WO2015127870A1

WO2015127870A1 - Method and apparatus for recommending application

Info

Publication number: WO2015127870A1
Application number: PCT/CN2015/073017
Authority: WO
Inventors: Xiaodan LIN
Original assignee: Tencent Technology (Shenzhen) Company Limited
Priority date: 2014-02-25
Filing date: 2015-02-13
Publication date: 2015-09-03
Also published as: CN104866505B; CN104866505A

Abstract

It relates to the field of Internet technologies and provides a method and an apparatus for recommending an application. The method includes: detecting first applications already installed in a system; determining second applications that match the detected first applications; and loading a display page and loading the determined second applications in the display page. Applications a user may prefer or need are predicted in the background according to applications that are already installed in the system, and the predicted applications are loaded in a corresponding display page, so that the user no longer needs to spend a long time searching for required applications on a network, which greatly improves convenience of access to the applications.

Description

METHOD AND APPARATUS FOR RECOMMENDING APPLICATION

FIELD OF THE TECHNOLOGY

The present disclosure relates to the field of Internet technologies, and in particular, to a method and an apparatus for recommending an application.

BACKGROUND OF THE DISCLOSURE

A web application (WebApp) refers to an application that runs on a network and a standard browser, and is developed on the basis of webpage technologies for implementing specific functions, for example, a webpage that helps a house purchaser to calculate mortgage loan details, or a large and complex Web site that provides full travel services for a vacationer. Because the web applications have advantages such as a low developing cost and good compatibility, and can be used directly with no need to install, the web applications are favored by more and more users.

With rising enthusiasm for developing web applications, a great number of web applications have been developed and uploaded, and wait for access from the users through the browser. However, a problem arises accordingly, that is, categories of web applications are diversified, and the number of web applications is large. A user often needs to spend a long time searching in the browser before the user can find a web application he or she really likes or needs, thereby affecting convenience of access to the web application.

SUMMARY

Embodiments of the present invention provide a method for recommending an application, so as to solve a problem that it is inconvenient to access an application currently.

The embodiments of the present invention are implemented in this way: a method for recommending an application, including:

detecting first applications already installed in a system;

determining second applications that match the detected first applications; and

loading a display page and loading the determined second applications in the display page.

Embodiments of the present invention also provide an apparatus for recommending an application, including:

a detection unit, configured to detect first applications already installed in a system;

a determining unit, configured to determine second applications that match the detected first applications; and

a display unit, configured to load a display page and load the determined second applications in the display page.

In the embodiments of the present invention, applications that a user may prefer or need are predicted in the background according to applications that are already installed in the system, and the predicted applications are loaded in a corresponding display page, so that the user no longer needs to spend a long time searching for required applications on the network, which greatly improves convenience of access to the applications.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is an implementation flowchart of a method for recommending an application according to an embodiment of the present invention;

FIG. 2 is a specific implementation flowchart of S101 of a method for recommending an application according to an embodiment of the present invention;

FIG. 3 is an implementation flowchart of a method for recommending an application according to another embodiment of the present invention;

FIG. 4 is a specific implementation flowchart of S102 of a method for recommending an application according to an embodiment of the present invention;

FIG. 5 is a structural block diagram of an apparatus for recommending an application according to an embodiment of the present invention; and

FIG. 6 is a block diagram of the structure of a part of a mobile phone related to a terminal according to an embodiment of the present invention.

DESCRIPTION OF EMBODIMENTS

To make the technical solutions and advantages of the present disclosure clearer, the following further describes the present disclosure in detail with reference to the accompanying drawings and the embodiments of the present invention. It should be understood that the specific embodiments described herein are only used to explain the present disclosure, not used to limit the present disclosure.

In the embodiments of the present invention, applications that a user may prefer or need are predicted in the background according to applications that are already installed in the system, and the predicted applications are loaded in a corresponding display page, so that the user no longer needs to spend a long time searching for required applications on a network, which greatly improves convenience of access to the applications.

In the following embodiments, in order to facilitate description, recommendation for a web application is used as an example to describe the method and the apparatus for recommending an application according to the embodiments of the present invention in detail. It is easily thought of that the same principle can also be applied in a method for recommending an application of other categories, which is not further described in the subsequent embodiments.

