CN111026955A - Application program recommendation method and electronic equipment - Google Patents
Application program recommendation method and electronic equipment Download PDFInfo
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- CN111026955A CN111026955A CN201911136851.8A CN201911136851A CN111026955A CN 111026955 A CN111026955 A CN 111026955A CN 201911136851 A CN201911136851 A CN 201911136851A CN 111026955 A CN111026955 A CN 111026955A
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Abstract
The embodiment of the invention provides an application program recommendation method and electronic equipment, and relates to the technical field of electronic equipment. According to the method and the device, historical operating parameters when a user performs first operation on a first application program interface displayed on a screen of the electronic equipment are obtained, target operating parameters are determined by an artificial intelligence algorithm according to the historical operating parameters, the target operating parameters are used for representing the operating habits of the user, a second application program matched with the target operating parameters is searched according to the target operating parameters, and the second application program is recommended to the user. The target operation parameters are predicted according to the historical operation parameters, the matched second application programs are searched according to the target operation parameters to be recommended to the user, the second application programs recommended to the user are searched according to the operation habits of the user, the requirements of the user are met, the operation is simple, excessive manual participation in related operations is not needed, and the second application programs required by the user can be quickly searched.
Description
Technical Field
The invention relates to the technical field of electronic equipment, in particular to an application program recommendation method and electronic equipment.
Background
With the continuous development of electronic device technologies, electronic devices such as mobile phones and tablet computers have become essential tools in life and work, and the actual requirements of users cannot be met by traditional browser access, so that various application programs are produced, most of the electronic devices of users are provided with various application programs, different application programs, especially different game application programs, and the operation habits of each user are often different.
At present, when a user wants to find a new second application program for use after using a first application program for a long time, at the moment, the user needs to randomly download and install a certain application program from a network, and when the user starts to use the downloaded application program, the user finds that the application program is used according to own operation habits, the experience effect of the application program is poor, namely the user is not smooth in using the application program, the user is most likely to uninstall the application program, and the user finds the new application program again to determine whether the application program meets the requirements.
However, the current method for finding an application is complex in operation and takes a long time, and it is difficult to quickly find a needed second application.
Disclosure of Invention
The embodiment of the invention provides an application program recommending method and electronic equipment, and aims to solve the problems that the existing method for searching an application program is complex in operation, long in time and difficult to quickly find a needed second application program.
In order to solve the technical problem, the invention is realized as follows:
in a first aspect, an embodiment of the present invention provides an application program recommendation method, which is applied to an electronic device, and the method includes:
acquiring historical operation parameters when a user performs first operation on a first application program interface displayed on a screen of the electronic equipment;
determining target operation parameters by using an artificial intelligence algorithm according to the historical operation parameters; the target operation parameters are used for representing the operation habits of the user;
searching a second application program matched with the target operation parameter according to the target operation parameter;
recommending the second application program to the user.
In a second aspect, an embodiment of the present invention further provides an electronic device, including:
the historical operating parameter acquiring module is used for acquiring historical operating parameters when a user performs first operation on a first application program interface displayed on a screen of the electronic equipment;
the target operating parameter determining module is used for determining a target operating parameter by using an artificial intelligence algorithm according to the historical operating parameter; the target operation parameters are used for representing the operation habits of the user;
the second application program searching module is used for searching a second application program matched with the target operation parameter according to the target operation parameter;
and the second application program recommending module is used for recommending the second application program to the user.
In a third aspect, an embodiment of the present invention further provides an electronic device, which includes a processor, a memory, and a computer program stored on the memory and executable on the processor, where the computer program, when executed by the processor, implements the steps of the application recommendation method described above.
In a fourth aspect, the present invention provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the steps of the application recommendation method described above.
In the embodiment of the invention, historical operation parameters when a user performs first operation on a first application program interface displayed on a screen of the electronic equipment are obtained, target operation parameters are determined by an artificial intelligence algorithm according to the historical operation parameters, the target operation parameters are used for representing the operation habits of the user, a second application program matched with the target operation parameters is searched according to the target operation parameters, and the second application program is recommended to the user. The method for searching the application program is simple in operation, does not need to participate in related operations manually, does not need to spend long time, and can quickly search the second application program needed by the user.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the description of the embodiments of the present invention will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to these drawings without inventive labor.
