CN108769159A - A kind of electronic cookbook intelligent recommendation method - Google Patents
A kind of electronic cookbook intelligent recommendation method Download PDFInfo
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- CN108769159A CN108769159A CN201810469750.1A CN201810469750A CN108769159A CN 108769159 A CN108769159 A CN 108769159A CN 201810469750 A CN201810469750 A CN 201810469750A CN 108769159 A CN108769159 A CN 108769159A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/50—Network services
- H04L67/55—Push-based network services
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/50—Network services
- H04L67/535—Tracking the activity of the user
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- Computer Networks & Wireless Communication (AREA)
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- Computer Hardware Design (AREA)
- General Engineering & Computer Science (AREA)
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
Abstract
A kind of electronic cookbook intelligent recommendation method provided by the invention, by obtaining the operation behavior information of user's registration information and user to electronic cookbook, determine user's portrait label of user, the menu of user is recommended to according to user's portrait tag match, solve the problems, such as that existing recommendation method recommendation is inaccurate, can menu accurately be pushed to user according to the demand of user, avoid time waste caused by user browses uninterested menu, the user experience is improved.
Description
Technical field
The present embodiments relate to personalized recommendation technical fields, and in particular to a kind of electronic cookbook intelligent recommendation method.
Background technology
With the development of internet, the also growing growth of electronic cookbook class business, the menu quantity of major menu website
Increase severely.How suitable menu recommended into suitable user, makes user within the limited browsing time, obtain and oneself want to see
The content arrived has become the major issue of electronic cookbook business scope one.
In the sector field, traditional electronic cookbook way of recommendation, usually will most popular or newest menu to all
User recommends, and this way of recommendation has that precision is not high, and user may waste the plenty of time and not feel emerging
On the menu of interest, user experience is reduced；Another program is by the basic personal information of user, such as taste preference, dieting information
As the foundation for carrying out menu recommendation to user, the shortcomings that being recommended using which, is not accounting for user in terms of food and drink
Hobby be easy to happen large change, can not accurately obtain user in the recent period to the real demand of menu；Yet another aspect will
The historical viewings menu of user is as the reference frame for recommending menu for user, this scheme, first, can not be by the long-term need of user
It asks such as health, weight-reducing etc. to take into account, second is that being difficult to quantitatively indicate consumer taste by historical viewings, recommends menu result
Without explanatory well, third, being difficult to carry out real-time user preference feature description and dish by the current navigation patterns of user
Spectrum is recommended.
Invention content
In order to solve the above-mentioned technical problem above-mentioned technical problem or is at least partly solved, an embodiment of the present invention provides
A kind of electronic cookbook intelligent recommendation method.
In view of this, in a first aspect, the embodiment of the present invention provides a kind of electronic cookbook intelligent recommendation method, including：
From User Information Database, the log-on message of user is obtained；
Obtain operation behavior information of the user to electronic cookbook；
According to log-on message and operation behavior information, user's portrait label of the user is determined；
According to user's portrait tag match menu；
Matched menu is pushed to the user.
According to log-on message and operation behavior information, user's portrait label of the user is determined, including：
The initial user portrait label of user is determined according to user's registration information；
The historical operation behavior of electronic cookbook carries out initial user portrait label information according to the user of acquisition perfect
And amendment, obtain user's portrait label.
According to log-on message and operation behavior information, user's portrait label of the user is determined, including：
The initial user portrait label of user is determined according to user's registration information；
The real-time operation behavior of electronic cookbook carries out initial user portrait label information according to the user of acquisition perfect
And amendment, obtain user's portrait label.
The operation behavior information includes：It browses, collect, search for, comment on and/or thumbs up.
According to user's portrait tag match menu, including：
According to correspondence, user and the user of the menu that pre-establishes and menu label draw a portrait label correspondence with
And the correspondence of user tag and menu label, the correspondence of user and menu label are obtained, determines matching menu；
According to user and the correspondence of menu label and the correspondence of menu and menu label, matching menu is calculated
Recommendation index；
Menu recommendation order is determined according to the recommendation index of the matching menu.