In the embodiments of the present invention, when a predicted application is the web application, the embodiments may be executed by a browser used for running the web application, and users all access the web application through the browser. Further, when the web application is a mobile terminal web application, the embodiments are executed by a browser that runs on the mobile terminal such as a mobile phone and a tablet.

FIG. 1 shows an implementation process of a method for recommending an application according to an embodiment of the present invention. Detailed description is as follows:

S101: Detect first applications already installed in a system.

The applications already installed in the system, on one hand, can reflect the preference of a user, for example, an application related to a travel plan or guide can reflect that the user has an interest in travel; on the other hand, the applications can reflect actual needs of the user, for example, an application related to image optimizing can reflect that the user has a need for an image processing application. Therefore, on the basis of the applications already installed in the system that direct to the preference or needs of the user, in S101, the applications already installed in the system are detected first and is used as data basis for subsequent prediction in the background for a web application that a user may prefer or need.

As an embodiment of the present invention, the applications already installed in the system may be detected by directly querying for the applications already installed in the system and relevant information thereof by calling an application programming interface (API) provided by the system. For example, an Android system provides a PackageManager function, where the function can query for the applications already installed in the system, and meanwhile can return the relevant information about the applications already installed in the system, including a name, an icon, a cache size, and a data size of the application. Therefore, the relevant function returns a corresponding query result by calling the API provided by the system, and the query result includes the applications already installed in the system and the relevant information thereof.

As another embodiment of the present invention, the applications already installed in the system and the relevant information thereof can be queried for by using a software management program in the system. As shown in FIG. 2, S101 specifically is:

S201: Access the software management program in the system.

The software management program may be security software installed in the system, which provides services such as downloading, managing, uninstalling, and information query for software, and may be a third-party application downloading client installed in the system, which provides a resource list of the application, and meanwhile supports services such as managing, uninstalling and information querying for an application downloaded and installed through the client. The software management program has a function of scanning the applications already installed in the system, and can return the query result related to application software installed in the system to a querying party.

In this embodiment, the software management program may also be accessed by using an API provided by the software management program, thereby implementing data interaction with the software management program.

S202: Query, in the software management program, for the first applications already installed in the system.

After the data interaction with the software management program is implemented by using a corresponding API, a data query request is initiated to the software management program, so that the software management program returns the corresponding query result, thereby determining the applications already installed in the system and the relevant information thereof.

Because some applications installed in the system are preinstalled in the system, or are preinstalled by manufacturers before delivery, these applications cannot reflect real preference or needs of the user. Further, as an embodiment of the present invention, as shown in FIG. 3, after S101 and before S102, the method further includes:

S104: Perform filtering on the detected first applications to remove the first applications that are preinstalled in the system.

That is, after the applications installed in the system are detected, filtering is performed on the applications to remove the applications that are preinstalled in the system. Distinguishing the applications that are preinstalled in the system and applications installed by the user can be implemented by detecting downloading or installing time of the applications. For example, if the downloading or installing time of an application is after delivery time of a device, or is after update time of a current system, the application is obviously an application installed by the user. In the determining process, the delivery time of the device and the update time of the current system can be acquired by reading a configuration file of the system, and the downloading or installing time of the application can be acquired by querying a log file of the software management program.

In the subsequent processing, the filtered applications are used as analysis basis to predict the web application that a user may prefer or need, which can improve accuracy of prediction, enabling the finally displayed web application to better satisfy actual needs of the user.

S102: Determine the second applications that match the detected first applications.

As regards the applications installed in the system detected in S101, it is needed to determine web applications that match the applications, where the "matching" refers to that the determined web applications and the applications belong to a same category in aspects such as an application category and field. For example, a web application used for querying for lyrics matches a music player in terms of the interest field, and for another example, a web application used for posting mircoblogs matches a network community application in terms of the application category.

In this embodiment, by performing, in the background, web application searching in relevant application categories or field categories, matching web applications can be found for each of the detected applications. Further, in order to improve matching precision of the web application, as an embodiment of the present invention, as shown in FIG. 4, S102 specifically is:

S401: Classify the detected first applications.

