CN112163548A - Recipe recommendation method and apparatus - Google Patents
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- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
- G06V40/161—Detection; Localisation; Normalisation
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- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
- G06V40/161—Detection; Localisation; Normalisation
- G06V40/166—Detection; Localisation; Normalisation using acquisition arrangements
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- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
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Abstract
The application provides a recipe recommendation method and device. The method comprises the following steps: receiving face data of a user, and generating mood grade information according to the face data; receiving physical sign data of a user, and generating health grade information according to the physical sign data; and generating a recommended menu of the user at least according to the mood grade information and the health grade information. The technical problems that the recommended recipes cannot accurately meet the actual conditions of the user and the user experience is low due to the fact that the recipes are recommended to the user only according to the dietary preferences of the user in the conventional intelligent refrigerator are solved.
Description
Technical Field
The application belongs to the field of computers and relates to a recipe recommendation method and device.
Background
With the development of the internet and the internet of things technology, as various sensor technologies, chip technologies and big data technologies mature, the clothes and eating habits of the user increasingly depend on the decision given by the big data, and the intelligent refrigerator can know the preference of the user based on the obtained big data and recommend the user to carry out reasonable diet collocation, so that the physical and mental health of the user is facilitated.
It should be noted that, the existing intelligent refrigerator recommends recipes for the user only according to the dietary preferences of the user, so that the recommended recipes cannot accurately meet the actual conditions of the user, and the user experience is low.
Disclosure of Invention
The application provides a recipe recommendation method and device.
According to a first aspect of the present application, there is provided a recipe recommendation method, the method comprising: receiving face data of a user, and generating mood grade information according to the face data; receiving physical sign data of a user, and generating health grade information according to the physical sign data; and generating a recommended menu of the user at least according to the mood grade information and the health grade information.
Further, the method further comprises: acquiring food material information in the refrigerator, wherein the food material information at least comprises: the shelf life of each food material, wherein the generation of the recommended menu of the user at least according to the mood grade information and the health grade information comprises: and generating a recommended menu of the user according to the mood grade information, the health grade information and the shelf life of each food material.
Further, generating the recommended menu of the user according to the mood grade information, the health grade information and the shelf life of each food material comprises: matching a first recommended menu associated with the health grade information from the database according to a first preset association relation; matching a second recommended menu associated with the mood grade information in the first recommended menu according to a second preset association relation; and matching the second recommended menu to the recommended menu of the user according to the shelf life of each food material.
Further, the recommended recipe of the user includes a plurality of recipes, wherein after the recommended recipe of the user is generated according to at least the mood level information and the health level information, the method further includes: and controlling the recommended menu of the user to be displayed on a display of the intelligent refrigerator.
Further, the method comprises: receiving mood information, health information and menu information input by a user; establishing a first preset incidence relation according to the health information and the menu information; and establishing a second preset association relation according to the mood information and the menu information.
According to a second aspect of the present application, there is provided a recipe recommendation apparatus comprising: the first receiving unit is used for receiving face data of a user and generating mood grade information according to the face data; the first receiving unit is used for receiving the physical sign data of the user and generating health grade information according to the physical sign data; and the recommending unit is used for generating a recommended menu of the user at least according to the mood grade information and the health grade information.
Further, the apparatus further comprises: an obtaining unit, configured to obtain food material information in the refrigerator, where the food material information at least includes: shelf life of each food material, wherein the recommendation unit comprises: and the recommending module is used for generating a recommended menu of the user according to the mood grade information, the health grade information and the quality guarantee period of each food material.
Further, the recommendation module includes: the first matching module is used for matching a first recommended menu associated with the health grade information from the database according to a first preset association relation; the second matching module is used for matching a second recommended menu associated with the mood grade information in the first recommended menu according to a second preset association relation; and the third matching module is used for matching the second recommended menu with the recommended menu of the user according to the quality guarantee period of each food material.
Further, the recommended recipe of the user includes a plurality of recipes, wherein the apparatus further includes: and the control unit is used for controlling the recommended menu of the user to be displayed on the display of the intelligent refrigerator.
Further, the apparatus further comprises: the third receiving unit is used for receiving the mood information, the health information and the menu information input by the user; the first establishing unit is used for establishing a first preset incidence relation according to the health information and the menu information; and the second establishing unit is used for establishing a second preset association relation according to the mood information and the menu information.
