Incoming call reminder methods, devices, terminal equipment and computer-readable storage media

Abstract

This application provides a method, apparatus, terminal device, and computer-readable storage medium for incoming call reminders. The method includes: acquiring an incoming call event; collecting multi-dimensional data information based on the incoming call event; predicting a target incoming call reminder strategy based on the multi-dimensional data information; and executing an incoming call reminder for the incoming call event according to the target incoming call reminder strategy. The incoming call reminder method provided by this application can collect multi-dimensional data information about the acquired incoming call event to obtain data on various dimensions of the event. Then, based on the multi-dimensional data information, an appropriate target incoming call reminder strategy can be predicted, and the incoming call event can be reminded according to the target incoming call reminder strategy, thus achieving timely reminders for the incoming call event and avoiding the need for users to manually adjust the incoming call reminder method.

Description

Technical Field

[0001] This application relates to the technical field of mobile terminals, specifically to a method, apparatus, terminal device, and computer-readable storage medium for incoming call reminders. Background Technology

[0002] Currently, smartphone call notification modes (such as ring, vibrate, and silent) are usually tied to the phone's overall system settings, and users can only adjust them manually or through simple scenario rules. For example, users can only adjust whether to silence the phone using the side button on the phone, or adjust the phone's vibration and ringtone settings. This adjustment method, especially for users who switch between multiple scenarios, causes significant inconvenience due to the frequent manual adjustments to call notification methods. Summary of the Invention

[0003] This application provides a call reminder method that can predict suitable target call reminder strategies for users and adaptively and automatically switch call reminder modes.

[0004] Firstly, this application provides a method for reminding people of incoming calls, the method comprising: Obtain incoming call events; Based on the incoming call event, collect data information from multiple dimensions; Based on the data information of each dimension, predict the target call reminder strategy; According to the target call reminder policy, execute the call reminder for the call event.

[0005] In some embodiments of this application, predicting the target call reminder strategy based on the data information of each dimension includes: Based on the data information of each dimension, predict whether the current scene is a quiet scene; If the current scenario is the quiet scenario, the target call reminder strategy is predicted to be the silent call reminder strategy; If the current scenario is not a quiet scenario, the target call reminder strategy is predicted to be a non-silent call reminder strategy.

[0006] In some embodiments of this application, each of the dimensional data information includes at least one of the following: current location information, terminal displacement information, environmental noise information, current date information, current time information, caller identity information, user behavior information corresponding to historical missed calls, and feedback information corresponding to the user behavior information; The step of predicting the target call reminder strategy based on the data information of each dimension includes: The target decision model is input with at least one of the following dimensions: current location information, terminal displacement information, environmental noise information, current date information, current time information, caller identity information, user behavior information corresponding to historical missed calls, and feedback information corresponding to user behavior information, to predict the target call reminder strategy.

[0007] In some embodiments of this application, each of the dimensional data information includes at least one of the following: current location information, terminal displacement information, environmental noise information, current date information, current time information, caller identity information, user behavior information corresponding to historical missed calls, and feedback information corresponding to the user behavior information; The step of predicting the target call reminder strategy based on the data information of each dimension includes: If the current location information, terminal displacement information, environmental noise information, caller identity information, user behavior information corresponding to the historical missed calls, and feedback information corresponding to the user behavior information are not obtained, then the current date information and current time information are used to determine whether it is during working hours. Predict target call reminder strategies based on whether it is during the stated working hours.

[0008] In some embodiments of this application, each of the dimensional data information includes at least one of the following: current location information, terminal displacement information, environmental noise information, current date information, current time information, caller identity information, user behavior information corresponding to historical missed calls, and feedback information corresponding to the user behavior information; The step of predicting the target call reminder strategy based on the data information of each dimension includes: If the terminal displacement information, the environmental noise information, the caller identity information, the user behavior information corresponding to the historical missed calls and the feedback information corresponding to the user behavior information, the current date information and the current time information are not obtained, then the current location information is used to determine whether the user is at the work location. Predict target call reminder strategies based on whether the target is at the stated work location.

[0009] In some embodiments of this application, the method further includes: optimizing the target decision model; The optimization of the target decision model includes: Record different historical data for each call reminder setting manually configured by the user; The target decision model is optimized based on the preset period and the different historical data.