In this embodiment, the detected applications can be classified in terms of the application category or the field according to a classifying result or according to classifying categories preset in the background. Because for most applications, the third-party application downloading client performs classifying processing on them when they are downloaded from the third-party application downloading client, a category of the applications can be determined by tracing downloading sources of the applications, or reading downloading information carried in installation and configuration files of the applications.

As an implementation example of the present disclosure, the detected applications can be classified according to categories such as entertainment, tools, social, music, efficiency, life, reference, travel, sports, navigation, news, finance, photography, food, and transportation.

S402: Determine a user use index of each category according to the classifying result, where the user use index is for indicating use preference of the user for applications in the category.

In this embodiment, the applications in each category are further parsed according to the classifying result in S401, thereby determining a user use index of each category. The user use index can indicate a use preference degree of the user for the applications in the category.

In this embodiment, the user use index is determined according to at least one of the following:

the number of the first applications in each category and a sum of durations of all the first applications in each category since installation.

When the user use index is represented by the number of the applications in each category, specifically, the number of the detected applications belonging to each category needs to be counted according to the classifying result, and the obtained number of the applications in each category is used as the user use index of the category. Obviously, the category having the most applications has the highest user use index. Because the user usually tends to choose to download and install an application that the user is interested in or has actual use needs, using the obtained number of the applications in each category as the user use index of the category can reflect the use preference degree of the user for the applications in the category to some degree.

When the user use index is represented by a sum of the durations of all the applications in each category since installation, the calculation process is as follows: the duration of each application already installed in the system is separately determined by reading a configuration file of the application or querying for the installing time of the application in the software management program, and then a sum of the durations of all the applications in each category since installation is calculated, and the sum of the obtained durations in each category since installation is used as the user use index of the category. Obviously, the category having the highest sum of the durations has the highest user use index. The user usually uses an application that the user is interested in or has actual use needs for a long period of time, and usually chooses to uninstall an application that the user is not interested in or does not have actual use needs after trying the application for a period of time. Therefore, using the sum of the obtained durations in each category since installation as the user use index of the category can reflect the use preference degree of the user for the applications in the category to some degree.

It can be easily thought of that in a case that running time of an application can be traced, a sum of running time of all applications in each category can also be used as the user use index of the category, which can also reflect the use preference degree of the user for the applications in the category to some degree. For example, for instant messaging software, total online time during which users log in to the instant messaging software on the current device can be acquired, and the total online time is used as running time of the instant messaging software.

Meanwhile, in order to further improve a matching degree between the determined web application and the use preference of the user, the user use index can be determined according to the number of applications in each category and the sum of the durations of all the applications in each category since installation at the same time. For example, the categories may be sorted according to the number of applications and according to the sum of the durations since installation, to generate a first sequence corresponding to the number of applications and a second sequence corresponding to the sum of the durations respectively, summation or weighted summation is performed on ranks of each category in the two sequences to obtain a final rank of each category, and the sorting result is used as the user use index of the category.

S403: Acquire applications that have not been installed in the system, and determine, in applications that have not been installed in the system, applications belonging to the categories that correspond to the first N highest user use indexes as the second applications, where N is an integer greater than 0.

Specifically, a list of applications that can be downloaded or accessed can be acquired from an application downloading source provided by the server. The first applications already installed in the system are excluded, so as to acquire the applications that have not been installed in the system. Finally, the web applications belonging to categories that correspond to first N (for example, the first three) highest user use indexes are determined as web applications that finally need to be displayed to the user.

S103: Load a display page and load the determined second applications in the display page.

Finally, after a relevant matching process is completed, the found web applications can be displayed in relevant pages of the browser. Specifically, each time the display page is loaded, the found web applications in a specific category can be selected and displayed, or the found web applications in multiple categories can be displayed in the same display page at the same time.

The method for recommending an application described in the above embodiments enables the browser to predict the use preference of the user in the background. Thereby, when a recommending page is loaded, applications meeting the use preference of the user are automatically pushed to the user. On one hand, the user no longer needs to spend a long time searching for applications meeting the need on a network, which greatly improves convenience of access to the web applications; on the other hand, because time for accessing the applications is shortened, the user can find an application that the user actually needs without repeatedly searching on the network, which also saves network traffic cost to some degree.

