Smart home equipment recommendation method and device, storage medium, equipment and product

Abstract

The invention discloses a recommendation method and device of smart home equipment, a storage medium, equipment and a product, and relates to the technical field of smart home / smart home, the recommendation method of the smart home equipment comprises the steps that a smart home scene model of a user is acquired, and the smart home scene model comprises use scene features of the smart home equipment; according to the smart home scene model, determining a to-be-replaced device in a plurality of corresponding smart home devices in the current use scene; and according to the use scene feature of the to-be-replaced device and the use scene features of a plurality of candidate devices of the same type as the to-be-replaced device, determining a first recommendation device from the plurality of candidate devices, and pushing the first recommendation device to the user terminal. According to the method, more accurate home equipment recommendation is provided, the effectiveness of the recommendation result is improved, more propendent recommendation is provided for the user, and the use experience of the user is improved.

Description

Technical Field

[0001] The present application relates to the field of smart home / smart family, and specifically, to a method, device, storage medium, equipment and product for recommending smart home devices. Background Art

[0002] A modern recommendation system is a system that uses data analysis and machine learning techniques to provide users with personalized content or product recommendations. With the development of the Internet and big data, recommendation systems have been widely used in e-commerce, social media, online streaming and other fields.

[0003] In the prior art, product recommendation algorithms are commonly used by e-commerce platforms, online retailers, and content providers. However, the existing recommendation technology has the problem of poor recommendation effect when recommending products to users. Summary of the invention

[0004] The present application provides a recommendation method, apparatus, storage medium, device and product for smart home devices, which are used to solve the technical problem that the existing recommendation technology has poor recommendation effect when recommending products to users.

[0005] In a first aspect, the present application provides a method for recommending a smart home device, comprising:

[0006] Acquire a smart home scenario model of the user, wherein the smart home scenario model includes usage scenario characteristics of smart home devices, and the usage scenario characteristics of the smart home devices are determined based on one or more of purchase records, usage records, environmental information, and device information of the smart home devices;

[0007] Determine a device to be replaced among the smart home devices according to the smart home scene model;

[0008] Based on the usage scenario characteristics of the device to be replaced and the usage scenario characteristics of multiple candidate devices of the same type as the device to be replaced, a first recommended device is determined from the multiple candidate devices, and the first recommended device is pushed to the user terminal, wherein the usage scenario characteristics of the candidate device are determined based on the device information of the candidate device.

[0009] Optionally, determining the first recommended device from the multiple candidate devices according to the usage scenario characteristics of the device to be replaced and the usage scenario characteristics of multiple candidate devices of the same type as the device to be replaced includes:

[0010] The usage scenario feature of the device to be replaced is matched with the usage scenario feature of each of the candidate devices for similarity, and a preset number of candidate devices ranked first in the similarity matching results are determined as the first recommended devices.

[0011] Optionally, the method further includes:

[0012] In response to the usage scenario update information input by the user, updating the usage scenario characteristics of the device to be replaced;

[0013] According to the updated usage scenario characteristics of the device to be replaced and the usage scenario characteristics of the multiple candidate devices, a second recommended device is determined from the multiple candidate devices, and the second recommended device is pushed to the user terminal.

[0014] Optionally, the method further includes:

[0015] Obtaining one or more of the purchase record, usage record, environment information, and device information of the smart home device;

[0016] According to the preset multiple scenario features corresponding to the smart home device, based on one or more of the purchase record, usage record, environmental information and device information, the usage scenario features of the smart home device are determined, wherein the usage scenario features of the smart home device are used to characterize the correlation between the smart home device and each usage scenario feature.

[0017] Optionally, the method further includes:

[0018] Obtaining device information of the candidate device;

[0019] According to the preset multiple scenario features corresponding to the smart home device, based on the device information, the usage scenario features of the candidate device are determined, wherein the usage scenario features of the candidate device are used to characterize the correlation between the candidate device and each usage scenario feature.

[0020] Optionally, the method further includes:

[0021] Determining a recommended latest replacement time for the device to be replaced according to the smart home scenario model;

[0022] Sending a prompt message to the user terminal, wherein the prompt message includes the device to be replaced and the recommended latest replacement time.

[0023] In a second aspect, the present application provides a recommendation device for a smart home device, comprising:

[0024] An acquisition module is used to acquire a user's smart home scene model, wherein the smart home scene model includes usage scenario characteristics of smart home devices, and the usage scenario characteristics of the smart home devices are determined based on one or more of the purchase records, usage records, environmental information and device information of the smart home devices.

[0025] A determination module is used to determine the device to be replaced in the smart home device according to the smart home scene model.

[0026] The determination module is also used to determine a first recommended device from multiple candidate devices based on usage scenario characteristics of the device to be replaced and usage scenario characteristics of multiple candidate devices of the same type as the device to be replaced, wherein the usage scenario characteristics of the candidate device are determined based on device information of the candidate device.

[0027] A processing module is used to push the first recommended device to the user terminal.

[0028] Optionally, the processing module is further used to perform similarity matching between the usage scenario characteristics of the device to be replaced and the usage scenario characteristics of each of the candidate devices.

[0029] The determination module is further configured to determine a preset number of candidate devices ranked first in the similarity matching results as the first recommended devices.