FIG. 1 is a flowchart illustrating an application recommendation method according to a first embodiment of the present invention;
FIG. 2 is a flowchart illustrating an application recommendation method according to a second embodiment of the present invention;
fig. 3 is a block diagram showing an electronic device according to a third embodiment of the present invention;
fig. 4 is a block diagram showing another electronic device according to a third embodiment of the present invention;
fig. 5 is a schematic diagram showing a hardware configuration of an electronic device according to a fourth embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be appreciated that reference throughout this specification to "one embodiment" or "an embodiment" means that a particular feature, structure or characteristic described in connection with the embodiment is included in at least one embodiment of the present invention. Thus, the appearances of the phrases "in one embodiment" or "in an embodiment" in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.
In various embodiments of the present invention, it should be understood that the sequence numbers of the following processes do not mean the execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.
Example one
Referring to fig. 1, a flowchart of an application recommendation method according to an embodiment of the present invention is shown, and is applied to an electronic device, where the method specifically includes the following steps:
In the embodiment of the invention, the electronic equipment is provided with a screen, icons corresponding to various installed application programs, such as icons of shopping application programs, icons of game application programs, icons of social application programs and the like, are displayed on the screen of the electronic equipment, a user can perform touch operation on the screen, click a first application program icon, open and run the first application program, and then a first application program interface is displayed on the screen; the first application program is any application program installed in the electronic device, and specifically may be a game application program installed in the electronic device.
When a user performs first operations such as clicking and sliding on a first application program interface displayed on a screen of electronic equipment, first historical parameters of the user during each first operation are collected through a sensor arranged in the electronic equipment, and the first historical parameters collected by the sensor within a preset time period are counted to obtain historical operation parameters of the user during the first operation on the first application program interface displayed on the screen of the electronic equipment.
Wherein the historical operating parameters comprise historical operating force and/or historical operating frequency.
The method comprises the steps that a sensor arranged in the electronic equipment is a pressure sensor, when a user carries out first operation on a first application program interface displayed on a screen of the electronic equipment, the pressure sensor collects first historical parameters of the user when the user carries out the first operation each time, and the first historical parameters comprise first historical strength and/or first historical frequency.
The first historical force refers to pressure data which are pressed by a user and collected by a pressure sensor when the user performs first operation on a first application program interface; the first historical frequency refers to the number of times of operation of a user in a first application program interface in a unit time period, when the pressure sensor collects one piece of pressure data, the number of times of operation is recorded, the first historical frequency can be obtained by counting the number of times of operation in the unit time, the unit time can be set manually, for example, when the unit time is 1 minute, the number of times of operation of the user is 50, and the first historical frequency is 50 times/minute.
Then, the first historical parameter collected by the sensor within the preset time period is counted to obtain the historical operating parameter, and the preset time period can be set manually, for example, the preset time period can be 1 month, 3 months, half a year, and the like.
When the first historical parameter collected by the pressure sensor is only the first historical strength, the corresponding historical operating parameter only comprises the historical operating strength; when the first historical parameter collected by the pressure sensor is only the first historical frequency, the corresponding historical operating parameter only comprises the historical operating frequency; when the first historical parameter collected by the pressure sensor comprises the first historical strength and the first historical frequency, the corresponding historical operating parameter comprises the historical operating strength and the historical operating frequency.
It should be noted that the historical operating parameters refer to data collected by the sensor within a preset time period before the current time of the user, and if the preset time period is 1 month, the historical operating parameters refer to data collected by the sensor before one month.
In the embodiment of the invention, after the historical operating parameters when the user performs the first operation on the first application program interface displayed on the screen of the electronic equipment are obtained, the target operating parameters are predicted by using an artificial intelligence algorithm according to the historical operating parameters, and the target operating parameters are used for representing the operating habits of the user. Wherein, the target operation parameter comprises a target operation strength and/or a target operation frequency.
And predicting the target operation parameters according to the historical operation parameters, namely analyzing the previous first operation of the user and predicting the operation habit of the user, wherein the operation habit of the user refers to the operation strength and/or the operation frequency adopted by the habit of the user when the user operates on a screen.
The artificial intelligence algorithm is actually a neural network model, which can be an artificial neural network model, a cyclic neural network model, a convolutional neural network model, and the like, and needs to be trained according to the sample operating parameters of a plurality of sample users and the current actual operating parameters of the sample users to obtain the neural network model.
