CN109753521A - User model method for building up and its device, electronic equipment, computer-readable medium - Google Patents
User model method for building up and its device, electronic equipment, computer-readable medium Download PDFInfo
- Publication number
- CN109753521A CN109753521A CN201811517641.9A CN201811517641A CN109753521A CN 109753521 A CN109753521 A CN 109753521A CN 201811517641 A CN201811517641 A CN 201811517641A CN 109753521 A CN109753521 A CN 109753521A
- Authority
- CN
- China
- Prior art keywords
- user
- data
- stream compression
- use habit
- sample
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Abstract
This application discloses a kind of user model method for building up and its device, electronic equipment, computer-readable mediums, user model method for building up includes: the sample for collecting participating user's model foundation, the data use habit and the stream compression track that generates due to user is followed to carry out dynamic migration for data that the sample includes user；User model is established according to the data use habit of the user and the stream compression track generated because user is followed to carry out dynamic migration for data, so as to realize according to the model of user to user's recommending data, user is allowed relatively rapid to obtain the data of its concern according to the variation in its geographical location.
Description
Technical field
This application involves internet area more particularly to a kind of user model method for building up and its device, electronic equipment, meter
Calculation machine readable medium.
Background technique
Nowadays, big data cloud storage popularity is higher and higher, and undoubtedly the privacy of its information also has and is compromised
Risk, thus caused problem of data safety is to cannot be neglected.
Data are often stored in the database with certain forms, and user is facilitated to access and operate.Nowadays, big data is relied on
Occur in more extensive more open cloud platform, still, since the demand of user is ever-changing, how dynamically to meet the number of user
According to demand, become one of the technical issues of urgently providing.
Summary of the invention
The purpose of the application is to propose a kind of user model method for building up and its device, electronic equipment, computer-readable
Medium, for solving the above problem in the prior art.
In a first aspect, the embodiment of the present application provides a kind of user model method for building up comprising:
Collect participating user's model foundation sample, the sample include user data use habit and because data with
The stream compression track for carrying out dynamic migration with user and generating；
According to the data use habit of the user and the data generated because user is followed to carry out dynamic migration for data
Guiding circulation track establishes user model.
Optionally, in any embodiment of the application, the sample of participating user's model foundation study is collected, comprising: root
The sample of participating user's model foundation study is collected according to the off-line data Collection Rules of setting or online Collection Rules.
Optionally, in any embodiment of the application, further includes: according to the data use habit and stream compression rail
Mark establishes data use habit vector and stream compression track vector.
Optionally, in any embodiment of the application, according to the data use habit of the user and because data with
User model is established in the stream compression track for carrying out dynamic migration with user and generating, comprising: according to data use habit vector
And stream compression track vector establishes user model.
Optionally, in any embodiment of the application, further includes: pre-establish sample database, and the data of user are made
It is added in the sample database with habit and stream compression track.
Optionally, in any embodiment of the application, further includes: according to the corresponding data use habit of newly-increased data with
And stream compression track carries out incremental update to the sample database.
Optionally, in any embodiment of the application, further includes: according to new data use habit and new data
Guiding circulation track carries out full dose update to the sample database.
Second aspect, the embodiment of the present application also provide a kind of user model and establish device comprising:
First program unit, for collecting the sample of participating user's model foundation study, the sample includes the number of user
According to use habit and the stream compression track generated because user is followed to carry out dynamic migration for data；
Second program unit, for the data use habit according to the user and because data follow user to carry out dynamic
User model is established in the stream compression track for migrating and generating.
The third aspect, the embodiment of the present application provide a kind of electronic equipment, comprising:
One or more processors；
Computer-readable medium is configured to store one or more programs,
When one or more of programs are executed by one or more of processors, so that one or more of processing
Device realizes the method as described in the embodiment of the present application is any.
Fourth aspect, the embodiment of the present application provide a kind of computer-readable medium, are stored thereon with computer program, should
The method as described in above-mentioned any embodiment is realized when program is executed by processor.