The application provides a recipe recommendation method and device. The method comprises the following steps: receiving face data of a user, and generating mood grade information according to the face data; receiving physical sign data of a user, and generating health grade information according to the physical sign data; and generating a recommended menu of the user at least according to the mood grade information and the health grade information. The technical problems that the recommended recipes cannot accurately meet the actual conditions of the user and the user experience is low due to the fact that the recipes are recommended to the user only according to the dietary preferences of the user in the conventional intelligent refrigerator are solved.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the application.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a flowchart of a recipe recommendation method according to a first embodiment of the present invention; and
fig. 2 is a schematic diagram of a recipe recommendation apparatus according to a second embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the technical solutions of the present application will be described in detail below. It is to be understood that the embodiments described are only a few embodiments of the present application and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the examples given herein without making any creative effort, shall fall within the protection scope of the present application.
Example one
As shown in fig. 1, the present application provides a recipe recommendation method, which may include:
and step S11, receiving the face data of the user, and generating mood grade information according to the face data.
Specifically, in the scheme, a controller of the intelligent refrigerator or a gateway of the intelligent home can be adopted to receive user facial data collected by a camera outside the intelligent refrigerator, and mood level information of the user is generated based on the recognition of the human face features, wherein the mood level information can be used for representing mood states of the user, such as pleasure, generality and impairment.
And step S13, receiving the physical sign data of the user, and generating health grade information according to the physical sign data.
Specifically, in the scheme, characteristic data (for example, body parameters such as blood pressure and heart rate) of a user collected by an external sensor (for example, a smart bracelet, a smart watch and the like) can be received, and health grade information can be generated according to the physical sign data, and the health grade information can be used for representing the health grade of the user, for example, diseases, sub-health, hypoglycemia, hyperglycemia, hypertension and the like.
It should be noted that in an alternative embodiment, the health level information manually input by the user may also be received.
Step S15, a recommended menu for the user is generated based on at least the mood level information and the health level information.
Specifically, in the scheme, the recommended menu of the user can be generated according to the mood level information and the health level information at the same time, so that the menu is recommended according to the real-time mood and the health condition of the user in the recommended menu of the user, compared with the existing menu recommending technology, the health menu generated according to the health condition and the mood condition has very high accuracy and better accords with the actual condition of the user, and therefore the scheme generates the mood level information according to the face data by receiving the face data of the user; receiving physical sign data of a user, and generating health grade information according to the physical sign data; the recommended recipes of the user are generated at least according to the mood grade information and the health grade information, and the technical problems that the recommended recipes cannot accurately accord with the actual conditions of the user and the user experience is low due to the fact that the recipes are recommended to the user only according to the diet preference of the user in the conventional intelligent refrigerator are solved.
Optionally, the method of this scheme may further include:
acquiring food material information in the refrigerator, wherein the food material information at least comprises: the shelf life of each food material, wherein the step S15 of generating the recommended menu of the user according to at least the mood level information and the health level information may include:
and step S151, generating a recommended menu of the user according to the mood grade information, the health grade information and the quality guarantee period of each food material.
Specifically, in the scheme, the built-in camera of the intelligent refrigerator can identify and record the food type and the time information of the food in the refrigerator (for example, the quality guarantee period of the food can be generated according to the placement time), and then the recommended menu is generated according to the mood level information, the health level information and the three dimensions of the quality guarantee period of each food material in the refrigerator, namely, compared with the existing technology of recommending menus, the accuracy of the health menu generated according to the health condition and the mood condition is very high, and then the menu is generated by combining the real-time quality guarantee period of the food materials in the refrigerator, so that the recipe is higher in accuracy and simultaneously accords with the physiology, the psychology and the cost of a user, and the problem that the recommended recipe cannot accurately accord with the actual condition of the user due to the fact that the recipe is recommended by only according to the dietary favor of the user in the existing intelligent refrigerator is solved, The technical problem of low user experience is solved.
Optionally, the step S151 of generating the recommended menu of the user according to the mood level information, the health level information, and the shelf life of each food material may include:
step S1511, a first recommended menu associated with the health grade information is matched from the database according to a first preset association relation.