According to user and the correspondence of menu label and the correspondence of menu and menu label, dish is calculated as follows
The recommendation index of spectrum：
Wherein, SnIt is menu n for the recommendation index of user, liFor the correspondence of user and menu label i, if with
Family has menu label i, then li=1, otherwise li=0, pinFor the correspondence of menu n and menu label i, if menu n has
Menu label i, then pin=1, otherwise pin=0, ωiFor setting menu label i to recommend index weighing factor, m is menu
The sum of label.
Menu recommendation order is determined according to the recommendation index of the matching menu, including：
According to recommending, index is descending to be ranked up the matching menu.
According to correspondence, user and the user of the menu that pre-establishes and menu label draw a portrait label correspondence with
And the correspondence of user tag and menu label, the correspondence of user and menu label are obtained, determines matching menu, before
Further include：
By manually mark or machine learning method be menu add menu label.
User's portrait label, including：Region, user's taste, the style of cooking that user aviods certain food, user likes, user where user
Cooking method, user's occupation and/or the age of user liked.
Optionally,
Second aspect, the embodiment of the present invention also provide a kind of electronic cookbook intelligent recommendation system, including：
First acquisition module, for from User Information Database, obtaining the log-on message of user；
Second acquisition module, for obtaining operation behavior information of the user to electronic cookbook；
Portrait module, for according to log-on message and operation behavior information, determining user's portrait label of the user；
Menu matching module, for according to user's portrait tag match menu；
Pushing module, for matched menu to be pushed to the user.
The portrait module determines user's portrait label of the user, packet according to log-on message and operation behavior information
It includes：
The initial user portrait label of user is determined according to user's registration information；
The historical operation behavior of electronic cookbook carries out initial user portrait label information according to the user of acquisition perfect
And amendment, obtain user's portrait label.
The portrait module determines user's portrait label of the user, packet according to log-on message and operation behavior information
It includes：
The initial user portrait label of user is determined according to user's registration information；
The real-time operation behavior of electronic cookbook carries out initial user portrait label information according to the user of acquisition perfect
And amendment, obtain user's portrait label.
Fourth aspect, the embodiment of the present invention also propose a kind of non-transient computer readable storage medium, the non-transient meter
Calculation machine readable storage medium storing program for executing stores computer instruction, and the computer instruction makes the computer execute side as described in relation to the first aspect
The step of method.
Compared with prior art, a kind of electronic cookbook intelligent recommendation method that the embodiment of the present invention proposes, by obtaining user
Log-on message and user determine user's portrait label of user, are drawn a portrait and marked according to user to the operation behavior information of electronic cookbook
Label matching recommends to the menu of user, solves the problems, such as that existing recommendation method recommendation is inaccurate, can be according to user
Demand accurately push menu to user, avoiding the time caused by user browses uninterested menu wastes, and improves
User experience.
Description of the drawings
In order to illustrate the technical solution of the embodiments of the present invention more clearly, below will be in embodiment or description of the prior art
Required attached drawing is briefly described, it should be apparent that, the accompanying drawings in the following description is only some realities of the present invention
Example is applied, it for those of ordinary skill in the art, without having to pay creative labor, can also be attached according to these
Figure obtains other attached drawings.
Fig. 1 is a kind of flow chart of electronic cookbook intelligent recommendation method provided in an embodiment of the present invention；
Fig. 2 is a kind of block diagram of electronic cookbook intelligent recommendation system provided by one embodiment of the present invention.
Specific implementation mode
In order to make the object, technical scheme and advantages of the embodiment of the invention clearer, below in conjunction with the embodiment of the present invention
In attached drawing, technical scheme in the embodiment of the invention is clearly and completely described, it is clear that described embodiment is
A part of the embodiment of the present invention, instead of all the embodiments.Based on the embodiments of the present invention, ordinary skill people
The every other embodiment that member is obtained without making creative work, shall fall within the protection scope of the present invention.
Referring to Fig.1, Fig. 1 is a kind of electronic cookbook intelligent recommendation method provided by one embodiment of the present invention, it may include with
Lower step：
From User Information Database, the log-on message of user is obtained；
Obtain operation behavior information of the user to electronic cookbook；
According to log-on message and operation behavior information, user's portrait label of the user is determined；
According to user's portrait tag match menu；
Matched menu is pushed to the user.