Specifically, sample operation parameters of a plurality of sample users are obtained, the sample operation parameters are sample operation strength and/or sample operation frequency, the sample operation parameters are input into an initial neural network model, corresponding sample results are output, the sample results are used for predicting operation habits of the sample users, the sample results are compared with current actual operation parameters, parameters in the initial neural network model are corrected according to the comparison results, training is carried out according to the process until the difference value between the output sample results and the current actual operation parameters is smaller than a set threshold value, and finally the neural network model is obtained through training.
And inputting the historical operating parameters into a neural network model obtained by final training, so as to obtain target operating parameters.
When the historical operating parameters only comprise historical operating force, the corresponding target operating parameters only comprise target operating force; when the historical operating parameters only comprise the historical operating frequency, the corresponding target operating parameters only comprise the target operating frequency; when the historical operating parameters include historical operating force and historical operating frequency, the corresponding target operating parameters include target operating force and/or target operating frequency.
And 103, searching a second application program matched with the target operation parameter according to the target operation parameter.
In the embodiment of the invention, according to the predicted target operation parameter, the second application program matched with the target operation parameter is searched from the network, namely, according to the operation habit of the user, the second application program which can adapt to the operation habit of the user is searched from the network.
The second application program is the same as the first application program in type, and when the first application program is a game application program, the second application program is also the game application program; the second application and the first application are mainly directed to game applications, but other types of applications may be applied to the embodiments of the present invention.
It should be noted that, in the embodiment of the present invention, the target operation parameter is predicted by using an artificial intelligence algorithm according to the historical operation parameter, and the second application program is searched based on the target operation parameter, instead of directly searching the second application program according to the operation parameter currently acquired by the sensor, because the operation parameter currently acquired by the sensor is relatively large in contingency, for example, the user has too large operation force or too low operation frequency during operation due to some reasons, and if the second application program is searched only according to the operation parameter currently acquired by the sensor, the searched second application program is very likely to be inconsistent with the operation habit of the user.
And 104, recommending the second application program to the user.
In the embodiment of the invention, after the second application program matched with the target operation parameter is searched, the second application program is recommended to the user, an icon of the recommended second application program can be displayed on a screen of the electronic equipment so as to be downloaded and installed by the user, and a scene interface in the recommended second application program can also be displayed on the screen of the electronic equipment.
In the embodiment of the invention, the target operation parameters are predicted according to the historical operation parameters, the matched second application program is searched according to the target operation parameters to be recommended to the user, and the second application program recommended to the user is searched according to the operation habits of the user, so that the recommended second application program meets the requirements of the user.
Example two
Referring to fig. 2, a flowchart of an application program recommendation method according to a second embodiment of the present invention is shown, which may specifically include the following steps:
In the embodiment of the invention, when a user opens a first application program, a first application program interface is displayed on a screen, and a first operation of the user on the first application program interface displayed on the screen of the electronic equipment is received.
In the embodiment of the invention, after receiving a first operation of a user on a first application program interface displayed on a screen of an electronic device, in response to the first operation, namely a processor in the electronic device generates an execution instruction in response to the first operation and sends the execution instruction to a first application program, the first application program receives the execution instruction in response to the first operation and then executes a corresponding operation according to the execution instruction.
For example, for a certain game application program, the first operation is a click operation on a skill release button of a game interface, the processor generates an execution instruction according to the first operation and sends the execution instruction to the game application program, the game application program receives the execution instruction sent by the processor, then releases a corresponding skill according to the execution instruction, and displays a skill effect animation on a screen.
At this time, the first history parameters corresponding to the first operation need to be acquired at the same time. Specifically, the pressure sensor acquires a first historical parameter when a user performs a first operation each time, and then acquires the first historical parameter acquired by the pressure sensor; the first historical parameter includes a first historical strength and/or a first historical frequency.
In the embodiment of the invention, first historical parameters collected by a sensor within a preset time length are counted to obtain historical operation parameters when a user performs first operation on a first application program interface displayed on a screen of electronic equipment, wherein the historical operation parameters comprise historical operation strength and/or historical operation frequency.
Optionally, before step 203, the method further includes: and filtering out second historical parameters which do not meet preset conditions in the first historical parameters.