[0030] Optionally, the processing module is further used to update the usage scenario characteristics of the device to be replaced in response to usage scenario update information input by the user.

[0031] The determination module is further configured to determine a second recommended device from the multiple candidate devices according to the updated usage scenario characteristics of the device to be replaced and the usage scenario characteristics of the multiple candidate devices.

[0032] The processing module is further configured to push the second recommended device to the user terminal.

[0033] Optionally, the acquisition module is further used to obtain one or more of the purchase record, usage record, environmental information and device information of the smart home device.

[0034] The determination module is further used to determine the usage scenario characteristics of the smart home device according to multiple preset scenario characteristics corresponding to the smart home device, based on one or more of the purchase record, usage record, environmental information and device information, wherein the usage scenario characteristics of the smart home device are used to characterize the correlation between the smart home device and each usage scenario characteristic.

[0035] Optionally, the acquisition module is further used to acquire device information of the candidate device.

[0036] The determination module is also used to determine the usage scenario characteristics of the candidate device based on the device information according to multiple preset scenario characteristics corresponding to the smart home device, wherein the usage scenario characteristics of the candidate device are used to characterize the correlation between the candidate device and each usage scenario characteristic.

[0037] Optionally, the determination module is further used to determine the recommended latest replacement time of the device to be replaced based on the smart home scene model.

[0038] The processing module is further configured to send a prompt message to the user terminal, wherein the prompt message includes the device to be replaced and the latest recommended replacement time.

[0039] In a third aspect, the present application provides a computer-readable storage medium having computer-executable instructions stored thereon, which, when executed by a processor, are used to implement the method for recommending smart home devices as described in the first aspect and various possible implementations of the first aspect.

[0040] In a fourth aspect, the present application provides an electronic device, comprising: a processor, and a memory communicatively connected to the processor;

[0041] The memory stores computer-executable instructions;

[0042] The processor executes the computer-executable instructions stored in the memory to implement the method for recommending smart home devices as described in the first aspect and various possible implementations of the first aspect.

[0043] In a fifth aspect, the present application provides a program product, including a computer program, which, when executed by a processor, implements the smart home device recommendation method as described above.

[0044] The recommendation method, device, storage medium, equipment and product of smart home devices provided by the present application obtain the user's smart home scene model, wherein the smart home scene model includes the usage scene characteristics of the smart home device, and then determine the device to be replaced in the smart home device according to the smart home scene model, and perform similarity matching on the usage scene characteristics of the device to be replaced and the usage scene characteristics of each candidate device, and determine the preset number of candidate devices ranked first in the similarity matching result as the first recommended device, and push the first recommended device to the user terminal; in response to the usage scene update information input by the user, update the usage scene characteristics of the device to be replaced, and determine the second recommended device from multiple candidate devices according to the updated usage scene characteristics of the device to be replaced and the usage scene characteristics of multiple candidate devices, and push the second recommended device to the user terminal. The method provides users with more accurate home device recommendations based on the actual needs and preferences of users, combined with the similarity between the device to be replaced and the usage environment of the device, improves the effectiveness of the recommendation results, provides users with more inclined recommendations, and provides users with more relevant trade-in suggestions, thereby improving the user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0046] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0047] Figure 1 A schematic diagram of the hardware environment for the recommended method of the smart home device provided in this application;

[0048] Figure 2 Schematic diagram of the process of recommending the method for smart home devices provided in this application Figure 1 ;

[0049] Figure 3 Schematic diagram of the process of recommending the method for smart home devices provided in this application Figure 2 ;

[0050] Figure 4 A schematic diagram of the structure of a recommended device for a smart home device provided in this application;

[0051] Figure 5 A schematic diagram of the structure of the recommended smart home devices provided for this application. DETAILED DESCRIPTION

[0052] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present application.

[0053] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0054] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant laws, regulations and standards, and provide corresponding operation entrances for users to choose to authorize or refuse.

[0055] According to one aspect of an embodiment of the present application, a method for interacting with a smart home device is provided. The method for interacting with a smart home device is widely used in smart home, smart home, smart home device ecosystem, smart home ecosystem and other whole-house intelligent digital control application scenarios. Optionally, in this embodiment, the method for interacting with the smart home device can be applied to Figure 1 In the hardware environment composed of the terminal device 102 and the server 104 shown in FIG. Figure 1As shown, the server 104 is connected to the terminal device 102 via a network, and can be used to provide services (such as application services, etc.) for the terminal or a client installed on the terminal. A database can be set on the server or independently of the server to provide data storage services for the server 104. Cloud computing and / or edge computing services can be configured on the server or independently of the server to provide data computing services for the server 104.

[0056] The network may include but is not limited to at least one of the following: wired network, wireless network. The wired network may include but is not limited to at least one of the following: wide area network, metropolitan area network, local area network, and the wireless network may include but is not limited to at least one of the following: WIFI (Wireless Fidelity), Bluetooth. The terminal device 102 may be but is not limited to a PC, a mobile phone, a tablet computer, a smart air conditioner, a smart range hood, a smart refrigerator, a smart oven, a smart stove, a smart washing machine, a smart water heater, a smart washing equipment, a smart dishwasher, a smart projection equipment, a smart TV, a smart clothes drying rack, a smart curtain, a smart audio and video, a smart socket, a smart speaker, a smart speaker, a smart fresh air equipment, a smart kitchen and bathroom equipment, a smart bathroom equipment, a smart sweeping robot, a smart window cleaning robot, a smart mopping robot, a smart air purification equipment, a smart steamer, a smart microwave oven, a smart kitchen treasure, a smart purifier, a smart water dispenser, a smart door lock, etc.

