CN113222702A - Beverage recipe recommendation method and system for automatic beverage machine - Google Patents
Beverage recipe recommendation method and system for automatic beverage machine Download PDFInfo
- Publication number
- CN113222702A CN113222702A CN202110547715.9A CN202110547715A CN113222702A CN 113222702 A CN113222702 A CN 113222702A CN 202110547715 A CN202110547715 A CN 202110547715A CN 113222702 A CN113222702 A CN 113222702A
- Authority
- CN
- China
- Prior art keywords
- beverage
- recipe
- user
- data
- recommended
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/06—Buying, selling or leasing transactions
- G06Q30/0601—Electronic shopping [e-shopping]
- G06Q30/0631—Item recommendations
-
- G—PHYSICS
- G07—CHECKING-DEVICES
- G07F—COIN-FREED OR LIKE APPARATUS
- G07F13/00—Coin-freed apparatus for controlling dispensing or fluids, semiliquids or granular material from reservoirs
Landscapes
- Business, Economics & Management (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Accounting & Taxation (AREA)
- Finance (AREA)
- Economics (AREA)
- Development Economics (AREA)
- Marketing (AREA)
- Strategic Management (AREA)
- General Business, Economics & Management (AREA)
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
A beverage recipe recommendation method and system for an automatic beverage machine, the method comprising the steps of: acquiring historical purchase data of a user; generating at least a first beverage recommended recipe and a second beverage recommended recipe according to the historical purchase data; acquiring climate characteristics; judging whether the first recommended beverage recipe is suitable or not according to the climate characteristics; if so, recommending the first beverage recommendation recipe to the user; and if not, recommending the second beverage recommendation recipe to the user. The beverage recipe recommendation method and the beverage recipe recommendation system for the automatic beverage machine can provide proper beverage recipes for users according to historical purchase data and climate characteristics of the users, and meet beverage requirements of different customers under different climate conditions.
Description
Technical Field
The invention belongs to the technical field of automatic beverage machines, and particularly relates to a method and a system for recommending beverage recipes of an automatic beverage machine.
Background
The automatic beverage machine can be seen in various places such as squares, markets and the like, and can provide beverages for people to solve the problem of thirst. However, the beverages provided by the current automatic beverage machine are all of fixed types, and proper beverage recipes cannot be provided according to the conditions of the customers.
Disclosure of Invention
In order to solve the above problems, the present invention provides a method for recommending a beverage recipe of an automatic beverage machine, the method comprising the steps of:
acquiring historical purchase data of a user;
generating at least a first beverage recommended recipe and a second beverage recommended recipe according to the historical purchase data;
acquiring climate characteristics;
judging whether the first recommended beverage recipe is suitable or not according to the climate characteristics;
if so, recommending the first beverage recommendation recipe to the user;
and if not, recommending the second beverage recommendation recipe to the user.
Preferably, before the obtaining of the historical purchase data of the user, the method comprises the following steps:
setting a purchase data storage database in the automated beverage machine;
acquiring all historical selling data of the automatic beverage machine;
selecting data corresponding to the user from all the historical selling data;
and storing the data corresponding to the user into the purchase data storage database.
Preferably, after the step of storing the user corresponding data into the purchase data storage database, the method further comprises the steps of:
judging whether a mobile terminal exists in a preset range around the automatic beverage machine or not;
if so, establishing a communication link between the mobile terminal and the automatic beverage machine;
if not, keeping the current state of the automatic beverage machine, and returning to the step of judging whether a mobile terminal exists in a preset range around the automatic beverage machine;
and at least displaying a purchasing program and a browser of the automatic beverage machine on the display interface of the mobile terminal.
Preferably, the acquiring the historical purchase data of the user comprises the steps of:
acquiring a click operation of a user on a display interface of the mobile terminal;
judging whether a user clicks a purchasing program of the automatic beverage machine on a display interface of the mobile terminal;
if yes, selecting data corresponding to all users from a purchase data storage database;
if not, keeping the current state of the automatic beverage machine, and returning to the step of obtaining the click operation of the user on the display interface of the mobile terminal.
