Device card adjustment method and device, electronic device, and storage medium

Abstract

The application relates to a device card adjustment method and device, an electronic device and a storage medium, wherein the method comprises the following steps: obtaining target characteristic values of devices in a target local area network, wherein the target characteristics comprise characteristic values for representing device signal strengths, characteristic values for representing user behavior habits, characteristic values for representing device category functions and characteristic values for representing labels; generating a characteristic vector based on a target vector, and obtaining respective scores of the devices based on the characteristic vector and weights corresponding to the target characteristics; and adjusting the order of the cards corresponding to the devices on a terminal display page according to a preset classification result and the scores. Through the application, the problem that, in the prior art, when there are multiple device cards, the multiple device cards are placed in a disorderly manner on a display page, so that a user cannot quickly find the card of a device that needs to be frequently used is solved.

Description

Technical Field

[0001] This application relates to the field of device card adjustment, and more particularly to a method and apparatus for adjusting device cards, an electronic device, and a storage medium. Background Technology

[0002] The current mainstream smart home products provide users with an interaction method where they can set up small cards for devices on the main page. Clicking on these cards leads to the corresponding device control details page. However, as the number of devices under a user's account continues to increase, there are often many device cards on the homepage, and these cards are placed haphazardly on the display page. This forces users to scroll down the page to find the target device card, and even for frequently used devices, it is difficult for users to quickly find the corresponding device card. Summary of the Invention

[0003] This application provides a method and apparatus for adjusting device cards, an electronic device, and a storage medium to solve the problem in the prior art where multiple device cards are placed haphazardly on the display page, making it difficult for users to quickly find the card of the device they frequently need.

[0004] In a first aspect, this application provides a method for adjusting device cards, the method comprising: obtaining target feature values ​​of each device in a target local area network, wherein the target features include feature values ​​for characterizing device signal strength, feature values ​​for characterizing user behavior habits, feature values ​​for characterizing device category functions, and feature values ​​for characterizing tags; generating feature vectors based on the target vectors, and obtaining scores corresponding to each device based on the feature vectors and weights corresponding to the target features; adjusting the order of the cards corresponding to each device on the terminal display page according to a preset classification result and the scores, wherein the classification result is used to characterize whether the cards corresponding to each device are on the homepage of the display page.

[0005] Secondly, this application provides a device for adjusting device cards, comprising: an acquisition module, configured to acquire target feature values ​​of each device within a target local area network, wherein the target features include feature values ​​characterizing device signal strength, feature values ​​characterizing user behavior habits, feature values ​​characterizing device category functions, and feature values ​​characterizing tags; a first processing module, configured to generate feature vectors based on the target vectors, and obtain scores corresponding to each device based on the feature vectors and weights corresponding to the target features; and an adjustment module, configured to adjust the order of the cards corresponding to each device on the terminal display page according to a preset classification result and the scores, wherein the classification result characterizes whether the cards corresponding to each device are on the homepage of the display page.

[0006] Thirdly, this application provides an electronic device, comprising: at least one communication interface; at least one bus connected to the at least one communication interface; at least one processor connected to the at least one bus; and at least one memory connected to the at least one bus, wherein the processor is configured to execute the device card adjustment method described in the first aspect of this application.

[0007] Fourthly, this application also provides a computer storage medium storing computer-executable instructions for performing the device card adjustment method described in the first aspect of this application.

[0008] Compared with the prior art, the technical solution provided in this application has the following advantages: In this application embodiment, by considering the feature values ​​used to characterize the signal strength of the device, the feature values ​​used to characterize the user's behavioral habits, the feature values ​​used to characterize the device category function, and the feature values ​​used to characterize the tag and their corresponding weights, a score for each device is obtained. Then, based on the score and classification results, the order of the cards corresponding to each device on the terminal display page is arranged, which is more in line with the user's usage habits and the current network environment. This allows users to quickly find the card corresponding to the device that they frequently use and that has a good signal strength, improving the user's control efficiency over the device from the terminal. It also solves the problem in the prior art where, when there are multiple device cards, they are placed randomly on the display page, making it difficult for users to quickly find the card of the device they frequently need. Attached Figure Description

[0009] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0010] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0011] One or more embodiments are illustrated by way of example with reference numerals in the accompanying drawings. These illustrations do not constitute a limitation on the embodiments. Elements with the same reference numerals in the drawings are denoted as similar elements. Unless otherwise stated, the figures in the drawings are not to be limited by scale.