[0057] A modern recommendation system is a system that uses data analysis and machine learning techniques to provide users with personalized content or product recommendations. With the development of the Internet and big data, recommendation systems have been widely used in e-commerce, social media, online streaming and other fields.

[0058] In the existing technology, product recommendation algorithms are commonly used by e-commerce platforms, online retailers and content providers to improve user experience, increase user satisfaction and loyalty, and drive sales and increase conversion rates. In addition to traditional e-commerce and streaming media, recommendation system technology has also been applied to news, social media, education, health and other fields to help users discover content and services of interest.

[0059] At present, the industry's commonly used recommendation algorithm is content-based recommendation, which makes recommendations based on the user's previous preferences and the characteristics of the product. However, when recommending products to users, the existing recommendation technology recommends a wide variety of products, but lacks personalization and tendency. It is still difficult for users to choose the most suitable product, resulting in poor recommendation results.

[0060] The method for recommending smart home devices provided in this application is intended to solve the above technical problems of the prior art. This method aims at the characteristics of home appliances as consumables, long repurchase cycles, and relatively fixed scenarios, and combines the characteristics of the home appliance consumables industry and similarity recommendation algorithms to provide users with more accurate product recommendations. Different from the traditional recommendation model based on user browsing and behavior records, it brings a more convenient user experience for old-for-new exchanges in the field of home appliances and promotes repurchase conversions. This method is based on the actual needs and preferences of users, combined with the correlation between the device to be recommended and the environment in which the device is used, to provide users with more accurate recommendations for home appliances, improve the effectiveness of the recommendation results, provide users with more biased recommendations, and provide users with more relevant old-for-new suggestions to enhance user experience.

[0061] The technical solution of the present application and how the technical solution of the present application solves the above-mentioned technical problems are described in detail below with specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present application will be described below in conjunction with the accompanying drawings.

[0062] Figure 2 Schematic diagram of the process of recommending a smart home device provided in an embodiment of the present application Figure 1 The execution subject of this embodiment may be, for example, a smart home platform provided with a device recommendation module. Figure 2 As shown, the recommendation method of the smart home device provided in this embodiment includes:

[0063] S201: Acquire a smart home scene model of the user, wherein the smart home scene model includes usage scene features of smart home devices.

[0064] Among them, the usage scenario characteristics of the smart home device are used to characterize the correlation between the smart home device and each usage scenario characteristic.

[0065] In an embodiment of the present application, the usage scenario characteristics of the smart home device are determined based on one or more of the purchase record, usage record, environmental information and device information of the smart home device, and the usage scenario characteristics of the smart home device refer to the usage feature data corresponding to each smart home device when the user uses multiple smart home devices. The usage feature data can reflect the specific usage of different smart home devices, and help the device recommendation module to better clarify the user's needs and preferences in different situations, so as to provide more accurate device recommendations when exchanging existing smart home devices for new ones.

[0066] Specifically, purchase records refer to the historical data of users' purchases of goods, including information on all products purchased by users in the past, such as purchase date, product category, brand, model, price, purchase frequency, etc.; usage records refer to the historical data of users' interactions with products, such as product usage frequency, usage duration, usage patterns, etc.; environmental information refers to relevant data on the physical and social environment in which users use smart home devices when using smart home devices, such as geographic location, family structure, house type, climatic conditions, etc.; device information refers to relevant data on smart home devices currently owned by users, such as the brand, model, specifications, age, performance status, etc. of the equipment.

[0067] It should be noted that different users correspond to different smart home scene models, and the smart home scene model is a data model of smart home devices generated for the same user and is unique; specifically, the smart home scene model includes usage scenario characteristics of multiple smart home devices under the same usage scenario, and the usage scenario characteristics corresponding to different home appliances are different.

[0068] Exemplarily, the smart home scenario model of the user currently obtained includes: "Air conditioning: time, duration, mode; Washing machine: mode, water quality, timeliness of collection; Family size: population"; wherein, for air conditioning, the usage scenario characteristics include time, duration, mode, and the time dimension also corresponds to further characteristic values: "Night -0.9"; for washing machine, the usage scenario characteristics include mode, water quality, timeliness of collection, and the mode dimension also corresponds to further characteristic values: "Small items -0.6, large items -0.3".

[0069] In some embodiments, the establishment of the smart home scene model is determined based on multiple scene characteristics and user's specific usage data.

[0070] In the embodiment of the present application, the scene features are pre-established, and the usage scene features are data information corresponding to different home appliances and different scene features in specific usage scenarios, and the scene features can also be extracted using historical usage data of different users and different types of home appliances; therefore, different users have the same scene features, but due to differences in usage habits and preferences of different users, the usage scene features corresponding to different users are different.