Specifically, a first preset association relationship may be established in the database in advance, and the first association relationship may be a correspondence relationship between different health states and different recipes, that is, each state (disease, sub-health, hypoglycemia, hyperglycemia, hypertension) corresponds to different menu contents, for example, a diabetic patient has a professional menu plan recommended by the diabetic patient, a hypertensive patient has a professional menu plan recommended by the hypertensive patient, and a hypoglycemic patient also has a professional menu recommendation plan, and the menu contents can be determined according to different health types and disease types, the recipe which is most suitable for the current health state is recommended by the intelligent refrigerator according to the health information of the user corresponding to different recipe collocation, the health grade information of the user is matched in the database through the first preset incidence relation to obtain a first recommended recipe, and the first recommended recipe (a plurality of recipes) is screened at present through the health information.
Step 1512, matching a second recommended menu associated with the mood grade information in the first recommended menu according to a second preset association relation.
Specifically, a second preset association relationship may be established in the database in advance, where the second association relationship may be a correspondence relationship between different moods and different recipes, that is, each mood (pleasant, general and sad) corresponds to different recipe contents, for example, enjoying durian eating, mood eating general bowl noodles, and distressing eating huge spicy turkey noodles. According to the scheme, the mood grade information of the user is matched in the first menu through the second preset incidence relation to obtain the first recommended menu, namely, the second recommended menu (a plurality of menus) is screened at present through the mood, namely, the first menu is screened from the database at first, and then the second menu is continuously screened from the first menu. It should be noted that the scheme can firstly provide a questionnaire based on the menu, inquire the user in a multi-choice question mode, like which kind of food to eat most when happy, like which kind of food to eat when the mood is general, like which kind of food to eat when the mood is fidget, and then record the menu corresponding to the mood into the background database.
And step S1513, matching the second recommended menu with the recommended menu of the user according to the quality guarantee period of each food material.
Specifically, in the scheme, a first menu is screened from the database through the steps S1511 and S1512, then a second menu is continuously screened from the first menu, then the food materials with the shelf life as fast as possible in the intelligent refrigerator are obtained, and then the menu including the food materials with the shelf life as fast as possible in the second menu is gathered as a final recommended menu (a plurality of menus), it needs to be stated that the menu of the food closest to the shelf life date is higher in priority, and if a tomato is out of date today, the menu including the tomato is matched with the menu most preferentially.
Optionally, the recommended recipe of the user includes a plurality of recipes, wherein, after the step S15 is performed to generate the recommended recipe of the user according to at least the mood level information and the health level information, the method further includes:
and step S16, controlling the recommended menu of the user to be displayed on the display of the intelligent refrigerator.
Specifically, in the present solution, after a plurality of recommended recipes are generated, the recommended recipes may be pushed to a display in the intelligent refrigerator for display.
Optionally, the method of this scheme may further include:
in step S08, mood information, health information, and menu information input by the user are received.
Step S09, a first preset association relationship is established according to the health information and the menu information.
And step S10, establishing a second preset association relation according to the mood information and the menu information.
Specifically, in the present scheme, mood information, health information, and menu information input by a user may be received in advance, and then the first preset association relationship and the second preset association relationship are respectively established.
An alternative embodiment of the present solution is presented below:
step A: and acquiring sign data of the user through a sign acquisition module.
And B: and analyzing diseases and sub-health states according to the acquired data through the processing chip module.
And C: the method comprises the steps of collecting face data of a user through an external camera device of the refrigerator.
Step D: the pleasurable, the so-called and the bad mood grade are analyzed by the processing chip module according to the collected data.
Step E: and configuring questionnaire survey when the refrigerator leaves a factory, collecting dishes which the user likes to eat in different moods, and storing the database into a background.
Step F: the type of food materials is collected through a built-in camera of the refrigerator, and shelf life information is calculated according to the placement time.
And G, screening out the most suitable and most economical recipe scheme for the user according to the information in the step B, D, F, and recommending the most suitable and most economical recipe scheme to the user through the first screen.
In summary, the following technical problems are solved by the present invention:
(1) the large-screen refrigerator competitive products on the market at present do not recommend targeted beneficial menus according to the physical health state of users (and family members), and the scheme can solve the problem.
(2) The scheme can collect the daily moods of the family members and match the healthy menu according to the moods.
(3) According to the scheme, the food materials which are about to expire in the refrigerator can be matched according to the screened menu, the menu matched with the food materials which are about to expire is recommended by the first screen, and optimization, saving and health are achieved.
