CN104092775B - Intelligent appliance self-learning method and system - Google Patents
Intelligent appliance self-learning method and system Download PDFInfo
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- CN104092775B CN104092775B CN201410355368.XA CN201410355368A CN104092775B CN 104092775 B CN104092775 B CN 104092775B CN 201410355368 A CN201410355368 A CN 201410355368A CN 104092775 B CN104092775 B CN 104092775B
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Abstract
The present invention provides a kind of intelligent appliance self-learning method, identity identification information and the API information of itself to the webserver including sending home appliance, whether inquiry has the identity identification information of matching with its usage history information, when it is determined that set up the entrance of identity identification information during identity identification information without matching, and statistical learning is carried out to the use habit of user according to all API states using the home appliance.The present invention also provides a kind of intelligent appliance self learning system, and using the present invention, analysis and record by the configuration information to home appliance reduce setting time and the work of user, household electrical appliances is set and initialization according to user's custom is automatic.
Description
Technical field
The present invention relates to home wiring control technical field, more particularly to a kind of intelligent appliance self-learning method and system.
Background technology
Each user has the use habit of oneself when using specific household electrical appliances, such as, some user is practised using air-conditioning
It is used to be arranged on 25 degree, and open dehumidification function；One, center is seen using television habits, brightness is set to 80, volume and is set to 50；
Using roller washing machine, custom is transferred to 25 degree of washings, and wash time is 50 minutes, and washing mode is gentle mode.If user
Want to allow a home appliance to reach the use habit of oneself, current method is typically that user needs to use the plenty of time family
Electricity is set to the setting of the mode of operation or custom of oneself needs, even changes the home appliance to a same model
When, it is still desirable to repeat to set work.Also, when reopening household electrical appliances every time, needed for the household electrical appliances without automatic Memory function
Reset.
The content of the invention
In view of the above problems, the present invention provides a kind of one kind for overcoming above mentioned problem or at least partly solving the above problems
Intelligent appliance self-learning method and system.
The present invention provides a kind of intelligent appliance self-learning method, and this method includes：
The identity identification information and API information of home appliance are sent to the webserver.
Whether the identity identification information with matching determines whether the home appliance for webserver inquiry
Usage history information, wherein, the identity identification information of home appliance and corresponding usage history information are previously stored.And
When it is determined that according to all API states using the home appliance to user's during identity identification information without matching
Use habit carries out statistical learning.
The present invention also provides a kind of intelligent appliance self learning system, including user terminal, the webserver and multiple families
Electric equipment, each home appliance is communicated to connect with the webserver, and the webserver includes：
Memory cell, has prestored the identity identification information and corresponding usage history information of multiple home appliances.
Operation historical record unit, for the identity identification information and API that are sent according to the home appliance in the storage list
The identity identification information whether inquired about in member has matching determines whether the usage history information with the home appliance.
Use habit unit, when the operation historical record unit determines the usage history information without the home appliance
When, for carrying out statistical learning to the use habit of user according to all API states using the home appliance.
A kind of intelligent appliance self learning system and method that the present invention is provided, pass through point of the configuration information to home appliance
Analysis and record, make user by unique account anywhere by user's terminal logs in different home appliances after, it is logical
User's use habit that server memory and study are obtained is crossed, corresponding device is provided with to the configuration being accustomed to for user automatically
And initialization, setting time and the work of user are greatly reduced, and access to your account can across distinct device type, same type
The household electrical appliances of different model are used, so as to complete to set and initialization according to user's custom is automatic.
Brief description of the drawings
Fig. 1 be embodiment of the present invention in intelligent appliance self learning system hardware structure schematic diagram；
Fig. 2 be embodiment of the present invention in intelligent appliance self learning system high-level schematic functional block diagram；
Fig. 3 be embodiment of the present invention in intelligent appliance self-learning method schematic flow sheet；
Fig. 4 is the sub-process schematic diagram for carrying out statistical learning in embodiment of the present invention to the use habit of user.
Label declaration：
Intelligent appliance self learning system 10
User terminal 11
The webserver 12
Operation historical record unit 120
Language scripts storehouse 121
Memory cell 122
Log in control unit 123
Use habit unit 124
Configuration item sets up module 125
Configuration write-in control module 126
Use habit statistical analysis unit 127
Home appliance 13
Api interface converting unit 14
Big data analysis system 20
Embodiment
To describe the technology contents of the present invention in detail, feature, the objects and the effects being constructed, below in conjunction with embodiment
And coordinate accompanying drawing to be explained in detail.