[0071] In the process of establishing the smart home scene model, the usage data, environmental information and device information of the same user and different home appliances are preprocessed, as well as the environmental information and device information of the user. Specifically, the data includes: removing noise and outliers in the data, converting data information of different scales into a unified format, and then clustering the normalized data according to preset scene features to obtain specific usage data corresponding to different home appliances under the same user and different scene features; and using the preprocessed specific usage data to build a smart home scene model corresponding to the current user.

[0072] It is understandable that the usage data of different home appliances is constantly changing. Based on the user usage data obtained in real time by the smart home platform, the user's smart home scene model can be updated in real time; in addition, the smart home scene model can reflect the detailed scenarios of the user's use of home appliances.

[0073] In some embodiments, one or more of the purchase record, usage record, environmental information, and device information of the smart home device are obtained; and according to a plurality of preset scene features corresponding to the smart home device, based on one or more of the purchase record, usage record, environmental information, and device information, the usage scene features of the smart home device are determined.

[0074] It can be understood that the usage scenario characteristics are obtained by analyzing the usage data of the same household appliance in different dimensions, and the usage scenario characteristics include but are not limited to: the correlation between the usage scenario characteristics and different scenario characteristics, wherein the usage scenario characteristics have multiple dimensions, for example: the usage scenario characteristics belonging to the same dimension in the usage scenario characteristics include: time, duration, mode, and the usage scenario characteristics of this dimension are also the preset scenario characteristics. Each usage scenario characteristic can be further subdivided into more specific usage scenario characteristics, including: time can be subdivided into: night, duration can be subdivided into: extra long and medium, and the dimension of the usage scenario characteristic "night" is lower than the dimension of the usage scenario characteristic "time", that is to say, the low-dimensional usage scenario characteristics refer to the specific data corresponding to the preset scenario characteristics under the current user's usage scenario.

[0075] For example, for air conditioning, the usage scenario features include time, duration, and mode, and the corresponding usage scenario feature under the time dimension is: night, and the corresponding relevance is: "night-0.9".

[0076] In some embodiments, the usage scenario features may also be pre-set. Specifically, the user's historical usage data may be analyzed and processed to extract a variety of feature information. In this case, the obtained feature information may be directly used as the usage scenario feature, or the extracted multiple feature information may be modified in combination with the user's usage preferences, and the modified multiple feature information may be used as the usage scenario feature.

[0077] It should be noted that by analyzing the user's purchase records, the device recommendation module can understand the user's preferences and consumption habits, thereby providing product recommendations that are more in line with the user's needs. For example, if the user frequently purchases products of a certain brand, the device recommendation module can give priority to recommending new products of that brand; usage records can help the device recommendation module understand how the user uses its products, thereby providing more personalized recommendations. For example, if the user frequently uses a certain function, the system can recommend products with similar or enhanced functions; environmental information can help the device recommendation module recommend products suitable for the user's specific environment. For example, in cold areas, the device recommendation module may recommend more efficient heating equipment, and in small households, recommend space-saving home appliances; in addition, by understanding the information of the user's existing equipment, the device recommendation module can provide more relevant recommendations. For example, the device recommendation module can recommend products that are compatible with existing equipment, or recommend better performance alternatives when trading in old equipment for new ones.

[0078] Exemplarily, one or more of the purchase record, usage record, environmental information and device information of the smart home equipment in the home usage scenario of the same user is obtained; using the correlation calculation model, according to the preset multiple scenario features corresponding to the smart home equipment, one or more of the purchase record, usage record, environmental information and device information are input into the correlation calculation model, so as to determine the correlation corresponding to the multiple usage scenario features of the smart home equipment, and associate the obtained correlation with the corresponding usage features to obtain the usage scenario features of the corresponding smart home equipment; wherein the correlation corresponding to the multiple usage scenario features obtained this time can specifically be: for air conditioning, the corresponding usage scenario features under the time dimension include: "Night-0.9", the corresponding usage scenario features under the duration dimension include: "Extra long-0.6, Medium-0.3", and the corresponding usage scenario features under the mode dimension include: "Cooling-1".

[0079] S202: Determine a device to be replaced in the smart home devices according to the smart home scene model.

[0080] Among them, the devices to be replaced are used to indicate smart home devices that are about to reach the end of their service life and need to be replaced or upgraded.

[0081] It can be understood that the smart home scene model stores the purchase records, usage records, environmental information and device information of multiple smart home devices in the current user's home environment; therefore, by utilizing the purchase records, usage records, environmental information and device information of different smart home devices that can be obtained, the usage of any smart home device can be determined, and then it can be determined whether the smart home device needs to be replaced; in addition, the number of devices to be replaced can be one or more, and according to the service life and degree of wear of different smart home devices, the replacement time of the corresponding devices also varies, and therefore, the number of devices to be replaced determined at different times also varies.

[0082] Since the service life and degree of wear of different smart home devices vary, the time when each device needs to be replaced will also be different; among them, the service life of the device is determined by its design specifications and manufacturing quality, while the degree of wear is affected by the frequency of daily use and the environment in which it is used. Both together determine when the smart home device needs to be replaced to ensure its normal operation and optimal performance.