In technical solution disclosed in the embodiment of the present application, by collecting the sample of participating user's model foundation, the sample
Data use habit including user and the stream compression track generated because user is followed to carry out dynamic migration for data；According to
The data use habit of the user and the stream compression track generated because user is followed to carry out dynamic migration for data are established
User model allows user according to its geographical location so as to realize according to the model of user to user's recommending data
Variation relatively rapid obtain its concern data.
Detailed description of the invention
By reading a detailed description of non-restrictive embodiments in the light of the attached drawings below, the application's is other
Feature, objects and advantages will become more apparent upon:
Fig. 1 is the flow diagram of user model method for building up in the embodiment of the present application one；
Fig. 2 is the flow diagram of user model method for building up in the embodiment of the present application two；
Fig. 3 is the flow diagram of user model method for building up in the embodiment of the present application three；
Fig. 4 is the flow diagram of user model method for building up in the embodiment of the present application four；
Fig. 5 is the flow diagram of user model method for building up in the embodiment of the present application five；
Fig. 6 is the structural schematic diagram that user model establishes device in the embodiment of the present application six；
Fig. 7 is the structural schematic diagram of electronic equipment in the embodiment of the present application seven；
Fig. 8 is the hardware configuration of electronic equipment in the embodiment of the present application eight.
Specific embodiment
The application is described in further detail with reference to the accompanying drawings and examples.It is understood that this place is retouched
The specific embodiment stated only is only configured to explain related invention, rather than the restriction to the invention.It also should be noted that being
Convenient for description, part relevant to related invention is illustrated only in attached drawing.
It should be noted that in the absence of conflict, the features in the embodiments and the embodiments of the present application can phase
Mutually combination.The application is described in detail below with reference to the accompanying drawings and in conjunction with the embodiments.
In technical solution disclosed in the embodiment of the present application, by collecting the sample of participating user's model foundation, the sample
Data use habit including user and the stream compression track generated because user is followed to carry out dynamic migration for data；According to
The data use habit of the user and the stream compression track generated because user is followed to carry out dynamic migration for data are established
User model allows user according to its geographical location so as to realize according to the model of user to user's recommending data
Variation relatively rapid obtain its concern data.
The user model method for building up provided in the following embodiments of the application, core concept are to include: to collect to participate in
The sample that user model is established, the sample include the data use habit of user and move because data follow user to carry out dynamic
The stream compression track moved and generated；It is moved according to the data use habit of the user and because data follow user to carry out dynamic
User model is established in the stream compression track moved and generated.
Fig. 1 is the flow diagram of user model method for building up in the embodiment of the present application one；As shown in Figure 1, comprising:
S101, participating user's model foundation is collected according to the off-line data Collection Rules of setting or online Collection Rules
The sample of habit.
In the present embodiment, the sample includes the data use habit of user and moves because data follow user to carry out dynamic
The stream compression track moved and generated.In the present embodiment, for collected offline, pass can be automatically extracted by web crawlers
Connection and the information of stream compression track and the data of data use habit, from one or several data sources, from data source
During grabbing data, data source address is constantly put into queue, certain stop condition until meeting system.It is all to be climbed
The data of worm crawl will be stored, and certain analysis, filtering be carried out, and establish index, so as to inquiry and retrieval later.
In the present embodiment, the generation of stream compression track such as be can be since the physical location of user changes, and
In order to allow user's more data close to required for it, dynamic adjustment stores the back end of the data.Stream compression track
It can specifically be reflected by the ID of back end.Data use habit such as includes the preference of user, the activity of the user etc..
S102, it is generated according to the data use habit of the user and because user is followed to carry out dynamic migration data
Stream compression track is established user model and is practiced.
In the present embodiment, user model is such as decision tree, by the way that example is aligned to some leaf node from root node
Carry out classified instance, leaf node is classification belonging to example, it indicates decision and its possible with tree-like figure or model
Consequence, influence, resource consumption and purposes including chance event.