Preferably, the selecting of all user corresponding data from the purchase data storage database includes the steps of:
acquiring all the data corresponding to the users;
acquiring a corresponding time period of the data corresponding to each user;
grouping all the data corresponding to the users according to the corresponding time period;
and reserving the user corresponding data corresponding to the corresponding time period closest to the current time.
Preferably, the acquiring the historical purchase data of the user comprises the steps of:
acquiring a search operation of a user on a display interface of the mobile terminal;
judging whether a user searches a browser on a display interface of the mobile terminal for a purchase program of the automatic beverage machine;
if yes, selecting data corresponding to all users from a purchase data storage database;
if not, keeping the current state of the automatic beverage machine, and returning to the step of obtaining the click operation of the user on the display interface of the mobile terminal.
Preferably, the generating at least a first and a second beverage recommendation recipe from the historical purchase data comprises the steps of:
acquiring first user corresponding data and second user corresponding data of a user in a purchase program of the automatic beverage machine in a first corresponding time period and a second corresponding time period;
grouping purchased beverages in the first user corresponding data and the second user corresponding data according to beverage names;
sorting the purchased beverages in each grouping in descending order by purchase frequency;
summarizing the beverage names corresponding to the purchased beverages with the first highest frequency and the second highest frequency as a first beverage recommended recipe and a second beverage recommended recipe.
Preferably, the generating at least a first and a second beverage recommendation recipe from the historical purchase data comprises the steps of:
acquiring first user corresponding data and second user corresponding data of a user in the browser in a first corresponding time period and a second corresponding time period;
grouping purchased beverages in the first user corresponding data and the second user corresponding data according to beverage names;
sorting the purchased beverages in each grouping in descending order by purchase frequency;
summarizing the beverage names corresponding to the purchased beverages with the first highest frequency and the second highest frequency as a first beverage recommended recipe and a second beverage recommended recipe.
Preferably, the step of judging whether the first recommended food recipe is suitable according to the climate characteristics comprises the following steps:
acquiring first temperature information in the climate characteristics;
acquiring second temperature information corresponding to the beverage in the first recommended recipe of the beverage;
judging whether the first temperature information corresponds to the second temperature information;
if so, judging that the first beverage recommended recipe is appropriate;
if not, judging that the first recommended beverage recipe is not appropriate.
The invention also provides a beverage recipe recommendation system for an automatic beverage machine, the system comprising:
the data acquisition module is used for acquiring historical purchase data of a user;
the recipe generation module is used for generating at least a first beverage recommended recipe and a second beverage recommended recipe according to the historical purchase data;
the characteristic acquisition module is used for acquiring climate characteristics;
the judging module is used for judging whether the first recommended beverage recipe is suitable or not according to the climate characteristics;
the execution module is used for executing preset operation according to the judgment result of the judgment module;
when the judgment module judges that the first beverage recommended recipe is the first beverage recommended recipe, the execution module recommends the first beverage recommended recipe to a user; and when the judgment module judges that the second beverage is not the first beverage, the execution module recommends the second beverage recommendation recipe to the user.
The beverage recipe recommendation method and the beverage recipe recommendation system for the automatic beverage machine can provide proper beverage recipes for users according to historical purchase data and climate characteristics of the users, and meet beverage requirements of different customers under different climate conditions.
Drawings
In order to more clearly illustrate the embodiments of the present invention 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, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
FIG. 1 is a schematic flow chart of a method for recommending a beverage recipe for an automatic beverage machine according to the present invention;
fig. 2 is a schematic composition diagram of a beverage recipe recommendation system of an automatic beverage machine provided by the invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be described in further detail with reference to the accompanying drawings in conjunction with the following detailed description. It should be understood that the description is intended to be exemplary only, and is not intended to limit the scope of the present invention. Moreover, in the following description, descriptions of well-known structures and techniques are omitted so as to not unnecessarily obscure the concepts of the present invention.
