Display control method, device, storage medium and electronic device

Abstract

The embodiment of the present application provides a display control method, device, storage medium and electronic device, the display control method comprising: constructing a first user feature vector according to the historical usage behavior information of a legitimate user; constructing a second user feature vector according to the current usage behavior information of the current user; judging whether the current user is the legitimate user according to the first user feature vector and the second user feature vector; if the current user is the legitimate user, controlling the display of a legitimate user interface; if the current user is not the legitimate user, controlling the display of a visitor interface. In the display control method, the electronic device can judge whether the current user is a legitimate user according to the user's usage behavior habits. If the current user is not a legitimate user, the privacy information of the legitimate user is hidden, thereby avoiding the leakage of the privacy information of the legitimate user and improving the information security of the electronic device.

Description

Technical Field

[0001] The present application relates to the field of electronic technology, and in particular to a display control method, device, storage medium and electronic device. Background Art

[0002] With the development of electronic technology, the functions of electronic devices such as smart phones are becoming more and more abundant, and users are using electronic devices in more and more situations.

[0003] In some cases, someone else may use the user's electronic device. For example, the user lends the electronic device to someone else for temporary use, or the user's electronic device is stolen, etc. When someone else uses the user's electronic device, the private information on the user's electronic device is at risk of being leaked. Summary of the invention

[0004] Embodiments of the present application provide a display control method, device, storage medium, and electronic device, which can improve the information security of the electronic device.

[0005] The present application provides a display control method, including:

[0006] Constructing a first user feature vector of the legitimate user according to the historical usage behavior information of the legitimate user;

[0007] Constructing a second user feature vector of the current user according to the current usage behavior information of the current user;

[0008] Determining whether the current user is the legal user according to the first user feature vector and the second user feature vector;

[0009] If the current user is the legal user, controlling the display of the legal user interface;

[0010] If the current user is not the legal user, a guest interface is controlled to be displayed, wherein the guest interface hides the privacy information of the legal user.

[0011] The present application also provides a display control device, including:

[0012] A first vector construction module, used to construct a first user feature vector of the legal user according to the historical usage behavior information of the legal user;

[0013] A second vector construction module, used to construct a second user feature vector of the current user according to the current usage behavior information of the current user;

[0014] A judging module, configured to judge whether the current user is the legal user according to the first user feature vector and the second user feature vector;

[0015] Control module for:

[0016] If the current user is the legal user, controlling the display of the legal user interface;

[0017] If the current user is not the legal user, a guest interface is controlled to be displayed, wherein the guest interface hides the privacy information of the legal user.

[0018] An embodiment of the present application further provides a storage medium, in which a computer program is stored. When the computer program is executed on a computer, the computer executes the above-mentioned display control method.

[0019] An embodiment of the present application also provides an electronic device, including a processor and a memory, wherein the memory stores a computer program, and the processor is used to execute the above-mentioned display control method by calling the computer program stored in the memory.

[0020] The display control method provided in the embodiment of the present application includes: constructing a first user feature vector of the legal user based on the historical usage behavior information of the legal user; constructing a second user feature vector of the current user based on the current usage behavior information of the current user; judging whether the current user is the legal user based on the first user feature vector and the second user feature vector; if the current user is the legal user, controlling the display of the legal user interface; if the current user is not the legal user, controlling the display of the guest interface, wherein the guest interface hides the privacy information of the legal user. In the display control method, the electronic device can judge whether the current user is a legal user based on the user's usage behavior habits. If the current user is not a legal user, the privacy information of the legal user is hidden and the hidden guest interface is displayed, thereby avoiding the leakage of the privacy information of the legal user and improving the information security of the electronic device. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present application, and those skilled in the art can obtain other drawings based on these drawings without creative work.

[0022] Figure 1 A schematic diagram of a panoramic perception architecture in an electronic device provided in an embodiment of the present application.

[0023] Figure 2 A first flow chart of a display control method provided in an embodiment of the present application.

[0024] Figure 3 A second flow chart of the display control method provided in an embodiment of the present application.

[0025] Figure 4 A third flow chart of the display control method provided in an embodiment of the present application.

[0026] Figure 5 A fourth flow chart of the display control method provided in an embodiment of the present application.

[0027] Figure 6 A fifth flow chart of the display control method provided in the embodiment of the present application.

[0028] Figure 7 A first structural schematic diagram of a display control device provided in an embodiment of the present application.

[0029] Figure 8 A second structural schematic diagram of the display control device provided in an embodiment of the present application.

[0030] Fig. 9 A first structural schematic diagram of an electronic device provided in an embodiment of the present application.

[0031] Fig.10 A second structural schematic diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0032] The technical solutions in the embodiments of the present application will be described clearly and completely 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, rather than all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present application.

[0033] refer to Figure 1 , Figure 1 The panoramic perception architecture in the electronic device provided in the embodiment of the present application is a schematic diagram. The panoramic perception architecture is the integration of hardware and software used to implement the display control method of the present application in the electronic device.

[0034] Among them, the panoramic perception architecture includes information perception layer, data processing layer, feature extraction layer, scenario modeling layer and intelligent service layer.

[0035] The information perception layer is used to obtain information about the electronic device itself or information in the external environment. The information perception layer may include multiple sensors. For example, the information perception layer includes multiple sensors such as distance sensors, magnetic field sensors, light sensors, acceleration sensors, fingerprint sensors, Hall sensors, position sensors, gyroscopes, inertial sensors, attitude sensors, barometers, heart rate sensors, etc.

[0036] Among them, the distance sensor can be used to detect the distance between the electronic device and the external object. The magnetic field sensor can be used to detect the magnetic field information of the environment in which the electronic device is located. The light sensor can be used to detect the light information of the environment in which the electronic device is located. The acceleration sensor can be used to detect the acceleration data of the electronic device. The fingerprint sensor can be used to collect the fingerprint information of the user. The Hall sensor is a magnetic field sensor made according to the Hall effect, which can be used to realize the automatic control of the electronic device. The position sensor can be used to detect the current geographical location of the electronic device. The gyroscope can be used to detect the angular velocity of the electronic device in all directions. The inertial sensor can be used to detect the motion data of the electronic device. The attitude sensor can be used to sense the attitude information of the electronic device. The barometer can be used to detect the air pressure of the environment in which the electronic device is located. The heart rate sensor can be used to detect the heart rate information of the user.

[0037] The data processing layer is used to process the data obtained by the information perception layer. For example, the data processing layer can perform data cleaning, data integration, data transformation, data reduction, etc. on the data obtained by the information perception layer.