According to the method, the physiological sign data of the user are collected according to the human body sensor, the expression of the user is identified according to the camera, the corresponding mood data is matched, the food in the refrigerator is detected and identified according to the built-in camera of the refrigerator, the food which is about to expire is identified, and the menu is accurately recommended, so that the user experience of the large-screen intelligent refrigerator is improved.
Example two
As shown in fig. 2, the present invention provides a recipe recommendation apparatus, which can be used for implementing the method of one of the above embodiments, and can also be disposed in an intelligent refrigerator, and the apparatus can include: a first receiving unit 20, configured to receive face data of a user and generate mood level information according to the face data; the first receiving unit 22 is configured to receive sign data of a user, and generate health level information according to the sign data; and the recommending unit 24 is used for generating a recommended menu of the user according to at least the mood grade information and the health grade information.
Specifically, in the scheme, the recommended menu of the user can be generated according to the mood level information and the health level information at the same time, so that the menu is recommended according to the real-time mood and health condition of the user in the recommended menu of the user, compared with the existing menu recommending technology, the health menu generated according to the health condition and the mood condition has very high precision and better accords with the actual condition of the user, and therefore the mood level information is generated according to the face data by receiving the face data of the user through a plurality of units in the device; receiving physical sign data of a user, and generating health grade information according to the physical sign data; the recommended recipes of the user are generated at least according to the mood grade information and the health grade information, and the technical problems that the recommended recipes cannot accurately accord with the actual conditions of the user and the user experience is low due to the fact that the recipes are recommended to the user only according to the diet preference of the user in the conventional intelligent refrigerator are solved.
Optionally, the apparatus further comprises: an obtaining unit, configured to obtain food material information in the refrigerator, where the food material information at least includes: shelf life of each food material, wherein the recommendation unit comprises: and the recommending module is used for generating a recommended menu of the user according to the mood grade information, the health grade information and the quality guarantee period of each food material.
Optionally, the recommending module includes: the first matching module is used for matching a first recommended menu associated with the health grade information from the database according to a first preset association relation; the second matching module is used for matching a second recommended menu associated with the mood grade information in the first recommended menu according to a second preset association relation; and the third matching module is used for matching the second recommended menu with the recommended menu of the user according to the quality guarantee period of each food material.
Optionally, the recommended recipe of the user includes a plurality of recipes, wherein the apparatus further includes: and the control unit is used for controlling the recommended menu of the user to be displayed on the display of the intelligent refrigerator.
Optionally, the apparatus further comprises: the third receiving unit is used for receiving the mood information, the health information and the menu information input by the user; the first establishing unit is used for establishing a first preset incidence relation according to the health information and the menu information; and the second establishing unit is used for establishing a second preset association relation according to the mood information and the menu information.
It is understood that the same or similar parts in the above embodiments may be mutually referred to, and the same or similar parts in other embodiments may be referred to for the content which is not described in detail in some embodiments.
It should be noted that, in the description of the present application, the terms "first", "second", etc. are used for descriptive purposes only and are not to be construed as indicating or implying relative importance. In addition, in the description of the present application, the meaning of "plurality" means at least two unless otherwise specified.
It will be understood that when an element is referred to as being "secured to" or "disposed on" another element, it can be directly on the other element or intervening elements may also be present; when an element is referred to as being "connected" to another element, it can be directly connected to the other element or intervening elements may also be present, and further, as used herein, connected may include wirelessly connected; the term "and/or" is used to include any and all combinations of one or more of the associated listed items.
Any process or method descriptions in flow charts or otherwise described herein may be understood as: represents modules, segments or portions of code which include one or more executable instructions for implementing specific logical functions or steps of a process, and the scope of the preferred embodiments of the present application includes other implementations in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the embodiments of the present application.
It should be understood that portions of the present application may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the various steps or methods may be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.
It will be understood by those skilled in the art that all or part of the steps carried by the method for implementing the above embodiments may be implemented by hardware related to instructions of a program, which may be stored in a computer readable storage medium, and when the program is executed, the program includes one or a combination of the steps of the method embodiments.
In addition, functional units in the embodiments of the present application may be integrated into one processing module, or each unit may exist alone physically, or two or more units are integrated into one module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode. The integrated module, if implemented in the form of a software functional module and sold or used as a stand-alone product, may also be stored in a computer readable storage medium.
The storage medium mentioned above may be a read-only memory, a magnetic or optical disk, etc.