After a first history parameter corresponding to a first operation is obtained, the first history parameter is compared with a preset condition, a second history parameter which does not meet the preset condition in the first history parameter is filtered, the rest first history parameters which meet the preset condition are reserved, and the reserved first history parameters are counted subsequently to obtain a history operation parameter.
When a user uses the electronic device, due to some abnormal operation behaviors, such as screen bumping, etc., the first historical parameters acquired by the sensor are too large or too small, and if the first historical parameters corresponding to the abnormal operation behaviors are counted, target operation parameters predicted according to the historical operation parameters are inaccurate.
It should be noted that the preset condition may be set manually, the preset condition is actually a preset range, when the first history parameter is within the preset range, the preset condition is met, and when the first history parameter is outside the preset range, the preset condition is not met; the preset range comprises a preset force range and/or a preset frequency range.
For example, the preset frequency range is 10 times/minute to 100 times/minute, and when the user does not perform the first operation on the first application program interface for some reason, at this time, the first historical frequency acquired by the pressure sensor is 0, which is outside the preset frequency range, does not satisfy the preset condition, and needs to be filtered.
This step is similar to the principle of step 101 in the first embodiment, and is not described herein again.
This step is similar to the step 102 in the first embodiment, and is not described herein again.
And step 206, comparing the target operating parameters with the operating parameter ranges corresponding to each application program respectively.
In the embodiment of the invention, the predicted target operation parameters are respectively compared with the operation parameter range corresponding to each application program on the network; wherein, each application program is provided with a corresponding operating parameter range according to historical use data of a plurality of users.
For each application program, counting historical use data of a plurality of users in advance, wherein the historical use data refers to historical use operation force and/or historical use operation frequency of the users on a screen when the application program is used, calculating an average value of the historical use data of the users, adding a first set parameter to the average value to obtain an upper limit value of an operation parameter range, and subtracting a second set parameter from the average value to obtain a lower limit value of the operation parameter range so as to obtain an operation parameter range corresponding to the application program; the first setting parameter and the second setting parameter may be the same or different, and the first setting parameter and the second setting parameter may be set artificially.
When the target operation parameter only comprises the target operation strength, the operation parameter range is an operation strength range which is set according to the historical use operation strengths of a plurality of users, and the target operation strength is compared with the operation strength range; when the target operating parameter includes only the target operating frequency, the operating parameter range is an operating frequency range, which is set according to the historical use operating frequencies of the plurality of users, and the target operating frequency is compared with the operating frequency range; when the target operation parameter includes the target operation force and the target operation frequency, the operation parameter range includes an operation force range and an operation frequency range, the target operation force is compared with the operation force range, and the target operation frequency is compared with the operation frequency range.
In the embodiment of the present invention, the application program corresponding to the operating parameter range containing the target operating parameter is determined as the second application program matching the target operating parameter, that is, if the target operating parameter is within the operating parameter range of an application program, the application program is the second application program.
For example, the application programs include an application program a, an application program B and an application program C, the operating parameter range of the application program a is a 1-a 2, the operating parameter range of the application program B is B1-B2, the operating parameter range of the application program C is C1-C2, the target operating parameter is M, the target operating parameter M is located in the operating parameter range a 1-a 2, the target operating parameter M is located in the operating parameter range B1-B2, and the target operating parameter M is located outside the operating parameter range C1-C2, and then the application program a and the application program B are determined to be the second application program.
It should be noted that, if a scene interface in the second application is finally recommended, a corresponding operating parameter range needs to be set for each scene interface in each application, and the target operating parameter is compared with the operating parameter range corresponding to each scene interface in each application.
In the embodiment of the invention, when the number of the searched second applications is N, the download amount of each second application is obtained, and the second applications are sorted from high to low according to the download amount of each second application.
And 209, sequentially displaying icons corresponding to each second application program on the screen of the electronic equipment according to the sequencing result so as to recommend the second application programs to the user.
In the embodiment of the invention, after the second applications are sorted from high to low according to the downloading amount of each second application, the icons corresponding to the second applications are sequentially displayed on the screen of the electronic equipment according to the sorting result, so that the second applications are recommended to the user.
For example, the second application includes application a and application B, the download amount of application a is 20 ten thousand, and the download amount of application B is 1 ten thousand, and then application a and application B are displayed on the screen of the electronic device in order from top to bottom.