[0038] Among them, data cleaning refers to cleaning the large amount of data obtained by the information perception layer to eliminate invalid data and duplicate data. Data integration refers to integrating multiple single-dimensional data obtained by the information perception layer into a higher or more abstract dimension to comprehensively process multiple single-dimensional data. Data transformation refers to converting the data type or format of the data obtained by the information perception layer so that the transformed data meets the processing requirements. Data reduction refers to maximizing the reduction of data volume while keeping the original appearance of the data as much as possible.

[0039] The feature extraction layer is used to extract features from the data processed by the data processing layer to extract features included in the data. The extracted features can reflect the state of the electronic device itself, the state of the user, or the environmental state of the environment in which the electronic device is located.

[0040] Among them, the feature extraction layer can extract features or process the extracted features through filtering, packaging, integration and other methods.

[0041] The filtering method refers to filtering the extracted features to delete redundant feature data. The packaging method is used to screen the extracted features. The integration method refers to integrating multiple feature extraction methods together to build a more efficient and accurate feature extraction method for extracting features.

[0042] The scenario modeling layer is used to construct a model based on the features extracted by the feature extraction layer, and the obtained model can be used to represent the state of the electronic device, the state of the user, or the state of the environment, etc. For example, the scenario modeling layer can construct a key value model, a pattern identification model, a graph model, an entity relationship model, an object-oriented model, etc. based on the features extracted by the feature extraction layer.

[0043] The intelligent service layer is used to provide intelligent services to users based on the model constructed by the scenario modeling layer. For example, the intelligent service layer can provide basic application services to users, perform system intelligent optimization for electronic devices, and provide personalized intelligent services to users.

[0044] In addition, the panoramic perception architecture may also include multiple algorithms, each of which can be used to analyze and process data, and the multiple algorithms may constitute an algorithm library. For example, the algorithm library may include Markov algorithm, implicit Dirichlet distribution algorithm, Bayesian classification algorithm, support vector machine classification algorithm, K-means clustering algorithm, K-nearest neighbor algorithm, conditional random field, residual network, long short-term memory network, convolutional neural network, recurrent neural network and other algorithms.

[0045] The embodiment of the present application provides a display control method, which can be applied to electronic devices. The electronic devices can be smart phones, tablet computers, gaming devices, AR (Augmented Reality) devices, cars, data storage devices, audio playback devices, video playback devices, laptop computers, desktop computing devices, wearable devices such as electronic watches, electronic glasses, electronic helmets, electronic bracelets, electronic necklaces, electronic clothing, and other devices.

[0046] refer to Figure 2 , Figure 2 A first flow chart of a display control method provided in an embodiment of the present application.

[0047] The display control method comprises the following steps:

[0048] 110 , constructing a first user feature vector of the legal user according to the historical usage behavior information of the legal user.

[0049] The owner of the electronic device (i.e., the machine owner) can be regarded as the legal user of the electronic device. The legal user of the electronic device has all the rights to the electronic device. The legal user can store private information in the electronic device.

[0050] Among them, the private information may include applications involving user personal information such as address books and payment applications, interfaces involving user personal information in applications such as social applications, user personal files such as photos and video files stored on electronic devices, and usage records generated by users in the process of using electronic devices, etc. It can be understood that the private information may also include other information not listed above, and this application is not limited to the above examples.

[0051] When a legitimate user uses an electronic device, the electronic device can continuously obtain the usage behavior information of the legitimate user, thereby obtaining the historical usage behavior information of the legitimate user.

[0052] Among them, the historical usage behavior information may include application operation habit information, electronic device holding habit information, display screen operation habit information and other information. Among them, the application operation habit information may include the user's use frequency of each application, the time period of each application, the duration of each use of each application and other information. The electronic device holding habit information may include the user's gripping part of the electronic device, the size of the gripping force and other information. The electronic device may detect the user's gripping part, the size of the gripping force and other information through a pressure sensor. The display screen operation habit information may include the pressing area and the pressing pressure when the user presses the display screen, and may also include the sliding speed and sliding distance when the user slides on the display screen and other information.

[0053] It is understandable that even if an electronic device is used by others, it is still used by the legal user most of the time. Therefore, in the process of using the electronic device, the user corresponding to the information that matches the usage habits of the same user the most among the usage behavior information obtained by the electronic device can be considered as the legal user.

[0054] For example, among the usage behavior information obtained by the electronic device, 90% of the information is consistent with the usage habits of user A, 6% of the information is consistent with the usage habits of user B, and 4% of the information is consistent with the usage habits of user C. Then, the electronic device can consider user A as a legitimate user of the electronic device.

[0055] After obtaining the historical usage behavior information of the legal user, the electronic device can extract multiple features from the historical usage behavior information, and construct a first user feature vector M1 of the legal user based on the extracted multiple features.

[0056] Among them, the first user feature vector M1 includes three dimensions, namely, application operation habits x1, electronic device holding habits y1, and display screen operation habits z1. For example, the first user feature vector can be expressed as M1(x1, y1, z1). It can be understood that x1, y1, and z1 can be features, or they can be sub-vectors composed of multiple features. For example, x1 can be expressed as a sub-vector x1(a, b, c), y1 can be expressed as a sub-vector y1(d, e), and z1 can be expressed as a sub-vector z1(f, g). Among them, a, b, and c can respectively represent the application operation frequency, application usage time period, and application usage duration; d and e can respectively represent the holding position and the holding force; f and g can respectively represent the pressing area and the pressing pressure.

[0057] It is understandable that, since the user's usage habits may change at different times, the electronic device may continuously update the constructed first user feature vector M1 according to the historical usage behavior information of the legitimate user that is continuously collected.

[0058] 120 . Construct a second user feature vector of the current user according to the current usage behavior information of the current user.

[0059] When the current user uses the electronic device, the electronic device can obtain the current user's current usage behavior information, and construct the second user feature vector M2 of the current user according to the current usage behavior information. The second user feature vector M2 includes three dimensions: application operation habit x2, electronic device holding habit y2, and display screen operation habit z2. For example, the second user feature vector M2 can be expressed as M2(x2, y2, z2).

[0060] The construction process of the second user feature vector M2 is consistent with the construction process of the first user feature vector M1, and the features included in the second user feature vector M2 are consistent with the features included in the first user feature vector M1. The difference is that the first user feature vector M1 is for a legitimate user, while the second user feature vector M2 is for the current user.

[0061] It is understandable that the current user may be the legal user or another user other than the legal user. The current user changes according to the actual usage of the electronic device.

[0062] 130. Determine whether the current user is the legal user according to the first user feature vector and the second user feature vector.

[0063] After acquiring the first user feature vector and the second user feature vector, the electronic device compares the first user feature vector with the second user feature vector to determine whether the current user is the legal user.