[0010] In some embodiments of this application, the dimensional data information includes caller identity information; The step of predicting the target call reminder strategy based on the data information of each dimension includes: Determine if there are any target preference caller settings enabled; If it is determined that the target preference call settings are set, then the target call reminder strategy corresponding to the caller identity information is predicted based on the target preference call settings.

[0011] Secondly, this application also provides a call reminder device, the device comprising: The acquisition module is used to acquire incoming call events; The data acquisition module is used to collect data information from multiple dimensions based on the incoming call event. The prediction module is used to predict the target call reminder strategy based on the data information of each dimension. The execution module is used to execute the incoming call reminder for the incoming call event according to the target incoming call reminder strategy.

[0012] Thirdly, this application also provides a terminal device, the terminal device including a processor, a memory, and a computer program stored in the memory and executable on the processor, the processor executing the computer program to implement the steps in any of the call reminder methods described above.

[0013] Fourthly, this application also provides a computer-readable storage medium storing a computer program that is executed by a processor to implement the steps of any of the call reminder methods described above.

[0014] The incoming call reminder method provided in this application can collect multi-dimensional data information about an incoming call event, obtaining data on various dimensions of the event. Then, based on the data from each dimension, an appropriate target incoming call reminder strategy can be predicted, and the incoming call event can be reminded according to the target strategy. This achieves the goal of reminding users of incoming call events in a suitable manner, avoiding the need for users to manually adjust the call reminder method. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1This is a schematic diagram of a scenario for the call reminder system provided in the embodiments of this application; Figure 2 This is a schematic flowchart of one embodiment of the call reminder method in this application; Figure 3 This is a schematic diagram of a functional module of the call reminder device in the embodiments of this application; Figure 4 This is a schematic diagram of the structure of the terminal device in the embodiments of this application. Detailed Implementation

[0017] 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, and 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.

[0018] In the description of this application, it should be understood that the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this application, "multiple" means two or more, unless otherwise explicitly specified.

[0019] In this application, the term "exemplary" is used to mean "used as an example, illustration, or description." Any embodiment described as "exemplary" in this application is not necessarily to be construed as being more preferred or advantageous than other embodiments. Furthermore, it is understood that in the specific embodiments of this application, user information, user data, and other related data are involved. When the above embodiments of this application are applied to specific products or technologies, user permission or consent is required, and the collection, use, and processing of related data must comply with the relevant laws, regulations, and standards of the relevant countries and regions.

[0020] To enable any person skilled in the art to implement and use this application, the following description is provided. In this description, details are set forth for purposes of explanation. It should be understood that those skilled in the art will recognize that this application can be implemented without using these specific details. In other instances, well-known structures and processes will not be described in detail to avoid obscuring the description of this application with unnecessary detail. Therefore, this application is not intended to be limited to the embodiments shown, but is consistent with the broadest scope of the principles and features disclosed in this application.

[0021] This application provides a method, apparatus, device, and storage medium for incoming call reminders, which are described in detail below.

[0022] Please see Figure 1 , Figure 1 This is a schematic diagram of a call reminder system provided in an embodiment of this application. The call reminder system may include a terminal device 100, which can collect data. Figure 1 The terminal device 100 can capture data from various dimensions corresponding to incoming call events based on its own sensors and data acquisition programs in order to execute the incoming call reminder method in this application.

[0023] In this embodiment of the application, the terminal device 100 may include, but is not limited to, desktop computers, portable computers, PDAs (personal digital assistants), tablet computers, wireless terminal devices, mobile phones, etc.

[0024] It should be noted that, Figure 1 The schematic diagram of the incoming call reminder system shown is merely an example. The incoming call reminder system and scenarios described in this application are intended to more clearly illustrate the technical solutions of this application and do not constitute a limitation on the technical solutions provided in this application. As those skilled in the art will know, with the evolution of incoming call reminder systems and the emergence of new business scenarios, the technical solutions provided in this application are also applicable to similar technical problems.

[0025] like Figure 2 As shown, Figure 2 This is a flowchart illustrating one embodiment of the call reminder method in this application. The call reminder method may include the following steps 201-204: 201. Obtain incoming call events.

[0026] In this embodiment, the incoming call event can be an event indicating that a phone call has been made to the mobile terminal device. When another user calls the local mobile terminal, the local mobile terminal can obtain the incoming call event.

[0027] 202. Collect data information from multiple dimensions based on incoming call events.

