CN104899220B - Application program recommendation method and system - Google Patents
Application program recommendation method and system Download PDFInfo
- Publication number
- CN104899220B CN104899220B CN201410081705.0A CN201410081705A CN104899220B CN 104899220 B CN104899220 B CN 104899220B CN 201410081705 A CN201410081705 A CN 201410081705A CN 104899220 B CN104899220 B CN 104899220B
- Authority
- CN
- China
- Prior art keywords
- program
- access
- browser
- category
- application
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/10—Office automation; Time management
Abstract
An application program recommendation method, comprising the steps of: acquiring a webpage application program accessed by a browser; acquiring the program type of the webpage application program to obtain the program type accessed by the browser; counting access indexes corresponding to the program categories accessed by the browser, and extracting the program categories with the preset number before the access indexes; acquiring information of an application program corresponding to the extracted program type; and pushing the acquired information of the application program. According to the method, the program types of the webpage application programs which are interested by the user are counted in the webpage application programs used by the user, the information of the application programs corresponding to the program types which are interested by the user is obtained, the information of the application programs is recommended to the user, the probability that the user receives the application programs is high, the related information of the application programs is pushed in a large amount, and the network bandwidth and the system resource utilization rate can be improved. In addition, an application program recommendation system is further provided.
Description
Technical Field
The invention relates to the technical field of networks and computers, in particular to an application program recommendation method and system. Background
A Web application, abbreviated as Web app in english, is application software that operates on the internet or an intranet using a Web browser. Since the web application is an application written in a web language (e.g., programming languages such as HTML, JavaScript, Java, etc.), the web application needs to be run through a browser.
Many web applications are popular today because, among other reasons, web applications can be run directly on various computer platforms without the need for prior installation or periodic upgrades, etc. Common web applications are Webmail, web stores, web auctions, wiki, web forums, blogs, web games, and many others.
The number and coverage of the user groups determine the development of the application programs, and the application programs need to be popularized and used. Generally, an application operator promotes information related to an application to a user through various ways, for example, information related to an application to be promoted is presented to the user through web contents of a website, a pop-up attached to a web page, various client interfaces, and the like.
On one hand, the recommendation information of the application programs spread over the ground causes harassment to users on certain programs, and on the other hand, the probability of the users receiving the recommended application programs is low, so that the related information of the application programs is massively pushed under the condition that no specific target is pushed to a user group, and the method is a waste of network bandwidth and computer system resources.
Disclosure of Invention
Based on this, there is a need for an application recommendation method that can improve network bandwidth and system resource utilization.
An application program recommendation method, comprising the steps of:
acquiring a webpage application program accessed by a browser;
acquiring the program type of the webpage application program to obtain the program type accessed by the browser;
counting access indexes corresponding to the program categories accessed by the browser, and extracting the program categories with the preset number before the access indexes;
acquiring information of an application program corresponding to the extracted program type;
and pushing the acquired information of the application program.
In addition, there is a need to provide an application recommendation system that can improve network bandwidth and system resource utilization.
An application recommendation system comprising:
the access program acquisition module is used for acquiring a webpage application program accessed by the browser;
the access category acquisition module is used for acquiring the program category to which the webpage application program belongs to obtain the program category accessed by the browser;
the category extraction module is used for counting access indexes corresponding to the program categories accessed by the browser and extracting the program categories with the preset number before the access indexes;
the program information acquisition module is used for acquiring the information of the application program corresponding to the extracted program type;
and the information pushing module is used for pushing the obtained information of the application program.
The application program recommendation method and the application program recommendation system acquire the program types to which the webpage application programs accessed by the browser belong, count the access indexes corresponding to the program types accessed by the browser, acquire the information of the application programs corresponding to the program types with the access indexes before, and recommend the information of the application programs to a user; the webpage application programs accessed by the browser are webpage application programs used by a user, the program category with the front access index can represent the category of the webpage application programs interested by the user, the application program recommending method and the application program recommending system can count the program category of the webpage application programs interested by the user in the webpage application programs used by the user, acquire the information of the webpage application programs corresponding to the program category interested by the user, recommend the information of the webpage application programs to the user, have high probability of receiving the webpage application programs, and can improve the network bandwidth and the system resource utilization rate compared with the method and the system which can massively push the relevant information of the application programs under the condition that a specific target push user group does not exist.