[0012] Figure 1 A flowchart illustrating a method for adjusting a device card as provided in an embodiment of this application;

[0013] Figure 2A schematic diagram of the structure of an adjustment device for a device card provided in an embodiment of this application;

[0014] Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0015] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0016] The following disclosure provides numerous different embodiments or examples for implementing various structures of the invention. To simplify the disclosure, specific examples of components and arrangements are described below. These are merely examples and are not intended to limit the scope of the invention. Furthermore, reference numerals and / or letters may be repeated in different examples. Such repetition is for simplification and clarity and does not in itself indicate a relationship between the various embodiments and / or arrangements discussed.

[0017] Figure 1 A flowchart illustrating a method for adjusting a device card as provided in this application embodiment is shown below. Figure 1 As shown, the steps of this method include:

[0018] Step 101: Obtain the target feature values ​​of each device in the target local area network. The target features include feature values ​​that characterize the signal strength of the device, feature values ​​that characterize the user's behavior habits, feature values ​​that characterize the category and function of the device, and feature values ​​that characterize the tag.

[0019] The target local area network in this application embodiment can refer to a local area network in a home environment, or a local area network in an office or business environment. The devices can be refrigerators, televisions, air conditioners, washing machines, water heaters, lights, etc. For lights and air conditioners, corresponding device cards can be set according to different areas of the local area network; that is, one corresponding device card can be set for each air conditioner or light in a room.

[0020] Step 102: Generate feature vectors based on target vectors, and obtain the scores corresponding to each device based on feature vectors and weights corresponding to target features;

[0021] The weights in this application embodiment can be set according to the user's actual needs. For example, the weight of features that the user values ​​more can be set higher, and the weight of features that the user does not value more can be set lower. For example, if the user values ​​the feature corresponding to user behavior habits more, since it is a manifestation of the user's operating habits, the corresponding weight can be set higher.

[0022] Step 103: Adjust the order of the cards corresponding to each device on the terminal display page according to the preset classification results and scores. The classification results are used to indicate whether the cards corresponding to each device are on the homepage of the display page.

[0023] Through steps 101 to 103 above, in this embodiment of the application, by considering the feature values ​​used to characterize device signal strength, the feature values ​​used to characterize user behavior habits, the feature values ​​used to characterize device category functions, and the feature values ​​used to characterize tags and their corresponding weights, a score for each device is obtained. Then, based on the score and classification results, the order of the cards corresponding to each device on the terminal display page is adjusted, thereby making the sorting of device cards on the terminal display page more in line with user habits and the current network environment. This allows users to quickly find the card corresponding to frequently used devices with good signal strength, improving the efficiency of user control over devices from the terminal. It also solves the problem in the prior art where multiple device cards are placed haphazardly on the display page, making it difficult for users to quickly find the card of the device they frequently need.

[0024] In an optional embodiment of this application, when the target feature is a feature value used to characterize the signal strength of a device, the method for obtaining the target feature values ​​of each device in the target local area network involved in step 101 above may further include:

[0025] Step 11: Periodically scan the signals of each device in the target local area network to obtain the signal strength of each device in different periods;

[0026] Step 12: Sort the signal strength of each device in each device, and obtain N signal strengths in order from the sorted signal strengths; where N is an odd number greater than or equal to 5;

[0027] Step 13: Calculate the average value of each of the N signal strengths, and normalize the average value corresponding to each device to obtain the characteristic value of the signal strength corresponding to each device.

[0028] For steps 11 and 13 above, in a specific example, if the current devices include air conditioners, refrigerators, water heaters, and washing machines, the signal strength of the air conditioners, refrigerators, water heaters, and washing machines is periodically scanned. For each device, a set of corresponding signal strength values ​​is obtained. Taking the refrigerator as an example, the scanned signals are shown in Table 1.