[0028] When a local terminal device receives an incoming call event, it can acquire data information related to that event across various dimensions. For example, current date, current time, and current location information. These are all data information within different dimensions. Once the data information across these different dimensions is collected, the data information for each dimension can be obtained. This application does not limit the specific dimensions; the dimensions involved can be collected according to user settings.

[0029] The methods for obtaining data information of different dimensions can be obtained through corresponding means. For example, the current location information can be obtained through the positioning module of the terminal device, while date information, time information, etc. can be obtained based on the calendar and clock. Therefore, the collection methods for specific dimension data vary with the dimension, and this application embodiment will not elaborate on or limit them.

[0030] 203. Based on data from various dimensions, predict the target call reminder strategy.

[0031] The above steps allow us to obtain data information from various dimensions, and based on this data, we can predict the target call reminder strategy. For example, if the data information includes the current date, current time, and current location, predictions can be made based on these three dimensions. For instance, if the current date corresponds to a weekday, the current time is within working hours (e.g., 9 AM to 6 PM), and the current location indicates the mobile device is located at a company address, then the device is in a working environment, and the predicted call reminder strategy is a silent strategy. Alternatively, if the current date corresponds to a weekday, the current time is within working hours (e.g., 9 AM to 6 PM), and the current location does not indicate the mobile device is located at a company address, then the device is not in a working environment, and the predicted call reminder strategy is a ringing strategy. Conversely, if the current date corresponds to a non-working day, the current time is within working hours (e.g., 9 AM to 6 PM), and the current location indicates the mobile device is located at a company address, then the device is in an overtime work environment, and the predicted call reminder strategy is a silent strategy.

[0032] Of course, the above embodiments illustrate how to formulate ringing or muting strategies. In practice, call alerts can also include volume levels. Therefore, in this embodiment, the data information for each dimension can also include ambient noise information, which can be collected through the microphone of the terminal device. If ambient noise information can also be collected, and if a ringing strategy is determined, the volume of the call alert can be adjusted accordingly. The higher the ambient noise level (in decibels) represented by the ambient noise information, the higher the volume, up to the upper limit; conversely, the lower the ambient noise level (in decibels), the lower the volume, until it approaches muting. Therefore, this embodiment can determine a specific target call alert strategy based on specific dimensional data information.

[0033] 204. Execute call reminders for incoming call events according to the target call reminder strategy.

[0034] Based on the steps above, a specific target call reminder strategy can be determined. Therefore, the call reminder can be executed according to the specific target call reminder strategy, such as muting, ringing, or adjusting the volume on the basis of ringing.

[0035] It should also be noted that after executing the call reminder for the incoming call event according to the target call reminder policy, the current call reminder mode corresponding to the target call reminder policy and the reason for switching can also be displayed on the display interface, which is convenient for users to understand and manage.

[0036] The incoming call reminder method provided in this application can collect multi-dimensional data information about an incoming call event, obtaining data on various dimensions of the event. Then, based on the data from each dimension, an appropriate target incoming call reminder strategy can be predicted, and the incoming call event can be reminded according to the target strategy. This achieves the goal of reminding users of incoming call events in a suitable manner, avoiding the need for users to manually adjust the call reminder method.

[0037] To better implement the embodiments of this application, in one embodiment, a target call reminder strategy is predicted based on data information from various dimensions, including: Based on data from various dimensions, predict whether the current scenario is a quiet scenario; if the current scenario is a quiet scenario, predict the target call reminder strategy as a silent call reminder strategy; if the current scenario is not a quiet scenario, predict the target call reminder strategy as a non-silent call reminder strategy.

[0038] The above embodiments provide an implementation method for determining a target call reminder strategy based on data information from different dimensions. However, in practical application scenarios, users' usual usage preferences for call reminders typically only include silent and ringing, and users usually do not adjust the ringing volume. Therefore, in order to fit the actual scenario, this application embodiment also provides an implementation method.