Drawings
FIG. 1 is a flow diagram that illustrates a method for application recommendation, according to one embodiment;
FIG. 2 is a schematic flow chart illustrating step S106 of FIG. 1 according to an embodiment;
FIG. 3 is a schematic flow chart illustrating step S202 of FIG. 2 according to one embodiment;
FIG. 4 is a block diagram that illustrates an application recommendation system, in one embodiment;
FIG. 5 is a block diagram of a category extraction module in one embodiment;
FIG. 6 is a block diagram of a program information acquisition module in one embodiment;
FIG. 7 is a diagram illustrating an application recommendation system in accordance with another embodiment;
FIG. 8 is a schematic structural diagram of an application recommendation system in a further embodiment;
FIG. 9 is a block diagram of a computer system 1000 upon which embodiments of the present invention may be implemented.
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.
Unless the context clearly dictates otherwise, the elements and components of the present invention may be present in either single or in multiple forms and are not limited thereto. Although the steps in the present invention are arranged by using reference numbers, the order of the steps is not limited, and the relative order of the steps can be adjusted unless the order of the steps is explicitly stated or other steps are required for the execution of a certain step. It is to be understood that the term "and/or" as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items.
As shown in fig. 1, in one embodiment, an application recommendation method includes the steps of:
step S102, acquiring a webpage application program accessed by the browser.
In one embodiment, a web application to which a quick access mode is added in a browser may be obtained. There are various ways in which web applications can be added with quick access in a browser, for example, as bookmarks or quick links, as well as in browser favorites, and so forth. The webpage application program added with the quick access mode can be conveniently and quickly accessed, and is often the webpage application program which is interested by the user and has high access frequency.
In another embodiment, a web application with a browser access frequency meeting a preset condition may be obtained. The preset condition may be reaching a preset threshold, such as three times a month, etc.; step S102 may acquire a web application program with a browser access frequency reaching a preset threshold. The preset condition can also be that the access frequency is ranked at the top by a preset number of bits, and the like; step S102 may acquire a preset number of web applications with high browser access frequency.
In other embodiments, a web application to which a shortcut access mode is added in a browser may be acquired, and a web application whose browser access frequency meets a preset condition may be acquired.
In the embodiment, the web application programs which are more interested in the web application programs accessed by the user are obtained by obtaining the web application programs added with the quick access mode in the browser or the access frequency of the browser meets the preset condition, so that the web application programs which are more interested in the user can be conveniently obtained in the following steps according to the web application programs which are more interested in the user.
And step S104, acquiring the program type of the webpage application program accessed by the browser, and acquiring the program type accessed by the browser.
First, a program category to which each web application accessed by the browser belongs may be obtained.
In one embodiment, the program category may be preset, the web application corresponding to the program category may be set, and the correspondence between the program category and the web application may be stored. The program type can be set according to the program type input by the user, and the webpage application program corresponding to the program type can also be set according to the webpage application program corresponding to the program type input by the user. For example, the following program categories may be set: entertainment, tools, social, music, efficiency, life, references, travel, sports, navigation, news, finance, photography, food, travel, etc., and web applications corresponding to music program categories may be set including: "cool me music", "thousands of silent listening", etc. Step S104 may search a corresponding program category from the correspondence between the pre-stored program categories and the web application programs according to the web application program acquired in step S102, and mark the program category to which the web application program belongs.
In another embodiment, the program categories may be preset, and the keywords corresponding to each program category may be counted. The program category may be set according to a program category input by a user. In one embodiment, the search may be performed according to the program category name, and the high frequency words in the search result may be counted, and the obtained high frequency words may be used as the keywords corresponding to the program category, and further the correspondence between the program category and the corresponding keywords may be stored. Step S104 can access the page of the web application program, extract the high-frequency words in the page of the web application program, match the extracted high-frequency words with the keywords corresponding to the program types, and acquire the program type corresponding to the highest matching degree as the program type to which the web application program belongs.
Further, the program types accessed by the browser can be obtained by acquiring the set of the program types to which all the webpage application programs accessed by the browser belong.
And step S106, counting access indexes corresponding to all program types accessed by the browser, and extracting the program types with the preset number before the access indexes.
As shown in fig. 2, in one embodiment, step S106 includes the steps of:
step S202, the access duration corresponding to each program category accessed by the browser is counted, and the program categories with the preset number of the corresponding access durations before are extracted.
As shown in fig. 3, the step of counting access durations corresponding to the program categories accessed by the browser includes the following steps:
step S302, the access duration of the webpage application program is obtained according to the access record of the webpage application program.
In this embodiment, the method for recommending an application program further includes a process of forming a web application program access record, including the following steps: and monitoring and recording the starting time and the ending time of the browser for accessing the webpage application program to obtain the access record of the webpage application program.
Step S302 may calculate the access duration of the web application each time according to the start time and the result time of each access of the web application in the web application access record, and accumulate the access duration each time to obtain the access duration of the web application.
Step S304, accumulating the access time lengths of the webpage application programs belonging to the same program type to obtain the access time lengths corresponding to the program types.