API：Application programming interfaces (API：Application Program Interface), be one group of definition, program and
The set of agreement, being in communication with each other between computer software is realized by api interface.An API major function is to provide logical
Use function collection.Programmer is by using api function development and application program, so as to avoid writing useless program, to mitigate volume
Journey task.API is also simultaneously a kind of middleware, and data sharing is provided for various different platforms.
Fig. 1 is refer to, is the hardware structure schematic diagram of the intelligent appliance self learning system in embodiment of the present invention, this is
System 10 includes user terminal 11, the webserver 12 and multiple home appliances 13.Wherein, each home appliance 13 passes through net
Network is communicated to connect with the webserver 12.The communication connection mode can be wifi, infrared, bluetooth, 3G, 4G, cable broadband
Deng.In the present embodiment, the webserver 12 is cloud server.
Please refer to Fig. 2, in the present embodiment, the system 10 also includes api interface converting unit 14, is connected to this
Between the webserver 12 and home appliance 13.The webserver 12 includes operation historical record unit 120, language scripts storehouse
121st, memory cell 122, log in control unit 123, use habit unit 124 and use habit statistical analysis unit 127.
Wherein, the language scripts storehouse 121 is used to store a variety of initialization language, and every kind of initialization language is that a kind of household electrical appliances are set
The standby bottom machine language used, for example, C++, java, perl, C# etc..The api interface converting unit 14 is used for according to language
Corresponding initialization language arrives the action of configuration unification of hardware and software the conversion of api interface in script bank 121.Specifically,
The home appliance 13 can send the configuration information (as used function and relative parameters setting) of hardware or software to the API
Interface conversion unit 14, the api interface converting unit obtains corresponding initialization language to configure from language scripts storehouse 121
Information is changed to API configuration informations and is uploaded in the webserver 12, and the webserver 12 can send out API configuration informations
The api interface converting unit 14 is delivered to, is converted to API configuration informations and the home appliance 13 with the opriginal language according to acquisition
The configuration of the hardware and software of matching is simultaneously downloaded by home appliance 13.
The user terminal 11 is communicatively coupled by network with a home appliance 13, in the present embodiment, the user
Terminal 11 is NFC device, is communicatively coupled by NFC with the home appliance 13.Further, the user terminal 11 has only
One account information for being used to recognize identity, the home appliance 13 can prestore one or more account informations, and pass through
Checking to account information determines whether that the user terminal 11 carries out logging in connection., should when account information is by verifying
User terminal 11 is set up with the home appliance 13 and communicated to connect, and the home appliance 13 sends to the webserver 12 and logged in
The account information of the home appliance 13, i.e., the account information that the user terminal 11 is used are carried in request, the log on request.Should
Multiple account informations have been prestored in the memory cell 122 of the webserver 12.Also, the webserver 12 logs in control
Multiple account informations that unit 123 processed is stored according to memory cell 122 verify to the account information carried in log on request,
And when being verified, i.e., the account information that the account information carried in the log on request is stored with memory cell 122 is matched,
Set up and communicate to connect with the home appliance 13, while feedback one logs in successful signal to the home appliance 13.
When the home appliance 13 is successfully connected with the webserver 12, that is, receive the feedback logs in successful letter
Number, identity identification information and the api interface of itself are sent by the api interface converting unit 14, to notify the webserver
The identity identification information and workable api interface of 12 home appliances 13.Wherein, the identity identification information can be that household electrical appliances are set
Standby classification (such as air-conditioning, refrigerator, washing machine), can also be the model of home appliance.
The memory cell 122 has also prestored the identity identification information and corresponding usage history of multiple home appliances
Information, wherein, the usage history information can include parameter configuration, user's use habit information of the home appliance etc..
Further, the memory cell 122 is divided into the storage region of multiple ranks, such as first order classification storage region, the second level
Classification storage region ..., and the storage region of the plurality of rank is in tree.It is used to store difference per one-level storage region
Configuration information.For example, first order classification storage region is used for the classification (such as refrigerator, washing machine) for storing home appliance, the
Secondary classification storage region is used to store the other model of each household appliances (the refrigerator, RTS2016 models such as RTS2006 models
Refrigerator), third level classification storage region is used for basic function (the refrigerator tool of such as RTS2006 models for storing each household electrical appliances model
There is refrigeration automatic temperature-control, refrigerate the function of zoned temperature control, the refrigerator of RTS2016 models has digital temperature adjustment, refrigeration zoned temperature control
Function).