FIG. 5 shows a structural block diagram of an apparatus for recommending an application according to an embodiment of the present invention. The apparatus is configured to run the method for recommending an application according to the embodiments of FIG. 1 to FIG. 4 of the present invention. In order to facilitate description, only parts related to this embodiment are shown.

Referring to FIG. 5, the apparatus includes:

a detection unit 51, configured to detect first applications already installed in a system;

a determining unit 52, configured to determine second applications that match the detected first application; and

a display unit 53, configured to load a display page and load the determined second applications in the display page.

Optionally, the detection unit 51 is specifically configured to:

query for the first applications already installed in the system by using an API provided by the system.

Optionally, the detection unit 51 includes:

an accessing subunit, configured to access a software management program in the system; and

a query subunit, configured to, query for the first applications already installed in the system in the software management program.

Optionally, the apparatus further includes:

a filtering unit, configured to perform filtering on the detected first applications to remove the first applications that are preinstalled in the system.

Optionally, the determining unit 52 includes:

a classifying subunit, configured to classify the detected first applications;

a first determining subunit, configured to determine a user use index of each category according to a classifying result, where the user use index is used for indicating use preference of a user for applications in the category; and

a second determining subunit, configured to acquire applications that have not been installed in the system, and determine, in the applications that have not been installed in the system, applications in the categories that correspond to the first N highest user use indexes as the second applications, where N is an integer greater than 0.

Optionally, the user use indexes are determined according to at least one of the following:

FIG. 6 is a block diagram of the structure of a part of a mobile phone related to a terminal according to an embodiment of the present invention. Referring to FIG. 6, the mobile phone includes components such as a radio frequency (RF) circuit 610, a memory 620, an input unit 630, a display unit 640, a sensor 650, an audio circuit 660, a wireless module 670, a processor 680, and a power supply 690. A person skilled in the art may understand that the structure of the mobile phone shown in FIG. 6 does not constitute a limitation to the mobile phone, and the mobile phone may include more components or fewer components than those shown in the figure, or some components may be combined, or a different component deployment may be used.

The following specifically describes the components of the mobile phone with reference to FIG. 6.

The RF circuit 610 may be configured to receive and send signals during an information receiving and sending process or a call process. Particularly, the RF circuit 610 receives downlink information from a base station, then delivers the downlink information to the processor 680 for processing, and sends related uplink data to the base station. Generally, the RF circuit includes, but is not limited to, an antenna, at least one amplifier, a transceiver, a coupler, a low noise amplifier (LNA), and a duplexer. In addition, the RF circuit 610 may also communicate with a network and another device by wireless communication. The wireless communication may use any communications standard or protocol, which includes, but is not limited to, Global System for Mobile communications (GSM), General Packet Radio Service (GPRS), Code Division Multiple Access (CDMA), Wideband Code Division Multiple Access (WCDMA), Long Term Evolution (LTE), e-mail, Short Messaging Service (SMS), and the like.

The memory 620 may be configured to store a software program and module. The processor 680 runs the software program and module stored in the memory 620, to implement various functional applications and data processing of the mobile phone. The memory 620 may mainly include a program storage area and a data storage area. The program storage area may store an operating system, an application program required by at least one function (such as a sound playback function and an image display function), and the like. The data storage area may store data (such as audio data and an address book) created according to use of the mobile phone, and the like. In addition, the memory 620 may include a high speed random access memory, and may also include a non-volatile memory such as at least one magnetic disk storage device, a flash memory, or another volatile solid-state storage device.

The input unit 630 may be configured to receive input digit or character information, and generate a keyboard signal input related to the user setting and function control of the mobile phone 600. Specifically, the input unit 630 may include a touch panel 631 and another input device 632. The touch panel 631, which may also be referred to as a touch screen, may collect a touch operation of a user on or near the touch panel (such as an operation of a user on or near the touch panel 631 by using any suitable object or accessory such as a finger or a stylus), and drive a corresponding connection apparatus according to a preset program. Optionally, the touch panel 631 may include two parts: a touch detection apparatus and a touch controller. The touch detection apparatus detects a touch position of the user, detects a signal generated by the touch operation, and transfers the signal to the touch controller. The touch controller receives the touch signal from the touch detection apparatus, converts the touch signal into touch point coordinates, and sends the touch point coordinates to the processor 680. Moreover, the touch controller can receive and execute a command sent from the processor 680. In addition, the touch panel 631 may be a resistive, capacitive, infrared, or surface sound wave type touch panel. In addition to the touch panel 631, the input unit 630 may further include the another input device 632. Specifically, the another input device 632 may include, but is not limited to, one or more of a physical keyboard, a functional key (such as a volume control key or a switch key), a track ball, a mouse, and a joystick.

The display unit 640 may be configured to display information input by the user or information provided for the user, and various menus of the mobile phone. The display unit 640 may include a display panel 641. Optionally, the display panel 641 may be configured by using a liquid crystal display (LCD), an organic light-emitting diode (OLED), or the like. Further, the touch panel 631 may cover the display panel 641. After detecting a touch operation on or near the touch panel 631, the touch panel 631 transfers the touch operation to the processor 680, so as to determine the type of the touch event. Then, the processor 880 provides a corresponding visual output on the display panel 641 according to the type of the touch event. Although, in FIG. 6, the touch panel 631 and the display panel 641 are used as two separate parts to implement input and output functions of the mobile phone, in some embodiments, the touch panel 631 and the display panel 641 may be integrated to implement the input and output functions of the mobile phone.

The mobile phone 600 may further include at least one sensor 650 such as an optical sensor, a motion sensor, and other sensors. Specifically, the optical sensor may include an ambient light sensor and a proximity sensor. The ambient light sensor may adjust luminance of the display panel 641 according to brightness of the ambient light. The proximity sensor may switch off the display panel 641 and/or backlight when the mobile phone is moved to the ear. As one type of motion sensor, an acceleration sensor may detect magnitude of accelerations in various directions (generally on three axes), may detect magnitude and a direction of the gravity when static, and may be applied to an application that recognizes the attitude of the mobile phone (for example, switching between landscape orientation and portrait orientation, a related game, and magnetometer attitude calibration), a function related to vibration recognition (such as a pedometer and a knock), and the like. Other sensors such as a gyroscope, a barometer, a hygrometer, a thermometer, and an infrared sensor, which may be configured in the mobile phone, are not further described herein.

The audio circuit 660, a loudspeaker 661, and a microphone 662 may provide audio interfaces between the user and the mobile phone. The audio circuit 660 may convert received audio data into an electric signal and transmit the electric signal to the loudspeaker 661. The loudspeaker 661 converts the electric signal into a sound signal for output. On the other hand, the microphone 662 converts a collected sound signal into an electric signal. The audio circuit 660 receives the electric signal and converts the electric signal into audio data, and outputs the audio data to the processor 680 for processing. Then, the processor 680 sends the audio data to, for example, another mobile phone by using the RF circuit 610, or outputs the audio data to the memory 620 for further processing.

The wireless module is based on a short distance wireless transmission technology. The mobile phone may help, by using the wireless communications unit 670, the user to receive and send e-mails, browse a webpage, access stream media, and so on, which provides wireless broadband Internet access for the user. Although FIG. 6 shows the wireless communications unit 670, it may be understood that the wireless communications unit is not a necessary component of the mobile phone 600, and when required, the wireless communications unit may be omitted as long as the scope of the essence of the present disclosure is not changed.

The processor 680 is the control center of the mobile phone, and is connected to various parts of the mobile phone by using various interfaces and lines. By running or executing the software program and/or module stored in the memory 620, and invoking data stored in the memory 620, the processor 680 performs various functions and data processing of the mobile phone, thereby performing overall monitoring on the mobile phone. Optionally, the processor 680 may include one or more processing units. Preferably, the processor 680 may integrate an application processor and a modem. The application processor mainly processes an operating system, a user interface, an application program, and the like. The modem mainly processes wireless communication. It may be understood that the foregoing modem may also not be integrated into the processor 680.

The mobile phone 600 further includes the power supply 690 (such as a battery) for supplying power to the components. Preferably, the power supply may be logically connected to the processor 680 by using a power management system, thereby implementing functions such as charging, discharging and power consumption management by using the power management system.

Although not shown in the figure, the mobile phone 600 may further include a camera, a Bluetooth module, and the like, which are not further described herein.

In the embodiments of the present invention, the processor 680 included in the terminal further has the following functions: a method for recommending an application, including:

detecting first applications already installed in a system;

determining second applications that match the detected first applications; and

Further, the detecting first applications already installed in a system includes:

querying for the first applications already installed in the system by using an API provided by the system.

accessing a software management program in the system; and

querying, in the software management program, for the first applications already installed in the system.

Further, after the detecting first applications already installed in a system, and before the determining second applications that match the detected first applications, the method further includes:

performing filtering on the detected first applications to remove the first applications that are preinstalled in the system.

Further, the determining second applications that match the detected first applications includes:

classifying the detected first applications;

determining a user use index of each category according to a classifying result, where the user use index is used for indicating use preference of a user for applications in the category; and

acquiring applications that have not been installed in the system, and determining, in the applications that have not been installed in the system, applications belonging to the categories that correspond to the first N highest user use indexes as the second applications, where N is an integer greater than 0.

Further, the user use indexes are determined according to at least one of the following:

The foregoing descriptions are merely preferred embodiments of the present invention, but are not intended to limit the present disclosure. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present disclosure shall fall within the protection scope of the present disclosure.

Claims

A method for recommending an application, comprising:

detecting first applications already installed in a system;

determining second applications that match the detected first applications; and

loading a display page and loading the determined second applications in the display page.
The method according to claim 1, wherein the detecting first applications already installed in a system comprises:

querying for the first applications already installed in the system by using an application programming interface (API) provided by the system.
The method according to claim 1, wherein the detecting first applications already installed in a system comprises:

accessing a software management program in the system; and

querying, in the software management program, for the first applications already installed in the system.
The method according to claim 2 or 3, wherein after the detecting first applications already installed in a system, and before the determining second applications that match the detected first applications, the method further comprises:

performing filtering on the detected first applications to remove the first applications that are preinstalled in the system.
The method according to claim 1, wherein the determining second applications that match the detected first applications comprises:

classifying the detected first applications;

determining a user use index of each category according to a classifying result, wherein the user use index is used for indicating use preference of a user for applications in the category; and

acquiring applications that have not been installed in the system, and determining, in applications that have not been installed in the system, the applications belonging to the categories that correspond to the first N highest user use indexes as the second applications, wherein N is an integer greater than 0.
The method according to claim 5, wherein the user use index is determined according to at least one of the following:

the number of the first applications in each category and a sum of durations of all the first applications in each category since installation.
An apparatus for recommending an application, comprising:

a detection unit, configured to detect first applications already installed in a system;

a determining unit, configured to determine second applications that match the detected first applications; and

a display unit, configured to load a display page and load the determined second applications in the display page.
The apparatus according to claim 7, wherein the detection unit is specifically configured to:

query for the first applications already installed in the system by using an application programming interface (API) provided by the system.
The apparatus according to claim 7, wherein the detection unit comprises:

an accessing subunit, configured to access a software management program in the system; and

a query subunit, configured to query, in the software management program, for the first applications already installed in the system.
The apparatus according to claim 8 or 9, further comprising:

a filtering unit, configured to perform filtering on the detected first applications to remove the first applications that are preinstalled in the system.
The apparatus according to claim 7, wherein the determining unit comprises:

a classifying subunit, configured to classify the detected first applications;

a first determining subunit, configured to determine a user use index of each category according to a classifying result, wherein the user use index is used for indicating use preference of a user for applications in the category; and

a second determining subunit, configured to acquire applications that have not been installed in the system, and determine, in applications that have not been installed in the system, the applications belonging to the categories that correspond to the first N highest user use indexes as the second applications, wherein N is an integer greater than 0.
The apparatus according to claim 11, wherein the user use index is determined according to at least one of the following:

the number of the first applications in each category and a sum of durations of all the first applications in each category since installation.