In the present embodiment, in step S202, number can be established according to the data use habit and data guiding circulation track
According to use habit vector and stream compression track vector, go through transition according further to data use habit vector and data flow
Mark vector establishes user model, goes through transition so that the user model established is associated with simultaneously with data use habit and data flow
The user model accuracy of mark, foundation is higher.
Fig. 2 is the flow diagram of user model method for building up in the embodiment of the present application two；As shown in Fig. 2, comprising:
S201, collect participating user's model foundation sample, the sample include user data use habit and because
Data follow user to carry out dynamic migration and the stream compression track that generates；
It is similar to the above embodiments in the present embodiment, association and stream compression track are automatically extracted by web crawlers
The data of information and data use habit, from one or several data sources, during grabbing data from data source, no
It is disconnected that data source address is put into queue, certain stop condition until meeting system.All data by crawler capturing will be by
Storage carries out certain analysis, filtering, and establishes index, so as to inquiry and retrieval later.
S202, it is generated according to the data use habit of the user and because user is followed to carry out dynamic migration data
The classifier as user model is established in stream compression track.
In the present embodiment, above-mentioned classifier can be specifically established using Adaboost algorithm, to be directed to the same sample
The different classifier (such as Weak Classifier) of this collection (several input datas) training, then gets up these weak classifier sets,
Constitute a stronger final classification device (strong classifier).And whether just according to the classification of each sample among each training set
Really and the accuracy rate of the general classification of last time, to determine the weight of each sample (several input datas).Weight will be modified
New data is given sub-classification device and is trained, and the Multiple Classifier Fusion for then obtaining each training is determined as last
Plan classifier.
Fig. 3 is the flow diagram of user model method for building up in the embodiment of the present application three；As shown in figure 3, comprising:
S301, collect participating user's model foundation sample, the sample include user data use habit and because
Data follow user to carry out dynamic migration and the stream compression track that generates；
It is similar to the above embodiments in the present embodiment, association and stream compression track are automatically extracted by web crawlers
The data of information and data use habit, from one or several data sources, during grabbing data from data source, no
It is disconnected that data source address is put into queue, certain stop condition until meeting system.All data by crawler capturing will be by
Storage carries out certain analysis, filtering, and establishes index, so as to inquiry and retrieval later.
S302, it is generated according to the data use habit of the user and because user is followed to carry out dynamic migration data
The neural network as user model is established in stream compression track.
In the present embodiment, neural network interconnects non-linear, the adaptive information processing system that form by a large amount of processing units
System.In neural network, constituted by being coupled to each other between a large amount of node (or neuron).Each node on behalf is a kind of specific
Output function, referred to as excitation function (activation function).Connection between every two node all represents one for logical
The weighted value of the connection signal, referred to as weight are crossed, this is equivalent to the memory of artificial neural network.The output of network is then according to network
Connection type, the difference of weighted value and excitation function and it is different.And network itself be usually all to certain algorithm of nature or
Person's function approaches, it is also possible to the expression to a kind of logic strategy.
Fig. 4 is the flow diagram of user model method for building up in the embodiment of the present application four；As shown in figure 4, comprising:
S401, collect participating user's model foundation sample, the sample include user data use habit and because
Data follow user to carry out dynamic migration and the stream compression track that generates；
It is similar to the above embodiments in the present embodiment, association and stream compression track are automatically extracted by web crawlers
The data of information and data use habit, from one or several data sources, during grabbing data from data source, no
It is disconnected that data source address is put into queue, certain stop condition until meeting system.All data by crawler capturing will be by
Storage carries out certain analysis, filtering, and establishes index, so as to inquiry and retrieval later.
S402, it is generated according to the data use habit of the user and because user is followed to carry out dynamic migration data
The vector machine as user model is established in stream compression track.