[0083] In some embodiments, the determination of the device to be replaced can be achieved using a machine learning model. Specifically, a machine learning model is used for training based on historical replacement data of different users and different smart home devices, as well as the smart home scene model of the corresponding user, to obtain a replacement time prediction model. Therefore, the smart home scene model of the current user is input into the replacement time prediction model to determine the device that needs to be replaced in the smart home scene model of the current user, that is, the device to be replaced.

[0084] In other embodiments, the determination of the device to be replaced can also be achieved by utilizing the service life of different smart home devices. Specifically, the service life of different smart home devices is different, and the service life is fixed. Therefore, the current time node is obtained in real time, and the current time node is compared with the time node when the smart home device starts to be used, and the length of time used for different smart home devices is calculated respectively, and then compared with their respective service lives, so as to determine the device that needs to be replaced in the corresponding user's home environment, that is, the device to be replaced.

[0085] Exemplarily, the smart home devices in the current user's home environment include: air conditioner, washing machine, refrigerator; based on the smart home scene model of the corresponding user, the specific usage of different smart home devices is analyzed to determine the device to be replaced, and the device to be replaced can be: air conditioner.

[0086] S203: Determine a first recommended device from the multiple candidate devices according to the usage scenario characteristics of the device to be replaced and the usage scenario characteristics of multiple candidate devices of the same type as the device to be replaced, and push the first recommended device to the user terminal.

[0087] Among them, the candidate devices are used to update and replace the devices to be replaced, and the user terminal can be, for example, a smart communication device; the usage scenario characteristics of the candidate devices are used to characterize the correlation between the candidate devices and the characteristics of each usage scenario, and the recommended devices are used to indicate smart home devices that meet the user's usage needs.

[0088] In an embodiment of the present application, the usage scenario characteristics of the candidate device are determined based on the device information of the candidate device, and the usage scenario characteristics of the candidate device refer to the usage characteristic data of any smart home device in different usage scenarios. The usage characteristic data can reflect the specific usage of different smart home devices in different usage scenarios, and help the device recommendation module to better recommend smart home devices that meet the user's usage habits and usage needs.

[0089] It can be understood that the usage scenario characteristics refer to the correlation between different smart home devices and each usage scenario characteristics, and smart home devices of the same type have the same usage scenario characteristics. After respectively determining the usage scenario characteristics of the device to be replaced and the usage scenario characteristics of the candidate devices, the correlation between the device to be replaced and the current usage scenario characteristics, as well as the corresponding specific scenario characteristics under the current usage scenario can be obtained; according to the specific scenario characteristics corresponding to the current usage scenario, the usage scenario characteristics of the candidate devices are screened, thereby obtaining the correlation of multiple identical usage scenario characteristics, thereby assisting in the determination of the first recommended device.

[0090] According to the usage scenario characteristics of the device to be replaced and the usage scenario characteristics of multiple candidate devices of the same type as the device to be replaced, the correlations corresponding to the usage scenario characteristics of the device to be replaced and the candidate devices are matched, and one or more smart home devices with a high degree of match with the device to be replaced are determined from the multiple candidate devices, and the device with a high degree of match is determined as the first recommended device, and then the first recommended device is pushed to the user terminal.

[0091] It is understandable that the number of the first recommended devices determined this time may be one or more. The present application does not impose any special limitation on the number of the first recommended devices.

[0092] In some embodiments, device information of the candidate device is obtained; and usage scenario characteristics of the candidate device are determined based on the device information according to a plurality of preset scenario characteristics corresponding to the smart home device.

[0093] The usage scenario characteristics of the candidate device are used to characterize the correlation between the candidate device and the preset scenario characteristics.

[0094] It can be understood that the calculation of the usage scenario characteristics of smart homes and the usage scenario characteristics of candidate devices is essentially the same. The usage scenario characteristics of smart homes are based on the user's specific usage scenarios, and the correlation between different smart home devices and the usage scenarios is calculated separately. The usage scenario characteristics of candidate devices are based on the device as the dimension, and the correlation between different devices and different usage scenario characteristics in different usage scenarios is calculated separately.

[0095] For example, if the candidate device currently being calculated for usage scenario features is water heater A, and the correlation corresponding to the usage scenario features under the "family size" subdivision dimension is calculated for the usage scenario features, the usage scenario features under this subdivision dimension include: "three-mouth, four-mouth, five-mouth", and the corresponding correlations are: "0.9, 0.4, 0", respectively.

[0096] In some embodiments, when screening the first recommended device, a matching threshold may be set, and the matching degree between the device to be replaced and the candidate devices is screened according to the matching threshold to determine the first recommended device to be recommended.

[0097] It is understandable that the matching degree threshold can be set by the user, or can be obtained by analyzing historical replacement data. This application does not impose any special restrictions on the method for determining the matching degree threshold.

[0098] In some embodiments, the device recommendation module can be set in the smart home platform or in the user terminal, and the existence form of the device recommendation module varies according to different setting locations; for example, the device recommendation module can be set in the user terminal and exist in the form of a smart home application.

[0099] The method for recommending smart home devices provided in this embodiment obtains the user's smart home scene model, wherein the smart home scene model includes the usage scene characteristics of the smart home devices; according to the currently obtained smart home scene model, the device to be replaced among multiple smart home devices in the current usage scene is determined; according to the usage scene characteristics of the device to be replaced and the usage scene characteristics of multiple candidate devices of the same type as the device to be replaced, the first recommended device is determined from multiple candidate devices, and the first recommended device is pushed to the user terminal. This method is based on the user's actual needs and preferences, combined with the correlation between the device to be recommended and the usage environment of the device, to provide users with more accurate home device recommendations, improve the effectiveness of the recommendation results, and enhance the user's usage experience.

