CN110910213A - Air conditioner purchase recommendation method and device, storage medium and electronic equipment - Google Patents
Air conditioner purchase recommendation method and device, storage medium and electronic equipment Download PDFInfo
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Abstract
The invention relates to the technical field of information recommendation, in particular to an air conditioner purchase recommendation method, an air conditioner purchase recommendation device, a storage medium and electronic equipment, wherein the method comprises the following steps: the method comprises the steps of obtaining target installation area information and preset characteristic information of air conditioners of various models, searching environment information of a target installation area and historical data of air conditioners of each model correspondingly installed in the target installation area according to the target installation area information, and obtaining recommendation information according to the preset characteristic information of the air conditioners of various models, the environment information and the historical data of the air conditioners of each model, wherein the recommendation information comprises recommended air conditioner models so as to analyze the environment of the target installation area information and the air conditioners of different models, and accurate assessment is achieved so that the best air conditioner model recommendation scheme is provided for users. The problem that recommendation information including the air conditioner model is difficult to recommend to a user in the prior art is solved.
Description
Technical Field
The invention relates to the technical field of information recommendation, in particular to an air conditioner purchase recommendation method and device, a storage medium and electronic equipment.
Background
The traditional air conditioner purchasing mode is that a user judges whether the user likes or needs according to product introduction, needs to browse a large number of commodities and learn related parameter knowledge.
However, the air conditioners have various functions, the environments and requirements of users are different, and it is difficult to accurately screen out the appropriate air conditioners through manual selection and purchase.
Disclosure of Invention
In order to solve the above problems, the present invention provides an air conditioner purchase recommendation method, which solves the problem in the prior art that it is difficult to accurately screen out a suitable air conditioner.
In a first aspect, the present application provides an air conditioner purchase recommendation method, including:
acquiring target installation area information and preset characteristic information of various types of air conditioners;
searching environmental information of a target installation area and historical data of each type of air conditioner correspondingly installed in the target installation area according to the target installation area information;
and obtaining the recommended model air conditioners according to the preset characteristic information and the environmental information of the air conditioners with various models and the historical data of each model air conditioner.
According to an embodiment of the application, optionally, in the air conditioner purchase recommendation method, the method further includes:
acquiring demand information, and analyzing the demand information to obtain demand characteristic information;
obtaining recommended model air conditioners according to preset characteristic information, environmental information and historical data of each model air conditioner of the air conditioners with various models, and the method comprises the following steps:
acquiring functional characteristic information of the air conditioner according to the environment information, and acquiring performance characteristic information of each type of air conditioner in the target installation area according to historical data of each type of air conditioner;
obtaining actual characteristic information of each type of air conditioner in the target installation area according to preset characteristic information and performance characteristic information of the air conditioner;
judging whether a target model air conditioner which simultaneously meets the requirement characteristic information and the function characteristic information exists in the actual characteristic information of the air conditioners with various models;
and when the target model air conditioner exists, taking the target model air conditioner as a recommended model air conditioner.
According to an embodiment of the application, optionally, in the above air conditioner purchase recommendation method, the historical data of each type of air conditioner includes selling data, maintenance data, and usage feedback data of each type of air conditioner, and the obtaining of the performance characteristic information of each type of air conditioner according to the historical data of each type of air conditioner includes:
obtaining the maintenance proportion of each type of air conditioner according to the selling data and the maintenance data of each type of air conditioner;
and searching performance characteristic information of each type of air conditioner in a target area from a preset corresponding relation according to the maintenance proportion of each type of air conditioner and corresponding use feedback data, wherein the preset corresponding relation stores various types of performance characteristic information, and maintenance proportion ranges and use feedback data which respectively correspond to each type of performance information.
According to an embodiment of the application, optionally, in the air conditioner purchase recommendation method, when there is no target model air conditioner, the method further includes:
and acquiring a target model air conditioner meeting the functional characteristic information from the actual characteristic information of the signal air conditioners of the air conditioners with various models as a recommended model air conditioner.
According to an embodiment of the application, optionally, in the air conditioner purchase recommendation method, when there is no target model air conditioner, the method further includes:
recommending household auxiliary household appliances according to the demand characteristic information and the function characteristic information, wherein the household auxiliary household appliances comprise at least one of a humidifier, a dehumidifier and a heater.