[0064] For example, the electronic device may compare whether the first user feature vector is the same as the second user feature vector. If they are the same, it is determined that the current user is the legal user; if they are different, it is determined that the current user is not the legal user.

[0065] 140. If the current user is the legal user, control the display of a legal user interface; if the current user is not the legal user, control the display of a guest interface, wherein the guest interface hides the privacy information of the legal user.

[0066] If the electronic device determines that the current user is a legitimate user, it controls the display of a legitimate user interface. The legitimate user interface is an interface where all information in the electronic device can be displayed. For example, when entering the desktop of the electronic device, all application icons on the desktop are displayed; when entering the address book of the electronic device, the information of all contacts in the address book is displayed.

[0067] If the electronic device determines that the current user is not a legitimate user, it controls the display of the guest interface. The guest interface hides the privacy information of the legitimate user. That is, the guest interface only displays other information in the legitimate user interface that does not involve the privacy information of the legitimate user. For example, when entering the desktop of an electronic device, only some application icons on the desktop that do not involve the privacy information of the legitimate user are displayed, and the application icons that involve the privacy information of the legitimate user are hidden, or false icons are used to disguise the application icons that involve the privacy information of the legitimate user. For another example, when entering the address book of an electronic device, all contact information in the address book is hidden, that is, only an empty address book is displayed or a false address book that has been disguised is displayed.

[0068] For example, in some embodiments, during the process of a user using an electronic device (including use by a legitimate user and use by other users other than the legitimate user), the electronic device can obtain the user's usage data through the information perception layer. The user usage data obtained by the electronic device through the information perception layer includes the usage data of the legitimate user and the usage data of other users other than the legitimate user. Thus, the electronic device can obtain the historical usage behavior information of the legitimate user and the current usage behavior information of the current user.

[0069] The electronic device can extract features from the historical usage behavior information of the legal user through the feature extraction layer, and construct a first user feature vector of the legal user based on the extracted multiple features. It is understandable that before the feature extraction layer extracts features from the historical usage behavior information of the legal user, the electronic device can also process the historical usage behavior information data of the legal user through the data processing layer, such as performing data cleaning, data transformation, etc.

[0070] The electronic device may also perform feature extraction on the current user's current usage behavior information through the feature extraction layer, and construct a second user feature vector of the current user based on the extracted multiple features. Similarly, before the feature extraction layer performs feature extraction on the current user's current usage behavior information, the electronic device may also process the current user's usage behavior information data through the data processing layer, such as performing data cleaning, data transformation, and the like.

[0071] Subsequently, the electronic device determines whether the current user is a legitimate user through the intelligent service layer according to the first user feature vector and the second user feature vector. If the current user is the legitimate user, the intelligent service layer controls the display of the legitimate user interface; if the current user is not the legitimate user, the intelligent service layer controls the display of the guest interface, wherein the guest interface hides the privacy information of the legitimate user.

[0072] The display control method provided in the embodiment of the present application can determine whether the current user is a legitimate user based on the user's usage behavior habits. If the current user is not a legitimate user, the privacy information of the legitimate user is hidden and the hidden visitor interface is displayed, thereby avoiding the leakage of the privacy information of the legitimate user and improving the information security of the electronic device.

[0073] In some embodiments, reference Figure 3 , Figure 3 A second flow chart of the display control method provided in an embodiment of the present application.

[0074] Wherein, step 130, judging whether the current user is the legal user according to the first user feature vector and the second user feature vector, comprises the following steps:

[0075] 131, calculating a matching degree between the first user feature vector and the second user feature vector;

[0076] 132, determining whether the matching degree is greater than a preset matching degree threshold;

[0077] 133. If the matching degree is greater than the preset matching degree threshold, it is determined that the current user is the legal user; if the matching degree is not greater than the preset matching degree threshold, it is determined that the current user is not the legal user.

[0078] After acquiring the first user feature vector and the second user feature vector, the electronic device calculates the matching degree between the first user feature vector and the second user feature vector. For example, the electronic device may calculate the matching degree between the first user feature vector and the second user feature vector using a dynamic time warping algorithm.

[0079] Subsequently, the electronic device compares the calculated matching degree with a preset matching degree threshold to determine whether the matching degree is greater than the preset matching degree threshold. The preset matching degree threshold may be a value pre-stored in the electronic device, such as 90%.

[0080] If the matching degree is greater than the preset matching degree threshold, it is determined that the current user is the legal user. If the matching degree is not greater than the preset matching degree threshold, it is determined that the current user is not the legal user.

[0081] For example, if the matching degree calculated by the electronic device is 95%, then the matching degree is greater than the preset matching degree threshold of 90%, and the electronic device can determine that the current user is a legitimate user. For another example, if the matching degree calculated by the electronic device is 60%, then the matching degree is less than the preset matching degree threshold of 90%, and the electronic device can determine that the current user is not a legitimate user.

[0082] In some embodiments, reference Figure 4 , Figure 4 A third flow chart of the display control method provided in an embodiment of the present application.

[0083] Wherein, step 131, calculating the matching degree between the first user feature vector and the second user feature vector, comprises the following steps:

[0084] 1311, calculating the cosine similarity between the first user feature vector and the second user feature vector;

[0085] 1312. Determine the cosine similarity as a matching degree between the first user feature vector and the second user feature vector.

[0086] After the electronic device obtains the first user feature vector and the second user feature vector, it can calculate the cosine similarity between the first user feature vector and the second user feature vector according to the cosine similarity algorithm, and determine the cosine similarity as the matching degree between the first user feature vector and the second user feature vector.

[0087] For example, if the cosine similarity between the first user feature vector and the second user feature vector calculated by the electronic device is 85%, then it can be determined that the matching degree between the first user feature vector and the second user feature vector is 85%.

[0088] In some embodiments, reference Figure 5 , Figure 5 A fourth flow chart of the display control method provided in an embodiment of the present application.

[0089] Wherein, before step 132, determining whether the matching degree is greater than a preset matching degree threshold, the following steps are also included:

[0090] 151, obtaining the perception data of the current scene;

[0091] 152, identifying the current scene according to the perception data to obtain a recognition result;

[0092] 153. Obtain a preset matching degree threshold according to the recognition result.

[0093] An electronic device can obtain perception data of the current scene. The current scene is the scene of the environment in which the electronic device is currently located, that is, the scene of the environment in which the user of the electronic device is currently located. The perception data may include arbitrary data. For example, the perception data may include environmental data such as ambient temperature, ambient light intensity, and ambient noise. The perception data may also include operating data of the electronic device, such as image data on the electronic device, memory data, and text data displayed on the electronic device. The perception data may also include user behavior habit data, such as the user's work and rest time, the user's entertainment activities, etc.