[0039] Specifically, if the collected data includes current date, current time, and current location, the logic for predicting the target call reminder strategy based on this data can still follow the above method to determine whether it's a quiet or non-quiet scenario. If the data also includes ambient noise information, it can further determine whether the scenario is quiet or non-quiet, rather than simply using it for volume control. For example, if the current date, current time, and current location indicate the user is likely working, and the ambient noise level is high, the user is in a noisy work environment. Therefore, if the call reminder is in ring mode, it won't disturb others. Thus, it can be determined as a non-quiet scenario. Conversely, if the current date, current time, and current location indicate the user is likely working, but the ambient noise level is low, the user is likely in a quiet work environment, and in this case, the scenario can be predicted as quiet. Then, based on the classification information of non-quiet and quiet scenarios, the specific target call reminder strategy is determined, such as a silent strategy or a ringing strategy, without needing to further involve volume, thus reducing the complexity of adjusting the call reminder strategy.

[0040] To better implement the embodiments of this application, in one embodiment, the data information of each dimension includes at least one of the following: current location information, terminal displacement information, environmental noise information, current date information, current time information, caller identity information, user behavior information corresponding to historical missed calls, and feedback information corresponding to user behavior information; based on the data information of each dimension, a target call reminder strategy is predicted, including: Input at least one dimension of data, including current location information, terminal displacement information, environmental noise information, current date information, current time information, caller identity information, user behavior information corresponding to historical missed calls, and feedback information corresponding to user behavior information, into the target decision model to predict the target call reminder strategy.

[0041] The above embodiments provide implementation methods for determining target call reminder strategies based on data information from different dimensions. To further improve the accuracy of prediction, this application also provides an implementation method.

[0042] Specifically, compared to the above embodiments, the data information in each dimension has been further refined, such as current location information, terminal displacement information, ambient noise information, current date information, current time information, caller identity information, user behavior information corresponding to historical missed calls, and feedback information corresponding to user behavior information. The methods for collecting current location information, current date information, current time information, and ambient noise information have been described in the previous embodiments and will not be repeated here. As for terminal displacement information, it can still be calculated by using the positioning module to collect the terminal's displacement per unit time. In addition, caller identification information can be obtained from the terminal device's address book, such as the corresponding number's notes. If the caller identification information cannot be determined from the address book, the caller ID will usually be the number displayed, in which case it can be determined that the caller is an unknown number. User behavior information corresponding to historical missed calls can include the user's subsequent actions after receiving the call, such as calling back or ignoring it. User behavior information for missed calls can be collected from the terminal device's historical operation logs. After a user generates corresponding user behavior information for historical missed calls, the user may also provide feedback on the specific user behavior information, and feedback information can be obtained. For example, for missed calls, the user may make notes such as "in a meeting" or "did not hear" to indicate the reason for the historical missed call. This feedback information can be collected through user notes. In this embodiment, the current location information can be used, as in the embodiments described above, to predict whether the user is at their work address; the current date and current time information can be used to predict whether the user is at work time; the terminal displacement information represents the user's movement status. Even if the user is at work time and at their work address, the probability of them being stationary inside a room is low because they may be moving. In a moving state, the probability of being surrounded by colleagues or in a meeting is also low. Therefore, this information can also be used to predict the ringing or muting strategy; the caller ID information can prevent missing important calls. For example, if the caller ID information indicates a hospital, police station, or court, etc. These callers' calls are usually very important, and making a silent prediction could lead to significant losses for users. Therefore, caller ID information can be changed for specific call events, thus aiding decision-making. User behavior information, environmental noise information, and feedback information corresponding to user behavior information from historical missed calls can be used to comprehensively determine the volume. If a user with a historical missed call is subsequently called back, and the caller ID strategy for that historical missed call was ringing, and the user's feedback after calling back is "did not hear," then the model can appropriately increase the volume when the subsequent call reminder strategy is ringing, up to the maximum volume.

[0043] Therefore, it is evident that the data involved in each dimension can alter the specific call reminder strategy. Thus, for a specific target call reminder strategy, after collecting data from each dimension, this data can be input into the target decision model to obtain the predicted target call reminder strategy. In this embodiment, the target decision model can be any neural network model, and this embodiment does not limit it, such as decision trees, large models, etc.

[0044] To better implement the embodiments of this application, in one embodiment, the data information of each dimension includes at least one of the following: current location information, terminal displacement information, environmental noise information, current date information, current time information, caller identity information, user behavior information corresponding to historical missed calls, and feedback information corresponding to user behavior information; based on the data information of each dimension, a target call reminder strategy is predicted, including: If the current location information, terminal displacement information, environmental noise information, caller identity information, user behavior information corresponding to historical missed calls, and feedback information corresponding to user behavior information are not obtained, then the current date information and current time information are used to determine whether it is during working hours; based on whether it is during working hours, the target call reminder strategy is predicted.