When the webserver 12 receives the identity identification information and workable api interface of the home appliance 13 transmission
When, the operation historical record unit 120 inquired about in memory cell 122 whether have matching identity identification information so that it is determined that
Whether the usage history information of the home appliance 13 is had.If not provided, the use habit unit 124 is set according to using household electrical appliances
Standby 13 all API states carry out statistical learning to the use habit of user.
The statistical learning theory of user's use habit will be lifted so that identity identification information is household electrical appliances model as an example below
Example explanation.
The use habit unit 124 sets up module 125 and configuration write-in control module 126 including configuration item.When
When determining that the home appliance 13 does not have usage history information in the webserver 12, the configuration item sets up module 125 and sets up type
Number entrance, and to the home appliance 13 feed back an API and send and ask.The home appliance 13 receives the API and sent after request, hair
The api interface that the home appliance is supported is given to the webserver 12.For example, the API that certain model air-conditioning is supported has refrigeration/system
Heat/ventilation selection (Configuration Values are 0/1/2,0 representative refrigeration, and 1 representative is heated, and 2 represent ventilation), temperature setting (configures scope 16
To wind (Configuration Values 0/1,0, which are represented, to be closed, and 1 representative is opened) 30), is swept up and down, wind is swept in left and right, and (Configuration Values 0/1,0, which are represented, to close, and 1 represents
Open), plasma wind function (Configuration Values 0/1,0, which are represented, to be closed, and 1 representative is opened), (Configuration Values 0/1,0 are represented to close dehumidification function, and 1 represents
Open).
The configuration write-in control module 126 of the webserver 12 sets up all according to the identity information of the home appliance 13
API configuration items, when current all API states using the home appliance 13 after finishing can also be sent to the network by user
Server 12.The storage of these API status informations is arrived corresponding API by the configuration write-in control module 126 of the webserver 12
In configuration item.For example, the use habit statistical analysis unit 127 determines that the classification of the home appliance 13 is washing machine, model
QRS2055, and corresponding API configuration items are set up, the API states can include water level, temperature, rinsing time of washing machine etc..
User after finishing the home appliance 13 using shutdown command is sent, and the home appliance 13 will be current before the shutdown command is responded
All API states be sent in the webserver 12.The configuration writes control module 126 and believes the API states received
Breath is accordingly stored in the API configuration items pre-established.So as to, as described above, completion user use habit, configuration information
Record.
When it is determined that the home appliance 13 has usage history information in the webserver 12, then the webserver 12
Operation historical record unit 120 obtains corresponding usage history information from the memory cell 122 and configured with forming corresponding API
Information, and send initialization requests and API configuration informations to the home appliance 13.The home appliance 13 receives the initialization
When request and API configuration informations, the initialization after start is completed according to the API configuration informations, i.e., configured according to API configuration informations
The corresponding function of home appliance is parameter, and user is that the home appliance for meeting oneself use habit can be used directly.
Further, user is using complete home appliance and sends shutdown command, and the home appliance 13 is responding shutdown life
Current all API states are sent to the webserver 12 before order, then the home appliance 13 responds the shutdown command and closed
Machine.The API status informations received storage is arrived memory cell 122 by the operation historical record unit 120 of the webserver 12
In, and it is corresponding with the usage history information.In the present embodiment, the use habit statistical analysis unit 127 is rerun
User custom API configuration, and by the configuration information update newly calculated into corresponding API configuration items.
Specifically, the use habit statistical analysis unit 127 is accustomed to API configuration bags according to API status information computings user
Include statistical model, mode of learning and memory pattern.Wherein, statistical model refers to the statistics use of use habit statistical analysis unit 127
Family performs most operations in the same equipment, and most initial setting up when being provided as starting shooting of operation.Remember mould
Formula refers to that the API before each home appliance 13 is closed is recorded using operation historical record unit 120 to be configured, and in the home appliance
The operative configuration of last time start can be automatically restored to when starting shooting next time.Mode of learning refers to use habit statistical analysis
Division of operations weights of the counting user of unit 127 in the same equipment, higher, the more long operation weights of nearest operation weights
It is lower, obtain final configuration information after weights are cumulative.