[0094] Among them, the electronic device can collect the perception data of the current scene through the information perception layer in the above-mentioned panoramic perception architecture. For example, the electronic device can detect the ambient temperature through a temperature sensor, detect the ambient light intensity through a light sensor, detect the ambient noise through a microphone, retrieve the image data, memory data, etc. on the electronic device through the processing circuit of the electronic device, and obtain the text data displayed on the electronic device through the display control circuit. In addition, the electronic device can also perceive the user's behavior through the information perception layer and record it to form the user's behavior habit data.

[0095] Subsequently, the electronic device may identify the current scene according to the sensing data to obtain a recognition result. For example, the recognition result may be a scene such as home, office, subway station, shopping mall, etc. The electronic device may obtain a preset matching degree threshold according to the recognition result.

[0096] For example, the electronic device may pre-store a preset matching degree threshold corresponding to each scene. The preset matching degree threshold corresponding to each scene may be set by a professional based on experience. The preset matching degree thresholds corresponding to different scenes may be different. The electronic device may query according to the recognition result to obtain the preset matching degree threshold corresponding to the recognition result.

[0097] In some embodiments, reference Figure 6 , Figure 6 A fifth flow chart of the display control method provided in the embodiment of the present application.

[0098] Wherein, step 153, obtaining a preset matching degree threshold according to the recognition result, includes the following steps:

[0099] 1531, acquiring, according to the recognition result, a first weight corresponding to the application operation habit, a second weight corresponding to the electronic device holding habit, and a third weight corresponding to the display screen operation habit;

[0100] 1532. Calculate a preset matching degree threshold value according to the first weight, the second weight, the third weight, a first preset matching degree corresponding to the application operation habit, a second preset matching degree corresponding to the electronic device holding habit, and a third preset matching degree corresponding to the display screen operation habit.

[0101] In the electronic device, the corresponding first preset matching degree, second preset matching degree, and third preset matching degree can be set for the application operation habits, the electronic device holding habits, and the display screen operation habits. The meaning of the first preset matching degree, the second preset matching degree, and the third preset matching degree is that if the matching degree between the application operation habits in the first user feature vector and the application operation habits in the second user feature vector is greater than the first preset matching degree, and the matching degree between the electronic device holding habits in the first user feature vector and the electronic device holding habits in the second user feature vector is greater than the second preset matching degree, and the matching degree between the display screen operation habits in the first user feature vector and the display screen operation habits in the second user feature vector is greater than the third preset matching degree, then it can be considered that the matching degree between the first user feature vector and the second user feature vector is greater than the preset matching degree threshold.

[0102] For example, the first preset matching degree for application operation habits may be 80%, the second preset matching degree for electronic device holding habits may be 90%, and the third preset matching degree for display screen operation habits may be 95%. The first preset matching degree, the second preset matching degree, and the third preset matching degree may be set by professionals based on experience.

[0103] In addition, users may have different habits of using electronic devices in different scenarios. For example, the amount of pressure a user applies to holding an electronic device indoors and outdoors may be different. Another example is that a user may use a navigation application at home and at a subway station at different frequencies. Therefore, different weights can be set for different scenarios in the electronic device based on the characteristics of the three dimensions of application operation habits, electronic device holding habits, and display screen operation habits. Among them, the weight set for application operation habits is the first weight, the weight set for electronic device holding habits is the second weight, and the weight set for display screen operation habits is the third weight. Among them, the first weight, the second weight, and the third weight may be different for different scenarios. The first weight, the second weight, and the third weight can be set by professionals based on experience.

[0104] For example, for an office scenario, the first weight may be 0.5, the second weight may be 0.2, and the third weight may be 0.3; for a subway station scenario, the first weight may be 0.3, the second weight may be 0.4, and the third weight may be 0.3.

[0105] After the electronic device recognizes the current scene and obtains the recognition result, the first weight corresponding to the application operation habit, the second weight corresponding to the electronic device holding habit, and the third weight corresponding to the display screen operation habit can be obtained according to the recognition result. Subsequently, the preset matching degree threshold is calculated according to the first weight, the second weight, the third weight, the first preset matching degree corresponding to the application operation habit, the second preset matching degree corresponding to the electronic device holding habit, and the third preset matching degree corresponding to the display screen operation habit.

[0106] In some embodiments, the electronic device calculates the preset matching degree threshold according to the following formula:

[0107] P=k1×P1+k2×P2+k3×P3

[0108] Among them, P is the preset matching degree threshold, k1 is the first weight, k2 is the second weight, k3 is the third weight, P1 is the first preset matching degree, P2 is the second preset matching degree, and P3 is the third preset matching degree.

[0109] It can be understood that in other embodiments, the electronic device can also calculate the preset matching degree threshold in other ways.

[0110] In the description of this application, it should be understood that terms such as "first", "second", "third" and the like are only used to distinguish similar objects and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features.

[0111] In specific implementation, the present application is not limited by the execution order of the various steps described. If no conflict occurs, some steps can be performed in other orders or simultaneously.

[0112] As can be seen from the above, the display control method provided in the embodiment of the present application includes: constructing a first user feature vector of the legal user based on the historical usage behavior information of the legal user; constructing a second user feature vector of the current user based on the current usage behavior information of the current user; judging whether the current user is the legal user based on the first user feature vector and the second user feature vector; if the current user is the legal user, controlling the display of the legal user interface; if the current user is not the legal user, controlling the display of the guest interface, wherein the guest interface hides the privacy information of the legal user. In the display control method, the electronic device can judge whether the current user is a legal user based on the user's usage behavior habits. If the current user is not a legal user, the privacy information of the legal user is hidden, and the hidden guest interface is displayed, thereby avoiding the leakage of the privacy information of the legal user and improving the information security of the electronic device.

[0113] The embodiment of the present application also provides a display control device, which can be integrated in an electronic device. The electronic device can be a smart phone, a tablet computer, a gaming device, an AR (Augmented Reality) device, a car, a data storage device, an audio playback device, a video playback device, a laptop computer, a desktop computing device, a wearable device such as an electronic watch, an electronic glasses, an electronic helmet, an electronic bracelet, an electronic necklace, an electronic clothing, and the like.

[0114] refer to Figure 7 , Figure 7 A first structural schematic diagram of a display control device provided in an embodiment of the present application.

[0115] The display control device 200 includes: a first vector construction module 201 , a second vector construction module 202 , a determination module 203 , and a control module 204 .

[0116] The first vector construction module 201 is used to construct a first user feature vector of a legitimate user according to the historical usage behavior information of the legitimate user.