In an embodiment of the present application, as shown in fig. 1, the present invention provides a beverage recipe recommendation method for an automatic beverage machine, the method comprising the steps of:
s1: acquiring historical purchase data of a user;
in the embodiment of the present application, the obtaining of the user historical purchase data in step S1 includes the steps of:
setting a purchase data storage database in the automated beverage machine;
acquiring all historical selling data of the automatic beverage machine;
selecting data corresponding to the user from all the historical selling data;
and storing the data corresponding to the user into the purchase data storage database.
In the embodiment of the application, before obtaining the historical purchase data of the user, firstly, a purchase data storage database is arranged in the automatic beverage machine, then all the historical selling data of the automatic beverage machine are obtained, the corresponding data of the user is selected from all the historical selling data, and then the corresponding data of the user is stored in the purchase data storage database.
In this embodiment of the present application, after the storing the data corresponding to the user in the purchase data storage database, the method further includes the steps of:
judging whether a mobile terminal exists in a preset range around the automatic beverage machine or not;
if so, establishing a communication link between the mobile terminal and the automatic beverage machine;
if not, keeping the current state of the automatic beverage machine, and returning to the step of judging whether a mobile terminal exists in a preset range around the automatic beverage machine;
and at least displaying a purchasing program and a browser of the automatic beverage machine on the display interface of the mobile terminal.
In the embodiment of the application, after the data corresponding to the user is stored in the purchase data storage database, it is first required to determine whether a mobile terminal exists in a preset range around the automatic beverage machine, and if so, establishing a communication link between the mobile terminal and the automatic beverage machine; if the judgment is not available, the current state of the automatic beverage machine is kept, the step of judging whether a mobile terminal exists in a preset range around the automatic beverage machine or not is returned, and then at least a purchase program and a browser of the automatic beverage machine are displayed on a display interface of the mobile terminal.
In the embodiment of the present application, the acquiring of the historical purchase data of the user in step S1 includes the steps of:
acquiring a click operation of a user on a display interface of the mobile terminal;
judging whether a user clicks a purchasing program of the automatic beverage machine on a display interface of the mobile terminal;
if yes, selecting data corresponding to all users from a purchase data storage database;
if not, keeping the current state of the automatic beverage machine, and returning to the step of obtaining the click operation of the user on the display interface of the mobile terminal.
In the embodiment of the application, when historical purchase data of a user is acquired, specifically, clicking operation of the user on a display interface of the mobile terminal is acquired, and whether the user clicks a purchase program of the automatic beverage machine on the display interface of the mobile terminal is judged; if yes, selecting data corresponding to all users from a purchase data storage database; if so, keeping the current state of the automatic beverage machine, and returning to the step of obtaining the click operation of the user on the display interface of the mobile terminal.
In an embodiment of the present application, the selecting data corresponding to all users from the purchase data storage database includes:
acquiring all the data corresponding to the users;
acquiring a corresponding time period of the data corresponding to each user;
grouping all the data corresponding to the users according to the corresponding time period;
and reserving the user corresponding data corresponding to the corresponding time period closest to the current time.
In the embodiment of the application, when all the data corresponding to the users are selected from the purchase data storage database, specifically, all the data corresponding to the users are obtained, and the corresponding time period of each data corresponding to the users is obtained; and then grouping all the user corresponding data according to the corresponding time period, and reserving the user corresponding data corresponding to the corresponding time period closest to the current time.
In the embodiment of the present application, the acquiring of the historical purchase data of the user in step S1 includes the steps of:
acquiring a search operation of a user on a display interface of the mobile terminal;
judging whether a user searches a browser on a display interface of the mobile terminal for a purchase program of the automatic beverage machine;
if yes, selecting data corresponding to all users from a purchase data storage database;
if not, keeping the current state of the automatic beverage machine, and returning to the step of obtaining the click operation of the user on the display interface of the mobile terminal.