[0029] refrigerator <![CDATA[P1]]> <![CDATA[P2]]> <![CDATA[P3]]> ....... <![CDATA[P i-1 ]]> <![CDATA[P i ]]> ......

[0030] Table 1

[0031] We can take N P values ​​sequentially from Table 1, not necessarily starting from P1. For example, we can take 7 consecutive values ​​from P3, and then calculate the average of m=5 after removing the largest and smallest terms from the 7 P values.

[0032]

[0033] Further, RSSI = 10 * lgP; P is the power value after node smoothing. Then, the above signal strength value is normalized to obtain the signal strength feature value x1.

[0034]

[0035] The same approach applies to other devices within the local area network (LAN), allowing us to obtain the signal strength characteristics of each device. These signal strength values ​​provide the signal strength of each device within the LAN. For subsequent control, we can prioritize controlling devices with stronger signals, or use mobile terminals to control devices with weaker signals.

[0036] In another optional embodiment of this application, when the target feature is a feature value used to characterize user behavior habits, the method for obtaining the target feature values ​​of each device in the target local area network involved in step 101 above may further include:

[0037] Step 21: Obtain the product of the number of times the user operates on the cards of each device on the terminal and the duration of each operation within a preset time period;

[0038] Step 22: Normalize the product results for each device to obtain the feature values ​​of each device used to characterize user behavior habits.

[0039] For steps 21 and 22 above, in a specific example, it can be to collect user operation card records and calculate the product of the number of operations within the statistical period and the duration of each operation using the following formula:

[0040] T = n * t

[0041] Where T is the product result, n is the number of operations within the cycle, and t is the duration of each operation.

[0042] Therefore, after normalizing the above time information, the user behavior habit feature value x2 can be obtained using the following formula:

[0043]

[0044] As can be seen, the user behavior habit feature values ​​of each device can be obtained through the above method. These user behavior habit feature values ​​can be used to further confirm the user's usage habits. In the subsequent process of sorting device cards, the device cards corresponding to frequently used devices can be placed in a relatively early position to facilitate users' search.

[0045] In an optional embodiment of this application, when the target feature is a feature value used to characterize the function of a device category, the method for obtaining the target feature value of each device in the target local area network involved in step 101 above may further include:

[0046] Step 31: Assign values ​​to each device based on its feature richness and whether the function is a commonly used function;

[0047] Step 32: Normalize the assigned values ​​for each device to obtain the feature values ​​of each device's category function.

[0048] As shown in steps 31 and 32 above, the category function is assigned a value according to the functions of different equipment categories. For example, air conditioning equipment has functions such as start-up, stop-up, cooling, heating, dehumidification, air supply, fan speed adjustment, and air swing. Therefore, this parameter can be assigned a value according to the richness of the equipment's functions and whether it is a commonly used function. Assuming this value is C, this value is also normalized to obtain the equipment category function feature value x3:

[0049]

[0050] As can be seen, the category function feature value of each device can be obtained through the above method. The richness of the category function of the device can be further obtained through the category function feature value. Then, in the subsequent sorting process of device cards, the device cards corresponding to devices with richer category functions can be placed in a higher position to facilitate users to find them.

[0051] In an optional embodiment of this application, when the target feature is a feature value used to characterize a tag, the method for obtaining the target feature values ​​of each device in the target local area network involved in step 101 above may further include:

[0052] Step 41: Obtain the user's preference tag settings for each device in the terminal, and assign values ​​to each device based on the preference tag settings;

[0053] Step 42: Normalize the assigned values ​​for each device to obtain the feature values ​​of each device's category function.

[0054] The preference tag settings mentioned in steps 41 and 42 above refer to the user's setting of tags for devices on the terminal, such as setting the device card to be on top or to be hidden. Devices can be assigned values ​​based on different preference tags, and then the feature values ​​of each device's category function can be obtained through normalization processing.

[0055] In an optional embodiment of this application, before adjusting the order of the cards corresponding to each device on the terminal display page according to the preset classification results and scores, the method of this application may further include:

[0056] Step 51: Input the classification effect of whether the card is displayed on the homepage for each device and the processing speed into the target neural network to obtain the classification result.