According to log-on message and operation behavior information, user's portrait label of the user is determined, including：
The initial user portrait label of user is determined according to user's registration information；
The historical operation behavior of electronic cookbook carries out initial user portrait label information according to the user of acquisition perfect
And amendment, obtain user's portrait label.
According to log-on message and operation behavior information, user's portrait label of the user is determined, including：
The initial user portrait label of user is determined according to user's registration information；
The real-time operation behavior of electronic cookbook carries out initial user portrait label information according to the user of acquisition perfect
And amendment, obtain user's portrait label.
The operation behavior information includes：It browses, collect, search for, comment on and/or thumbs up.
According to user's portrait tag match menu, including：
According to correspondence, user and the user of the menu that pre-establishes and menu label draw a portrait label correspondence with
And the correspondence of user tag and menu label, the correspondence of user and menu label are obtained, determines matching menu；
According to user and the correspondence of menu label and the correspondence of menu and menu label, matching menu is calculated
Recommendation index；
Menu recommendation order is determined according to the recommendation index of the matching menu.
According to user and the correspondence of menu label and the correspondence of menu and menu label, dish is calculated as follows
The recommendation index of spectrum：
Wherein, SnIt is menu n for the recommendation index of user, liFor the correspondence of user and menu label i, if with
Family has menu label i, then li=1, otherwise li=0, pinFor the correspondence of menu n and menu label i, if menu n has
Menu label i, then pin=1, otherwise pin=0, ωiFor setting menu label i to recommend index weighing factor, m is menu
The sum of label.
Menu recommendation order is determined according to the recommendation index of the matching menu, including：
According to recommending, index is descending to be ranked up the matching menu.
According to correspondence, user and the user of the menu that pre-establishes and menu label draw a portrait label correspondence with
And the correspondence of user tag and menu label, the correspondence of user and menu label are obtained, determines matching menu, before
Further include：
By manually mark or machine learning method be menu add menu label.
User's portrait label, including：Region, user's taste, the style of cooking that user aviods certain food, user likes, user where user
Cooking method, user's occupation and/or the age of user liked.
One specific example
The recommendation main body of the present invention is electronic cookbook.Electronic cookbook can have multiple menu labels, to menu into
Row classifies and particular content is described, for example, can be divided into Sichuan cuisine, Guangdong dishes, Shandong cuisine, Wei Yang Dish etc. by the style of cooking, it can by food materials
It is divided into meat, seafood, vegetarian diet etc..The recommended of this programme is the user of menu website.User can also have multiple portraits mark
Label, for example, health, weight-reducing, pregnant woman, student etc..
A kind of electronic cookbook intelligent recommendation method provided in this embodiment, including：
1, menu label is added.
Electronic cookbook is that user is uploaded to website manually in the present embodiment, and the menu label of menu carries out hand by operation personnel
Dynamic addition.The corresponding relation database for obtaining menu and menu label is as shown in table 1：
Table 1
2, addition user portrait label.
The embodiment of the present invention determines that user's portrait stamp methods include the following steps：
Pass through the information filled in when user's registration, the addition users such as user and region, taste, occupation, age portrait label
Correspondence.
It obtains in user's certain time to the operation behavior of menu, such as browsing of the nearly one month to menu, collection
Or comment etc. analyzes user and its according to the nearly one month browsing of user, the corresponding menu label of menu of collection or comment
The correspondence of users' portrait label such as recent interest preference.
User's current time is analyzed to the operation behavior of menu, for example, the nearly ten minutes to the browsing of menu, collection or
Comment etc., according to the nearly ten minutes browsing of user, the corresponding menu label of menu of collection or comment, analysis user is close with it
The correspondence of the portrait label such as phase interest preference.