According to an embodiment of the application, optionally, in the air conditioner purchase recommendation method, the step of analyzing the demand information to obtain the demand characteristic information includes:
and carrying out clustering analysis on the demand information by adopting a clustering algorithm to obtain demand characteristic information.
In a second aspect, an embodiment of the present invention further provides an air conditioner purchase recommendation apparatus, where the apparatus includes:
the first acquisition module is used for acquiring target installation area information and preset characteristic information of air conditioners of various models;
the searching module is used for searching the environmental information of the target installation area and the historical data of each type of air conditioner correspondingly installed in the target installation area according to the information of the target installation area;
and the recommendation module is used for obtaining the recommended model air conditioners according to the preset characteristic information and the environmental information of the air conditioners with various models and the historical data of each model of air conditioner.
According to an embodiment of the application, optionally, in the above air conditioner purchase recommending apparatus, the apparatus further includes:
the second acquisition module is used for acquiring the demand information and analyzing the demand information to obtain demand characteristic information;
the recommendation module comprises:
the first obtaining submodule is used for obtaining functional characteristic information of the air conditioner according to the environment information and obtaining performance characteristic information of each type of air conditioner in the target installation area according to historical data of each type of air conditioner;
the second obtaining submodule is used for obtaining actual characteristic information of each type of air conditioner in the target installation area according to preset characteristic information and performance characteristic information of the type of air conditioner;
the judgment submodule is used for judging whether a target model air conditioner which simultaneously meets the requirement characteristic information and the function characteristic information exists in the actual characteristic information of the air conditioners with various models;
and the recommending submodule is used for taking the target model air conditioner as the recommended model air conditioner when the target model air conditioner exists.
In a third aspect, the present application provides a storage medium storing a computer program executable by one or more processors for implementing the air conditioner purchase recommendation method as described above.
In a fourth aspect, the present application provides an electronic device, comprising a memory and a processor, wherein the memory stores a computer program, and the computer program, when executed by the processor, executes the air conditioner purchase recommendation method applied to the first terminal.
Compared with the prior art, one or more embodiments in the above scheme can have the following advantages or beneficial effects:
according to the air conditioner purchase recommendation method, the air conditioner purchase recommendation device, the storage medium and the electronic equipment, the target installation area information and the preset characteristic information of the air conditioners of various types are obtained, the environment information of the target installation area and the historical data of each type of air conditioner correspondingly installed in the target installation area are searched according to the target installation area information, and the recommended type of air conditioner is obtained according to the preset characteristic information and the environment information of the air conditioners of various types and the historical data of each type of air conditioner, so that the problem that accurate recommendation of the air conditioner of the proper type is difficult to achieve in the prior art is solved.
Drawings
The invention will be described in more detail hereinafter on the basis of embodiments and with reference to the accompanying drawings.
Fig. 1 is a flowchart illustrating an air conditioner purchase recommendation method according to an embodiment of the present invention.
Fig. 2 is another schematic flow chart of an air conditioner purchase recommendation method according to an embodiment of the present invention.
Fig. 3 is a connection block diagram of an air conditioner purchase recommendation device according to a second embodiment of the present invention.
Fig. 4 is another connection block diagram of an air conditioner purchase recommending apparatus according to a second embodiment of the present invention.
In the drawings, like parts are designated with like reference numerals, and the drawings are not drawn to scale.
Detailed Description
The following detailed description of the embodiments of the present invention will be provided with reference to the accompanying drawings and examples, so that how to apply the technical means to solve the technical problems and achieve the corresponding technical effects can be fully understood and implemented. The embodiments and the features of the embodiments can be combined without conflict, and the technical solutions formed are all within the scope of the present invention.
Example one
Referring to fig. 1, the present invention provides an air conditioner purchase recommendation method, which may be applied to an electronic device with data processing capability, such as a computer, a server, or a tablet, and when the air conditioner purchase recommendation method is applied to the electronic device, steps S110 to S130 may be performed.
Step S110: and acquiring target installation area information and preset characteristic information of air conditioners of various models.
Step S120: and searching the environmental information of the target installation area and the historical data of each type of air conditioner correspondingly installed in the target installation area according to the information of the target installation area.
Step S130: and obtaining the recommended model air conditioners according to the preset characteristic information and the environmental information of the air conditioners with various models and the historical data of each model air conditioner.
In the step S110, the target installation area information may be obtained by receiving target installation area information input by a shopping guide or a purchasing user, where the target installation area information may be an area name of the target installation area information or a longitude and latitude of the target installation area information, and the setting may be performed according to actual requirements.