[0057] In a specific example of step 51 above, considering the classification effect and processing speed of whether to display cards on the homepage, a shallow neural network structure is used to train a binary classification model (outputting the classification result of whether it belongs to the homepage). By continuously accumulating user operation data, the network is fine-tuned using the backpropagation method to obtain a model that is more in line with the personalized classification of users.

[0058] In an optional embodiment of this application, the method of adjusting the order of cards corresponding to each device on the terminal display page according to preset classification results and scores in step 103 above may further include:

[0059] Step 51: If the classification result of the device card is not displayed on the homepage, sort the device cards on the homepage according to their scores.

[0060] Step 52: If the classification results of the device cards are displayed on the homepage, and there are multiple cards displayed on the homepage, sort the device cards on the homepage according to their scores.

[0061] Step 53: If the device card is categorized as displayed on the homepage and only one card is displayed on the homepage, then display the device's control details page on the homepage.

[0062] As can be seen from steps 51 to 53 above, non-homepage device cards are arranged according to their scores. When there is only one device card on the homepage, the specific device control details page is displayed directly. When there are multiple device cards on the homepage, they are arranged according to their scores. Since the score in this embodiment is a comprehensive representation of the features used to characterize device signal strength, user behavior habits, device category functions, and tags, the sorting of device cards based on scores takes into account user habits, device category, and device signal strength. A higher score indicates that the device is frequently used by the user, has a relatively rich category, and has good signal strength. The device card corresponding to this device should be placed in a position that is easy for the user to find on the homepage or at the beginning of non-homepage sections.

[0063] In optional embodiments of this application, the method in this application may further include:

[0064] Step 61: Receive user voice control commands and identify the voice control commands used to control multiple devices;

[0065] Step 62: If there are cards displayed on the homepage on multiple devices, control the device corresponding to the card displayed on the homepage based on voice control commands.

[0066] As can be seen, after adjusting the device cards through the above-described method in this application embodiment, when the user's voice dialogue does not specify the device name but only includes a general device type, such as "Help me turn on the air conditioner", the air conditioner device corresponding to the device card on the homepage will be prioritized (such as the living room air conditioner; there are also air conditioners in other rooms, but the corresponding device cards are not on the homepage). This reduces the number of multiple rounds of interaction for the user to complete the slots, reduces the dialogue steps, and improves the user's control efficiency over the device.

[0067] Corresponding to the above Figure 1 This application also provides an adjustment device for a device card, such as... Figure 2 As shown, the device includes:

[0068] The acquisition module 202 is used to acquire the target feature values ​​of each device in the target local area network. The target features include feature values ​​that characterize the signal strength of the device, feature values ​​that characterize the user's behavior habits, feature values ​​that characterize the category and function of the device, and feature values ​​that characterize the tag.

[0069] The first processing module 204 is used to generate feature vectors based on target vectors, and obtain the scores corresponding to each device based on feature vectors and weights corresponding to target features.

[0070] The adjustment module 206 is used to adjust the order of the cards corresponding to each device on the terminal display page according to the preset classification results and scores. The classification results are used to indicate whether the cards corresponding to each device are on the homepage of the display page.

[0071] The apparatus in this application embodiment considers feature values ​​representing device signal strength, feature values ​​representing user behavior habits, feature values ​​representing device category functions, and feature values ​​representing tags and their corresponding weights to obtain a score for each device. Then, based on the score and classification results, the order of the corresponding cards for each device on the terminal display page is adjusted. This arrangement better aligns with user habits and the current network environment, allowing users to quickly find the cards corresponding to frequently used devices with good signal strength. This improves the efficiency of user control over devices from the terminal and solves the problem in the prior art where multiple device cards are randomly placed on the display page, making it difficult for users to quickly find the cards of frequently used devices.

[0072] In an optional embodiment of this application, when the target feature is a feature value used to characterize the signal strength of a device, the acquisition module 202 in this application embodiment may further include: a scanning unit, used to periodically scan the signals of each device in the target local area network to obtain the signal strength of each device in different periods; a first processing unit, used to sort the signal strength of each device and obtain N signal strengths in order from the sorted signal strengths; wherein N is an odd number greater than or equal to 5; and a second processing unit, used to calculate the average value of the N signal strengths and perform normalization processing based on the average value corresponding to each device to obtain the feature value of the signal strength corresponding to each device.