[0100] Figure 3 Schematic diagram of the process of recommending a smart home device provided in an embodiment of the present application Figure 2 .like Figure 3 As shown, in this embodiment Figure 2Based on the embodiment, a method for recommending smart home devices is described in detail. The method for recommending smart home devices shown in this embodiment includes:

[0101] S301: Acquire a smart home scene model of a user, wherein the smart home scene model includes usage scene features of smart home devices.

[0102] S302: Determine a device to be replaced in the smart home devices according to the smart home scene model.

[0103] Step S301 is similar to the above step S201 and will not be described again.

[0104] S303: Performing similarity matching between the usage scenario characteristics of the device to be replaced and the usage scenario characteristics of each candidate device, and determining a preset number of candidate devices ranked first in the similarity matching results as first recommended devices.

[0105] S304 pushes the first recommended device to the user terminal.

[0106] The usage scenario characteristics of the device to be replaced are matched with the usage scenario characteristics of each candidate device respectively, and the similarity between the device to be replaced and each candidate device is obtained respectively. That is to say, for any usage scenario characteristics, each candidate device has a unique corresponding similarity; according to the similarities of all the candidate devices currently determined, all candidate devices are sorted in descending order, and a preset number of candidate devices in the front order are determined as the first recommended devices, and the first recommended devices are pushed to the user terminal.

[0107] In some embodiments, all candidate devices may be sorted in ascending order according to their similarities, and a preset number of candidate devices ranked later may be determined as first recommended devices, and the first recommended devices determined at that time may be pushed to the user terminal.

[0108] In the embodiment of the present application, the preset number can be set by the user independently, or can be set according to the maximum number of devices that can be recommended to the user at the same time. The present application does not impose any special restrictions on the determination of the preset number.

[0109] Exemplarily, if the current device to be replaced is air conditioner A, multiple candidate devices include: air conditioner 1, air conditioner 2, air conditioner 3, air conditioner 4; cosine similarity is used to calculate the similarity between air conditioner A and multiple candidate devices, and the results are: the similarity of air conditioner 1 is 0.5, the similarity of air conditioner 2 is 0.6, the similarity of air conditioner 3 is 0.8, and the similarity of air conditioner 4 is 0.4. The obtained similarity matching results are sorted in descending order to obtain the arrangement results of multiple candidate devices: air conditioner 3, air conditioner 2, air conditioner 4, air conditioner 1; if the current preset number is set to 2, air conditioner 3 and air conditioner 2 in the arrangement results are selected as the first recommended devices, and air conditioners 3 and air conditioners 2 are recommended to the user terminal.

[0110] S305: In response to the usage scenario update information input by the user, the usage scenario characteristics of the device to be replaced are updated.

[0111] S306: Determine a second recommended device from the multiple candidate devices according to the updated usage scenario characteristics of the device to be replaced and the usage scenario characteristics of the multiple candidate devices, and push the second recommended device to the user terminal.

[0112] Among them, the usage scenario update information is used to update the scenario data of the user's current usage scenario, and the second recommended device is used to indicate the smart home device that is re-recommended for the user based on the actual needs and preferences input by the user.

[0113] It is understandable that the usage scenario update information can reflect the changes in the user's usage scenario, and the usage scenario update information can identify the dynamic changes in user behavior and preferences, so that the device recommendation module can make timely adjustments and provide devices that better meet the user's current needs; in addition, the number of second recommended devices determined at this time can be one or more. This application does not impose any special restrictions on the number of second recommended devices.

[0114] In response to the usage scenario update information input by the user, the usage scenario characteristics of the device to be replaced are updated; the updated usage scenario characteristics of the device to be replaced are similarly matched with the usage scenario characteristics of each candidate device, and the similarities between the device to be replaced and each candidate device corresponding to different usage characteristics are obtained respectively; according to the similarities of all the candidate devices currently determined, all the candidate devices are sorted in descending order, and a preset number of candidate devices in the front order are determined as one or more second recommended devices, and the second recommended devices are pushed to the user terminal.

[0115] In some embodiments, the recommendation method for smart home devices further includes:

[0116] Determine the recommended latest replacement time for the device to be replaced based on the smart home scenario model; and send a prompt message to the user terminal.

[0117] The prompt information includes the device to be replaced and the recommended latest replacement time.

[0118] It can be understood that the smart home model includes the usage scenario characteristics of multiple smart home devices in the same usage scenario, and the usage scenario characteristics also include feature data corresponding to the user's usage records and purchase records. Therefore, the smart home scenario model can be used to determine the maximum usage time of different smart home devices in the current usage scenario, so as to determine the latest replacement time of the corresponding device.

[0119] For example, the currently generated prompt information may be: "The current equipment to be replaced is: Air Conditioner A; the latest replacement time is recommended: 3 months later." The present application does not impose any special restrictions on the specific content and prompt method of the prompt information.