The preset characteristic information of each air conditioner may include one or more of a heating characteristic, a cooling characteristic, a dehumidification characteristic, a phonation characteristic, a silencing characteristic, a stepless speed regulation characteristic, an applicable space range characteristic, a service life characteristic, an intelligent characteristic and the like.
In step S120, the environmental information of the target installation area may be searched for, so that the environmental information is searched for from a preset website or a preset database according to the installation area name or longitude and latitude. When searching from presetting the website, can obtain the crawler program according to installation area name to adopt the crawler program to crawl the environmental information who presets in the website, wherein, environmental information includes temperature information and humidity information, environmental information can also include air quality situation information.
The historical data of each type of air conditioner can be obtained by obtaining the corresponding historical data of each type of air conditioner from a database associated with an air conditioner after-sales management platform. The historical data comprises a sale record and a maintenance record, and the historical data can also comprise a use feedback record and a complaint record.
In step S130, the maintenance proportion of each type of air conditioner may be obtained according to the sales record and the maintenance record in the historical data of the air conditioner, wherein the maintenance record is the maintenance record of the air conditioner in the warranty period. And when the maintenance proportion of the target type air conditioner is larger than the preset value, marking the performance characteristic of the target type air conditioner as poor performance characteristic. Obtaining abnormal performance characteristic information of each type of air conditioner according to feedback records and complaint records included in historical data of the air conditioners, obtaining functional characteristic information according to environmental information, removing target type air conditioners in the air conditioners with various types, selecting type air conditioners which meet the functional characteristic information and are not the abnormal performance characteristic information from the air conditioners with various types with the target type removed, and taking the type air conditioners as recommended types.
By adopting the method, the air conditioner suitable for being installed in the target installation area is recommended to the customer, and the problem that the air conditioner suitable for the installation area where the user is located cannot be accurately screened in the prior art is avoided.
In general, air conditioners suitable for the same installation area generally have multiple models, and in order to achieve more precise recommendation according to different requirements of users, in this embodiment, please refer to fig. 2, the method further includes step S140.
Step S140: and acquiring demand information, and analyzing the demand information to obtain demand characteristic information.
The requirement information comprises requirements that the air conditioner to be selected has silence, phonation and/or intellectualization. The method for acquiring the demand information may be to acquire demand information input by a user through a human-computer interaction device, or may be to acquire demand information input by a voice mode, which is not specifically limited herein.
The method for analyzing the demand information to obtain the demand characteristic information may be that a clustering algorithm is used to perform clustering and summarizing to obtain the demand characteristic information, where the demand characteristic information includes silence characteristic information, speech recognition characteristic information and/or intelligent control characteristic information, and specifically, the clustering algorithm may be a k-means algorithm, that is, a k-means algorithm.
When the air conditioner purchase recommendation method includes step S140, step S130 may specifically be:
step S132: and acquiring functional characteristic information of the air conditioner according to the environment information, and acquiring performance characteristic information of each type of air conditioner in the target installation area according to historical data of each type of air conditioner.
When the environmental information comprises a temperature range of-10 ℃ to 40 ℃ and a humidity range of 10% to 30%, the corresponding functional characteristics are a refrigeration characteristic, a heating characteristic and a humidification characteristic; when the environmental dimension is between minus 10 ℃ and 30 ℃ and the humidity range is between 10% and 30%, the corresponding functional characteristics are heating characteristics and humidifying characteristics; when the environmental dimension is between 15 degrees celsius and 40 degrees celsius and the humidity range is between 50% and 130%, the corresponding functional features should be a cooling feature and a dehumidifying feature.
The historical data of each type of air conditioner includes sales data, maintenance data, and usage feedback data, and the maintenance data may be maintenance data during a warranty period or for a preset duration (e.g., one, two, or three years) after sales. The step S132 may specifically be that a maintenance ratio is obtained according to the number of the maintenance data and the number of the sales data of each type of air conditioner, and the performance characteristic information of the type of air conditioner in the target area is searched from a preset corresponding relationship according to the maintenance ratio and the corresponding use feedback data of each type of air conditioner, where the preset corresponding relationship stores a plurality of types of performance characteristic information, and a maintenance ratio range and use feedback data respectively corresponding to each type of performance information. The obtained performance characteristic information is information such as excellent performance, general performance, poor performance and the like, and it can be understood that the feedback data may further include cooling feedback, heating feedback or volume feedback, and thus the obtained performance information may be cooling performance information, heating performance information, volume performance information and the like.