[0117] The owner of the electronic device (i.e., the machine owner) can be regarded as the legal user of the electronic device. The legal user of the electronic device has all the rights to the electronic device. The legal user can store private information in the electronic device.

[0118] Among them, the private information may include applications involving user personal information such as address books and payment applications, interfaces involving user personal information in applications such as social applications, user personal files such as photos and video files stored on electronic devices, and usage records generated by users in the process of using electronic devices, etc. It can be understood that the private information may also include other information not listed above, and this application is not limited to the above examples.

[0119] When a legitimate user uses an electronic device, the electronic device can continuously obtain the usage behavior information of the legitimate user, thereby obtaining the historical usage behavior information of the legitimate user.

[0120] Among them, the historical usage behavior information may include application operation habit information, electronic device holding habit information, display screen operation habit information and other information. Among them, the application operation habit information may include the user's use frequency of each application, the time period of each application, the duration of each use of each application and other information. The electronic device holding habit information may include the user's gripping part of the electronic device, the size of the gripping force and other information. The electronic device may detect the user's gripping part, the size of the gripping force and other information through a pressure sensor. The display screen operation habit information may include the pressing area and the pressing pressure when the user presses the display screen, and may also include the sliding speed and sliding distance when the user slides on the display screen and other information.

[0121] It is understandable that even if an electronic device is used by others, it is still used by the legal user most of the time. Therefore, in the process of using the electronic device, the user corresponding to the information that matches the usage habits of the same user the most among the usage behavior information obtained by the electronic device can be considered as the legal user.

[0122] For example, among the usage behavior information obtained by the electronic device, 90% of the information is consistent with the usage habits of user A, 6% of the information is consistent with the usage habits of user B, and 4% of the information is consistent with the usage habits of user C. Then, the electronic device can consider user A as a legitimate user of the electronic device.

[0123] After the electronic device obtains the historical usage behavior information of the legitimate user, the first vector construction module 201 can extract multiple features from the historical usage behavior information, and construct the first user feature vector M1 of the legitimate user according to the extracted multiple features.

[0124] Among them, the first user feature vector M1 includes three dimensions, namely, application operation habits x1, electronic device holding habits y1, and display screen operation habits z1. For example, the first user feature vector can be expressed as M1(x1, y1, z1). It can be understood that x1, y1, and z1 can be features, or they can be sub-vectors composed of multiple features. For example, x1 can be expressed as a sub-vector x1(a, b, c), y1 can be expressed as a sub-vector y1(d, e), and z1 can be expressed as a sub-vector z1(f, g). Among them, a, b, and c can respectively represent the application operation frequency, application usage time period, and application usage duration; d and e can respectively represent the holding position and the holding force; f and g can respectively represent the pressing area and the pressing pressure.

[0125] It is understandable that, since the user's usage habits may change at different times, the first vector construction module 201 may continuously update the constructed first user feature vector M1 according to the historical usage behavior information of the legitimate users continuously collected.

[0126] The second vector construction module 202 is used to construct a second user feature vector of the current user according to the current usage behavior information of the current user.

[0127] When the current user uses the electronic device, the electronic device can obtain the current user's current usage behavior information, and the second vector construction module 202 constructs the second user feature vector M2 of the current user according to the current usage behavior information. The second user feature vector M2 includes three dimensions: application operation habit x2, electronic device holding habit y2, and display screen operation habit z2. For example, the second user feature vector M2 can be expressed as M2(x2, y2, z2).

[0128] The construction process of the second user feature vector M2 is consistent with the construction process of the first user feature vector M1, and the features included in the second user feature vector M2 are consistent with the features included in the first user feature vector M1. The difference is that the first user feature vector M1 is for a legitimate user, while the second user feature vector M2 is for the current user.

[0129] It is understandable that the current user may be the legal user or another user other than the legal user. The current user changes according to the actual usage of the electronic device.

[0130] The judgment module 203 is used to judge whether the current user is the legal user according to the first user feature vector and the second user feature vector.

[0131] After acquiring the first user feature vector and the second user feature vector, the judgment module 203 compares the first user feature vector with the second user feature vector to judge whether the current user is the legal user.

[0132] For example, the judgment module 203 may compare whether the first user feature vector is the same as the second user feature vector. If they are the same, it is judged that the current user is the legal user; if they are different, it is judged that the current user is not the legal user.

[0133] The control module 204 is used to: if the current user is the legal user, control the display of the legal user interface; if the current user is not the legal user, control the display of the guest interface, wherein the guest interface hides the privacy information of the legal user.

[0134] If the judgment module 203 determines that the current user is a legitimate user, the control module 204 controls the display of a legitimate user interface. The legitimate user interface is an interface in which all information in the electronic device can be displayed. For example, when entering the desktop of the electronic device, all application icons on the desktop are displayed; when entering the address book of the electronic device, the information of all contacts in the address book is displayed.

[0135] If the judgment module 203 determines that the current user is not a legitimate user, the control module 204 controls the display of the visitor interface. Among them, the visitor interface hides the privacy information of the legitimate user. That is, the visitor interface only displays other information in the legitimate user interface that does not involve the privacy information of the legitimate user. For example, when entering the desktop of an electronic device, only some application icons on the desktop that do not involve the privacy information of the legitimate user are displayed, and the application icons involving the privacy information of the legitimate user are hidden, or false icons are used to disguise the application icons involving the privacy information of the legitimate user. For another example, when entering the address book of an electronic device, all contact information in the address book is hidden, that is, only an empty address book is displayed or a false address book after disguise is displayed.

[0136] The display control device provided in the embodiment of the present application can determine whether the current user is a legitimate user based on the user's usage behavior habits. If the current user is not a legitimate user, the privacy information of the legitimate user is hidden and the hidden visitor interface is displayed, thereby avoiding the leakage of the privacy information of the legitimate user and improving the information security of the electronic device.

[0137] In some embodiments, the determination module 203 is used to perform the following steps:

[0138] Calculating a matching degree between the first user feature vector and the second user feature vector;

[0139] Determining whether the matching degree is greater than a preset matching degree threshold;

[0140] If the matching degree is greater than the preset matching degree threshold, it is determined that the current user is the legal user; if the matching degree is not greater than the preset matching degree threshold, it is determined that the current user is not the legal user.

[0141] After obtaining the first user feature vector and the second user feature vector, the judgment module 203 calculates the matching degree between the first user feature vector and the second user feature vector. For example, the judgment module 203 can calculate the matching degree between the first user feature vector and the second user feature vector by a dynamic time warping algorithm.

[0142] Then, the determination module 203 compares the calculated matching degree with a preset matching degree threshold to determine whether the matching degree is greater than the preset matching degree threshold. The preset matching degree threshold may be a value pre-stored in the electronic device, such as 90%.