In the embodiment of the application, when historical purchase data of a user is acquired, specifically, firstly, a search operation of the user on a display interface of the mobile terminal is acquired, and then whether the user searches a purchase program of the automatic beverage machine in a browser on the display interface of the mobile terminal is judged; if so, selecting data corresponding to all users from a purchase data storage database; and when the judgment result is no, maintaining the current state of the automatic beverage machine, and returning to the step of obtaining the click operation of the user on the display interface of the mobile terminal.
S2: generating at least a first beverage recommended recipe and a second beverage recommended recipe according to the historical purchase data;
in an embodiment of the present application, the generating at least a first beverage recommendation recipe and a second beverage recommendation recipe from the historical purchase data in step S2 includes the steps of:
acquiring first user corresponding data and second user corresponding data of a user in a purchase program of the automatic beverage machine in a first corresponding time period and a second corresponding time period;
grouping purchased beverages in the first user corresponding data and the second user corresponding data according to beverage names;
sorting the purchased beverages in each grouping in descending order by purchase frequency;
summarizing the beverage names corresponding to the purchased beverages with the first highest frequency and the second highest frequency as a first beverage recommended recipe and a second beverage recommended recipe.
In this embodiment of the application, when at least a first beverage recommended recipe and a second beverage recommended recipe are generated according to the historical purchase data, specifically, first user corresponding data and second user corresponding data in a purchase program of a user on the automatic beverage machine in a first corresponding time period and a second corresponding time period are obtained first, then purchased beverages in the first user corresponding data and the second user corresponding data are grouped according to beverage names, and the purchased beverages in each group are sorted in a descending order according to purchase frequency; and then summarizing the beverage names corresponding to the purchased beverages with the first highest frequency and the second highest frequency as a first beverage recommended recipe and a second beverage recommended recipe.
In an embodiment of the present application, the generating at least a first beverage recommendation recipe and a second beverage recommendation recipe from the historical purchase data in step S2 includes the steps of:
acquiring first user corresponding data and second user corresponding data of a user in the browser in a first corresponding time period and a second corresponding time period;
grouping purchased beverages in the first user corresponding data and the second user corresponding data according to beverage names;
sorting the purchased beverages in each grouping in descending order by purchase frequency;
summarizing the beverage names corresponding to the purchased beverages with the first highest frequency and the second highest frequency as a first beverage recommended recipe and a second beverage recommended recipe.
In the embodiment of the application, when at least a first beverage recommended recipe and a second beverage recommended recipe are generated according to the historical purchase data, specifically, first user corresponding data and second user corresponding data of a user in the browser in a first corresponding time period and a second corresponding time period are obtained, and purchased beverages in the first user corresponding data and the second user corresponding data are grouped according to beverage names; and then sorting the purchased beverages in each group in a descending order according to the purchase frequency, and summarizing beverage names corresponding to the purchased beverages with the first highest frequency and the second highest frequency as a first beverage recommendation recipe and a second beverage recommendation recipe.
S3: acquiring climate characteristics;
in the embodiment of the application, various climate characteristics such as temperature, weather conditions, humidity and the like can be acquired.
S4: judging whether the first recommended beverage recipe is suitable or not according to the climate characteristics;
in this embodiment of the application, the step of determining whether the first recommended food recipe is suitable according to the climate characteristics in step S4 includes the steps of:
acquiring first temperature information in the climate characteristics;
acquiring second temperature information corresponding to the beverage in the first recommended recipe of the beverage;
judging whether the first temperature information corresponds to the second temperature information;
if so, judging that the first beverage recommended recipe is appropriate;
if not, judging that the first recommended beverage recipe is not appropriate.
In the embodiment of the application, when judging whether the first recommended diet of beverage is appropriate according to the climate characteristics, specifically, first temperature information in the climate characteristics is obtained, and second temperature information corresponding to the beverage in the first recommended diet of beverage is obtained; then judging whether the first temperature information corresponds to the second temperature information; if so, judging that the first recommended food recipe is appropriate; and when the first beverage recommended recipe is judged to be not suitable, judging that the first beverage recommended recipe is not suitable. For example, whether the first recommended diet is too hot or too cold to be suitable for drinking is judged according to the air temperature.