Above three step, obtains user and the corresponding relation database of user's portrait label is as shown in table 2：
Table 2
| User | User tag |
| User A | It replenishes the calcium |
| User A | Increase flesh |
| User A | New hand |
| User B | Pregnant woman |
| User B | It is light |
| User B | It bakes |
| User C | Health |
3, build and safeguard the corresponding relation database of user's portrait label and menu label, as shown in table 3：
Table 3
| User tag | Menu label |
| It bakes | Egg Tarts |
| Health | Hair care |
| Pregnant woman | Pregnant woman's recipe |
4, in above-described embodiment, according to obtained menu-menu label, user-user label, user tag-menu mark
The incidence relation of label, is matched, and the correspondence of user-menu label can be obtained, and further calculates out final each use
The recommendation exponential relationship at family and menu to be recommended.
In the calculating for recommending index, the influence that different type label recommends finally matching gained index can be adjusted flexibly
Weight.Specific calculation is, with U={ li| i=1 ..., m } indicate that user corresponds to menu Label space, if user has
I-th of label, then li=1, otherwise li=0；WithIndicate that menu corresponds to menu label
Space, pinFor the correspondence of menu n and menu label i, if menu n has menu label i, pin=1, otherwise pin=0,
ωiFor setting menu label i to recommend index weighing factor, m be menu label sum；With W={ ωi| i=1 ...,
M } indicate weighing factor of the menu label to consequently recommended index.
Menu n is as follows for the recommendation index of user：
Finally, above-described embodiment, which takes, recommends the menu that index S sorts from big to small personalized as user's menu user
Recommendation results.
In the above calculating process, C is the matrix that all menu labels to be recommended are constituted, and can be illustrated with following table 4, every in table
Whether one row expression menu includes some menu label, and 1 is comprising 0 is not comprising each menu of expression includes per a line in table
Menu label, 1 for comprising, 0 for not comprising.
Table 4
U is user's portrait label vector, can be illustrated with the following table 5, which indicates the corresponding menu mark of user's portrait label
Label, 1 for comprising, 0 for not comprising.
Table 5
Therefore, above-mentioned calculating process, actually by the corresponding menu label of user's portrait label and the included menu mark of menu
Label carry out matched process.The recommendation index s finally obtained is the weighting of the menu label and menu label weight that match
Summation.
Based on identical inventive concept, the embodiment of the present invention also provides a kind of electronic cookbook intelligent recommendation system, with reference to figure
2, the electronic cookbook intelligent recommendation system may include：
First acquisition module, for from User Information Database, obtaining the log-on message of user；
Second acquisition module, for obtaining operation behavior information of the user to electronic cookbook；
Portrait module, for according to log-on message and operation behavior information, determining user's portrait label of the user；
Menu matching module, for according to user's portrait tag match menu；
Pushing module, for matched menu to be pushed to the user.
The portrait module determines user's portrait label of the user, packet according to log-on message and operation behavior information
It includes：
The initial user portrait label of user is determined according to user's registration information；
The historical operation behavior of electronic cookbook carries out initial user portrait label information according to the user of acquisition perfect
And amendment, obtain user's portrait label.
The portrait module determines user's portrait label of the user, packet according to log-on message and operation behavior information
It includes：
The initial user portrait label of user is determined according to user's registration information；
The real-time operation behavior of electronic cookbook carries out initial user portrait label information according to the user of acquisition perfect
And amendment, obtain user's portrait label.
The embodiment of the present invention also provides a kind of non-transient computer readable storage medium, and the non-transient computer is readable to deposit
Storage media stores computer instruction, and the computer instruction makes the computer execute the method that each method embodiment is provided,
Such as including：
From User Information Database, the log-on message of user is obtained；
Obtain operation behavior information of the user to electronic cookbook；
According to log-on message and operation behavior information, user's portrait label of the user is determined；
According to user's portrait tag match menu；
Matched menu is pushed to the user.
It is understood that embodiments described herein can use hardware, software, firmware, middleware, microcode or its
It combines to realize.For hardware realization, processing unit may be implemented in one or more application-specific integrated circuits
(ApplicationSpecificIntegratedCircuits, ASIC), digital signal processor
(DigitalSignalProcessing, DSP), digital signal processing appts (DSPDevice, DSPD), programmable logic device
(ProgrammableLogicDevice, PLD), field programmable gate array (Field-ProgrammableGateArray,
FPGA), general processor, controller, microcontroller, microprocessor, other electronics lists for executing herein described function
In member or combinations thereof.