In the present embodiment, vector machine can specifically pass through SVM (Support Vector Machine): SVM method is supported
Vector machine algorithm is realized, it is assumed that in N-dimensional space, there is one group of point, each pair of point should include two types, and SVM generates a (N-1)
These points are divided into two groups by the hyperplane of dimension.SVM can find a straight line, these points are divided into two classes, and can be as far as possible
From these point.
Fig. 5 is the flow diagram of user model method for building up in the embodiment of the present application five；As shown in figure 5, comprising:
S501, collect participating user's model foundation sample, the sample include user data use habit and because
Data follow user to carry out dynamic migration and the stream compression track that generates；
It is similar to the above embodiments in the present embodiment, association and stream compression track are automatically extracted by web crawlers
The data of information and data use habit, from one or several data sources, during grabbing data from data source, no
It is disconnected that data source address is put into queue, certain stop condition until meeting system.All data by crawler capturing will be by
Storage carries out certain analysis, filtering, and establishes index, so as to inquiry and retrieval later
S502, it is generated according to the data use habit of the user and because user is followed to carry out dynamic migration data
The Logic Regression Models as user model are established in stream compression track.
In the present embodiment, the data for having one or more explanatory variable are established as binomial class by Logic Regression Models
The model of type, by the logical function estimated probability with accumulation logic distribution, measurement classification dependent variable and one or more are independent
Relationship between variable.Compared to linear regression, it is a more sigmoid function (or being Logistic function).
It further, can also include: to pre-establish sample database, and by user's on the basis of above-described embodiment earphone
Data use habit and stream compression track are added in the sample database.This pre-establishes the step of sample database can be upper
It executes before stating first step of scheme method embodiment, or is executed between step and second step at first.
It further, can also include: according to the newly-increased corresponding data use habit of data and stream compression track pair
The sample database carries out incremental update.Alternatively, according to new data use habit and new stream compression track to the sample
This library carries out full dose update
Fig. 6 is the structural schematic diagram that user model establishes device in the embodiment of the present application six；As shown in fig. 6, comprising:
First program unit 601, for collecting the sample of participating user's model foundation study, the sample includes user's
Data use habit and the stream compression track generated because user is followed to carry out dynamic migration for data；
Second program unit 602, for the data use habit according to the user and because data follow user to carry out
Dynamic migration and user model is established in the stream compression track generated
Fig. 7 is the structural schematic diagram of electronic equipment in the embodiment of the present application seven；The electronic equipment may include:
One or more processors 701；
Computer-readable medium 702 is configurable to store one or more programs,
When one or more of programs are executed by one or more of processors, so that one or more of processing
Device realizes the storage method as described in above-mentioned any embodiment.
Fig. 8 is the hardware configuration of electronic equipment in the embodiment of the present application eight；As shown in figure 8, the hardware knot of the electronic equipment
Structure may include: processor 801, communication interface 802, computer-readable medium 803 and communication bus 804；
Wherein processor 801, communication interface 802, computer-readable medium 803 are completed each other by communication bus 804
Communication；
Optionally, communication interface 802 can be the interface of communication module, such as the interface of gsm module；
Wherein, processor 801 is specifically configurable to: collecting the sample of participating user's model foundation, the sample includes
The data use habit of user and the stream compression track generated because user is followed to carry out dynamic migration for data；According to described
User is established in the data use habit of user and the stream compression track generated because user is followed to carry out dynamic migration for data
Model.
Processor 801 can be general processor, including central processing unit (Central Processing Unit, abbreviation
CPU), network processing unit (Network Processor, abbreviation NP) etc.；It can also be digital signal processor (DSP), dedicated
Integrated circuit (ASIC), ready-made programmable gate array (FPGA) either other programmable logic device, discrete gate or transistor
Logical device, discrete hardware components.It may be implemented or execute disclosed each method, step and the logic in the embodiment of the present application
Block diagram.General processor can be microprocessor or the processor is also possible to any conventional processor etc..