[0045] The above embodiments provide a scheme for predicting target call reminder strategies based on data information from different dimensions. However, in some cases, it is impossible to collect data information from multiple dimensions, such as when the user may have turned off the location module; when the user provides feedback; or when the caller's identity information is hidden and cannot be known. Therefore, when collecting data information from various dimensions, the current date and current time information may be collected. Even when only the current date and current time information are obtained, it is still necessary to determine the call reminder strategy. Based on this, in the embodiments of this application, if only the current date and current time information are obtained, the steps may include: 1) Calendar synchronization: The system automatically synchronizes calendar information such as statutory holidays, time off in lieu, and make-up work hours on a regular basis (e.g., every morning at midnight) (via cloud API or local calendar database) (set in advance).

[0046] 2) User get off work hours settings: Users can enter or import the company's get off work hours (e.g., 9:00-18:00) in the settings interface (set in advance).

[0047] 3) Current date information status judgment: The system determines whether the current day is a "workday", "rest day" or "make-up workday" based on the synchronized calendar information.

[0048] 4) Current time period determination: Based on the current time information, determine whether it is within the user's set working hours.

[0049] 5) Preliminary mode decision: If it is a weekday / make-up workday and during working hours, the initial setting is "vibration" or "silent" mode; If it is a rest day or after get off work hours, the initial setting is "ringing" mode.

[0050] 6) Output preliminary decision.

[0051] To better implement the embodiments of this application, in one embodiment, the data information of each dimension includes at least one of the following: current location information, terminal displacement information, environmental noise information, current date information, current time information, caller identity information, user behavior information corresponding to historical missed calls, and feedback information corresponding to user behavior information; based on the data information of each dimension, a target call reminder strategy is predicted, including: If terminal displacement information, environmental noise information, caller identity information, user behavior information corresponding to historical missed calls and feedback information corresponding to user behavior information, current date information, and current time information are not obtained, then the current location information is used to determine whether the user is at work; based on whether the user is at work, the target call reminder strategy is predicted.

[0052] The above embodiments provide a solution for predicting target call reminder strategies when some dimensional information is unavailable. Based on this, this application also provides an implementation method.

[0053] The above embodiments provide a scheme for predicting a target call reminder strategy based on current date and time information. However, in some application scenarios, the terminal device may only collect current location information. Therefore, if only current location information can be obtained, the steps for predicting the target call reminder strategy may include: 1) Location permission acquisition: The system requests and obtains location permission authorized by the user (set in advance).

[0054] 2) Setting Frequent Locations: Users can mark frequently used locations (such as "Office", "Home", "Gym", etc.) in the settings interface, and the system records the corresponding geographical coordinates. Alternatively, the system can automatically record and identify frequently used locations based on location information (set in advance).

[0055] 3) Real-time location detection: The system acquires current GPS / Wi-Fi location information periodically (e.g., every 5 minutes) or when the location changes.

[0056] 4) Geofencing determination: Determines whether the current coordinates have entered / left a pre-defined permanent location.

[0057] 5) Output preliminary decision: If entering the "Company" geofence, automatically switch to "vibrate" or "silent" mode; if leaving the "Company" and entering "Home" or other areas, automatically switch to "ring" mode.

[0058] To better implement the embodiments of this application, in one embodiment, the method further includes: optimizing the target decision model; the optimized target decision model includes: Record different historical data for each call reminder setting manually configured by the user; optimize the target decision model based on the preset period and different historical data.

[0059] The above embodiments provide a scheme for predicting target call reminder strategies using a neural network model. This application also provides a scheme for optimizing the target decision model. Specifically, in practice, users' usage habits, work addresses, and work hours may change, therefore the neural network model requires subsequent optimization. Therefore, the terminal device can collect dimensional data information corresponding to each call event and optimize the model according to a specific optimization cycle. The method of optimizing the model is essentially the same as the initial training method. This application does not limit the specific optimization scheme or training scheme. For example, it may include: 1) Behavioral data collection: Record the time, location, and scenario (such as meeting, going out, etc.) of each time the user manually switches the call reminder mode.

[0060] 2) Data storage and organization: The collected data is classified and stored according to dimensions such as time, location, and scenario.

[0061] 3) Behavioral pattern analysis: Regularly (e.g., daily / weekly) analyze the patterns of users switching modes, such as "switching to silent mode at the company every Monday at 9 am".