Step S134: and obtaining actual characteristic information of each type of air conditioner in the target installation area according to the preset characteristic information and the performance characteristic information of each type of air conditioner.
And replacing the corresponding preset characteristics with the performance characteristics to obtain the actual characteristic information of each type of air conditioner when the performance characteristics of each type of air conditioner are inconsistent with the corresponding preset characteristics.
Step S136: and judging whether the target model air conditioners which simultaneously meet the requirement characteristic information and the function characteristic information exist in the actual characteristic information of the air conditioners with various models.
The step may be specifically a target model air conditioner that determines whether the actual characteristic information of each model air conditioner satisfies the required characteristic information and the functional characteristic information at the same time, respectively.
Step S138: and when the target model air conditioner exists, generating recommendation information according to the model of the target model air conditioner.
When the actual characteristic information of one or more types of air conditioners simultaneously meets the requirement characteristic information and the function characteristic information, the type of air conditioner is used as a target type of air conditioner, and recommendation information is generated according to the type of the target type of air conditioner.
In order to provide better recommendations when the user requirements are not met, in this embodiment, optionally, when there is no air conditioner of the target model, the method further includes: and acquiring a target model air conditioner meeting the functional characteristic information from the actual characteristic information of the signal air conditioners of the air conditioners with various models as a recommended model air conditioner.
To facilitate the diversified recommendations, in this embodiment, when there is no target model air conditioner, the method further includes: recommending household auxiliary household appliances according to the demand characteristic information and the function characteristic information, wherein the household auxiliary household appliances comprise at least one of a humidifier, a dehumidifier and a heater.
Example two
Referring to fig. 3 and 4 in combination, an embodiment of the present application further provides an air conditioner purchase recommending apparatus, including:
the first obtaining module 110 is configured to obtain target installation area information and preset feature information of multiple types of air conditioners.
Since the first obtaining module 110 is similar to the implementation principle of step S110 in fig. 1, it will not be further described here.
The searching module 120 is configured to search, according to the target installation area information, environment information of a target installation area and historical data of each type of air conditioner installed in the target installation area correspondingly.
Since the searching module 120 is similar to the step S120 in fig. 1, the implementation principle of the step S120 is not further described here.
And the recommending module 130 is used for obtaining recommended models of air conditioners according to the preset characteristic information and the environmental information of the air conditioners with various models and the historical data of each model of air conditioner.
Since the recommendation module 130 is similar to the implementation principle of step S130 in fig. 1, it will not be further described here.
Optionally, in this embodiment, the air conditioner purchase recommending apparatus further includes:
the second obtaining module 140 is configured to obtain the requirement information, and analyze the requirement information to obtain requirement characteristic information.
Since the second obtaining module 140 is similar to the implementation principle of step S140 in fig. 2, it will not be further described here.
The recommending module 130 includes a first obtaining sub-module 132, a second obtaining sub-module 134, a judging sub-module 136, and a recommending sub-module 138.
And the first obtaining submodule 132 is used for obtaining the functional characteristic information of the air conditioner according to the environment information and obtaining the performance characteristic information of each type of air conditioner in the target installation area according to the historical data of each type of air conditioner.
Since the first obtaining sub-module 132 is similar to the implementation principle of step S132 in fig. 2, it will not be further described here.
And the second obtaining submodule 134 is configured to obtain actual characteristic information of each type of air conditioner in the target installation area according to preset characteristic information and performance characteristic information of the type of air conditioner.
Since the second obtaining submodule 134 is similar to the implementation principle of step S134 in fig. 2, it will not be further described here.
And the judging submodule 136 is configured to judge whether a target model air conditioner that simultaneously satisfies the required characteristic information and the functional characteristic information exists in the actual characteristic information of the multiple models of air conditioners.
Since the implementation principle of the determination sub-module 136 is similar to that of step S136 in fig. 2, no further description is provided here.
And the recommending submodule 138 is used for taking the target model air conditioner as the recommended model air conditioner when the target model air conditioner exists.
Since the implementation principle of the recommending submodule 138 is similar to that of the step S138 in fig. 2, no further description is provided here.