And displaying the icon corresponding to each second application program on the screen in sequence according to the downloading amount of the second application programs, so that the user can observe the second application programs with high downloading amount first, and the purpose of recommending the more popular second application programs to the user is achieved.
In the embodiment of the invention, the first historical parameters of the first operation of the user are acquired, the first historical parameters in the preset time length are counted to obtain the historical operation parameters, the target operation parameters are predicted according to the historical operation parameters, the matched second application programs are searched according to the target operation parameters, the second application programs are sorted from high to low according to the downloading amount of each second application program, the icons corresponding to the second application programs are displayed on a screen in sequence to be recommended to the user, the second application programs recommended to the user are searched according to the operation habits of the user, so that the recommended second application programs meet the requirements of the user, the method for searching the application programs is simple in operation, the second application programs required by the user can be searched quickly without excessive participation of related operations and spending of long time; and the icons corresponding to the second application programs are sequentially displayed on the screen according to the downloading amount of the second application programs, so that the user can observe the second application programs with high downloading amount first and recommend the more popular second application programs to the user.
With the above description of the application program recommendation method according to the embodiment of the present invention, an electronic device according to the embodiment of the present invention will be described with reference to the accompanying drawings.
EXAMPLE III
Referring to fig. 3, a block diagram of an electronic device according to a third embodiment of the present invention is shown.
The electronic device 300 includes:
a historical operation parameter obtaining module 301, configured to obtain a historical operation parameter when a user performs a first operation on a first application program interface displayed on a screen of the electronic device;
a target operation parameter determining module 302, configured to determine a target operation parameter according to the historical operation parameter by using an artificial intelligence algorithm; the target operation parameters are used for representing the operation habits of the user;
a second application search module 303, configured to search, according to the target operation parameter, a second application that matches the target operation parameter;
a second application recommendation module 304, configured to recommend the second application to the user.
Referring to fig. 4, a block diagram of another electronic device according to a third embodiment of the present invention is shown.
On the basis of fig. 3, optionally, the historical operating parameters include historical operating strength and/or historical operating frequency, and the target operating parameters include target operating strength and/or target operating frequency.
Optionally, the electronic device 300 further includes:
a first operation receiving module 305, configured to receive a first operation of a user on a first application program interface displayed on a screen of the electronic device;
a first history parameter obtaining module 306, configured to respond to the first operation and obtain a first history parameter corresponding to the first operation;
a historical operating parameter counting module 307, configured to count the first historical parameter within a preset time duration, to obtain the historical operating parameter.
Optionally, the electronic device 300 further includes:
and the second history parameter filtering module is used for filtering the second history parameters which do not meet the preset conditions in the first history parameters.
Optionally, the second application search module 303 includes:
an operating parameter comparison submodule 3031, configured to compare the target operating parameter with an operating parameter range corresponding to each application program respectively;
a second application program determining submodule 3032, configured to determine, as a second application program that is matched with the target operation parameter, an application program corresponding to the operation parameter range that includes the target operation parameter;
wherein, each application program is provided with a corresponding operating parameter range according to historical use data of a plurality of users.
Optionally, the second application recommendation module 304 includes:
a download amount sorting submodule 3041, configured to, when the number of the searched second applications is N, sort the second applications according to the download amount of each second application from high to low; n is a positive integer greater than 1;
the application icon display sub-module 3042 is configured to display, according to the sorting result, an icon corresponding to each second application program on the screen of the electronic device in sequence, so as to recommend the second application program to the user.
The electronic device 300 provided in the embodiment of the present invention can implement each process implemented by the electronic device in the method embodiments of fig. 1 to fig. 2, and is not described here again to avoid repetition.
In the embodiment of the invention, the target operation parameters are predicted according to the historical operation parameters, the matched second application program is searched according to the target operation parameters to be recommended to the user, and the second application program recommended to the user is searched according to the operation habits of the user, so that the recommended second application program meets the requirements of the user.
Example four
Referring to fig. 5, a hardware structure diagram of an electronic device according to a fourth embodiment of the present invention is shown.