For software implementations, the techniques described herein can be realized by executing the unit of function described herein.Software generation
Code is storable in memory and is executed by processor.Memory can in the processor or portion realizes outside the processor.
Those of ordinary skill in the art may realize that lists described in conjunction with the examples disclosed in the embodiments of the present disclosure
Member and algorithm steps can be realized with the combination of electronic hardware or computer software and electronic hardware.These functions are actually
It is implemented in hardware or software, depends on the specific application and design constraint of technical solution.Professional technician
Each specific application can be used different methods to achieve the described function, but this realization is it is not considered that exceed
The scope of the present invention.
It is apparent to those skilled in the art that for convenience and simplicity of description, the system of foregoing description,
The specific work process of device and unit, can refer to corresponding processes in the foregoing method embodiment, and details are not described herein.
In embodiment provided herein, it should be understood that disclosed device and method can pass through others
Mode is realized.For example, the apparatus embodiments described above are merely exemplary, for example, the division of the unit, only
A kind of division of logic function, formula that in actual implementation, there may be another division manner, such as multiple units or component can combine or
Person is desirably integrated into another system, or some features can be ignored or not executed.Another point, shown or discussed is mutual
Between coupling, direct-coupling or communication connection can be INDIRECT COUPLING or communication link by some interfaces, device or unit
It connects, can be electrical, machinery or other forms.
The unit illustrated as separating component may or may not be physically separated, aobvious as unit
The component shown may or may not be physical unit, you can be located at a place, or may be distributed over multiple
In network element.Some or all of unit therein can be selected according to the actual needs to realize the mesh of this embodiment scheme
's.
In addition, each functional unit in each embodiment of the present invention can be integrated in a processing unit, it can also
It is that each unit physically exists alone, it can also be during two or more units be integrated in one unit.
It, can be with if the function is realized in the form of SFU software functional unit and when sold or used as an independent product
It is stored in a computer read/write memory medium.Based on this understanding, the technical solution of the embodiment of the present invention is substantially
The part of the part that contributes to existing technology or the technical solution can embody in the form of software products in other words
Come, which is stored in a storage medium, including some instructions are used so that a computer equipment (can
To be personal computer, server or the network equipment etc.) execute all or part of each embodiment the method for the present invention
Step.And storage medium above-mentioned includes：USB flash disk, mobile hard disk, ROM, RAM, magnetic disc or CD etc. are various can to store program
The medium of code.
It should be noted that herein, the terms "include", "comprise" or its any other variant are intended to non-row
His property includes, so that process, method, article or device including a series of elements include not only those elements, and
And further include other elements that are not explicitly listed, or further include for this process, method, article or device institute it is intrinsic
Element.In the absence of more restrictions, the element limited by sentence "including a ...", it is not excluded that including this
There is also other identical elements in the process of element, method, article or device.
Through the above description of the embodiments, those skilled in the art can be understood that each reality of the present invention
Applying the method described in example can add the mode of required general hardware platform to realize by software, naturally it is also possible to by hardware,
But the former is more preferably embodiment in many cases.Based on this understanding, technical scheme of the present invention is substantially in other words
The part that contributes to existing technology can be expressed in the form of software products, which is stored in one
In a storage medium (such as ROM/RAM, magnetic disc, CD), including some instructions are used so that a station terminal equipment (can be hand
Machine, computer, server, air conditioner either network equipment etc.) execute method or implementation described in each embodiment of the present invention
Method described in certain parts of example.
It these are only the preferred embodiment of the present invention, be not intended to limit the scope of the invention, it is every to utilize this hair
Equivalent structure or equivalent flow shift made by bright specification and accompanying drawing content is applied directly or indirectly in other relevant skills
Art field, is included within the scope of the present invention.
Claims (9)
1. a kind of electronic cookbook intelligent recommendation method, which is characterized in that including：
From User Information Database, the log-on message of user is obtained；
Obtain operation behavior information of the user to electronic cookbook；
According to log-on message and operation behavior information, user's portrait label of the user is determined；
According to user's portrait tag match menu；
Matched menu is pushed to the user.
2. electronic cookbook intelligent recommendation method as described in claim 1, which is characterized in that according to log-on message and operation behavior
Information determines user's portrait label of the user, including：
The initial user portrait label of user is determined according to user's registration information；
The historical operation behavior of electronic cookbook is improved and repaiied to initial user portrait label information according to the user of acquisition
Just, user's portrait label is obtained.
3. electronic cookbook intelligent recommendation method as described in claim 1, which is characterized in that according to log-on message and operation behavior
Information determines user's portrait label of the user, including：
The initial user portrait label of user is determined according to user's registration information；
The real-time operation behavior of electronic cookbook is improved and repaiied to initial user portrait label information according to the user of acquisition
Just, user's portrait label is obtained.
4. electronic cookbook intelligent recommendation method as described in claim 1, which is characterized in that the operation behavior information includes：
It browses, collect, search for, comment on and/or thumbs up.
5. electronic cookbook intelligent recommendation method as described in claim 1, which is characterized in that according to user's portrait tag match dish
Spectrum, including：
According to the menu pre-established and the correspondence of menu label, the correspondence and use of user and user's portrait label
The correspondence of family label and menu label obtains the correspondence of user and menu label, determines matching menu；
According to user and the correspondence of menu label and the correspondence of menu and menu label, pushing away for matching menu is calculated
Recommend index；
Menu recommendation order is determined according to the recommendation index of the matching menu.
6. electronic cookbook intelligent recommendation method as claimed in claim 5, which is characterized in that according to pair of user and menu label
It should be related to and the correspondence of menu and menu label, the recommendation index of menu is calculated as follows：
Wherein, SnIt is menu n for the recommendation index of user, liFor the correspondence of user and menu label i, if user has
There is menu label i, then li=1, otherwise li=0, pinFor the correspondence of menu n and menu label i, if menu n has menu
Label i, then pin=1, otherwise pin=0, ωiFor setting menu label i to recommend index weighing factor, m be menu label
Sum.
7. electronic cookbook intelligent recommendation method as claimed in claim 5, which is characterized in that according to the recommendation of the matching menu
Index determines menu recommendation order, including：
According to recommending, index is descending to be ranked up the matching menu.
8. electronic cookbook intelligent recommendation method as claimed in claim 5, which is characterized in that according to the menu and dish pre-established
Compose the correspondence of label, the corresponding pass of user and the correspondence of user's portrait label and user tag and menu label
System obtains the correspondence of user and menu label, determines matching menu, further includes before：
By manually mark or machine learning method be menu add menu label.
9. electronic cookbook intelligent recommendation method as described in claim 1, which is characterized in that user's portrait label, including：User
Cooking method, user's occupation and/or the use that place region, user's taste, the style of cooking that user aviods certain food, user likes, user like
The family age.
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| CN112309543A (en) * | 2019-08-01 | 2021-02-02 | 广东美的白色家电技术创新中心有限公司 | Recipe recommendation processing method and device |
| CN113330475A (en) * | 2019-05-20 | 2021-08-31 | 深圳市欢太科技有限公司 | Information recommendation method and device, electronic equipment and storage medium |
| CN114416198A (en) * | 2021-12-31 | 2022-04-29 | 成都易达数安科技有限公司 | APP column intelligent sequencing method based on user image |
Citations (16)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20070226353A1 (en) * | 2006-03-24 | 2007-09-27 | George Eino Ruul | System and method for providing and maintaining dynamic media |
| US20110071805A1 (en) * | 2004-11-19 | 2011-03-24 | Chandra Pendyala | Automated method and system for object configuration |
| CN104957965A (en) * | 2015-06-27 | 2015-10-07 | 广东天际电器股份有限公司 | Intelligent cooking system capable of recognizing geographic position of user and judging preference of user and application of intelligent cooking system |
| CN105635251A (en) * | 2015-12-21 | 2016-06-01 | 美的集团股份有限公司 | Recipe pushing method and system and cloud server |
| CN105701092A (en) * | 2014-11-24 | 2016-06-22 | 中国移动通信集团公司 | Method and device for automatically recommending menu |
| CN105824912A (en) * | 2016-03-15 | 2016-08-03 | 平安科技（深圳）有限公司 | Personalized recommending method and device based on user portrait |
| CN105915439A (en) * | 2016-04-18 | 2016-08-31 | 百度在线网络技术（北京）有限公司 | Information pushing method, device and system |
| CN106021564A (en) * | 2016-05-30 | 2016-10-12 | 美的集团股份有限公司 | Method and device for recommending menus |
| CN106126582A (en) * | 2016-06-20 | 2016-11-16 | 乐视控股（北京）有限公司 | Recommend method and device |
| CN106288634A (en) * | 2016-08-04 | 2017-01-04 | 海信集团有限公司 | Menu recommends method, device and intelligent refrigerator |
| CN106383882A (en) * | 2016-09-13 | 2017-02-08 | 北京三快在线科技有限公司 | Information recommendation method and device and server |
| CN106874435A (en) * | 2017-01-25 | 2017-06-20 | 北京航空航天大学 | User portrait construction method and device |
| CN107302579A (en) * | 2017-06-30 | 2017-10-27 | 广东美的厨房电器制造有限公司 | Menu recommends methods, devices and systems |
| CN107590673A (en) * | 2017-03-17 | 2018-01-16 | 南方科技大学 | user classification method and device |
| CN107992583A (en) * | 2017-12-07 | 2018-05-04 | 合肥美的智能科技有限公司 | Information-pushing method and information push-delivery apparatus, equipment and storage medium |
| CN109408732A (en) * | 2018-12-29 | 2019-03-01 | 珠海优特智厨科技有限公司 | A kind of method and device for recommending menu |
-
2018
- 2018-05-16 CN CN201810469750.1A patent/CN108769159A/en active Pending
Patent Citations (16)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20110071805A1 (en) * | 2004-11-19 | 2011-03-24 | Chandra Pendyala | Automated method and system for object configuration |
| US20070226353A1 (en) * | 2006-03-24 | 2007-09-27 | George Eino Ruul | System and method for providing and maintaining dynamic media |
| CN105701092A (en) * | 2014-11-24 | 2016-06-22 | 中国移动通信集团公司 | Method and device for automatically recommending menu |
| CN104957965A (en) * | 2015-06-27 | 2015-10-07 | 广东天际电器股份有限公司 | Intelligent cooking system capable of recognizing geographic position of user and judging preference of user and application of intelligent cooking system |
| CN105635251A (en) * | 2015-12-21 | 2016-06-01 | 美的集团股份有限公司 | Recipe pushing method and system and cloud server |
| CN105824912A (en) * | 2016-03-15 | 2016-08-03 | 平安科技（深圳）有限公司 | Personalized recommending method and device based on user portrait |
| CN105915439A (en) * | 2016-04-18 | 2016-08-31 | 百度在线网络技术（北京）有限公司 | Information pushing method, device and system |
| CN106021564A (en) * | 2016-05-30 | 2016-10-12 | 美的集团股份有限公司 | Method and device for recommending menus |
| CN106126582A (en) * | 2016-06-20 | 2016-11-16 | 乐视控股（北京）有限公司 | Recommend method and device |
| CN106288634A (en) * | 2016-08-04 | 2017-01-04 | 海信集团有限公司 | Menu recommends method, device and intelligent refrigerator |
| CN106383882A (en) * | 2016-09-13 | 2017-02-08 | 北京三快在线科技有限公司 | Information recommendation method and device and server |
| CN106874435A (en) * | 2017-01-25 | 2017-06-20 | 北京航空航天大学 | User portrait construction method and device |
| CN107590673A (en) * | 2017-03-17 | 2018-01-16 | 南方科技大学 | user classification method and device |
| CN107302579A (en) * | 2017-06-30 | 2017-10-27 | 广东美的厨房电器制造有限公司 | Menu recommends methods, devices and systems |
| CN107992583A (en) * | 2017-12-07 | 2018-05-04 | 合肥美的智能科技有限公司 | Information-pushing method and information push-delivery apparatus, equipment and storage medium |
| CN109408732A (en) * | 2018-12-29 | 2019-03-01 | 珠海优特智厨科技有限公司 | A kind of method and device for recommending menu |
Non-Patent Citations (3)
| Title |
|---|
| 佚名: ""(40条消息) 如何实现基于内容和用户画像的个性化推荐"", 《HTTPS://BLOG.CSDN.NET/U010159842/ARTICLE/DETAILS/53390723》 * |
| 佚名: ""基于内容和用户画像的个性化推荐"", 《HTTP://WWW.360DOC.COM/CONTENT/17/0418/11/2459_646511412.SHTML》 * |
| 曾子明: "《信息推荐系统》", 31 May 2013 * |
Cited By (22)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109544288A (en) * | 2018-11-15 | 2019-03-29 | 拉扎斯网络科技（上海）有限公司 | User data processing method and device |
| CN111192657A (en) * | 2018-11-15 | 2020-05-22 | 宁波方太厨具有限公司 | Menu recommendation method based on user behavior heat |
| CN109741125A (en) * | 2018-11-27 | 2019-05-10 | 口碑(上海)信息技术有限公司 | Recommend method and device, the storage medium, electronic device of vegetable |
| CN109684554A (en) * | 2018-12-26 | 2019-04-26 | 腾讯科技（深圳）有限公司 | The determination method and news push method of the potential user of news |
| CN113330475A (en) * | 2019-05-20 | 2021-08-31 | 深圳市欢太科技有限公司 | Information recommendation method and device, electronic equipment and storage medium |
| CN113330475B (en) * | 2019-05-20 | 2024-06-04 | 深圳市欢太科技有限公司 | Information recommendation method, device, electronic equipment and storage medium |
| CN112149029B (en) * | 2019-06-26 | 2023-07-07 | 北京百度网讯科技有限公司 | Method and device for determining user value viewing labels |
| CN112149029A (en) * | 2019-06-26 | 2020-12-29 | 北京百度网讯科技有限公司 | Method and device for determining user value viewing label |
| CN110335118A (en) * | 2019-07-04 | 2019-10-15 | 合肥美的电冰箱有限公司 | Menu recommended method, menu recommendation apparatus and machine readable storage medium |
| WO2021000521A1 (en) * | 2019-07-04 | 2021-01-07 | 合肥美的电冰箱有限公司 | Recipe recommendation method, recipe recommendation device and machine readable storage medium |
| CN110472145B (en) * | 2019-07-25 | 2022-11-29 | 维沃移动通信有限公司 | Content recommendation method and electronic equipment |
| CN110472145A (en) * | 2019-07-25 | 2019-11-19 | 维沃移动通信有限公司 | A kind of content recommendation method and electronic equipment |
| CN112309543A (en) * | 2019-08-01 | 2021-02-02 | 广东美的白色家电技术创新中心有限公司 | Recipe recommendation processing method and device |
| CN111125533A (en) * | 2019-12-26 | 2020-05-08 | 珠海格力电器股份有限公司 | Menu recommendation method and device and computer readable storage medium |
| CN111552873A (en) * | 2020-04-21 | 2020-08-18 | 佛山市顺德区美的洗涤电器制造有限公司 | Menu recommendation method and device and storage medium |
| CN111625726A (en) * | 2020-06-02 | 2020-09-04 | 小红书科技有限公司 | User portrait processing method and device |
| CN111859121A (en) * | 2020-07-01 | 2020-10-30 | 海尔优家智能科技（北京）有限公司 | Method, device and equipment for menu recommendation |
| CN111858688A (en) * | 2020-07-20 | 2020-10-30 | 海尔优家智能科技（北京）有限公司 | Textile material, color chart recommendation method and device and storage medium |
| CN111858688B (en) * | 2020-07-20 | 2024-05-24 | 海尔优家智能科技（北京）有限公司 | Textile material, color card recommendation method and device and storage medium |
| CN111898026A (en) * | 2020-08-04 | 2020-11-06 | 广州视源电子科技股份有限公司 | User label generation method and device, electronic equipment and readable storage medium |
| CN112199593A (en) * | 2020-10-14 | 2021-01-08 | 珠海格力电器股份有限公司 | Menu recommendation method and device |
| CN114416198A (en) * | 2021-12-31 | 2022-04-29 | 成都易达数安科技有限公司 | APP column intelligent sequencing method based on user image |
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