EXAMPLE III
The present embodiment also provides a computer-readable storage medium, such as a flash memory, a hard disk, a multimedia card, a card-type memory (e.g., SD or DX memory, etc.), a Random Access Memory (RAM), a Static Random Access Memory (SRAM), a read-only memory (ROM), an electrically erasable programmable read-only memory (EEPROM), a programmable read-only memory (PROM), a magnetic memory, a magnetic disk, an optical disk, a server, an App application mall, etc., on which a computer program is stored, which when executed by a processor, can implement the air conditioner purchase recommendation method steps as in the first embodiment.
The specific embodiment process of the above method steps can be referred to as embodiment one, and the detailed description of this embodiment is not repeated herein.
Example four
An embodiment of the present invention provides an electronic device, which includes a memory and a processor, wherein when being executed by the processor, a computer program stored in the memory implements an air conditioner purchase recommendation method as in the first embodiment. For the specific embodiment process of the above method steps, reference may be made to embodiment one, and details are not repeated here.
In summary, the air conditioner purchase recommendation method, apparatus, storage medium and electronic device provided by the present invention include: the method comprises the steps of obtaining target installation area information, preset characteristic information and demand information of air conditioners of various models, searching environment information of a target installation area and historical data of each type of air conditioner correspondingly installed in the target installation area according to the target installation area information, and obtaining recommendation information according to the preset characteristic information, the environment information and the historical data of each type of air conditioner of the air conditioners of various models, wherein the recommendation information comprises recommended air conditioner models so as to analyze and calculate the environment where a user is located and the demand of the user, and realize accurate evaluation and provide the best air conditioner purchase scheme for the user. The problem that in the prior art, a suitable air conditioner is difficult to recommend to a user is solved.
In the embodiments provided in the present invention, it should be understood that the disclosed system and method can be implemented in other ways. The system and method embodiments described above are merely illustrative.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
Although the embodiments of the present invention have been described above, the above descriptions are only for the convenience of understanding the present invention, and are not intended to limit the present invention. It will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (10)
1. An air conditioner purchase recommendation method, characterized in that the method comprises:
acquiring target installation area information and preset characteristic information of various types of air conditioners;
searching environmental information of a target installation area and historical data of each type of air conditioner correspondingly installed in the target installation area according to the target installation area information;
and obtaining recommendation information according to preset characteristic information, environmental information and historical data of each type of air conditioner of the air conditioners with various types, wherein the recommendation information comprises recommended air conditioner types.
2. The air conditioner purchase recommendation method according to claim 1, further comprising:
acquiring demand information, and analyzing the demand information to obtain demand characteristic information;
obtaining recommendation information according to preset characteristic information, environmental information and historical data of each type of air conditioner of the air conditioners with various types, wherein the recommendation information comprises the following steps:
acquiring functional characteristic information of the air conditioner according to the environment information, and acquiring performance characteristic information of each type of air conditioner in the target installation area according to historical data of each type of air conditioner;
obtaining actual characteristic information of each type of air conditioner in the target installation area according to preset characteristic information and performance characteristic information of the air conditioner;
judging whether a target model air conditioner which simultaneously meets the requirement characteristic information and the function characteristic information exists in the actual characteristic information of the air conditioners with various models;
and when the target model air conditioner exists, generating recommendation information according to the model of the target model air conditioner.
3. The air conditioner purchase recommendation method according to claim 2, wherein the historical data of each type of air conditioner comprises selling data, maintenance data and use feedback data of each type of air conditioner, and the performance characteristic information of each type of air conditioner is obtained according to the historical data of each type of air conditioner, and the method comprises the following steps:
obtaining the maintenance proportion of each type of air conditioner according to the quantity of the selling data and the quantity of the maintenance data of each type of air conditioner;
and searching performance characteristic information of each type of air conditioner in a target area from a preset corresponding relation according to the maintenance proportion of each type of air conditioner and corresponding use feedback data, wherein the preset corresponding relation stores various types of performance characteristic information, and maintenance proportion ranges and use feedback data which respectively correspond to each type of performance information.
4. The air conditioner purchase recommendation method according to claim 2, wherein when there is no target model air conditioner, the method further comprises:
and acquiring a target model air conditioner meeting the functional characteristic information from the actual characteristic information of the signal air conditioners of the air conditioners with various models as a recommended model air conditioner.
5. The air conditioner purchase recommendation method according to claim 4, wherein when there is no target model air conditioner, the method further comprises:
recommending household auxiliary household appliances according to the demand characteristic information and the function characteristic information, wherein the household auxiliary household appliances comprise at least one of a humidifier, a dehumidifier and a heater.