In the present embodiment, the system also includes big data analysis system 20, and the operation historical record unit 120 is by institute
The historical record for having operation is sent to the big data analysis system 20, for other any big data analyses operated based on user
Using as such as personal medical big data analysis, the analysis of individual psychology state big data, personal lifestyle custom big data analysis
Deng.
Referring to Fig. 3, being the schematic flow sheet of the intelligent appliance self-learning method in embodiment of the present invention, this method bag
Include：
Step S30, the user terminal 11 logs in a home appliance 13, so as to set up communication link with the webserver 12
Connect.
The user terminal 11 has the account information for being only used for recognizing identity, and the home appliance 13 can be prestored
One or more account informations, and determine whether that the user terminal 11 carries out the company of logging in by the checking to account information
Connect.When account information is by verifying, the user terminal 11 is set up with the home appliance 13 and communicated to connect, and the home appliance
13 send the account information that the home appliance 13 is carried in log on request, the log on request to the webserver 12, i.e., should
The account information that user terminal 11 is used.Multiple account informations have been prestored in the memory cell 122 of the webserver 12.
Also, the multiple account informations that control unit 123 stores according to memory cell 122 of logging in of the webserver 12 please to logging in
The account information of middle carrying is asked to be verified, and the account information carried when being verified in the log on request and storage
The account information matching that unit 122 is stored, sets up with the home appliance 13 and communicates to connect, while feedback one logs in successful letter
Number to the home appliance 13.
Step S31, the home appliance 13 by the api interface converting unit 14 send identity identification information and itself
Api interface, to notify the identity identification information and workable api interface of the webserver 12 home appliance 13.
Wherein, the identity identification information can be the classification (such as air-conditioning, refrigerator, washing machine) of home appliance, can be with
It is the model of home appliance.
Step S32, the operation historical record unit 120 is inquired about the identity whether with matching in memory cell 122 and known
Other information determines whether the usage history information of the home appliance 13.If it is not, into step S33, otherwise, entering
Enter step S34.
The memory cell 122 has prestored the identity identification information and corresponding usage history letter of multiple home appliances
Breath, wherein, the usage history information can include parameter configuration, user's use habit information of the home appliance etc..Enter
One step, the memory cell 122 is divided into the storage region of multiple ranks, such as first order classification storage region, the second fraction
Class storage region ..., and the storage region of the plurality of rank is in tree.It is used to store different per one-level storage region
Configuration information.For example, first order classification storage region is used for the classification (such as refrigerator, washing machine) for storing home appliance, second
Level classification storage region is used to store the other model of each household appliances (such as refrigerator of RTS2006 models, the ice of RTS2016 models
Case), third level classification storage region is used to storing the basic function of each household electrical appliances model that (refrigerator of such as RTS2006 models to have
Refrigerate automatic temperature-control, refrigerate the function of zoned temperature control, the refrigerator of RTS2016 models has digital temperature adjustment, refrigerates zoned temperature control
Function).
Step S33, the use habit unit 124 is according to all API states using home appliance 13 to user's
Use habit carries out statistical learning.Then, flow terminates.
Wherein, the use habit unit 124 carries out statistical learning to the use habit of user includes following sub-step：
Sub-step S330, the configuration item sets up module 135 and sets up model entrance, and feeds back an API to the home appliance 13
Send request.
Sub-step S331, the API that the home appliance 13 transmission home appliance is supported to the webserver 12.
For example, the API that certain model air-conditioning is supported have the selection of refrigerating/heating/ventilation (Configuration Values are 0/1/2,0 to represent refrigeration,
1 representative is heated, and 2 represent ventilation), temperature setting (configuration scope 16 to 30), wind is swept up and down, and (Configuration Values 0/1,0 represent pass, 1 generation
Table is opened), wind (Configuration Values 0/1,0, which are represented, to be closed, and 1 representative is opened) is swept in left and right, and (Configuration Values 0/1,0 are represented to close plasma wind function, 1 generation
Table is opened), dehumidification function (Configuration Values 0/1,0, which are represented, to be closed, and 1 representative is opened).
Sub-step S332, configuration write-in control module 126 sets up all according to the identity information of the home appliance 13
API configuration items.