[0120] The method for recommending smart home devices provided in this embodiment obtains the user's smart home scene model, wherein the smart home scene model includes the usage scene characteristics of the smart home devices, and then determines the device to be replaced among multiple smart home devices in the current usage scene according to the smart home scene model, and performs similarity matching on the usage scene characteristics of the device to be replaced and the usage scene characteristics of each candidate device, and determines the preset number of candidate devices ranked first in the similarity matching result as the first recommended device, and pushes the first recommended device to the user terminal; in response to the usage scene update information input by the user, the usage scene characteristics of the device to be replaced are updated, and according to the updated usage scene characteristics of the device to be replaced and the usage scene characteristics of multiple candidate devices, a second recommended device is determined from multiple candidate devices, and the second recommended device is pushed to the user terminal. Based on the actual needs and preferences of the user, combined with the correlation between the device to be recommended and the usage environment of the device, the method provides the user with more accurate home device recommendations, improves the effectiveness of the recommendation results, provides the user with more inclined recommendations, and also provides the user with more relevant trade-in suggestions, thereby improving the user's usage experience.

[0121] Figure 4 This is a schematic diagram of the recommended structure of the smart home device provided by this application. Figure 4 As shown, the present application provides a recommendation device for smart home devices, and the recommendation device 400 for smart home devices includes:

[0122] The acquisition module 401 is used to obtain the user's smart home scene model, wherein the smart home scene model includes the usage scenario characteristics of the smart home device, and the usage scenario characteristics of the smart home device are determined based on one or more of the purchase record, usage record, environmental information and device information of the smart home device.

[0123] The determination module 402 is used to determine the device to be replaced in the smart home devices according to the smart home scene model.

[0124] The determination module 402 is further used to determine a first recommended device from the multiple candidate devices based on the usage scenario characteristics of the device to be replaced and the usage scenario characteristics of multiple candidate devices of the same type as the device to be replaced, wherein the usage scenario characteristics of the candidate device are determined based on the device information of the candidate device.

[0125] The processing module 403 is configured to push the first recommended device to the user terminal.

[0126] Optionally, the processing module 403 is further configured to perform similarity matching between the usage scenario feature of the device to be replaced and the usage scenario feature of each of the candidate devices.

[0127] The determination module 402 is further configured to determine a preset number of candidate devices ranked first in the similarity matching result as the first recommended devices.

[0128] Optionally, the processing module 403 is further configured to update the usage scenario characteristics of the device to be replaced in response to usage scenario update information input by a user.

[0129] The determination module 402 is further configured to determine a second recommended device from the multiple candidate devices according to the updated usage scenario characteristics of the device to be replaced and the usage scenario characteristics of the multiple candidate devices.

[0130] The processing module 403 is further configured to push the second recommended device to the user terminal.

[0131] Optionally, the acquisition module 401 is further used to acquire one or more of the purchase record, usage record, environmental information and device information of the smart home device.

[0132] The determination module 402 is further used to determine the usage scenario characteristics of the smart home device according to the preset multiple scenario characteristics corresponding to the smart home device, based on one or more of the purchase record, usage record, environmental information and device information, wherein the usage scenario characteristics of the smart home device are used to characterize the correlation between the smart home device and each usage scenario characteristic.

[0133] Optionally, the acquisition module 401 is further configured to acquire device information of the candidate device.

[0134] The determination module 402 is further used to determine the usage scenario characteristics of the candidate device based on the device information according to multiple preset scenario characteristics corresponding to the smart home device, wherein the usage scenario characteristics of the candidate device are used to characterize the correlation between the candidate device and each usage scenario characteristic.

[0135] Optionally, the determination module 402 is further used to determine the recommended latest replacement time of the device to be replaced according to the smart home scene model.

[0136] The processing module 403 is further configured to send a prompt message to the user terminal, where the prompt message includes the device to be replaced and the latest recommended replacement time.

[0137] Figure 5 This is a schematic diagram of the recommended smart home devices provided by this application. Figure 5 As shown, the present application provides a recommendation device for smart home devices, and the recommendation device 500 for smart home devices includes: a receiver 501, a transmitter 502, a processor 503 and a memory 504.

[0138] Receiver 501, used for receiving instructions and data;

[0139] A transmitter 502, used for sending instructions and data;

[0140] Memory 504, used to store computer-executable instructions;

[0141] The processor 503 is used to execute the computer-executable instructions stored in the memory 504 to implement the steps performed by the smart home device recommendation method in the above embodiment. For details, please refer to the relevant description in the above smart home device recommendation method embodiment.

[0142] Optionally, the memory 504 may be independent or integrated with the processor 503 .

[0143] When the memory 504 is independently provided, the electronic device further includes a bus for connecting the memory 504 and the processor 503 .

[0144] The implementation principle and technical effects of the electronic device provided in this embodiment can be found in the aforementioned embodiments and will not be described in detail here.

[0145] An embodiment of the present application further provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer-executable instructions. When a processor executes the computer-executable instructions, the method described in any of the above embodiments is implemented.

[0146] An embodiment of the present application further provides a computer program product, including a computer program, which implements the method described in any of the above embodiments when executed by a processor.

[0147] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of the modules is only a logical function division, and there may be other division methods in actual implementation, such as multiple modules can be combined or integrated into another system, or some features can be ignored or not executed.