[0143] If the matching degree is greater than the preset matching degree threshold, it is determined that the current user is the legal user. If the matching degree is not greater than the preset matching degree threshold, it is determined that the current user is not the legal user.

[0144] For example, if the matching degree calculated by the judgment module 203 is 95%, the matching degree is greater than the preset matching degree threshold of 90%, and the current user can be judged as a legitimate user. For another example, if the matching degree calculated by the judgment module 203 is 60%, the matching degree is less than the preset matching degree threshold of 90%, and the current user can be judged as not a legitimate user.

[0145] In some embodiments, when calculating the matching degree between the first user feature vector and the second user feature vector, the judgment module 203 is used to perform the following steps:

[0146] Calculating the cosine similarity between the first user feature vector and the second user feature vector;

[0147] The cosine similarity is determined as a degree of matching between the first user feature vector and the second user feature vector.

[0148] After acquiring the first user feature vector and the second user feature vector, the judgment module 203 may calculate the cosine similarity between the first user feature vector and the second user feature vector according to the cosine similarity algorithm, and determine the cosine similarity as the matching degree between the first user feature vector and the second user feature vector.

[0149] For example, if the cosine similarity between the first user feature vector and the second user feature vector calculated by the judgment module 203 is 85%, then it can be determined that the matching degree between the first user feature vector and the second user feature vector is 85%.

[0150] In some embodiments, reference Figure 8 , Figure 8 A second structural schematic diagram of the display control device provided in an embodiment of the present application.

[0151] The display control device 200 further includes an acquisition module 205, and the acquisition module 205 is used to perform the following steps:

[0152] Get the perception data of the current scene;

[0153] Identify the current scene according to the perception data to obtain a recognition result;

[0154] A preset matching degree threshold is obtained according to the recognition result.

[0155] The acquisition module 205 can acquire the perception data of the current scene. The current scene is the scene of the environment in which the electronic device is currently located, that is, the scene of the environment in which the user of the electronic device is currently located. The perception data may include arbitrary data. For example, the perception data may include environmental data such as ambient temperature, ambient light intensity, and ambient noise. The perception data may also include operating data of the electronic device such as image data on the electronic device, memory data, and text data displayed on the electronic device. The perception data may also include user behavior habit data, such as the user's work and rest time, the user's entertainment activities, etc.

[0156] Among them, the acquisition module 205 can collect the perception data of the current scene through the information perception layer in the panoramic perception architecture of the electronic device. For example, the acquisition module 205 can detect the ambient temperature through a temperature sensor, detect the ambient light intensity through a light sensor, detect the ambient noise through a microphone, retrieve the image data, memory data, etc. on the electronic device through the processing circuit of the electronic device, and obtain the text data displayed on the electronic device through the display control circuit. In addition, the acquisition module 205 can also perceive the user's behavior through the information perception layer and record it to form the user's behavior habit data.

[0157] Subsequently, the acquisition module 205 may identify the current scene according to the perception data to obtain an identification result. For example, the identification result may be a scene such as a home, an office, a subway station, a shopping mall, etc. The acquisition module 205 may obtain a preset matching degree threshold according to the identification result.

[0158] For example, the electronic device may pre-store a preset matching degree threshold corresponding to each scene. The preset matching degree threshold corresponding to each scene may be set by a professional based on experience. The preset matching degree thresholds corresponding to different scenes may be different. The acquisition module 205 may query according to the recognition result to obtain the preset matching degree threshold corresponding to the recognition result.

[0159] In some embodiments, when obtaining a preset matching degree threshold according to the recognition result, the obtaining module 205 is used to perform the following steps:

[0160] According to the recognition result, a first weight corresponding to the application operation habit, a second weight corresponding to the electronic device holding habit, and a third weight corresponding to the display screen operation habit are obtained;

[0161] The preset matching degree threshold is calculated according to the first weight, the second weight, the third weight, the first preset matching degree corresponding to the application operation habit, the second preset matching degree corresponding to the electronic device holding habit, and the third preset matching degree corresponding to the display screen operation habit.

[0162] In the electronic device, the corresponding first preset matching degree, second preset matching degree, and third preset matching degree can be set for the application operation habits, the electronic device holding habits, and the display screen operation habits. The meaning of the first preset matching degree, the second preset matching degree, and the third preset matching degree is that if the matching degree between the application operation habits in the first user feature vector and the application operation habits in the second user feature vector is greater than the first preset matching degree, and the matching degree between the electronic device holding habits in the first user feature vector and the electronic device holding habits in the second user feature vector is greater than the second preset matching degree, and the matching degree between the display screen operation habits in the first user feature vector and the display screen operation habits in the second user feature vector is greater than the third preset matching degree, then it can be considered that the matching degree between the first user feature vector and the second user feature vector is greater than the preset matching degree threshold.

[0163] For example, the first preset matching degree for application operation habits may be 80%, the second preset matching degree for electronic device holding habits may be 90%, and the third preset matching degree for display screen operation habits may be 95%. The first preset matching degree, the second preset matching degree, and the third preset matching degree may be set by professionals based on experience.

[0164] In addition, users may have different habits of using electronic devices in different scenarios. For example, the amount of pressure a user applies to holding an electronic device indoors and outdoors may be different. Another example is that a user may use a navigation application at home and at a subway station at different frequencies. Therefore, different weights can be set for different scenarios in the electronic device based on the characteristics of the three dimensions of application operation habits, electronic device holding habits, and display screen operation habits. Among them, the weight set for application operation habits is the first weight, the weight set for electronic device holding habits is the second weight, and the weight set for display screen operation habits is the third weight. Among them, the first weight, the second weight, and the third weight may be different for different scenarios. The first weight, the second weight, and the third weight can be set by professionals based on experience.

[0165] For example, for an office scenario, the first weight may be 0.5, the second weight may be 0.2, and the third weight may be 0.3; for a subway station scenario, the first weight may be 0.3, the second weight may be 0.4, and the third weight may be 0.3.

[0166] The acquisition module 205 recognizes the current scene, and after obtaining the recognition result, the first weight corresponding to the application operation habit, the second weight corresponding to the electronic device holding habit, and the third weight corresponding to the display screen operation habit can be obtained according to the recognition result. Subsequently, the preset matching degree threshold is calculated according to the first weight, the second weight, the third weight, the first preset matching degree corresponding to the application operation habit, the second preset matching degree corresponding to the electronic device holding habit, and the third preset matching degree corresponding to the display screen operation habit.

[0167] In some embodiments, the acquisition module 205 calculates the preset matching degree threshold according to the following formula:

[0168] P=k1×P1+k2×P2+k3×P3

[0169] Among them, P is the preset matching degree threshold, k1 is the first weight, k2 is the second weight, k3 is the third weight, P1 is the first preset matching degree, P2 is the second preset matching degree, and P3 is the third preset matching degree.