Sub-step S333, when current all API states using the home appliance 13 after finishing are sent to the net by user
The API status informations received are accordingly stored what is pre-established by network server 12, configuration write-in control module 126
In API configuration items.
Step S34, the operation historical record unit 120 obtains corresponding usage history information from the memory cell 122
To form corresponding API configuration informations, and initialization requests and API configuration informations are sent to the home appliance 13.
Step S35, the home appliance 13 completes the initialization after start according to the API configuration informations that receive, i.e., according to
The corresponding function of API configuration informations configuration home appliance is parameter, and user is that the family for meeting oneself use habit can be used directly
Electric equipment.
Step S36, user is using complete home appliance and sends shutdown command, and the home appliance 13 is responding the shutdown command
Current all API states are sent to the webserver 12 before, then the home appliance 13 responds shutdown command shutdown.
The API status informations received storage is arrived memory cell 122 by step S37, the operation historical record unit 120
In, and it is corresponding with the usage history information.
In the present embodiment, the use habit statistical analysis unit 127 rerun user custom API configuration, and
By the configuration information update newly calculated into corresponding API configuration items.
Further, the historical record of all operations is sent to the big data and analyzed by the operation historical record unit 120
System 20, application is analyzed so that other are any based on the big data that user operates, individual as such as personal medical big data analysis
Human psychological's state big data is analyzed, personal lifestyle custom big data analysis etc..
A kind of intelligent appliance self learning system and method that the present invention is provided, pass through point of the configuration information to home appliance
Analysis and record, make user by unique account anywhere by user's terminal logs in different home appliances after, it is logical
User's use habit that server memory and study are obtained is crossed, corresponding device is provided with to the configuration being accustomed to for user automatically
And initialization, setting time and the work of user are greatly reduced, and access to your account can across distinct device type, same type
The household electrical appliances of different model are used, so as to complete to set and initialization according to user's custom is automatic.
Embodiments of the invention are the foregoing is only, are not intended to limit the scope of the invention, it is every to utilize this hair
Equivalent structure or equivalent flow conversion that bright specification and accompanying drawing content are made, or directly or indirectly it is used in other related skills
Art field, is included within the scope of the present invention.
Claims (11)
1. a kind of intelligent appliance self-learning method, it is characterised in that methods described includes：
The identity identification information and API information of home appliance are sent to the webserver；
Whether the identity identification information with matching determines whether the home appliance for the webserver inquiry
Usage history information, wherein, the identity identification information of home appliance and corresponding usage history information are previously stored；
When it is determined that there is the identity identification information of matching, obtain corresponding usage history information to form corresponding API with confidence
Breath, and send initialization requests and API configuration informations to the home appliance；Household electrical appliances are completed according to the API configuration informations
The opening initialization of equipment, and configured according to the API configuration informations；
Current API states are sent to after the webserver after being terminated using the home appliance and shut down；And will receive
API status informations it is corresponding with usage history information preserve；
Current API states according to producing after being terminated using the home appliance recalculate computing user custom API configurations, with
And by the configuration information update newly calculated into corresponding API configuration items；Counting user is using same type of household electrical appliances
Division of operations weights during equipment, obtain final configuration information after weights are cumulative, and weights use the household electrical appliances according to user
The time point of equipment determines；
When it is determined that making according to using all API states of the home appliance to user during identity identification information without matching
Statistical learning is carried out with custom.
2. intelligent appliance self-learning method as claimed in claim 1, it is characterised in that send the identification letter of home appliance
Also include before breath and API information to the webserver：
User is inputted for recognizing that the account information of identity logs in home appliance so that and the webserver by a user terminal
Set up communication connection.
3. intelligent appliance self-learning method as claimed in claim 2, it is characterised in that the user is defeated by a user terminal
The account information of access customer identification identity logs in home appliance to be included so as to set up the step of communicating to connect with the webserver：
User is inputted account information and sent by network to the home appliance and deposited in advance with basis by the user terminal
The account information of storage is verified to determine whether that the user terminal logs in connection to the account information of the input；
When the account information of the input is by verifying, the user terminal is set up with the home appliance and communicated to connect, and
Sent by the home appliance and carry the log on request of the account information to the webserver；
The webserver enters according to the multiple account informations prestored to the account information carried in the log on request
Row checking；
Set up and communicate to connect with the home appliance when the account information carried in the log on request is by verifying.