S5: if so, recommending the first beverage recommendation recipe to the user;
s6: and if not, recommending the second beverage recommendation recipe to the user.
In the embodiment of the application, whether the first beverage recommended recipe is appropriate or not is judged according to the climate characteristics, and the first beverage recommended recipe or the second beverage recommended recipe is recommended to a user.
In an embodiment of the present application, as shown in fig. 2, the present invention further provides a beverage recipe recommendation system for an automatic beverage machine, the system comprising:
the data acquisition module 10 is used for acquiring historical purchase data of a user;
a recipe generating module 20, configured to generate at least a first beverage recommended recipe and a second beverage recommended recipe according to the historical purchase data;
a characteristic obtaining module 30, configured to obtain a climate characteristic;
the judging module 40 is used for judging whether the first recommended diet is suitable according to the climate characteristics;
an executing module 50, configured to execute a preset operation according to the determination result of the determining module 40;
when the judging module 40 judges that the first beverage recommended recipe is yes, the executing module 50 recommends the first beverage recommended recipe to the user; when the judgment module 40 judges no, the execution module 50 recommends the second beverage recommendation recipe to the user.
In the embodiment of the application, the invention provides a beverage recipe recommendation method of an automatic beverage machine, which can be realized by adopting the beverage recipe recommendation method of the automatic beverage machine and is not described herein again.
The beverage recipe recommendation method and the beverage recipe recommendation system for the automatic beverage machine can provide proper beverage recipes for users according to historical purchase data and climate characteristics of the users, and meet beverage requirements of different customers under different climate conditions.
It is to be understood that the above-described embodiments of the present invention are merely illustrative of or explaining the principles of the invention and are not to be construed as limiting the invention. Therefore, any modification, equivalent replacement, improvement and the like made without departing from the spirit and scope of the present invention should be included in the protection scope of the present invention. Further, it is intended that the appended claims cover all such variations and modifications as fall within the scope and boundaries of the appended claims or the equivalents of such scope and boundaries.
Claims (10)
1. A method for beverage recipe recommendation for an automatic beverage machine, the method comprising the steps of:
acquiring historical purchase data of a user;
generating at least a first beverage recommended recipe and a second beverage recommended recipe according to the historical purchase data;
acquiring climate characteristics;
judging whether the first recommended beverage recipe is suitable or not according to the climate characteristics;
if so, recommending the first beverage recommendation recipe to the user;
and if not, recommending the second beverage recommendation recipe to the user.
2. The beverage dispenser beverage recipe recommendation method according to claim 1, comprising the step of, before said obtaining user historical purchase data:
setting a purchase data storage database in the automated beverage machine;
acquiring all historical selling data of the automatic beverage machine;
selecting data corresponding to the user from all the historical selling data;
and storing the data corresponding to the user into the purchase data storage database.
3. The beverage dispenser beverage recipe recommendation method according to claim 2, further comprising the step after said storing of said user corresponding data into said purchase data storage database:
judging whether a mobile terminal exists in a preset range around the automatic beverage machine or not;
if so, establishing a communication link between the mobile terminal and the automatic beverage machine;
if not, keeping the current state of the automatic beverage machine, and returning to the step of judging whether a mobile terminal exists in a preset range around the automatic beverage machine;
and at least displaying a purchasing program and a browser of the automatic beverage machine on the display interface of the mobile terminal.
4. The beverage server beverage recipe recommendation method according to claim 1, wherein the obtaining user historical purchase data comprises the steps of:
acquiring a click operation of a user on a display interface of the mobile terminal;
judging whether a user clicks a purchasing program of the automatic beverage machine on a display interface of the mobile terminal;
if yes, selecting data corresponding to all users from a purchase data storage database;
if not, keeping the current state of the automatic beverage machine, and returning to the step of obtaining the click operation of the user on the display interface of the mobile terminal.
5. The beverage dispenser beverage recipe recommendation method according to claim 4, wherein said selecting all user corresponding data from a purchase data storage database comprises the steps of:
acquiring all the data corresponding to the users;
acquiring a corresponding time period of the data corresponding to each user;
grouping all the data corresponding to the users according to the corresponding time period;
and reserving the user corresponding data corresponding to the corresponding time period closest to the current time.