In above-described embodiment, electronic equipment can be the intelligent terminal of front end, or the server on backstage, when for before
When the intelligent terminal at end, to be intelligent appliance.The household electrical appliances may include following at least one, such as: TV, digital video disc
(DVD) player, audio device, refrigerator, air-conditioning, vacuum cleaner, oven, micro-wave oven, washing machine, air purifier, machine top
Box, home automation controlling panel, security control panel, TV box are (for example, SAMSUNG HOMESYNCTM, APPLE TVTM
Or GOOGLE TVTM), game machine (for example, XBOXTM and PLAYSTATIONTM), electronic dictionary, electron key, video camera and
Digital photo frame.
According to another embodiment, electronic equipment may include following at least one: various Medical Devices are (for example, various
Portable medical measuring device is (for example, blood glucose monitoring device, heart rate monitor apparatus, blood pressure measurement device, body temperature measuring devices
Deng), magnetic resonance angiography (MRA), magnetic resonance imaging (MRI), computed tomography (CT) instrument and Ultrasound Instrument), navigation
Equipment, global positioning system (GPS) receiver, event data recorder (EDR), flight data recorder (FDR), vehicle entertainment
Information equipment, the electronic equipment navigation equipment and gyro compass of ship (for example, be used for) for ship, avionic device,
Safety equipment, motor vehicle head unit, household or industrial robot, the ATM (ATM) in bank, the sale in shop
Point (POS) or internet of things equipment are (for example, bulb, various sensors, voltameter or gas gauge, sprinkling equipment, fire protection warning
Device, constant temperature controller, street lamp, toaster, sports apparatus, boiler, heater, water heater etc.).
According to some embodiments, electronic equipment may include following at least one: furniture or building/structure a part,
Electron plate, electronic signature receiving device, projector and various types of measuring instruments are (for example, watermeter, voltameter, gas gauge
Or radio wave meter).It can be the one or more of above-mentioned various equipment according to the electronic equipment of the various embodiments of the disclosure
Combination.It can be flexible apparatus according to the electronic equipment of some embodiments of the disclosure.In addition, according to disclosure embodiment party
The electronic equipment of formula is not limited to above equipment, and may include the new electronic equipment developed according to technology.
Particularly, in accordance with an embodiment of the present disclosure, it may be implemented as computer above with reference to the process of flow chart description
Software program.For example, embodiment of the disclosure includes a kind of computer program product comprising be carried on computer-readable medium
On computer program, which includes to be configured to the program code of method shown in execution flow chart.Such
In embodiment, which can be downloaded and installed from network by communications portion, and/or from detachable media quilt
Installation.When the computer program is executed by central processing unit (CPU), the above-mentioned function limited in the present processes is executed
Energy.It should be noted that computer-readable medium described herein can be computer-readable signal media or computer
Readable storage medium storing program for executing either the two any combination.Computer-readable medium for example can be, but not limited to be electricity, magnetic,
Optical, electromagnetic, the system of infrared ray or semiconductor, device or device, or any above combination.Computer-readable storage medium
The more specific example of matter can include but is not limited to: have the electrical connections of one or more conducting wires, portable computer diskette,
Hard disk, random access storage medium (RAM), read-only storage medium (ROM), erasable type may be programmed read-only storage medium (EPROM or
Flash memory), optical fiber, the read-only storage medium of portable compact disc (CD-ROM), optical storage media part, magnetic storage medium part or
Above-mentioned any appropriate combination.In this application, computer readable storage medium can be it is any include or storage program
Tangible medium, the program can be commanded execution system, device or device use or in connection.And in the application
In, computer-readable signal media may include in a base band or as carrier wave a part propagate data-signal, wherein
Carry computer-readable program code.The data-signal of this propagation can take various forms, including but not limited to electric
Magnetic signal, optical signal or above-mentioned any appropriate combination.Computer-readable signal media can also be computer-readable and deposit
Any computer-readable medium other than storage media, which can send, propagate or transmission configuration is served as reasons
Instruction execution system, device or device use or program in connection.The journey for including on computer-readable medium
Sequence code can transmit with any suitable medium, including but not limited to: wireless, electric wire, optical cable, RF etc. are above-mentioned
Any appropriate combination.