[0073] In an optional embodiment of this application, when the target feature is a feature value used to characterize user behavior habits, the acquisition module in this application embodiment may further include: an acquisition unit, used to acquire the product of the number of times the user operates on the cards of each device on the terminal and the duration of each operation within a preset time period; and a third processing unit, used to normalize the product results corresponding to each device to obtain the feature value of each device used to characterize user behavior habits.

[0074] In an optional embodiment of this application, when the target feature is a feature value used to characterize the category function of the device, the acquisition module in this application embodiment may further include: a fourth processing unit, used to assign values ​​to each device according to the function richness of each device and whether the function is a commonly used function; and a fifth processing unit, used to normalize the assigned values ​​corresponding to each device to obtain the feature value of the category function of each device.

[0075] In an optional embodiment of this application, when the target feature is a feature value used to characterize a tag, the acquisition module in this application embodiment may further include: a sixth processing unit, used to acquire the user's preference tag settings for each device in the terminal, and assign values ​​to each device based on the preference tag settings; and a seventh processing unit, used to normalize the assigned values ​​corresponding to each device to obtain the feature values ​​of the category functions of each device.

[0076] In an optional embodiment of this application, before adjusting the order of the cards corresponding to each device on the terminal display page according to the preset classification results and scores, the device in this application embodiment may further include: a second processing module, used to input the classification effect of whether the cards corresponding to each device are displayed on the homepage and the processing speed into the target neural network to obtain the classification result.

[0077] In an optional embodiment of this application, the adjustment module may further include: a first sorting unit, used to sort the device cards on the non-homepage according to their scores when the classification result of the device cards is not displayed on the homepage; a second sorting unit, used to sort the device cards on the homepage according to their scores when the classification result of the device cards is displayed on the homepage and there are multiple cards displayed on the homepage; and a display unit, used to display the device's control details page on the homepage when the classification result of the device cards is displayed on the homepage and there is only one card displayed on the homepage.

[0078] In an optional embodiment of this application, the apparatus may further include: a third processing module, configured to receive user voice control commands and identify the voice control commands for controlling multiple devices; and a control module, configured to control the device corresponding to the card displayed on the homepage based on the voice control commands when a card is displayed on the homepage among the multiple devices.

[0079] like Figure 3 As shown in the figure, this application provides an electronic device, including a processor 311, a communication interface 312, a memory 313, and a communication bus 314, wherein the processor 311, the communication interface 312, and the memory 313 communicate with each other through the communication bus 314.

[0080] Memory 313 is used to store computer programs;

[0081] In one embodiment of this application, when the processor 311 executes the program stored in the memory 313, it implements the device card adjustment method provided in any of the aforementioned method embodiments, and its function is similar, so it will not be described again here.

[0082] This application also provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the steps of the device card adjustment method provided in any of the foregoing method embodiments.

[0083] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0084] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented using software plus a general-purpose hardware platform, or of course, using hardware. Based on this understanding, the above technical solutions, in essence or the parts that contribute to the related technology, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0085] It should be understood that the terminology used herein is for the purpose of describing particular exemplary embodiments only and is not intended to be limiting. Unless the context clearly indicates otherwise, the singular forms “a,” “an,” and “described” as used herein may also include the plural forms. The terms “comprising,” “including,” “containing,” and “having” are inclusive and therefore indicate the presence of the stated features, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, elements, components, and / or combinations thereof. The method steps, processes, and operations described herein are not construed as requiring them to be performed in a particular order described or illustrated unless the order of performance is explicitly indicated. It should also be understood that additional or alternative steps may be used.

[0086] The above description is merely a specific embodiment of the present invention, enabling those skilled in the art to understand or implement the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the present invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features claimed herein.