6. The beverage server beverage recipe recommendation method according to claim 1, wherein the obtaining user historical purchase data comprises the steps of:
acquiring a search operation of a user on a display interface of the mobile terminal;
judging whether a user searches a browser on a display interface of the mobile terminal for a purchase program of the automatic beverage machine;
if yes, selecting data corresponding to all users from a purchase data storage database;
if not, keeping the current state of the automatic beverage machine, and returning to the step of obtaining the click operation of the user on the display interface of the mobile terminal.
7. The beverage dispenser beverage recipe recommendation method according to claim 1, wherein the generating at least a first beverage recommendation recipe and a second beverage recommendation recipe from the historical purchase data comprises the steps of:
acquiring first user corresponding data and second user corresponding data of a user in a purchase program of the automatic beverage machine in a first corresponding time period and a second corresponding time period;
grouping purchased beverages in the first user corresponding data and the second user corresponding data according to beverage names;
sorting the purchased beverages in each grouping in descending order by purchase frequency;
summarizing the beverage names corresponding to the purchased beverages with the first highest frequency and the second highest frequency as a first beverage recommended recipe and a second beverage recommended recipe.
8. The beverage dispenser beverage recipe recommendation method according to claim 1, wherein the generating at least a first beverage recommendation recipe and a second beverage recommendation recipe from the historical purchase data comprises the steps of:
acquiring first user corresponding data and second user corresponding data of a user in the browser in a first corresponding time period and a second corresponding time period;
grouping purchased beverages in the first user corresponding data and the second user corresponding data according to beverage names;
sorting the purchased beverages in each grouping in descending order by purchase frequency;
summarizing the beverage names corresponding to the purchased beverages with the first highest frequency and the second highest frequency as a first beverage recommended recipe and a second beverage recommended recipe.
9. The beverage dispenser beverage recipe recommendation method according to claim 1, wherein the determining whether the first beverage recommendation recipe is appropriate according to the climate characteristic comprises the steps of:
acquiring first temperature information in the climate characteristics;
acquiring second temperature information corresponding to the beverage in the first recommended recipe of the beverage;
judging whether the first temperature information corresponds to the second temperature information;
if so, judging that the first beverage recommended recipe is appropriate;
if not, judging that the first recommended beverage recipe is not appropriate.
10. A beverage server beverage recipe recommendation system, characterized in that the system comprises: the data acquisition module is used for acquiring historical purchase data of a user;
the recipe generation module is used for generating at least a first beverage recommended recipe and a second beverage recommended recipe according to the historical purchase data;
the characteristic acquisition module is used for acquiring climate characteristics;
the judging module is used for judging whether the first recommended beverage recipe is suitable or not according to the climate characteristics;
the execution module is used for executing preset operation according to the judgment result of the judgment module;
when the judgment module judges that the first beverage recommended recipe is the first beverage recommended recipe, the execution module recommends the first beverage recommended recipe to a user; and when the judgment module judges that the second beverage is not the first beverage, the execution module recommends the second beverage recommendation recipe to the user.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110547715.9A CN113222702A (en) | 2021-05-19 | 2021-05-19 | Beverage recipe recommendation method and system for automatic beverage machine |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110547715.9A CN113222702A (en) | 2021-05-19 | 2021-05-19 | Beverage recipe recommendation method and system for automatic beverage machine |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN113222702A true CN113222702A (en) | 2021-08-06 |