It can be write by one or more programming languages or combinations thereof in terms of the operation for being configured to execute the application
Calculation machine program code, described program design language include object oriented program language-such as Java, Smalltalk, C
++, further include conventional procedural programming language-such as " C " language or similar programming language.Program code can
Fully to execute, partly execute on the user computer on the user computer, be executed as an independent software package,
Part executes on the remote computer or executes on a remote computer or server completely on the user computer for part.
In situations involving remote computers, remote computer can pass through the network of any kind: including local area network (LAN) or extensively
Domain net (WAN)-be connected to subscriber computer, or, it may be connected to outer computer (such as provided using Internet service
Quotient is connected by internet).
Flow chart and block diagram in attached drawing are illustrated according to the system of the various embodiments of the application, method and computer journey
The architecture, function and operation in the cards of sequence product.In this regard, each box in flowchart or block diagram can generation
A part of one module, program segment or code of table, a part of the module, program segment or code are matched comprising one or more
It is set to the executable instruction of logic function as defined in realizing.There is specific precedence relationship in above-mentioned specific embodiment, but these are successively
Relationship is only exemplary, when specific implementation, these steps may less, more or execution sequence have adjustment.I.e.
In some implementations as replacements, function marked in the box can also be sent out in a different order than that indicated in the drawings
It is raw.For example, two boxes succeedingly indicated can actually be basically executed in parallel, they sometimes can also be by opposite suitable
Sequence executes, and this depends on the function involved.It is also noted that each box and block diagram in block diagram and or flow chart
And/or the combination of the box in flow chart, can with execute as defined in functions or operations dedicated hardware based system come
It realizes, or can realize using a combination of dedicated hardware and computer instructions.
Being described in unit involved in the embodiment of the present application can be realized by way of software, can also be by hard
The mode of part is realized.Described unit also can be set in the processor, for example, can be described as: a kind of processor packet
Include: the first program unit, for collecting the sample of participating user's model foundation study, the sample includes that the data of user use
Habit and the stream compression track generated because user is followed to carry out dynamic migration for data；Second program unit is used for basis
The data use habit of the user and the stream compression track generated because user is followed to carry out dynamic migration for data are established
User model.
As on the other hand, present invention also provides a kind of computer-readable mediums, are stored thereon with computer program, should
The method as described in above-mentioned any embodiment is realized when program is executed by processor.
As on the other hand, present invention also provides a kind of computer-readable medium, which be can be
Included in device described in above-described embodiment；It is also possible to individualism, and without in the supplying device.Above-mentioned calculating
Machine readable medium carries one or more program, when said one or multiple programs are executed by the device, so that should
Device: collecting the sample of participating user's model foundation, and the sample includes the data use habit of user and because data follow
User carries out dynamic migration and the stream compression track that generates；According to the data use habit of the user and because data follow
User model is established in the stream compression track that user carries out dynamic migration and generates.
Statement " first ", " second " used in various embodiments of the present disclosure, " first " or " described the
Two " can modify various parts and unrelated with sequence and/or importance, but these statements do not limit corresponding component.The above statement
It is only configured to the purpose for distinguishing element and other elements.For example, the first user equipment and second user equipment indicate different
User equipment, although being both user equipment.For example, first element can under the premise of without departing substantially from the scope of the present disclosure
Referred to as second element, similarly, second element can be referred to as first element.