In the description herein, reference to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the application. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
Although embodiments of the present application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present application, and that variations, modifications, substitutions and alterations may be made to the above embodiments by those of ordinary skill in the art within the scope of the present application.
Claims (10)
1. A recipe recommendation method, comprising:
receiving face data of a user, and generating mood grade information according to the face data;
receiving physical sign data of the user, and generating health grade information according to the physical sign data;
and generating a recommended menu of the user at least according to the mood grade information and the health grade information.
2. The method of claim 1, further comprising: acquiring food material information in a refrigerator, wherein the food material information at least comprises: the shelf life of each food material, wherein generating the recommended menu of the user at least according to the mood grade information and the health grade information comprises:
and generating a recommended menu of the user according to the mood grade information, the health grade information and the shelf life of each food material.
3. The method of claim 2, wherein generating the recommended recipe for the user based on the mood level information, the health level information, and the shelf life of each food material comprises:
matching a first recommended menu associated with the health grade information from a database according to a first preset association relation;
matching a second recommended menu associated with the mood grade information in the first recommended menu according to a second preset association relation;
and matching the second recommended menu to the recommended menu of the user according to the shelf life of each food material.
4. The method of claim 1, wherein the recommended recipe for the user comprises a plurality of recipes, wherein after generating the recommended recipe for the user based at least on the mood level information and the health level information, the method further comprises:
and controlling the recommended menu of the user to be displayed on a display of the intelligent refrigerator.
5. The method of claim 3, wherein the method comprises:
receiving mood information, health information and menu information input by a user;
establishing the first preset incidence relation according to the health information and the menu information;
and establishing the second preset association relation according to the mood information and the menu information.
6. A recipe recommendation apparatus comprising:
the first receiving unit is used for receiving face data of a user and generating mood grade information according to the face data;
the first receiving unit is used for receiving the physical sign data of the user and generating health grade information according to the physical sign data;
and the recommending unit is used for generating a recommended menu of the user at least according to the mood grade information and the health grade information.
7. The apparatus of claim 6, further comprising:
an obtaining unit, configured to obtain food material information in a refrigerator, where the food material information at least includes: shelf life of each food material, wherein the recommendation unit comprises:
and the recommending module is used for generating a recommended menu of the user according to the mood grade information, the health grade information and the quality guarantee period of each food material.
8. The apparatus of claim 7, wherein the recommendation module comprises:
the first matching module is used for matching a first recommended menu associated with the health grade information from a database according to a first preset association relation;
the second matching module is used for matching a second recommended menu associated with the mood grade information in the first recommended menu according to a second preset association relation;
and the third matching module is used for matching the second recommended menu with the recommended menu of the user according to the quality guarantee period of each food material.
9. The apparatus of claim 6, wherein the recommended recipe for the user comprises a plurality of recipes, wherein the apparatus further comprises:
and the control unit is used for controlling the recommended menu of the user to be displayed on a display of the intelligent refrigerator.
10. The apparatus of claim 8, further comprising:
the third receiving unit is used for receiving the mood information, the health information and the menu information input by the user;
the first establishing unit is used for establishing the first preset incidence relation according to the health information and the menu information;
and the second establishing unit is used for establishing the second preset association relation according to the mood information and the menu information.
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| CN202011094420.2A CN112163548A (en) | 2020-10-14 | 2020-10-14 | Recipe recommendation method and apparatus |
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| CN202011094420.2A CN112163548A (en) | 2020-10-14 | 2020-10-14 | Recipe recommendation method and apparatus |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113407830A (en) * | 2021-06-16 | 2021-09-17 | 海信集团控股股份有限公司 | Information recommendation method and device |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105509394A (en) * | 2015-05-05 | 2016-04-20 | 万军 | Refrigerator |
| 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 |
| CN111696647A (en) * | 2019-03-13 | 2020-09-22 | 青岛海尔电冰箱有限公司 | Method and device for recommending menu for refrigerator |
-
2020
- 2020-10-14 CN CN202011094420.2A patent/CN112163548A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105509394A (en) * | 2015-05-05 | 2016-04-20 | 万军 | Refrigerator |
| CN111696647A (en) * | 2019-03-13 | 2020-09-22 | 青岛海尔电冰箱有限公司 | Method and device for recommending menu for refrigerator |
| 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 |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113407830A (en) * | 2021-06-16 | 2021-09-17 | 海信集团控股股份有限公司 | Information recommendation method and device |
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Application publication date: 20210101 |