[0062] 4) Behavioral model optimization: Based on the analysis results, optimize user-specific behavioral models (such as time-location-pattern triples).

[0063] 5) Automatic suggestions and switching: When a scenario that is highly similar to the historical behavior pattern is detected, the system will proactively push switching suggestions to the user or automatically switch modes (the user can choose automatic / manual).

[0064] 6) User feedback collection: Record users' acceptance / rejection of suggestions to continuously optimize the behavior model.

[0065] Furthermore, the preset period can be set by the user or it can be the system's default value; this application embodiment does not limit it.

[0066] To better implement the embodiments of this application, in one embodiment, the data information of each dimension includes caller identity information; based on the data information of each dimension, a target call reminder strategy is predicted, including: Determine whether target preference call settings are set; if so, predict the target call reminder strategy corresponding to the caller's identity information based on the target preference call settings.

[0067] The above embodiments provide an implementation method for predicting a target call reminder strategy based on multiple dimensions of data information. However, as can be seen from the above embodiments, the different dimensions of data information may include caller identity information. Therefore, if caller identity information is included, other dimensions of data information can be ignored first, and the caller identity information can be determined first. For example, if caller identity information is included, and the user has set target preference call settings for specific caller identity information, such as ringing strategies for parents, family members, etc. Assuming that the caller identity information corresponds to the user's target preference call settings, the target call reminder strategy corresponding to the caller identity information can be determined directly based on the target preference call settings. If the caller identity information does not correspond to a specific target preference call setting, then prediction can be performed by combining other dimensions of data information. The prediction method can refer to any of the above implementation methods, and will not be elaborated here.

[0068] To better implement the call reminder method in the embodiments of this application, the embodiments of this application also provide a call reminder device, such as... Figure 3 As shown, the device 300 includes: The acquisition module 301 is used to acquire incoming call events; The data acquisition module 302 is used to collect data information from multiple dimensions based on incoming call events; Prediction module 303 is used to predict the target call reminder strategy based on data information from various dimensions; The execution module 304 is used to execute call reminders for incoming call events according to the target call reminder policy.

[0069] The incoming call reminder device provided in this application allows the acquisition module 301 to first acquire the incoming call event, and the collection module 302 to collect multi-dimensional data information about the acquired event, obtaining data on various dimensions of the event. Then, the prediction module 303 can predict an appropriate target incoming call reminder strategy based on the data information from each dimension, and the execution module 304 will remind the user of the incoming call event according to the target strategy. This achieves the goal of reminding the user of the incoming call event in a suitable way, avoiding the need for the user to manually adjust the incoming call reminder method.

[0070] In some embodiments of this application, the prediction module 303 is specifically used for: Based on data from various dimensions, predict whether the current scene is a quiet scene; If the current scene is a quiet scene, the predicted target call reminder strategy is a silent call reminder strategy; If the current scenario is not quiet, the predicted target call reminder strategy is a non-silent call reminder strategy.

[0071] In some embodiments of this application, the data information of each dimension includes at least one of the following: current location information, terminal displacement information, environmental noise information, current date information, current time information, caller identity information, user behavior information corresponding to historical missed calls, and feedback information corresponding to user behavior information. The prediction module 303 is further specifically used for: Input at least one dimension of data, including current location information, terminal displacement information, environmental noise information, current date information, current time information, caller identity information, user behavior information corresponding to historical missed calls, and feedback information corresponding to user behavior information, into the target decision model to predict the target call reminder strategy.

[0072] In some embodiments of this application, the data information of each dimension includes at least one of the following: current location information, terminal displacement information, environmental noise information, current date information, current time information, caller identity information, user behavior information corresponding to historical missed calls, and feedback information corresponding to user behavior information. The prediction module 303 is further specifically used for: If the current location information, terminal displacement information, environmental noise information, caller identity information, user behavior information corresponding to historical missed calls, and feedback information corresponding to user behavior information are not obtained, then the current date information and current time information will be used to determine whether it is during working hours. Based on whether it is during working hours, predict target call reminder strategies.