Term " module " used herein or " functional unit " can for example mean to include hardware, software and firmware
Unit or include two or more in hardware, software and firmware combined unit." module " can be " single with such as term
Member ", " logic ", " logical block ", " component " or " circuit " convertibly use." module " or " functional unit " can be integral part
The minimum unit of part element or a part of integrated component element." module " can be for executing one or more functions most
Junior unit or part of it." module " or " functional unit " mechanically or is electrically implemented.For example, according to the " mould of the disclosure
Block " or " functional unit " may include following at least one: specific integrated circuit (ASIC) chip, field programmable gate array (FPGA)
And it is known or leaved for development from now on for executing the programmable logic device of operation.Above description be only the application compared with
Good embodiment and explanation to institute's application technology principle.
It will be appreciated by those skilled in the art that invention scope involved in the application, however it is not limited to above-mentioned technical characteristic
Specific combination made of technical solution, while should also cover do not depart from foregoing invention design in the case where, by above-mentioned technology
Feature or its equivalent feature carry out any combination and other technical solutions for being formed.Such as features described above and disclosed herein
(but being not limited to) have the technical characteristic of similar functions replaced mutually and the technical solution that is formed.
When an element (for example, first element) referred to as " (operationally or can with another element (for example, second element)
Communicatedly) connection " or " (operationally or communicably) being attached to " another element (for example, second element) or " being connected to " are another
When one element (for example, second element), it is thus understood that an element is connected directly to another element or an element
Another element is indirectly connected to via another element (for example, third element).On the contrary, it is appreciated that when element (for example,
First element) it referred to as " is directly connected to " or when " directly connection " to another element (second element), then without element (for example, the
Three elements) it is inserted between the two.
Claims (10)
1. a kind of user model method for building up characterized by comprising
The sample of participating user's model foundation is collected, the sample includes the data use habit of user and because data follow use
Family carries out dynamic migration and the stream compression track that generates；
According to the data use habit of the user and the stream compression generated because user is followed to carry out dynamic migration for data
User model is established in track.
2. the method according to claim 1, wherein collecting the sample of participating user's model foundation study, comprising:
The sample of participating user's model foundation study is collected according to the off-line data Collection Rules of setting or online Collection Rules.
3. according to the method described in claim 2, it is characterized by further comprising: according to the data use habit and data flow
Transition mark, establishes data use habit vector and stream compression track vector.
4. according to the method described in claim 3, it is characterized in that, according to the data use habit of the user and because of data
Follow user to carry out dynamic migration and user model is established in the stream compression track that generates, comprising: according to data use habit to
Amount and stream compression track vector establish user model.
5. the method according to claim 1, wherein further include: pre-establish sample database, and by the data of user
Use habit and stream compression track are added in the sample database.
6. according to the method described in claim 5, it is characterized by further comprising: using habit according to the corresponding data of newly-increased data
Used and stream compression track carries out incremental update to the sample database.
7. according to the method described in claim 5, it is characterized by further comprising: according to new data use habit and new
Stream compression track carries out full dose update to the sample database.
8. a kind of data storage device characterized by comprising
First program unit, for collecting the sample of participating user's model foundation study, the sample includes that the data of user make
With habit and the stream compression track generated because user is followed to carry out dynamic migration for data；
Second program unit, for the data use habit according to the user and because data follow user to carry out dynamic migration
And user model is established in the stream compression track generated.
9. a kind of electronic equipment, comprising:
One or more processors；
Computer-readable medium is configured to store one or more programs,
When one or more of programs are executed by one or more of processors, so that one or more of processors are real
The now method as described in any in claim 1-7.
