains the attribute value of user；
For example, academic label can be quantified as six class, highest class is 100 points, and minimum class is 16.67, other
Label is similar；
Label is obtained into the information such as the wisdom value of user, financial resources value, ability value, physical strength value by algorithm again,
The algorithm of each attribute value is as follows:
The label that wisdom value=educational background label accounts for 80%+ shopping other classes of label 15%+ accounts for 5%；
Financial resources value=consumption label accounts for 60%+ shopping other class labels of label 30%+ and accounts for 5%；
Ability value=position label, which accounts for 40%+ educational background label and accounts for 30%+ consumption label and account for 20%+ other class labels, to be accounted for
10%；
Physical strength value=movement label, which accounts for 50%+ shopping label and accounts for 20%+ other labels, accounts for 30%；
The user draws a portrait generation module for the label and attribute value according to user, generates user's portrait.
In addition, different embodiments of the invention by software module or can also be stored in one or more computer-readable
The mode of computer-readable instruction on medium is realized, wherein the computer-readable instruction is when by processor or equipment group
When part executes, different embodiment of the present invention is executed.Similarly, software module, computer-readable medium and Hardware Subdivision
Any combination of part is all expected from the present invention.The software module can be stored in any type of computer-readable storage
On medium, such as RAM, EPROM, EEPROM, flash memory, register, hard disk, CD-ROM, DVD etc..
4, the system for being mounted with application program of embodiment according to the present invention
Referring to Fig. 4, it illustrates the running environment of the system according to an embodiment of the present invention for being mounted with application program.
In the present embodiment, the system of the installation application program is installed and is run in electronic device.The electronics
Device can be desktop PC, notebook, palm PC and server etc. and calculate equipment.The electronic device may include but not
It is limited to memory, processor and display.This Figure only shows the electronic devices with said modules, it should be understood that
It is not required for implementing all components shown, the implementation that can be substituted is more or less component.
The memory can be the internal storage unit of the electronic device, such as electronics dress in some embodiments
The hard disk or memory set.The memory is also possible to the External memory equipment of the electronic device in further embodiments,
Such as the plug-in type hard disk being equipped on the electronic device, intelligent memory card (Smart Media Card, SMC), secure digital
(Secure Digital, SD) card, flash card (Flash Card) etc..Further, the memory can also both include institute
The internal storage unit for stating electronic device also includes External memory equipment.The memory is installed on the electronics dress for storing
The application software and Various types of data set, such as the program code etc. of the system for installing application program.The memory may be used also
For temporarily storing the data that has exported or will export.
The processor can be in some embodiments central processing unit (Central Processing Unit,
CPU), microprocessor or other data processing chips, for running the program code stored in the memory or processing data,
Such as execute the system etc. of the installation application program.
The display can be in some embodiments light-emitting diode display, liquid crystal display, touch-control liquid crystal display with
And OLED (Organic Light-Emitting Diode, Organic Light Emitting Diode) touches device etc..The display is for showing
Show the information handled in the electronic device and for showing visual customer interface, such as application menu interface, answers
With icon interface etc..The component of the electronic device is in communication with each other by system bus.
Through the above description of the embodiments, those skilled in the art is it will be clearly understood that above embodiment
In method can realize by means of software and necessary general hardware platform, naturally it is also possible to realized by hardware,
But the former is more preferably embodiment in many cases.Based on this understanding, the technical solution of the application of the present invention is substantially
The part that contributes to existing technology can be embodied in the form of Software Commodities in other words, which deposits
Storage in a storage medium (such as ROM/RAM, magnetic disk, CD), including some instructions are used so that terminal device (can be with
It is mobile phone, computer, server, air conditioner or the network equipment etc.) execute side described in each embodiment of the application of the present invention
Method.
That is, according to an embodiment of the invention, additionally provide a kind of computer readable storage medium, the computer
The program of the method for executing embodiment according to the present invention is stored on readable storage medium storing program for executing, described program is processed
When device executes, each step of the method is executed.
By upper, it will be appreciated that for illustrative purposes, specific embodiments of the present invention are described herein, still, can make
Each modification, without departing from the scope of the present invention.It will be apparent to one skilled in the art that drawn in flow chart step or this
In the operation that describes and routine can be varied in many ways.More specifically, the order of step can be rearranged, step can be executed parallel
Suddenly, step can be omitted, it may include other steps can make the various combinations or omission of routine.Thus, the present invention is only by appended power
Benefit requires limitation.