4. intelligent appliance self-learning method as claimed in claim 1, it is characterised in that according to the institute using the home appliance
Having API states to carry out statistical learning to the use habit of user includes：
Entrance corresponding with the identity identification information is set up, and an API is fed back to the home appliance and sends request；
API that the home appliance supports is sent to the webserver；
All API configuration items are set up according to the identity identification information of the home appliance；And
The webserver will be sent to using the current API states of the home appliance, and be correspondingly saved in and pre-establishes
API configuration items in.
5. a kind of intelligent appliance self learning system, including user terminal, the webserver and multiple home appliances, each household electrical appliances
Equipment is communicated to connect with the webserver, it is characterised in that the webserver includes：
Memory cell, has prestored the identity identification information and corresponding usage history information of multiple home appliances；
Operation historical record unit, identity identification information and API information for being sent according to the home appliance are deposited described
Inquire about whether the identity identification information with matching determines whether the usage history with the home appliance in storage unit
Information；
When it is determined that there is the identity identification information of matching, the operation historical record unit is obtained accordingly from the memory cell
Usage history information to form corresponding API configuration informations, and send initialization requests to the home appliance and API matches somebody with somebody
Confidence ceases, and the home appliance completes opening initialization and configuration according to the API configuration informations；
The operation historical record unit is additionally operable to current all API states of home appliance feedback described in the use that will receive
Information is stored into memory cell, and corresponding with the usage history information；
The webserver is also including the use of habit statistical analytic unit, for being produced according to after being terminated using the home appliance
Raw current API states recalculate user's custom API configurations, and by the configuration information update newly calculated to correspondence
API configuration items in；Division of operations weights of counting user when using same type of home appliance, after weights are cumulative
Final configuration information is obtained, weights are determined according to user using the time point of the home appliance；
Use habit unit, when the operation historical record unit determines the usage history information without the home appliance
When for carrying out statistical learning to the use habit of user according to the API states using the home appliance.
6. intelligent appliance self learning system as claimed in claim 5, it is characterised in that user passes through account on a user terminal
Number home appliance described in log communicates to connect so as to be set up with the webserver, and when successful connection by the family
Electric equipment sends the identity identification information and API information of the home appliance to the webserver.
7. intelligent appliance self learning system as claimed in claim 6, it is characterised in that user is inputted by the user terminal
Account information is simultaneously sent to the home appliance with according to account information of the account information prestored to input by network
Verified to determine whether that the user terminal logs in connection, when the account information of input is by verifying, the use
Family terminal is set up with the home appliance and communicated to connect, and please by logging in for the home appliance transmission carrying account information
Ask to the webserver；
The webserver also includes logging in control unit, and multiple accounts for being prestored according to the memory cell are believed
Cease and the account information carried in the log on request is verified, and when the account information carried in the log on request passes through
Set up and communicate to connect with the home appliance during checking.
8. intelligent appliance self learning system as claimed in claim 7, it is characterised in that the user terminal is NFC device, is led to
Cross NFC and send the account information to the home appliance.
9. intelligent appliance self learning system as claimed in claim 5, it is characterised in that the use habit unit bag
Include：
Configuration item sets up module, is fed back for setting up entrance corresponding with the identity identification information, and to the home appliance
One API sends request, to trigger the API that the home appliance feeds back its support；
Configuration write-in control module, all API configuration items are set up according to the identity identification information of the home appliance, will be used
The current API status informations of the home appliance feedback are stored into corresponding API configuration items.
10. intelligent appliance self learning system as claimed in claim 5, it is characterised in that the system also turns including api interface
Unit is changed, the webserver also includes the language scripts storehouse for being used to store a variety of initialization language, the api interface conversion
Unit is used to mutually be turned the API information and the configuration information according to corresponding initialization language in language scripts storehouse
Change.
11. intelligent appliance self learning system as claimed in claim 5, it is characterised in that also including big data analysis system, is used
In the usage history information for receiving the webserver transmission, and should to usage history information progress big data analysis
With.
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| CN201410355368.XA CN104092775B (en) | 2014-07-24 | 2014-07-24 | Intelligent appliance self-learning method and system |
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| CN201410355368.XA CN104092775B (en) | 2014-07-24 | 2014-07-24 | Intelligent appliance self-learning method and system |
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