10. a kind of computer-readable medium, is stored thereon with computer program, which is characterized in that the program is executed by processor
Method of the Shi Shixian as described in any in claim 1-7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811517641.9A CN109753521A (en) | 2018-12-12 | 2018-12-12 | User model method for building up and its device, electronic equipment, computer-readable medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811517641.9A CN109753521A (en) | 2018-12-12 | 2018-12-12 | User model method for building up and its device, electronic equipment, computer-readable medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN109753521A true CN109753521A (en) | 2019-05-14 |
Family
ID=66403782
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201811517641.9A Pending CN109753521A (en) | 2018-12-12 | 2018-12-12 | User model method for building up and its device, electronic equipment, computer-readable medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109753521A (en) |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20080050902A (en) * | 2006-12-04 | 2008-06-10 | 삼성전자주식회사 | Method and system of recommending a music using user model, and update method of a conditional user model |
| US20080162387A1 (en) * | 2006-12-31 | 2008-07-03 | Singh Munindar P | Method, system, and computer program product for adaptively learning user preferences for smart services |
| CN104036002A (en) * | 2014-06-16 | 2014-09-10 | 深圳市英威诺科技有限公司 | Technical method for intelligently recommending data |
| CN106202534A (en) * | 2016-07-25 | 2016-12-07 | 十九楼网络股份有限公司 | A kind of content recommendation method based on community users behavior and system |
-
2018
- 2018-12-12 CN CN201811517641.9A patent/CN109753521A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20080050902A (en) * | 2006-12-04 | 2008-06-10 | 삼성전자주식회사 | Method and system of recommending a music using user model, and update method of a conditional user model |
| US20080162387A1 (en) * | 2006-12-31 | 2008-07-03 | Singh Munindar P | Method, system, and computer program product for adaptively learning user preferences for smart services |
| CN104036002A (en) * | 2014-06-16 | 2014-09-10 | 深圳市英威诺科技有限公司 | Technical method for intelligently recommending data |
| CN106202534A (en) * | 2016-07-25 | 2016-12-07 | 十九楼网络股份有限公司 | A kind of content recommendation method based on community users behavior and system |
Non-Patent Citations (2)
| Title |
|---|
| 朱杨勇等: "《生物数据整合与挖掘》", 31 May 2009 * |
| 李琳等: "《云计算与大数据实验教材系列 MAHOUT实验指南》", 30 April 2017 * |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US10699214B2 (en) | Automatic identification and deployment of virtual sensor models | |
| CN109922032A (en) | Method and apparatus for determining the risk of logon account | |
| CN109344908A (en) | Method and apparatus for generating model | |
| CN110413533A (en) | AB test method, system, equipment and storage medium | |
| Lin et al. | AItalk: a tutorial to implement AI as IoT devices | |
| CN109769144A (en) | Right management method and its device, electronic equipment, computer-readable medium | |
| CN104252520A (en) | Iterative learning for reliable sensor sourcing systems | |
| Amiri et al. | Resilient and dependability management in distributed environments: A systematic and comprehensive literature review | |
| CN111430042A (en) | Method, apparatus, computer device and storage medium for predicting the spread of an infectious disease | |
| Wang et al. | A decentralized sensor fault detection and self-repair method for HVAC systems | |
| US10998103B2 (en) | Medical risk factors evaluation | |
| US11295059B2 (en) | Adaptive processing and content control system | |
| CN109767089A (en) | Performance statistical method and its device, electronic equipment, computer-readable medium | |
| CN110162606A (en) | For solving the session proxy learning model services selection of client-side service request | |
| CN109783190A (en) | Data migration method and its device, electronic equipment, computer-readable medium | |
| Ahmadova et al. | Big data applications on the Internet of Things: A systematic literature review | |
| Li et al. | Towards Ubiquitous Semantic Metaverse: Challenges, Approaches, and Opportunities | |
| WO2018215825A1 (en) | Adaptive adjustment using sensor data and distributed data | |
| US11050835B2 (en) | Generating contextual user responses | |
| CN112486784A (en) | Method, apparatus and medium for diagnosing and optimizing data analysis system | |
| CN110069997A (en) | Scene classification method, device and electronic equipment | |
| CN109446384A (en) | For generating the method and system of personnel arrangement Schema information | |
| CN109522105A (en) | APP running background method, system, terminal device and can storage medium | |
| CN109753521A (en) | User model method for building up and its device, electronic equipment, computer-readable medium | |
| CN114900435B (en) | Connection relation prediction method and related equipment |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20190514 |