The electronic device 500 includes, but is not limited to: a radio frequency unit 501, a network module 502, an audio output unit 503, an input unit 504, a sensor 505, a display unit 506, a user input unit 507, an interface unit 508, a memory 509, a processor 510, and a power supply 511. Those skilled in the art will appreciate that the electronic device configuration shown in fig. 5 does not constitute a limitation of the electronic device, and that the electronic device may include more or fewer components than shown, or some components may be combined, or a different arrangement of components. In the embodiment of the present invention, the electronic device includes, but is not limited to, a mobile phone, a tablet computer, a notebook computer, a palm computer, a vehicle-mounted terminal, a wearable device, a pedometer, and the like.
The processor 510 is configured to obtain a historical operation parameter when a user performs a first operation on a first application program interface displayed on a screen of the electronic device; determining target operation parameters by using an artificial intelligence algorithm according to the historical operation parameters; the target operation parameters are used for representing the operation habits of the user; searching a second application program matched with the target operation parameter according to the target operation parameter; recommending the second application program to the user.
In the embodiment of the invention, the target operation parameters are predicted according to the historical operation parameters, the matched second application program is searched according to the target operation parameters to be recommended to the user, and the second application program recommended to the user is searched according to the operation habits of the user, so that the recommended second application program meets the requirements of the user.
It should be understood that, in the embodiment of the present invention, the radio frequency unit 501 may be used for receiving and sending signals during a message sending and receiving process or a call process, and specifically, receives downlink data from a base station and then processes the received downlink data to the processor 510; in addition, the uplink data is transmitted to the base station. In general, radio frequency unit 501 includes, but is not limited to, an antenna, at least one amplifier, a transceiver, a coupler, a low noise amplifier, a duplexer, and the like. In addition, the radio frequency unit 501 can also communicate with a network and other devices through a wireless communication system.
The electronic device provides wireless broadband internet access to the user via the network module 502, such as assisting the user in sending and receiving e-mails, browsing web pages, and accessing streaming media.
The audio output unit 503 may convert audio data received by the radio frequency unit 501 or the network module 502 or stored in the memory 509 into an audio signal and output as sound. Also, the audio output unit 503 may also provide audio output related to a specific function performed by the electronic apparatus 500 (e.g., a call signal reception sound, a message reception sound, etc.). The audio output unit 503 includes a speaker, a buzzer, a receiver, and the like.
The input unit 504 is used to receive an audio or video signal. The input Unit 504 may include a Graphics Processing Unit (GPU) 5041 and a microphone 5042, and the Graphics processor 5041 processes image data of a still picture or video obtained by an image capturing device (e.g., a camera) in a video capturing mode or an image capturing mode. The processed image frames may be displayed on the display unit 506. The image frames processed by the graphic processor 5041 may be stored in the memory 509 (or other storage medium) or transmitted via the radio frequency unit 501 or the network module 502. The microphone 5042 may receive sounds and may be capable of processing such sounds into audio data. The processed audio data may be converted into a format output transmittable to a mobile communication base station via the radio frequency unit 501 in case of the phone call mode.
The electronic device 500 also includes at least one sensor 505, such as light sensors, motion sensors, and other sensors. Specifically, the light sensor includes an ambient light sensor that can adjust the brightness of the display panel 5061 according to the brightness of ambient light, and a proximity sensor that can turn off the display panel 5061 and/or a backlight when the electronic device 500 is moved to the ear. As one type of motion sensor, an accelerometer sensor can detect the magnitude of acceleration in each direction (generally three axes), detect the magnitude and direction of gravity when stationary, and can be used to identify the posture of an electronic device (such as horizontal and vertical screen switching, related games, magnetometer posture calibration), and vibration identification related functions (such as pedometer, tapping); the sensors 505 may also include fingerprint sensors, pressure sensors, iris sensors, molecular sensors, gyroscopes, barometers, hygrometers, thermometers, infrared sensors, etc., which are not described in detail herein.
The display unit 506 is used to display information input by the user or information provided to the user. The Display unit 506 may include a Display panel 5061, and the Display panel 5061 may be configured in the form of a Liquid Crystal Display (LCD), an Organic Light-Emitting Diode (OLED), or the like.