[0148] The above-mentioned integrated module implemented in the form of a software function module can be stored in a computer-readable storage medium. The above-mentioned software function module is stored in a storage medium, including a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) or a processor to perform some steps of the method described in each embodiment of the present application.

[0149] It should be understood that the above-mentioned processor can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), etc. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor, etc. The steps of the method disclosed in the application can be directly embodied as being executed by a hardware processor, or can be executed by a combination of hardware and software modules in the processor. The memory may include a high-speed RAM memory, and may also include a non-volatile storage NVM, such as at least one disk memory, and can also be a USB flash drive, a mobile hard disk, a read-only memory, a disk or an optical disk, etc.

[0150] The above storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk. The storage medium can be any available medium that can be accessed by a general or special purpose computer.

[0151] An exemplary storage medium is coupled to a processor so that the processor can read information from the storage medium and write information to the storage medium. Of course, the storage medium can also be a component of the processor. The processor and the storage medium can be located in an application specific integrated circuit (ASIC). Of course, the processor and the storage medium can also exist as discrete components in an electronic device or a main control device.

[0152] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or device including the element.

[0153] The serial numbers of the above-mentioned embodiments of the present application are for description only and do not represent the advantages or disadvantages of the embodiments.

[0154] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, a magnetic disk, or an optical disk), and includes a number of instructions for enabling a terminal device (which can be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to execute the methods described in each embodiment of the present application.

[0155] The above is only a preferred implementation of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A method for recommending smart home devices, characterized in that: The method comprises: Acquire a smart home scenario model of the user, wherein the smart home scenario model includes usage scenario characteristics of smart home devices, and the usage scenario characteristics of the smart home devices are determined based on one or more of purchase records, usage records, environmental information, and device information of the smart home devices; Determine a device to be replaced among the smart home devices according to the smart home scene model; Based on the usage scenario characteristics of the device to be replaced and the usage scenario characteristics of multiple candidate devices of the same type as the device to be replaced, a first recommended device is determined from the multiple candidate devices, and the first recommended device is pushed to the user terminal, wherein the usage scenario characteristics of the candidate device are determined based on the device information of the candidate device.

2. The method for recommending smart home devices according to claim 1, characterized in that: The determining a first recommended device from among multiple candidate devices of the same type as the device to be replaced according to the usage scenario characteristics of the device to be replaced and the usage scenario characteristics of the multiple candidate devices includes: The usage scenario feature of the device to be replaced is matched with the usage scenario feature of each of the candidate devices for similarity, and a preset number of candidate devices ranked first in the similarity matching results are determined as the first recommended devices.

3. The method for recommending smart home devices according to claim 1, characterized in that: The method further comprises: In response to the usage scenario update information input by the user, updating the usage scenario characteristics of the device to be replaced; According to the updated usage scenario characteristics of the device to be replaced and the usage scenario characteristics of the multiple candidate devices, a second recommended device is determined from the multiple candidate devices, and the second recommended device is pushed to the user terminal.

4. The method for recommending smart home devices according to any one of claims 1 to 3, characterized in that: The method further comprises: Obtaining one or more of the purchase record, usage record, environment information, and device information of the smart home device; According to the preset multiple scenario features corresponding to the smart home device, based on one or more of the purchase record, usage record, environmental information and device information, the usage scenario features of the smart home device are determined, wherein the usage scenario features of the smart home device are used to characterize the correlation between the smart home device and each usage scenario feature.

5. The method for recommending smart home devices according to any one of claims 1 to 3, characterized in that: The method further comprises: Obtaining device information of the candidate device; According to the preset multiple scenario features corresponding to the smart home device, based on the device information, the usage scenario features of the candidate device are determined, wherein the usage scenario features of the candidate device are used to characterize the correlation between the candidate device and each usage scenario feature.

6. The method for recommending smart home devices according to any one of claims 1 to 3, characterized in that: The method further comprises: Determining a recommended latest replacement time for the device to be replaced according to the smart home scenario model; Sending a prompt message to the user terminal, wherein the prompt message includes the device to be replaced and the recommended latest replacement time.

7. A recommendation device for smart home devices, characterized in that: include: An acquisition module, configured to acquire a user's smart home scene model, wherein the smart home scene model includes usage scene features of smart home devices, and the usage scene features of the smart home devices are determined based on one or more of a purchase record, a usage record, environmental information, and device information of the smart home devices; A determination module, configured to determine a device to be replaced in the smart home device according to the smart home scene model; The determination module is further configured to determine a first recommended device from the multiple candidate devices according to the usage scenario characteristics of the device to be replaced and the usage scenario characteristics of multiple candidate devices of the same type as the device to be replaced, wherein the usage scenario characteristics of the candidate devices are determined based on the device information of the candidate devices; A processing module is used to push the first recommended device to the user terminal.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored program, wherein the program executes the method according to any one of claims 1 to 6 when executed.

9. An electronic device, comprising a memory and a processor, characterized in that: A computer program is stored in the memory, and the processor is configured to execute the method according to any one of claims 1 to 6 through the computer program.

10. A program product, characterized in that The invention comprises a computer program, which implements the method according to any one of claims 1 to 6 when being executed by a processor.

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