[0170] It is understandable that in other embodiments, the acquisition module 205 may also calculate the preset matching degree threshold in other ways.

[0171] In specific implementation, the above modules can be implemented as independent entities, or can be arbitrarily combined to be implemented as the same entity or several entities.

[0172] As can be seen from the above, the display control device 200 provided in the embodiment of the present application includes: a first vector construction module 201, which is used to construct the first user feature vector of the legal user according to the historical usage behavior information of the legal user; a second vector construction module 202, which is used to construct the second user feature vector of the current user according to the current usage behavior information of the current user; a judgment module 203, which is used to judge whether the current user is the legal user according to the first user feature vector and the second user feature vector; a control module 204, which is used to: if the current user is the legal user, control the display of the legal user interface; if the current user is not the legal user, control the display of the guest interface, wherein the guest interface hides the privacy information of the legal user. The display control device can judge whether the current user is a legal user according to the user's usage behavior habits. If the current user is not a legal user, the privacy information of the legal user is hidden, and the hidden guest interface is displayed, thereby avoiding the leakage of the privacy information of the legal user and improving the information security of the electronic device.

[0173] The present application also provides an electronic device, which may be a smart phone, a tablet computer, a gaming device, an AR (Augmented Reality) device, a car, a data storage device, an audio playback device, a video playback device, a laptop computer, a desktop computing device, a wearable device such as an electronic watch, electronic glasses, an electronic helmet, an electronic bracelet, an electronic necklace, electronic clothing, and the like.

[0174] refer to Fig. 9 , Fig. 9 A first structural schematic diagram of an electronic device provided in an embodiment of the present application.

[0175] The electronic device 300 includes a processor 301 and a memory 302. The processor 301 is electrically connected to the memory 302.

[0176] The processor 301 is the control center of the electronic device 300. It uses various interfaces and lines to connect various parts of the entire electronic device. It executes various functions of the electronic device and processes data by running or calling computer programs stored in the memory 302, and calling data stored in the memory 302, thereby monitoring the electronic device as a whole.

[0177] In this embodiment, the processor 301 in the electronic device 300 loads instructions corresponding to the processes of one or more computer programs into the memory 302 according to the following steps, and the processor 301 runs the computer program stored in the memory 302, thereby performing the following steps:

[0178] Constructing a first user feature vector of the legitimate user according to the historical usage behavior information of the legitimate user;

[0179] Constructing a second user feature vector of the current user according to the current usage behavior information of the current user;

[0180] Determining whether the current user is the legal user according to the first user feature vector and the second user feature vector;

[0181] If the current user is the legal user, controlling the display of the legal user interface;

[0182] If the current user is not the legal user, a guest interface is controlled to be displayed, wherein the guest interface hides the privacy information of the legal user.

[0183] In some embodiments, when determining whether the current user is the legal user according to the first user feature vector and the second user feature vector, the processor 301 performs the following steps:

[0184] Calculating a matching degree between the first user feature vector and the second user feature vector;

[0185] Determining whether the matching degree is greater than a preset matching degree threshold;

[0186] If the matching degree is greater than the preset matching degree threshold, it is determined that the current user is the legal user;

[0187] If the matching degree is not greater than the preset matching degree threshold, it is determined that the current user is not the legal user.

[0188] In some embodiments, when calculating the matching degree between the first user feature vector and the second user feature vector, the processor 301 performs the following steps:

[0189] Calculating the cosine similarity between the first user feature vector and the second user feature vector;

[0190] The cosine similarity is determined as a degree of matching between the first user feature vector and the second user feature vector.

[0191] In some embodiments, before determining whether the matching degree is greater than a preset matching degree threshold, the processor 301 further performs the following steps:

[0192] Get the perception data of the current scene;

[0193] Identify the current scene according to the perception data to obtain a recognition result;

[0194] A preset matching degree threshold is obtained according to the recognition result.

[0195] In some embodiments, when obtaining a preset matching degree threshold according to the recognition result, the processor 301 performs the following steps:

[0196] According to the recognition result, a first weight corresponding to the application operation habit, a second weight corresponding to the electronic device holding habit, and a third weight corresponding to the display screen operation habit are obtained;

[0197] The preset matching degree threshold is calculated according to the first weight, the second weight, the third weight, the first preset matching degree corresponding to the application operation habit, the second preset matching degree corresponding to the electronic device holding habit, and the third preset matching degree corresponding to the display screen operation habit.

[0198] In some embodiments, the processor 301 calculates the preset matching degree threshold according to the following formula:

[0199] P = k1 × P1 + k2 × P2 + k3 × P3;

[0200] Among them, P is the preset matching degree threshold, k1 is the first weight, k2 is the second weight, k3 is the third weight, P1 is the first preset matching degree, P2 is the second preset matching degree, and P3 is the third preset matching degree.

[0201] The memory 302 can be used to store computer programs and data. The computer programs stored in the memory 302 contain instructions that can be executed in the processor. The computer programs can form various functional modules. The processor 301 executes various functional applications and data processing by calling the computer programs stored in the memory 302.

[0202] In some embodiments, reference Fig.10 , Fig.10 A second structural schematic diagram of an electronic device provided in an embodiment of the present application.

[0203] The electronic device 300 further includes: a display screen 303, a control circuit 304, an input unit 305, a sensor 306 and a power supply 307. The processor 301 is electrically connected to the display screen 303, the control circuit 304, the input unit 305, the sensor 306 and the power supply 307 respectively.

[0204] The display screen 303 may be used to display information input by a user or information provided to a user and various graphical user interfaces of the electronic device. These graphical user interfaces may be composed of images, texts, icons, videos and any combination thereof.

[0205] The control circuit 304 is electrically connected to the display screen 303 and is used to control the display screen 303 to display information.

[0206] The input unit 305 can be used to receive input numbers, character information or user feature information (such as fingerprints), and generate keyboard, mouse, joystick, optical or trackball signal input related to user settings and function control. The input unit 305 can include a fingerprint recognition module.

[0207] The sensor 306 is used to collect information of the electronic device itself, the user's information, or the external environment information. For example, the sensor 306 may include a distance sensor, a magnetic field sensor, a light sensor, an acceleration sensor, a fingerprint sensor, a Hall sensor, a position sensor, a gyroscope, an inertial sensor, a posture sensor, a barometer, a heart rate sensor, and other sensors.

[0208] The power supply 307 is used to supply power to various components of the electronic device 300. In some embodiments, the power supply 307 may be logically connected to the processor 301 through a power management system, so that the power management system can manage charging, discharging, power consumption, and other functions.