The user input unit 507 may be used to receive input numeric or character information and generate key signal inputs related to user settings and function control of the electronic device. Specifically, the user input unit 507 includes a touch panel 5071 and other input devices 5072. Touch panel 5071, also referred to as a touch screen, may collect touch operations by a user on or near it (e.g., operations by a user on or near touch panel 5071 using a finger, stylus, or any suitable object or attachment). The touch panel 5071 may include two parts of a touch detection device and a touch controller. The touch detection device detects the touch direction of a user, detects a signal brought by touch operation and transmits the signal to the touch controller; the touch controller receives touch information from the touch sensing device, converts the touch information into touch point coordinates, sends the touch point coordinates to the processor 510, and receives and executes commands sent by the processor 510. In addition, the touch panel 5071 may be implemented in various types such as a resistive type, a capacitive type, an infrared ray, and a surface acoustic wave. In addition to the touch panel 5071, the user input unit 507 may include other input devices 5072. In particular, other input devices 5072 may include, but are not limited to, a physical keyboard, function keys (e.g., volume control keys, switch keys, etc.), a trackball, a mouse, and a joystick, which are not described in detail herein.
Further, the touch panel 5071 may be overlaid on the display panel 5061, and when the touch panel 5071 detects a touch operation thereon or nearby, the touch operation is transmitted to the processor 510 to determine the type of the touch event, and then the processor 510 provides a corresponding visual output on the display panel 5061 according to the type of the touch event. Although in fig. 5, the touch panel 5071 and the display panel 5061 are two independent components to implement the input and output functions of the electronic device, in some embodiments, the touch panel 5071 and the display panel 5061 may be integrated to implement the input and output functions of the electronic device, and is not limited herein.
The interface unit 508 is an interface for connecting an external device to the electronic apparatus 500. For example, the external device may include a wired or wireless headset port, an external power supply (or battery charger) port, a wired or wireless data port, a memory card port, a port for connecting a device having an identification module, an audio input/output (I/O) port, a video I/O port, an earphone port, and the like. The interface unit 508 may be used to receive input (e.g., data information, power, etc.) from external devices and transmit the received input to one or more elements within the electronic apparatus 500 or may be used to transmit data between the electronic apparatus 500 and external devices.
The memory 509 may be used to store software programs as well as various data. The memory 509 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required by at least one function (such as a sound playing function, an image playing function, etc.), and the like; the storage data area may store data (such as audio data, a phonebook, etc.) created according to the use of the cellular phone, and the like. Further, the memory 509 may include high-speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid-state storage device.
The processor 510 is a control center of the electronic device, connects various parts of the whole electronic device by using various interfaces and lines, performs various functions of the electronic device and processes data by running or executing software programs and/or modules stored in the memory 509 and calling data stored in the memory 509, thereby performing overall monitoring of the electronic device. Processor 510 may include one or more processing units; preferably, the processor 510 may integrate an application processor, which mainly handles operating systems, user interfaces, application programs, etc., and a modem processor, which mainly handles wireless communications. It will be appreciated that the modem processor described above may not be integrated into processor 510.
The electronic device 500 may further include a power supply 511 (e.g., a battery) for supplying power to various components, and preferably, the power supply 511 may be logically connected to the processor 510 via a power management system, so as to implement functions of managing charging, discharging, and power consumption via the power management system.
In addition, the electronic device 500 includes some functional modules that are not shown, and are not described in detail herein.
Preferably, an embodiment of the present invention further provides an electronic device, which includes a processor 510, a memory 509, and a computer program that is stored in the memory 509 and can be run on the processor 510, and when the computer program is executed by the processor 510, the processes of the foregoing application program recommendation method embodiment are implemented, and the same technical effect can be achieved, and in order to avoid repetition, details are not described here again.
The embodiment of the present invention further provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the computer program implements each process of the above-mentioned application program recommendation method embodiment, and can achieve the same technical effect, and in order to avoid repetition, details are not repeated here. The computer-readable storage medium may be a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which is stored in a storage medium (such as ROM/RAM, magnetic disk, optical disk) and includes instructions for enabling a terminal (such as a mobile phone, a computer, a server, an air conditioner, or a network device) to execute the method according to the embodiments of the present invention.
While the present invention has been described with reference to the embodiments shown in the drawings, the present invention is not limited to the embodiments, which are illustrative and not restrictive, and it will be apparent to those skilled in the art that various changes and modifications can be made therein without departing from the spirit and scope of the invention as defined in the appended claims.