[0073] In some embodiments of this application, the data information of each dimension includes at least one of the following: current location information, terminal displacement information, environmental noise information, current date information, current time information, caller identity information, user behavior information corresponding to historical missed calls, and feedback information corresponding to user behavior information. The prediction module 303 is further specifically used for: If terminal displacement information, environmental noise information, caller identity information, user behavior information corresponding to historical missed calls and feedback information corresponding to user behavior information, current date information and current time information are not obtained, then determine whether the user is at the work location based on the current location information. Based on whether the target is at work, predict incoming call reminder strategies.

[0074] In some embodiments of this application, the execution module 304 is further configured to optimize the target decision model, specifically including: Record different historical data for each call reminder setting manually configured by the user; The target decision-making model is optimized based on the preset period and different historical data.

[0075] In some embodiments of this application, the data information of each dimension includes caller identity information, and the prediction module 303 is specifically used for: Determine if there are any target preference caller settings enabled; If it is determined that there are target preference call settings, then the target call reminder strategy corresponding to the caller's identity information is predicted based on the target preference call settings.

[0076] This application also provides a terminal device, which includes a processor, a memory, and a computer program stored in the memory and executable on the processor. The processor executes the computer program to implement the steps of any of the call reminder methods in this application. This terminal device integrates any of the call reminder methods provided in this application, such as... Figure 4 As shown, it illustrates a structural schematic diagram of the terminal device involved in the embodiments of this application. Specifically: The terminal device may include components such as a processor 401 with one or more processing cores, a memory 402 with one or more computer-readable storage media, a power supply 403, and an input unit 404. Those skilled in the art will understand that... Figure 4 The terminal device structure shown does not constitute a limitation on the terminal device and may include more or fewer components than shown, or combine certain components, or have different component arrangements. Wherein: The processor 401 is the control center of the terminal device. It connects various parts of the terminal device via various interfaces and lines, and performs various functions and processes data by running or executing software programs and / or modules stored in the memory 402, and by calling data stored in the memory 402, thereby providing overall monitoring of the terminal device. Optionally, the processor 401 may include one or more processing cores; the processor 401 may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor. Preferably, the processor 401 may integrate an application processor and a modem processor, wherein the application processor mainly handles the operating system, user interface, and applications, and the modem processor mainly handles wireless communication. It is understood that the aforementioned modem processor may not be integrated into the processor 401.

[0077] The memory 402 can be used to store software programs and modules. The processor 401 executes various functional applications and data processing by running the software programs and modules stored in the memory 402. The memory 402 may mainly include a program storage area and a data storage area. The program storage area may store the operating system, application programs required for at least one function (such as sound playback function, image playback function, etc.), etc.; the data storage area may store data created according to the use of the terminal device, etc. In addition, the memory 402 may include high-speed random access memory, and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other volatile solid-state storage device. Accordingly, the memory 402 may also include a memory controller to provide the processor 401 with access to the memory 402.

[0078] The terminal device also includes a power supply 403 that supplies power to the various components. Preferably, the power supply 403 can be logically connected to the processor 401 through a power management system, thereby enabling functions such as charging, discharging, and power consumption management through the power management system. The power supply 403 may also include one or more DC or AC power supplies, recharging systems, power fault detection circuits, power converters or inverters, power status indicators, and other arbitrary components.

[0079] The terminal device may also include an input unit 404, which can be used to receive input digital or character information, and generate keyboard, mouse, joystick, optical or trackball signal inputs related to user settings and function control.

[0080] Although not shown, the terminal device may also include a display unit, etc., which will not be described in detail here. Specifically, in this embodiment, the processor 401 in the terminal device loads the executable files corresponding to the processes of one or more applications into the memory 402 according to the following instructions, and the processor 401 runs the applications stored in the memory 402 to realize various functions, such as: Obtain incoming call events; Collect data information from multiple dimensions based on incoming call events; Based on data from various dimensions, predict the target call reminder strategy; Based on the target call alert policy, execute call alerts for incoming call events.

[0081] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be performed by instructions, or by instructions controlling related hardware. These instructions can be stored in a computer-readable storage medium and loaded and executed by a processor.

[0082] Therefore, embodiments of this application provide a computer-readable storage medium, which may include: read-only memory (ROM), random access memory (RAM), a disk, or an optical disk, etc. A computer program is stored thereon, and the computer program is loaded by a processor to execute the steps in any of the incoming call reminder methods provided in embodiments of this application. For example, the computer program loaded by the processor can execute the following steps: Obtain incoming call events; Collect data information from multiple dimensions based on incoming call events; Based on data from various dimensions, predict the target call reminder strategy; Based on the target call alert policy, execute call alerts for incoming call events.