[0209] although Fig.10 Not shown, the electronic device 300 may also include a camera, a Bluetooth module, etc., which will not be described in detail here.

[0210] As can be seen from the above, an embodiment of the present application provides an electronic device, which performs the following steps: constructing a first user feature vector of a legitimate user based on historical usage behavior information of a legitimate user; constructing a second user feature vector of the current user based on the current usage behavior information of the current user; judging whether the current user is the legitimate user based on the first user feature vector and the second user feature vector; if the current user is the legitimate user, controlling the display of a legitimate user interface; if the current user is not the legitimate user, controlling the display of a visitor interface, wherein the visitor interface hides the privacy information of the legitimate user. The electronic device can judge whether the current user is a legitimate user based on the user's usage behavior habits. If the current user is not a legitimate user, hiding the privacy information of the legitimate user and displaying the hidden visitor interface, thereby avoiding leakage of the privacy information of the legitimate user and improving the information security of the electronic device.

[0211] An embodiment of the present application further provides a storage medium, wherein a computer program is stored in the storage medium. When the computer program runs on a computer, the computer executes the display control method described in any one of the above embodiments.

[0212] It should be noted that, a person skilled in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing related hardware through a computer program, and the computer program can be stored in a computer-readable storage medium, and the storage medium can include but is not limited to: read-only memory (ROM), random access memory (RAM), disk or optical disk, etc.

[0213] The display control method, device, storage medium and electronic device provided by the embodiments of the present application are described in detail above. Specific examples are used herein to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method and core idea of ​​the present application. At the same time, for those skilled in the art, according to the idea of ​​the present application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A display control method, characterized in that: include: Constructing a first user feature vector of the legitimate user according to the historical usage behavior information of the legitimate user; Constructing a second user feature vector of the current user according to the current usage behavior information of the current user; Determine whether the current user is the legitimate user according to the first user feature vector, the second user feature vector and a preset matching degree threshold, wherein the preset matching degree threshold is calculated according to a first weight corresponding to application operation habits, a second weight corresponding to electronic device holding habits, a third weight corresponding to display screen operation habits, and a first preset matching degree corresponding to application operation habits, a second preset matching degree corresponding to electronic device holding habits, and a third preset matching degree corresponding to display screen operation habits; The first weight, the second weight, and the third weight are obtained according to a recognition result, and the recognition result is obtained by recognizing the current scene according to the acquired perception data of the current scene; If the current user is the legal user, controlling the display of the legal user interface; If the current user is not the legal user, a guest interface is controlled to be displayed, wherein the guest interface hides the privacy information of the legal user.

2. The display control method according to claim 1, characterized in that: The step of judging whether the current user is the legal user according to the first user feature vector, the second user feature vector and a preset matching threshold comprises: Calculating a matching degree between the first user feature vector and the second user feature vector; Determining whether the matching degree is greater than a preset matching degree threshold; If the matching degree is greater than the preset matching degree threshold, it is determined that the current user is the legal user; If the matching degree is not greater than the preset matching degree threshold, it is determined that the current user is not the legal user.

3. The display control method according to claim 2, characterized in that: The step of calculating the matching degree between the first user feature vector and the second user feature vector comprises: Calculating the cosine similarity between the first user feature vector and the second user feature vector; The cosine similarity is determined as a degree of matching between the first user feature vector and the second user feature vector.

4. The display control method according to claim 2 or 3, characterized in that: Before the step of determining whether the matching degree is greater than a preset matching degree threshold, the step further includes: Get the perception data of the current scene; Identify the current scene according to the perception data to obtain a recognition result; A preset matching degree threshold is obtained according to the recognition result.

5. The display control method according to claim 4, characterized in that: The step of obtaining a preset matching degree threshold according to the recognition result comprises: According to the recognition result, a first weight corresponding to the application operation habit, a second weight corresponding to the electronic device holding habit, and a third weight corresponding to the display screen operation habit are obtained; The preset matching degree threshold is calculated according to the first weight, the second weight, the third weight, the first preset matching degree corresponding to the application operation habit, the second preset matching degree corresponding to the electronic device holding habit, and the third preset matching degree corresponding to the display screen operation habit.

6. The display control method according to claim 5, characterized in that: The preset matching threshold is calculated according to the following formula: P = k1 × P1 + k2 × P2 + k3 × P3; Among them, P is the preset matching degree threshold, k1 is the first weight, k2 is the second weight, k3 is the third weight, P1 is the first preset matching degree, P2 is the second preset matching degree, and P3 is the third preset matching degree.

7. A display control device, characterized in that: include: A first vector construction module, used to construct a first user feature vector of the legal user according to the historical usage behavior information of the legal user; A second vector construction module, used to construct a second user feature vector of the current user according to the current usage behavior information of the current user; a judgment module, configured to judge whether the current user is the legal user according to the first user feature vector, the second user feature vector and a preset matching degree threshold, wherein the preset matching degree threshold is calculated according to a first weight corresponding to an application operation habit, a second weight corresponding to an electronic device holding habit, a third weight corresponding to a display screen operation habit, and a first preset matching degree corresponding to the application operation habit, a second preset matching degree corresponding to the electronic device holding habit, and a third preset matching degree corresponding to the display screen operation habit; The first weight, the second weight, and the third weight are obtained according to a recognition result, and the recognition result is obtained by recognizing the current scene according to the acquired perception data of the current scene; Control module for: If the current user is the legal user, controlling the display of the legal user interface; If the current user is not the legal user, a guest interface is controlled to be displayed, wherein the guest interface hides the privacy information of the legal user.

8. The display control device according to claim 7, characterized in that: The judging module is used for: Calculating a matching degree between the first user feature vector and the second user feature vector; Determining whether the matching degree is greater than a preset matching degree threshold; If the matching degree is greater than the preset matching degree threshold, it is determined that the current user is the legal user; If the matching degree is not greater than the preset matching degree threshold, it is determined that the current user is not the legal user.

9. The display control device according to claim 8, characterized in that: When calculating the matching degree between the first user feature vector and the second user feature vector, the judgment module is used to: Calculating the cosine similarity between the first user feature vector and the second user feature vector; The cosine similarity is determined as a degree of matching between the first user feature vector and the second user feature vector.

10. A storage medium, characterized in that: The storage medium stores a computer program, and when the computer program is executed on a computer, the computer executes the display control method according to any one of claims 1 to 6.

11. An electronic device, characterized in that: The electronic device comprises a processor and a memory, wherein a computer program is stored in the memory, and the processor is used to execute the display control method according to any one of claims 1 to 6 by calling the computer program stored in the memory.

Images