Claims (13)
1. An application program recommendation method applied to an electronic device is characterized by comprising the following steps:
acquiring historical operation parameters when a user performs first operation on a first application program interface displayed on a screen of the electronic equipment;
determining target operation parameters by using an artificial intelligence algorithm according to the historical operation parameters; the target operation parameters are used for representing the operation habits of the user;
searching a second application program matched with the target operation parameter according to the target operation parameter;
recommending the second application program to the user.
2. The method of claim 1, wherein the historical operating parameters comprise historical operating effort and/or historical operating frequency, and the target operating parameters comprise target operating effort and/or target operating frequency.
3. The method according to claim 1, further comprising, before the step of obtaining the historical operating parameters when the user performs the first operation on the first application program interface displayed on the screen of the electronic device, the step of:
receiving a first operation of a user on a first application program interface displayed on a screen of the electronic equipment;
responding to the first operation, and acquiring a first history parameter corresponding to the first operation;
and counting the first historical parameters within a preset time length to obtain the historical operating parameters.
4. The method according to claim 3, wherein before the step of counting the first historical parameter within a preset time period to obtain the historical operating parameter, the method comprises:
and filtering out second historical parameters which do not meet preset conditions in the first historical parameters.
5. The method of claim 1, wherein the step of searching for a second application matching the target operating parameter based on the target operating parameter comprises:
comparing the target operating parameters with the operating parameter range corresponding to each application program respectively;
determining the application program corresponding to the operating parameter range containing the target operating parameter as a second application program matched with the target operating parameter;
wherein, each application program is provided with a corresponding operating parameter range according to historical use data of a plurality of users.
6. The method of claim 1, wherein the step of recommending the second application to the user comprises:
when the number of the searched second application programs is N, sorting the second application programs according to the downloading amount of each second application program from high to low; n is a positive integer greater than 1;
and according to the sequencing result, sequentially displaying icons corresponding to each second application program on a screen of the electronic equipment so as to recommend the second application programs to the user.
7. An electronic device, comprising:
the historical operating parameter acquiring module is used for acquiring historical operating parameters when a user performs first operation on a first application program interface displayed on a screen of the electronic equipment;
the target operating parameter determining module is used for determining a target operating parameter by using an artificial intelligence algorithm according to the historical operating parameter; the target operation parameters are used for representing the operation habits of the user;
the second application program searching module is used for searching a second application program matched with the target operation parameter according to the target operation parameter;
and the second application program recommending module is used for recommending the second application program to the user.
8. The electronic device of claim 7, wherein the historical operating parameters comprise historical operating effort and/or historical operating frequency, and wherein the target operating parameters comprise target operating effort and/or target operating frequency.
9. The electronic device of claim 7, further comprising:
the first operation receiving module is used for receiving first operation of a user for a first application program interface displayed on a screen of the electronic equipment;
the first history parameter acquisition module is used for responding to the first operation and acquiring a first history parameter corresponding to the first operation;
and the historical operating parameter counting module is used for counting the first historical parameter within a preset time length to obtain the historical operating parameter.
10. The electronic device of claim 9, further comprising:
and the second history parameter filtering module is used for filtering the second history parameters which do not meet the preset conditions in the first history parameters.
11. The electronic device of claim 7, wherein the second application search module comprises:
the operation parameter comparison submodule is used for comparing the target operation parameters with the operation parameter ranges corresponding to the application programs respectively;
the second application program determining submodule is used for determining the application program corresponding to the operating parameter range containing the target operating parameter as a second application program matched with the target operating parameter;
wherein, each application program is provided with a corresponding operating parameter range according to historical use data of a plurality of users.
12. The electronic device of claim 7, wherein the second application recommendation module comprises:
the download quantity sorting submodule is used for sorting the searched second application programs according to the download quantity of each second application program from high to low when the number of the searched second application programs is N; n is a positive integer greater than 1;
and the application program icon display sub-module is used for sequentially displaying the icon corresponding to each second application program on the screen of the electronic equipment according to the sequencing result so as to recommend the second application program to the user.
13. An electronic device comprising a processor, a memory and a computer program stored on the memory and executable on the processor, the computer program, when executed by the processor, implementing the steps of the application recommendation method of any one of claims 1 to 6.
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| CN201911136851.8A CN111026955A (en) | 2019-11-19 | 2019-11-19 | Application program recommendation method and electronic equipment |
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| CN201911136851.8A CN111026955A (en) | 2019-11-19 | 2019-11-19 | Application program recommendation method and electronic equipment |
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