[0083] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the detailed descriptions of other embodiments above, which will not be repeated here.

[0084] In practice, each of the above units or structures can be implemented as an independent entity or can be arbitrarily combined to be implemented as the same or several entities. For the specific implementation of each of the above units or structures, please refer to the previous method embodiments, which will not be repeated here.

[0085] For details on the implementation of each of the above operations, please refer to the previous examples, which will not be repeated here.

[0086] The above provides a detailed description of the incoming call reminder method and device provided in the embodiments of this application. Specific examples have been used to illustrate the principles and implementation methods of this application. The description of the above embodiments is only for the purpose of helping to understand the method and core ideas of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A method for reminding incoming calls, characterized in that, The method includes: Obtain incoming call events; Based on the incoming call event, collect data information from multiple dimensions; Based on the data information of each dimension, predict the target call reminder strategy; According to the target call reminder policy, execute the call reminder for the call event.

2. The call reminder method according to claim 1, characterized in that, The step of predicting the target call reminder strategy based on the data information of each dimension includes: Based on the data information of each dimension, predict whether the current scene is a quiet scene; If the current scenario is the quiet scenario, the target call reminder strategy is predicted to be the silent call reminder strategy; If the current scenario is not a quiet scenario, the target call reminder strategy is predicted to be a non-silent call reminder strategy.

3. The call reminder method according to claim 1, characterized in that, The data information of each dimension includes at least one of the following: current location information, terminal displacement information, environmental noise information, current date information, current time information, caller identity information, user behavior information corresponding to historical missed calls, and feedback information corresponding to the user behavior information; The step of predicting the target call reminder strategy based on the data information of each dimension includes: The target decision model is input with at least one of the following dimensions: current location information, terminal displacement information, environmental noise information, current date information, current time information, caller identity information, user behavior information corresponding to historical missed calls, and feedback information corresponding to user behavior information, to predict the target call reminder strategy.

4. The call reminder method according to claim 1, characterized in that, The data information of each dimension includes at least one of the following: current location information, terminal displacement information, environmental noise information, current date information, current time information, caller identity information, user behavior information corresponding to historical missed calls, and feedback information corresponding to the user behavior information; The step of predicting the target call reminder strategy based on the data information of each dimension includes: If the current location information, terminal displacement information, environmental noise information, caller identity information, user behavior information corresponding to the historical missed calls, and feedback information corresponding to the user behavior information are not obtained, then the current date information and current time information are used to determine whether it is during working hours. Predict target call reminder strategies based on whether it is during the stated working hours.

5. The call reminder method according to claim 1, characterized in that, The data information of each dimension includes at least one of the following: current location information, terminal displacement information, environmental noise information, current date information, current time information, caller identity information, user behavior information corresponding to historical missed calls, and feedback information corresponding to the user behavior information; The step of predicting the target call reminder strategy based on the data information of each dimension includes: If the terminal displacement information, the environmental noise information, the caller identity information, the user behavior information corresponding to the historical missed calls and the feedback information corresponding to the user behavior information, the current date information and the current time information are not obtained, then the current location information is used to determine whether the user is at the work location. Predict target call reminder strategies based on whether the target is at the stated work location.

6. The call reminder method according to claim 3, characterized in that, The method further includes: optimizing the target decision model; The optimization of the target decision model includes: Record different historical data for each call reminder setting manually configured by the user; The target decision model is optimized based on the preset period and the different historical data.

7. The call reminder method according to claim 1, characterized in that, The data information for each dimension includes caller identification information; The step of predicting the target call reminder strategy based on the data information of each dimension includes: Determine if there are any target preference caller settings enabled; If it is determined that the target preference call settings are set, then the target call reminder strategy corresponding to the caller identity information is predicted based on the target preference call settings.

8. A call reminder device, characterized in that, The device includes: The acquisition module is used to acquire incoming call events; The data acquisition module is used to collect data information from multiple dimensions based on the incoming call event. The prediction module is used to predict the target call reminder strategy based on the data information of each dimension. The execution module is used to execute the incoming call reminder for the incoming call event according to the target incoming call reminder strategy.

9. A terminal device, characterized in that, The terminal device includes a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the call reminder method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that is executed by a processor to implement the steps of the call reminder method according to any one of claims 1 to 7.

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