6. The air conditioner purchase recommendation method according to claim 2, wherein the step of analyzing the demand information to obtain demand characteristic information includes:
and carrying out clustering analysis on the demand information by adopting a clustering algorithm to obtain demand characteristic information.
7. An air conditioner purchase recommendation device, characterized in that the device comprises:
the first acquisition module is used for acquiring target installation area information and preset characteristic information of air conditioners of various models;
the searching module is used for searching the environmental information of the target installation area and the historical data of each type of air conditioner correspondingly installed in the target installation area according to the information of the target installation area;
and the recommendation module is used for obtaining the recommended model air conditioners according to the preset characteristic information and the environmental information of the air conditioners with various models and the historical data of each model of air conditioner.
8. An air conditioner purchase recommendation device according to claim 7, characterized in that said device further comprises:
the second acquisition module is used for acquiring the demand information and analyzing the demand information to obtain demand characteristic information;
the recommendation module comprises:
the first obtaining submodule is used for obtaining functional characteristic information of the air conditioner according to the environment information and obtaining performance characteristic information of each type of air conditioner in the target installation area according to historical data of each type of air conditioner;
the second obtaining submodule is used for obtaining actual characteristic information of each type of air conditioner in the target installation area according to preset characteristic information and performance characteristic information of the type of air conditioner;
the judgment submodule is used for judging whether a target model air conditioner which simultaneously meets the requirement characteristic information and the function characteristic information exists in the actual characteristic information of the air conditioners with various models;
and the recommending submodule is used for taking the target model air conditioner as the recommended model air conditioner when the target model air conditioner exists.
9. A storage medium storing a computer program executable by one or more processors to perform the air conditioner purchase recommendation method of any one of claims 1-6.
10. An electronic device comprising a memory and a controller, the memory having stored thereon a computer program that, when executed by the controller, performs the air conditioner purchase recommendation method of any one of claims 1-6.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911137343.1A CN110910213B (en) | 2019-11-19 | 2019-11-19 | Air conditioner purchase recommendation method and device, storage medium and electronic equipment |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911137343.1A CN110910213B (en) | 2019-11-19 | 2019-11-19 | Air conditioner purchase recommendation method and device, storage medium and electronic equipment |
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| CN110910213A true CN110910213A (en) | 2020-03-24 |
| CN110910213B CN110910213B (en) | 2023-04-07 |
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| CN201911137343.1A Active CN110910213B (en) | 2019-11-19 | 2019-11-19 | Air conditioner purchase recommendation method and device, storage medium and electronic equipment |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2023029449A1 (en) * | 2021-08-31 | 2023-03-09 | 佛山市顺德区美的电子科技有限公司 | Recommending method for air conditioner, air conditioner, and readable storage medium |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106846103A (en) * | 2017-01-11 | 2017-06-13 | 美的集团股份有限公司 | Method and apparatus are recommended in the purchase of home appliance |
| CN107016592A (en) * | 2017-03-08 | 2017-08-04 | 美的集团股份有限公司 | Home appliance based on application guide page recommends method and apparatus |
| CN107143970A (en) * | 2017-04-18 | 2017-09-08 | 珠海格力电器股份有限公司 | Air conditioner model selection method and device |
| CN109582863A (en) * | 2018-11-19 | 2019-04-05 | 珠海格力电器股份有限公司 | Recommendation method and server |
-
2019
- 2019-11-19 CN CN201911137343.1A patent/CN110910213B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106846103A (en) * | 2017-01-11 | 2017-06-13 | 美的集团股份有限公司 | Method and apparatus are recommended in the purchase of home appliance |
| CN107016592A (en) * | 2017-03-08 | 2017-08-04 | 美的集团股份有限公司 | Home appliance based on application guide page recommends method and apparatus |
| CN107143970A (en) * | 2017-04-18 | 2017-09-08 | 珠海格力电器股份有限公司 | Air conditioner model selection method and device |
| CN109582863A (en) * | 2018-11-19 | 2019-04-05 | 珠海格力电器股份有限公司 | Recommendation method and server |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2023029449A1 (en) * | 2021-08-31 | 2023-03-09 | 佛山市顺德区美的电子科技有限公司 | Recommending method for air conditioner, air conditioner, and readable storage medium |
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| CN110910213B (en) | 2023-04-07 |
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