Claims

1. A method for adjusting a device card, characterized in that, The method includes: Obtain target feature values ​​for each device within the target local area network, wherein the target features include feature values ​​characterizing device signal strength, feature values ​​characterizing user behavior habits, feature values ​​characterizing device category functions, and feature values ​​characterizing tags; Feature vectors are generated based on the target vector, and scores are obtained for each device based on the feature vectors and the weights corresponding to the target features. The order of the cards corresponding to each device on the terminal display page is adjusted according to the preset classification results and the scores, wherein the classification results are used to indicate whether the cards corresponding to each device are on the homepage of the display page.

2. The method according to claim 1, characterized in that, When the target feature is a feature value used to characterize the signal strength of a device, the target feature values ​​of each device in the target local area network are obtained, including: The signals of each device within the target local area network are periodically scanned to obtain the signal strength of each device in different periods. The signal strength of each of the devices is sorted, and N signal strengths are obtained sequentially from the sorted signal strengths; where N is an odd number greater than or equal to 5. The average value of the N signal strengths is calculated, and the average value corresponding to each device is normalized to obtain the feature value of the signal strength corresponding to each device.

3. The method according to claim 1, characterized in that, When the target feature is a feature value used to characterize user behavior habits, the target feature values ​​of each device within the target local area network are obtained, including: Obtain the product of the number of times the user operates on the cards of each device on the terminal within a preset time period and the duration of each operation; The product results corresponding to each device are normalized to obtain the feature values ​​of each device used to characterize user behavior habits.

4. The method according to claim 1, characterized in that, When the target feature is a feature value used to characterize the function of a device category, the target feature values ​​of each device in the target local area network are obtained, including: Each device is assigned a value based on its functional richness and whether its function is a commonly used function; The values ​​assigned to each device are normalized to obtain the feature values ​​of the category functions of each device.

5. The method according to claim 1, characterized in that, When the target feature is a feature value used to characterize a tag, the target feature values ​​of each device within the target local area network are obtained, including: Obtain the user's preference tag settings for each device on the terminal, and assign values ​​to each device based on the preference tag settings; The values ​​assigned to each device are normalized to obtain the feature values ​​of the category functions of each device.

6. The method according to claim 1, characterized in that, Before adjusting the order of the cards corresponding to each device on the terminal display page according to the preset classification results and the scores, the method further includes: The classification effect of whether each device displays a card on the homepage and the processing speed are input into the target neural network to obtain the classification result.

7. The method according to claim 1, characterized in that, Adjusting the order of the cards corresponding to each device on the terminal display page according to the preset classification results and the scores includes: If the classification result of the device's card is not displayed on the homepage, the device's cards are sorted on the homepage according to the score; If the classification result of the device's cards is displayed on the homepage, and there are multiple cards displayed on the homepage, the cards of the device are sorted on the homepage according to the scores; If the device's card classification result is displayed on the homepage, and only one card is displayed on the homepage, then the device's control details page will be displayed on the homepage.

8. The method according to claim 1, characterized in that, The method further includes: Receive user voice control commands and identify that the voice control commands are used to control multiple devices; If a card is displayed on the homepage among the multiple devices, the device corresponding to the card displayed on the homepage is controlled based on the voice control command.

9. An adjustment device for a device card, characterized in that, include: The acquisition module is used to acquire target feature values ​​of each device in the target local area network, wherein the target features include feature values ​​for characterizing device signal strength, feature values ​​for characterizing user behavior habits, feature values ​​for characterizing device category functions, and feature values ​​for characterizing tags. The first processing module is used to generate a feature vector based on the target vector, and to obtain the score corresponding to each device based on the feature vector and the weight corresponding to the target feature. An adjustment module is used to adjust the order of the cards corresponding to each device on the terminal display page according to a preset classification result and the score, wherein the classification result is used to indicate whether the cards corresponding to each device are on the homepage of the display page.

10. An electronic device, comprising: At least one communication interface; At least one bus connected to the at least one communication interface; At least one processor connected to the at least one bus; At least one memory connected to the at least one bus, wherein the processor is configured to execute the adjustment method of the device card according to any one of claims 1 to 8 of this application.

11. A computer storage medium storing computer-executable instructions for performing the adjustment method of a device card according to any one of claims 1 to 8 of this application.

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