Family
ID=77093216
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110547715.9A Pending CN113222702A (en) | 2021-05-19 | 2021-05-19 | Beverage recipe recommendation method and system for automatic beverage machine |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113222702A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113450176A (en) * | 2020-10-22 | 2021-09-28 | 齐喝彩(上海)管理咨询有限公司 | Remote purchase selection pushing method and system for unmanned vending machine |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103295067A (en) * | 2013-04-10 | 2013-09-11 | 南京邮电大学 | Vending machine managing system based on Internet of Things |
| CN105160007A (en) * | 2015-09-21 | 2015-12-16 | 深圳市九洲电器有限公司 | Diet recommendation method and system |
| CN107248222A (en) * | 2017-06-09 | 2017-10-13 | 深圳正品创想科技有限公司 | A kind of good selling method, device |
| CN108171499A (en) * | 2017-12-23 | 2018-06-15 | 北京漫游星际科技有限公司 | A kind of automatic vending method and Vending Machine |
| CN108764889A (en) * | 2018-05-03 | 2018-11-06 | 杭州乐湃网络科技有限公司 | The commodity or service transacting method of Vending Machine |
| CN109166007A (en) * | 2018-08-23 | 2019-01-08 | 深圳码隆科技有限公司 | A kind of Method of Commodity Recommendation and its device based on automatic vending machine |
-
2021
- 2021-05-19 CN CN202110547715.9A patent/CN113222702A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103295067A (en) * | 2013-04-10 | 2013-09-11 | 南京邮电大学 | Vending machine managing system based on Internet of Things |
| CN105160007A (en) * | 2015-09-21 | 2015-12-16 | 深圳市九洲电器有限公司 | Diet recommendation method and system |
| CN107248222A (en) * | 2017-06-09 | 2017-10-13 | 深圳正品创想科技有限公司 | A kind of good selling method, device |
| CN108171499A (en) * | 2017-12-23 | 2018-06-15 | 北京漫游星际科技有限公司 | A kind of automatic vending method and Vending Machine |
| CN108764889A (en) * | 2018-05-03 | 2018-11-06 | 杭州乐湃网络科技有限公司 | The commodity or service transacting method of Vending Machine |
| CN109166007A (en) * | 2018-08-23 | 2019-01-08 | 深圳码隆科技有限公司 | A kind of Method of Commodity Recommendation and its device based on automatic vending machine |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113450176A (en) * | 2020-10-22 | 2021-09-28 | 齐喝彩(上海)管理咨询有限公司 | Remote purchase selection pushing method and system for unmanned vending machine |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107730313B (en) | Shop recommendation method and device based on recommendation reason | |
| US7945484B1 (en) | Local product information | |
| CN110569432B (en) | Commodity sequence calculating method, commodity sequence calculating device, computer equipment and storage medium | |
| US20200320600A1 (en) | Virtual Marketplace Enabling Machine-to-Machine Commerce | |
| JP4886749B2 (en) | Recommended product selection device, recommended product selection program, and product search device | |
| US6282518B1 (en) | Process for internet ordering of industrial products | |
| CN104881807A (en) | Method and device for recommending goods information | |
| KR101956212B1 (en) | Method of start-up support services based on self-diagnosis by founder | |
| US8135713B2 (en) | Sourcing controller | |
| CN110766509A (en) | Service order processing and takeout order recommending method and device | |
| US20160055526A1 (en) | Information processing device, information processing method, and information processing program | |
| CN105488705A (en) | Auxiliary system and method of online shopping | |
| US9953286B2 (en) | Shipping preferences population systems and related methods | |
| CN111597447A (en) | Object pushing method and device, electronic equipment and storage medium | |
| CN113222702A (en) | Beverage recipe recommendation method and system for automatic beverage machine | |
| JP6170261B1 (en) | Information processing apparatus, information processing method, and information processing program | |
| AU2011253858B2 (en) | Providing package products | |
| CN110570271A (en) | information recommendation method and device, electronic equipment and readable storage medium | |
| JP2006236014A (en) | Shopping support system using shopping list | |
| JP2002358443A (en) | Product sale system | |
| CN112288507B (en) | Method and device for determining display information | |
| CN112418661A (en) | Catering evaluation method and system | |
| CN112989227A (en) | Method and system for selecting target address of interested object | |
| CN113409063A (en) | Data processing method and device, electronic equipment and storage medium | |
| JP5119988B2 (en) | Feature important diopter calculation system, feature important diopter calculation method, and computer program |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |