CN104866505B - Application recommendation method and device - Google Patents
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Abstract
The invention is suitable for the technical field of Internet, and provides an application recommendation method and device, which comprise the following steps: detecting an installed first application in a system; determining a second application matching the detected first application; and loading a display page, and loading the determined second application in the display page. According to the method and the device, background prediction is carried out on the applications which are possibly preferred or required by the user according to the applications installed in the system, and the predicted applications are loaded in the corresponding display pages, so that the user can find the applications meeting the requirements without searching for a long time in the network, and the access convenience of the applications is greatly improved.
Description
Technical Field
The invention belongs to the technical field of internet, and particularly relates to an application recommendation method and device.
Background
The Web application (WebApp) refers to an application running on a Web and a standard browser and developing to realize a specific function based on Web technology, for example, a Web page helping a buyer calculate house loan details, or a large and complex Web site providing a whole set of travel services for a vacationer. The webpage application has the advantages of low development cost, good compatibility, no need of installation and the like, and is more and more favored by the majority of users.
With the rise of the development popularity of the web applications, a large amount of web applications are developed and uploaded to wait for a user to access one by one through a browser, however, corresponding problems also occur, that is, the types of the web applications are rich and the number of the web applications is huge, and the user often needs to search for the web applications really liked or needed by the user through a long-time search in the browser, so that the access convenience of the web applications is influenced.
Disclosure of Invention
The embodiment of the invention aims to provide an application recommendation method, which solves the problem of low access convenience of the current application.
The embodiment of the invention is realized in such a way that an application recommendation method comprises the following steps:
detecting an installed first application in a system;
determining a second application matching the detected first application;
and loading a display page, and loading the determined second application in the display page.
Another object of an embodiment of the present invention is to provide an application recommendation apparatus, including:
a detection unit for detecting an installed first application in the system;
a determination unit configured to determine a second application that matches the detected first application;
and the display unit is used for loading a display page and loading the determined second application in the display page.
In the embodiment of the invention, the background prediction is carried out on the applications which are possibly preferred or needed by the user according to the applications installed in the system, and the predicted applications are loaded in the corresponding display pages, so that the user can find the applications which meet the requirements without searching for a long time in the network, and the access convenience of the applications is greatly improved.
Drawings
FIG. 1 is a flowchart illustrating an implementation of a recommendation method for an application according to an embodiment of the present invention;
fig. 2 is a flowchart of a specific implementation of the application recommendation method S101 according to an embodiment of the present invention;
FIG. 3 is a flowchart illustrating an implementation of a recommendation method for an application according to another embodiment of the present invention;
fig. 4 is a flowchart of a specific implementation of the application recommendation method S102 according to an embodiment of the present invention;
fig. 5 is a block diagram of a recommendation apparatus for an application according to an embodiment of the present invention;
fig. 6 is a block diagram of a part of the structure of a mobile phone related to a terminal provided by an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
In the embodiment of the invention, the background prediction is carried out on the applications which are possibly preferred or needed by the user according to the applications installed in the system, and the predicted applications are loaded in the corresponding display pages, so that the user can find the applications which meet the requirements without searching for a long time in the network, and the access convenience of the applications is greatly improved.
In the following embodiments, for convenience of description, recommendation of a web application is taken as an example, and the recommendation method and apparatus for an application described in the embodiments of the present invention are described in detail, it is easily conceivable that the same principle may also be applied to recommendation methods for other types of applications, and details in the following embodiments are not repeated.
In the embodiment of the present invention, when the predicted application is a web application, the execution main body may be a browser for running the web application, and the user accesses the web application through the browser, and further, when the web application is a mobile-end web application, the corresponding execution main body is a browser running in a mobile terminal including a mobile phone, a tablet, and the like.
Fig. 1 shows an implementation flow of the recommendation method for an application provided by an embodiment of the present invention, which is detailed as follows:
in S101, a first application installed in the system is detected.
For the application installed in the system, on one hand, the preference of the user can be reflected, for example, the application related to the travel plan or the strategy can reflect the interest of the user in the travel; on the other hand, the actual requirements of the user can be reflected, for example, the application related to the beautification of the picture can reflect that the user has the application requirements of the picture processing. Therefore, based on the directionality of the preference or demand of the user by the installed applications in the system, in S101, the installed applications in the system are first detected to serve as a data basis for performing subsequent background prediction on the web applications that the user may prefer or demand.
As an embodiment of the present invention, the detection of the installed Application in the system may directly query the installed Application and related information in the system by calling an Application Programming Interface (API) provided by the system. For example, for the Android system, it provides a PackageManager function, which can query the applications installed in the system, and at the same time, can return the related information of the applications installed in the system, including the names, icons, cache sizes, data sizes, and so on of the applications. Therefore, by calling the API provided by the system, the related function returns a corresponding query result, which includes the application installed in the system and the related information thereof.
As another embodiment of the invention, the software management program installed in the system can be used for inquiring the installed application and the related information in the system. As shown in fig. 2, S101 specifically is:
in S201, a software management program in the system is accessed.
The software management program can be safety software installed in the system and provides services of downloading, managing, unloading, information query and the like of the software; a client may be downloaded for a third party application installed in the system, which provides a resource list of the application while supporting services such as management, uninstallation, information query, etc. of the application downloaded and installed in the client. The software management program has a scanning function for the applications installed in the system, and can return inquiry results related to the application software installed in the system to an inquiring party.
In this embodiment, the data interaction with the software management program can also be realized by accessing the software management program through the API provided by the software management program.
In S202, the first application installed in the system is queried in the software management program.
After data interaction is realized with the software management program through the corresponding API, the software management program returns a corresponding query result by initiating a data query request to the software management program, so that the application installed in the system and the related information thereof are queried.
Since the part of the applications installed in the system is pre-installed by the system or pre-installed by the manufacturer after the device leaves the factory, and the part of the applications does not actually reflect the real preference or requirement of the user, further, as shown in fig. 3, after S101 and before S102, the method further includes:
in S104, the detected first application is filtered to remove the first application preinstalled in the system.
That is, after detecting an installed application in the system, the portion of the application is filtered to remove applications pre-installed therein by the system. The application preinstalled in the system and the application installed by the user can be distinguished by detecting the downloading or installation time of the application. For example, if the download or installation time for an application is after the device factory time or after the current system update time, then the application is obviously the application that the user installed himself. In the above determination process, the factory time of the device or the update time of the current system may be obtained by reading a configuration file of the system, and the download or installation time of the application may be obtained by querying a log file of the software management program.
In the subsequent processing process, the filtered application is used as an analysis basis to predict the webpage application which is possibly preferred or actually required by the user, so that the prediction accuracy can be improved, and the finally displayed webpage application is more suitable for the use psychology of the user.
In S102, the second application matching the detected first application is determined.
For the applications installed in the system detected in S101, it is necessary to determine the web applications that match the applications, where the matching means that the determined web applications belong to the same category as the applications in terms of application type, belonging field, and the like. For example, a web application for querying lyrics is matched with a music player in the interest field, and for example, a web application for posting a microblog is matched with a web community application in the application type, and the like.
In this embodiment, the background searches the web applications in the related application categories or domain categories, and each detected application can be matched with the related web application. Further, in order to improve the matching accuracy of the web application, as shown in fig. 4, as an embodiment of the present invention, S102 is specifically;
in S401, the detected first application is classified.
In this embodiment, the detected applications may be classified in terms of application types or fields thereof according to classification results of the web applications or classification categories preset in the background. For most applications, classification processing is already performed by the third-party application downloading client when the applications are downloaded from the third-party application downloading client, so that classification to which the applications belong can be judged by tracing the downloading source of the applications or reading the downloaded information carried in the application installation configuration file.
As an implementation example of the present invention, the detected applications may be classified according to categories of entertainment, tools, social, music, efficiency, life, reference, travel, sports, navigation, news, finance, photography, food, travel, and the like.
In S402, according to the classification result, a user usage index for each of the classifications is determined, where the user usage index is used to indicate the usage preference of the user for the applications belonging to the classification.
In this embodiment, according to the classification result in S401, the applications belonging to each classification are further analyzed, so as to determine a user usage index for each classification, where the user usage index may indicate the usage preference degree of the application belonging to the classification for the user.
In this embodiment, the user usage index may be determined according to at least one of:
the number of the first applications under each of the categories, and a sum of installed durations of all the first applications under each of the categories.
When the user usage index is expressed by the number of applications in each category, specifically, it is necessary to count the number of detected applications under each category according to the classification result, and use the counted number of applications under each category as the user usage index of the category, and it is obvious that, for the category with the largest number of applications, the higher the user usage index is, since the user usually has a higher tendency to select to download applications that are interested in installing the applications or have actual usage requirements, the usage preference degree of the applications under each category for the user can be reflected to a certain degree by using the counted number of applications under each category as the user usage index of the category.
When the user usage index is embodied by the sum of the installed durations of all applications in each category, first, it is necessary to count the installed durations of all applications installed in the system, respectively, by reading the configuration file of the application or querying the installation time of the application in the software management program, by determining the installation time of each application, then, calculating the sum of the installed durations of all applications in each category, and taking the sum of the installed durations counted under each category as the user usage index of the category, it is obvious that for the category with the highest sum of the installed durations, the higher the user usage index is, since the applications which are interested by the user or have actual usage requirements will be used for a long time, and for the applications which are not interested by the user or have no actual usage requirements, the applications will be selected to be unloaded after a period of trial, therefore, the sum of the installed time lengths counted under each classification is used as the user usage index of the classification, so that the usage preference degree of the user for the application belonging to each classification can be reflected to a certain degree.
It is easy to think that, in the case of application runtime traceability, the sum of the running times of all applications in each category can also be used as the user usage index of the category, and the usage preference degree of the application belonging to each category can also be reflected to a certain degree by the user. For example, for the instant messaging software, the total online time for the user to log in the instant messaging software on the device may be obtained, and the total online time may be used as the running time of the instant messaging software.
Meanwhile, in order to further improve the matching degree of the determined webpage applications and the user use preference, the user use index of each category can be determined according to the sum of the number of applications in each category and the installed time of all the applications in the category. For example, each category may be sorted according to the sum of the number of applications and the installed duration, a first sequence corresponding to the number of applications and a second sequence corresponding to the sum of the installed duration are generated, the ranking names of each category in the two sequences are added or weighted-added, so as to obtain the final ranking of each category, and the ranking result is used as the user usage index of the category.
In S403, applications not installed in the system are obtained, and the applications that belong to the first N categories with the highest user usage index are determined as the second applications, where N is an integer greater than 0.
Specifically, a list of applications that can be downloaded or accessed may be obtained from an application download source provided by the server, a first application installed in the system is removed to obtain applications that are not installed in the system, and finally, according to the determined user usage index of each category, the web applications under the top N categories (for example, the top 3 categories) with the highest user usage index are determined as the web applications that are finally required to be displayed to the user.
In S103, a display page is loaded, and the determined second application is loaded in the display page.
Finally, after the relevant matching process is completed, the matched web application can be displayed in the relevant page of the browser. Specifically, when the presentation page is loaded each time, the matched web applications in a specific category may be selected for presentation, or the web applications from multiple matching categories may be presented in the same presentation page at the same time.
Through the application recommendation method set forth in the embodiment, the browser can perform background prediction on the use preference of the user, so that the application meeting the use preference of the user is automatically pushed to the user when the recommended page is loaded, on one hand, the user does not need to search for the application meeting the requirement in the network for a long time, and the access convenience of the webpage application is greatly improved, on the other hand, meanwhile, as the access time of the application is shortened, the user does not need to search for the application really needed through repeated network search, and the network traffic cost is also saved to a certain extent.
Fig. 5 is a block diagram illustrating a recommendation apparatus for an application according to an embodiment of the present invention, where the apparatus is configured to execute a recommendation method for an application according to the embodiment of fig. 1 to 4. For convenience of explanation, only the portions related to the present embodiment are shown.
Referring to fig. 5, the apparatus includes:
the detection unit 51 detects the first application installed in the system.
The determining unit 52 determines a second application matching the detected first application.
And the display unit 53 loads a display page and adds the determined second application in the display page.
Optionally, the detecting unit 51 is specifically configured to:
and querying the first application installed in the system through an API provided by the system.
Optionally, the detection unit 51 includes:
the access subunit is used for accessing the software management program in the system;
and the query subunit is used for querying the first application installed in the system in the software management program.
Optionally, the apparatus further comprises:
and the filtering unit is used for filtering the detected first application to remove the first application preinstalled by the system.
Optionally, the determining unit 52 includes:
a classification subunit configured to classify the detected first application;
a first determining subunit, configured to determine, according to the classification result, a user usage index for each of the classifications, where the user usage index is used to indicate a usage preference of a user for an application belonging to the classification;
and the second determining subunit is used for acquiring applications which are not installed in the system, and determining the applications which belong to the first N categories with the highest user use index as the second applications, wherein N is an integer greater than 0.
Optionally, the user usage index is determined according to at least one of:
the number of the first applications under each of the categories, and a sum of installed durations of all the first applications under each of the categories.
Fig. 6 is a block diagram illustrating a partial structure of a mobile phone related to a terminal provided in an embodiment of the present invention. Referring to fig. 6, the handset includes: radio Frequency (RF) circuit 610, memory 620, input unit 630, display unit 640, sensor 650, audio circuit 660, wireless module 670, processor 680, and power supply 690. Those skilled in the art will appreciate that the handset configuration shown in fig. 6 is not intended to be limiting and may include more or fewer components than those shown, or some components may be combined, or a different arrangement of components.
The following describes each component of the mobile phone in detail with reference to fig. 6:
the RF circuit 610 may be used for receiving and transmitting signals during information transmission and reception or during a call, and in particular, receives downlink information of a base station and then processes the received downlink information to the processor 680; in addition, the data for designing uplink is transmitted to the base station. Typically, the RF circuitry includes, but is not limited to, an antenna, at least one Amplifier, a transceiver, a coupler, a Low Noise Amplifier (LNA), a duplexer, and the like. In addition, the RF circuitry 610 may also communicate with networks and other devices via wireless communications. The wireless communication may use any communication standard or protocol, including but not limited to Global System for Mobile communication (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 used to store software programs and modules, and the processor 680 may execute various functional applications and data processing of the mobile phone by operating the software programs and modules stored in the memory 620. The memory 620 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 620 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 input unit 630 may be used to receive input numeric or character information and generate key signal inputs related to user settings and function control of the cellular phone 600. Specifically, the input unit 630 may include a touch panel 631 and other input devices 632. The touch panel 631, also referred to as a touch screen, may collect touch operations of a user (e.g., operations of the user on the touch panel 631 or near the touch panel 631 by using any suitable object or accessory such as a finger or a stylus) thereon or nearby, and drive the corresponding connection device according to a preset program. Alternatively, the touch panel 631 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 680, and can receive and execute commands sent by the processor 680. In addition, the touch panel 631 may be implemented using various types, such as resistive, capacitive, infrared, and surface acoustic wave. The input unit 630 may include other input devices 632 in addition to the touch panel 631. In particular, other input devices 632 may include, but are not limited to, one or more of a physical keyboard, function keys (such as volume control keys, switch keys, etc.), a trackball, a mouse, a joystick, and the like.
The display unit 640 may be used to display information input by the user or information provided to the user and various menus of the mobile phone. The Display unit 640 may include a Display panel 641, and optionally, the Display panel 641 may be configured in the form of a Liquid Crystal Display (LCD), an Organic Light-Emitting Diode (OLED), or the like. Further, the touch panel 631 can cover the display panel 641, and when the touch panel 631 detects a touch operation thereon or nearby, the touch panel is transmitted to the processor 680 to determine the type of the touch event, and 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 two independent components to implement the 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 handset 600 may also include at least one sensor 650, such as a light sensor, motion sensor, and other sensors. Specifically, the light sensor may include an ambient light sensor that adjusts the brightness of the display panel 641 according to the brightness of ambient light, and a proximity sensor that turns off the display panel 641 and/or the backlight when the mobile phone is moved to the ear. As one of the motion sensors, the accelerometer sensor can detect the magnitude of acceleration in each direction (generally three axes), can detect the magnitude and direction of gravity when the mobile phone is stationary, can be used for applications of recognizing the gesture of the mobile phone (such as horizontal and vertical screen switching, related games, magnetometer gesture calibration), vibration recognition related functions (such as pedometer and tapping) and the like, and can also be configured with other sensors such as a gyroscope, a barometer, a hygrometer, a thermometer, an infrared sensor and the like, which are not described herein again.
The wireless module is based on short-distance wireless transmission technology, and the mobile phone can help the user to receive and send e-mails, browse webpages, access streaming media and the like through the wireless module 670, and provides wireless broadband internet access for the user. Although fig. 6 shows the wireless module 670, it is understood that it does not belong to the essential constitution of the cellular phone 600, and may be omitted entirely as needed within the scope not changing the essence of the invention.
The processor 680 is a control center of the mobile phone, and connects various parts of the entire mobile phone by using various interfaces and lines, and performs various functions of the mobile phone and processes data by operating or executing software programs and/or modules stored in the memory 620 and calling data stored in the memory 620, thereby performing overall monitoring of the mobile phone. Optionally, processor 680 may include one or more processing units; preferably, the processor 680 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 680.
The handset 600 also includes a power supply 690 (e.g., a battery) for powering the various components, which may preferably be logically coupled to the processor 680 via a power management system, such that the power management system may be used to manage charging, discharging, and power consumption.
Although not shown, the mobile phone 600 may further include a camera, a bluetooth module, and the like, which are not described in detail herein.
In the embodiment of the present invention, the processor 680 included in the terminal further has the following functions: the application recommendation method comprises the following steps:
detecting an installed first application in a system;
determining a second application matching the detected first application;
and loading a display page, and loading the determined second application in the display page.
Further, the first application installed in the detection system includes:
and querying the first application installed in the system through an Application Programming Interface (API) provided by the system.
Further, the first application installed in the detection system includes:
accessing a software management program in the system;
querying the software management program for the first application installed in the system.
Further, after detecting a first application installed in the system and before determining a second application matching the detected first application, the method further comprises:
and filtering the detected first application to remove the first application preinstalled by the system.
Further, the determining a second application matching the detected first application comprises:
classifying the detected first application;
determining a user usage index of each classification according to classification results, wherein the user usage index is used for representing the usage preference of a user for the application belonging to the classification;
acquiring applications which are not installed in a system, and determining the applications which belong to the first N categories with the highest user use index as the second applications, wherein N is an integer larger than 0.
Further, the user usage index is determined according to at least one of:
the number of the first applications under each of the categories, and a sum of installed durations of all the first applications under each of the categories.
In the embodiment of the invention, the background prediction is carried out on the applications which are possibly preferred or needed by the user according to the applications installed in the system, and the predicted applications are loaded in the corresponding display pages, so that the user can find the applications which meet the requirements without searching for a long time in the network, and the access convenience of the applications is greatly improved.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.
Claims (6)
1. A recommendation method of a webpage application based on a browser is characterized by comprising the following steps:
the browser detects an installed application in the system;
reading a configuration file of a system to obtain the updating time of the current system;
inquiring a log file of a software management program to obtain the downloading time of the installed application in the system;
filtering out applications with the downloading time later than the updating time of the system from the applications installed in the system to obtain the applications installed in the system by the user;
classifying the application types or the application fields which are installed by the user by tracing the downloading sources of the applications or reading the downloaded information carried in the application installation configuration file;
reading a configuration file of the application or inquiring the installation time of the application in the software management program to obtain the installation time of each application;
calculating the sum of the installed time lengths of all applications under each classification according to the installation time length of each application;
according to the classification result, carrying out quantity statistics on the detected applications belonging to each classification to obtain the application quantity of each classification;
sorting each classification according to the application number and the sum of the installed time length respectively to generate a first sequence corresponding to the application number and a second sequence corresponding to the sum of the installed time length;
carrying out weighted addition operation on the ranking names of each category in the first sequence and the second sequence to obtain a ranking result of each category, and using the ranking result as a user use index of the category so as to determine the use preference degree of the user on the application belonging to the category through the user use index;
acquiring an application list which can be downloaded or accessed from an application downloading source provided by a server;
removing applications installed in the system from the application list to determine web page applications not installed in the system;
according to the user use index of each classification, determining the first N classified applications with the highest user use index from the webpage applications not installed in the system as webpage applications needing to be displayed, wherein N is an integer greater than 0;
loading the display page of the browser, and
and displaying at least one classified webpage application in the webpage applications needing to be displayed in the display page so as to automatically push the webpage applications meeting the user preference or requirement to the user.
2. The method of claim 1, wherein the browser detecting an installed application in a system comprises:
the browser queries the installed applications in the system through an application programming interface provided by the system.
3. The method of claim 1, wherein the browser detecting an installed application in a system comprises:
accessing the software management program in the system through an API provided by the software management program;
and querying the software management program for the installed application in the system.
4. An apparatus for recommending a web application based on a browser, the apparatus comprising:
a detection unit for detecting an installed application in the system;
the filtering unit is used for reading the configuration file of the system to obtain the updating time of the current system;
inquiring a log file of a software management program to obtain the downloading time of the installed application in the system;
filtering out applications with the downloading time later than the updating time of the system from the applications installed in the system to obtain the applications installed in the system by the user;
the classification subunit is used for classifying the application types or the application fields of the applications installed by the users by tracing the downloading sources of the applications or reading the downloaded information carried in the application installation configuration files;
the first determining subunit is used for reading a configuration file of the application or inquiring the installation time of the application in the software management program to obtain the installation time of each application;
calculating the sum of the installed time lengths of all applications under each classification according to the installation time length of each application;
according to the classification result, carrying out quantity statistics on the detected applications belonging to each classification to obtain the application quantity of each classification;
sorting each classification according to the application number and the sum of the installed time length respectively to generate a first sequence corresponding to the application number and a second sequence corresponding to the sum of the installed time length;
carrying out weighted addition operation on the ranking names of each category in the first sequence and the second sequence to obtain a ranking result of each category, and using the ranking result as a user use index of the category so as to determine the use preference degree of the user on the application belonging to the category through the user use index;
the second determining subunit is used for acquiring an application list which can be downloaded or accessed from an application downloading source provided by the server;
removing applications installed in the system from the application list to determine web page applications not installed in the system;
according to the user use index of each classification, determining the first N classified applications with the highest user use index from the webpage applications not installed in the system as webpage applications needing to be displayed, wherein N is an integer greater than 0;
and the display unit is used for loading a display page of the browser and displaying at least one classified webpage application in the webpage applications needing to be displayed in the display page so as to automatically push the webpage applications meeting the preference or the requirement of the user to the user.
5. The apparatus according to claim 4, wherein the detection unit is specifically configured to query an application installed in the system through an application programming interface provided by the system.
6. The apparatus of claim 4, wherein the detection unit comprises:
the access subunit is used for accessing the software management program in the system through the API provided by the software management program;
and the query subunit is used for querying the applications installed in the system in the software management program.
Priority Applications (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201410065320.5A CN104866505B (en) | 2014-02-25 | 2014-02-25 | Application recommendation method and device |
| PCT/CN2015/073017 WO2015127870A1 (en) | 2014-02-25 | 2015-02-13 | Method and apparatus for recommending application |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201410065320.5A CN104866505B (en) | 2014-02-25 | 2014-02-25 | Application recommendation method and device |
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| WO2017000988A1 (en) | 2015-06-30 | 2017-01-05 | Brainlab Ag | Medical image fusion with reduced search space |
| CN105183464B (en) * | 2015-08-27 | 2018-10-16 | 北京金山安全软件有限公司 | Information display method and device and electronic equipment |
| CN105512241A (en) * | 2015-11-30 | 2016-04-20 | 小米科技有限责任公司 | Theme update method and device |
| CN105975540A (en) * | 2016-04-29 | 2016-09-28 | 北京小米移动软件有限公司 | Information display method and device |
| CN105975309A (en) * | 2016-05-05 | 2016-09-28 | 广东小天才科技有限公司 | Application updating method and apparatus for mobile terminal |
| TWI609315B (en) * | 2016-06-03 | 2017-12-21 | 宏碁股份有限公司 | Application recommendation method and electronic device using the same |
| CN106529158B (en) * | 2016-10-27 | 2019-06-14 | 北京小米移动软件有限公司 | The method and device of recommended dietary information |
| CN106874095A (en) * | 2017-02-28 | 2017-06-20 | 珠海市魅族科技有限公司 | One kind application loading method and device |
| CN107612974B (en) * | 2017-08-23 | 2020-04-17 | Oppo广东移动通信有限公司 | Information recommendation method and device, mobile terminal and storage medium |
| CN107506468A (en) * | 2017-08-31 | 2017-12-22 | 努比亚技术有限公司 | Application program searching method, terminal, server, computer-readable recording medium |
| CN109508227B (en) * | 2017-09-15 | 2021-06-22 | 阿里巴巴（中国）有限公司 | Application analysis method and device, computing equipment and storage medium |
| CN107832426B (en) * | 2017-11-13 | 2021-11-02 | 上海交通大学 | APP recommendation method and system based on using sequence context |
| CN110109668A (en) * | 2019-05-05 | 2019-08-09 | 北京金山安全软件有限公司 | Application page display method and device, terminal device and medium |
| CN110493075B (en) * | 2019-08-01 | 2021-06-25 | 京信通信系统（中国）有限公司 | Method, device and system for monitoring online duration of equipment |
| CN115665704B (en) * | 2022-11-21 | 2023-03-14 | 广州天辰信息科技有限公司 | Activity privacy safety recommendation method based on big data |
| CN116389444B (en) * | 2023-04-10 | 2023-09-15 | 北京智享嘉网络信息技术有限公司 | Traffic scheduling method and system based on user web application |
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| CN103024730A (en) * | 2012-12-05 | 2013-04-03 | 云之朗科技有限公司 | Application download method, terminal and server |
| CN103581314A (en) * | 2013-10-29 | 2014-02-12 | 广东欧珀移动通信有限公司 | Method and system for achieving application recommendation on APP starting page |
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| CN104866505A (en) | 2015-08-26 |
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