Claims (10)
1. a kind of user's portrait automatic generation method based on data processing, it is characterised in that include the following steps:
Step 1 collects user information, and the user information includes the static information and behavioural information of user；
Step 2, according to collected user information, generate the specific label of the user；
Step 3 quantifies label generated, and the attribute value of the user is calculated；
Step 4, according to the attribute value of the calculated user, generate user's portrait.
2. user's portrait automatic generation method according to claim 1, which is characterized in that the step 3 includes:
Step 3-1, each label of the user is quantified as multiple standard values；
Step 3-2, be directed to some attribute of the user, to the standard value after the quantization of the part labels of the user into
Row weighted sum generates the attribute value of the attribute of the user.
3. user's portrait automatic generation method according to claim 2, which is characterized in that the label includes gender mark
Label, academic label, consumption label, movement label, position label, shopping label, online consult label, hobby label, with
And the local label of activity；
Wherein, the user, which draws a portrait, shows the higher label of quantized value and attribute value.
4. user's portrait automatic generation method according to claim 3, which is characterized in that the attribute value includes wisdom
Value, financial resources value, ability value, the wisdom value, the financial resources value, the ability value calculation formula are as follows:
Wisdom value=educational background label × 80%+ shopping other classes of label × 15%+ label × 5%；
Financial resources value=consumption label × 60%+ shopping other class label × 10% of label × 30%+；
Ability value=position label × 40%+ educational background label × 30%+ consumes other label × 10% of label × 20%+；
Physical strength value=movement label × 50%+ shopping other label × 30% of label × 20%+；
Wherein, each label in above-mentioned formula represents the standard value after its quantization.
5. user's portrait automatic generation method according to claim 3, which is characterized in that the static information includes public
Data and in-house customer information, the customer information include the ascribed characteristics of population, commercial attribute data；
Wherein, the ascribed characteristics of population includes: region, age, gender, culture, occupation, income, living habit, consumption habit.
6. user's portrait automatic generation method according to claim 5, which is characterized in that the behavioural information includes described
Behavioural information, the website browsing behavioural information of user, customer transaction behavioural information of the user on network or application program,
In, the quantized value of the label depends on the behavioural information；
It is calculated by the following formula the probability of happening of behavior corresponding to the behavioural information of user:
P (A)=m/n,
Wherein, " A " indicates that behavior A, " m " indicate that the sum that behavior A occurs, " n " are the sums that whole behaviors occur；
Later, if P is greater than specific threshold, it is determined that behavior A is Great possibility, later, and behavior A is associated with the mark
Label.
7. user's portrait automatic generation method according to claim 1, which is characterized in that the step 1 includes:
Step 1-1, static information and behavioural information are pre-processed, user is obtained every according to pretreated behavioural information
Behavioral data in a default behavior classification makes the same category of behavioral data format having the same obtained.
8. user's portrait automatic generation method according to claim 1, which is characterized in that described
After step 4 further include:
Step 5, in social platform, according to the evaluation permission between each user, each user can give the attribute of other users
It gives a mark, then, background system is according to marking situation, to be modified to the attribute value of user.
9. a kind of draw to the user based on data processing of method described in any of 8 according to claim 1 for executing
As automatic creation system, characterized by comprising:
User information collection module, for collecting user information, the user information includes the static information and behavior letter of user
Breath；
User information analysis module generates the specific label of the user for analyzing user information；
The attribute value of the user is calculated for quantifying to label generated in user property computing module；
User's portrait generation module generates user's portrait for the label and attribute value according to user.
10. a kind of computer readable storage medium, which is characterized in that be stored on the computer readable storage medium for holding
Row is according to claim 1 to the program of method described in any of 8, when described program is executed by processor, described in execution
The step of method.
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| CN201811237829.8A CN109558530A (en) | 2018-10-23 | 2018-10-23 | User's portrait automatic generation method and system based on data processing |
| PCT/CN2018/124669 WO2020082596A1 (en) | 2018-10-23 | 2018-12-28 | Data processing-based automatic user profile generating method and system |
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