Further, the program categories may be arranged in descending order according to the corresponding access durations. And extracting a preset number of program categories positioned at the front in the program category sequence arranged in a descending order according to the access time length.
Step S204, counting the number of the webpage application programs included in each program type accessed by the browser, and extracting the program types with the preset number in front.
The program categories may be arranged in a descending order according to the number of included web applications, and a preset number of program categories positioned at the top in the sequence of program categories arranged in a descending order according to the number of included web applications may be extracted.
In step S206, a common program category among the twice extracted program categories is acquired.
In one embodiment, step S106 may comprise only step S202, or only step S204. In this embodiment, the program category in which the user is interested may be obtained by obtaining a program category with a long access time or a program category with a large number of web applications accessed by a browser.
The above-described embodiment of acquiring the common program category in the program category having a longer access time and the program category including the program category having a larger number of web applications accessed by the browser can acquire the program category in which the user is more interested.
Step S108, obtaining the information of the application program corresponding to the extracted program type.
In an embodiment, before step S108, the method for recommending a web application further includes the steps of: setting program types, setting application programs corresponding to the program types, and storing the corresponding relation between the program types and the application programs. The program type can be set according to the program type input by the user, and the application program corresponding to the program type can also be set according to the application program corresponding to the program type input by the user. In another embodiment, before step S108, the method for recommending a web application further includes the steps of: setting program types, searching according to the program type names, extracting the application programs in the search results, and storing the corresponding relation between the program types and the extracted application programs. Also, the program category may be set according to a program category input by the user.
The information of the application acquired in step S108 includes the name, icon, download address or download link, profile content, and the like of the application.
In one embodiment, step S108 includes the steps of: and acquiring information of the webpage application program which is not accessed by the browser and corresponds to the extracted program type.
The method can acquire the webpage application programs accessed by the browser, search the application programs corresponding to the program categories extracted in the step S106 in the pre-stored corresponding relation between the program categories and the application programs, filter the webpage application programs accessed by the browser and acquire the webpage application programs not accessed by the browser; further, the obtained related information of the webpage application program is obtained.
In another embodiment, step S108 includes the steps of: and acquiring information of the application program which is not installed in the local browser and corresponds to the extracted program type.
Browser-local refers to a device on which the browser is running. The method can acquire the locally installed application program of the browser, search the application program corresponding to the program type extracted in the step S106 in the corresponding relation between the pre-stored program type and the application program, and filter the locally installed application program of the browser to obtain the locally uninstalled application program of the browser; further, the obtained related information of the webpage application program is obtained.
In an embodiment thereof, step S108 includes the steps of: and acquiring information of the webpage application programs which are not accessed by the browser and correspond to the extracted program type, and acquiring information of the application programs which are not installed locally by the browser and correspond to the extracted program type.
And step S110, pushing the acquired information of the application program.
In one embodiment, the browser obtains the web application it accesses and sends the information of the obtained web application to the server. The method comprises the steps that a server obtains program types to which webpage application programs belong, obtains program types accessed by a browser, counts access indexes corresponding to the program types accessed by the browser, extracts program types with preset number before the access indexes, obtains application program information corresponding to the extracted program types, and further sends the obtained application program information to the browser.
In one embodiment, the method for recommending an application program further includes: and displaying the information of the application program through a browser. In one embodiment, a pop-up window may be generated through a browser, and information of an application program is displayed in the pop-up window; alternatively, information of the application program may be loaded into web page contents through a browser and displayed.
As shown in fig. 4, in one embodiment, an application recommendation system includes an access program obtaining module 10, an access category obtaining module 20, a category extracting module 30, a program information obtaining module 40, and an information pushing module 50, where:
the access program obtaining module 10 is used for obtaining a web application accessed by a browser.
In one embodiment, the access program obtaining module 10 is used for obtaining a web application to which a shortcut access mode is added in a browser. There are various ways in which web applications can be added with quick access in a browser, for example, as bookmarks or quick links, as well as in browser favorites, and so forth. The webpage application program added with the quick access mode can be conveniently and quickly accessed, and is often the webpage application program which is interested by the user and has high access frequency.
In another embodiment, the access program obtaining module 10 is configured to obtain a web application with a browser access frequency meeting a preset condition. The preset condition may be reaching a preset threshold, such as three times a month, etc.; the access program obtaining module 10 is configured to obtain a web application program with a browser access frequency reaching a preset threshold. The preset condition can also be that the access frequency is ranked at the top by a preset number of bits, and the like; the access program obtaining module 10 is configured to obtain a preset number of web applications with high browser access frequency.
In other embodiments, the access program obtaining module 10 is configured to obtain a web application to which a shortcut access mode is added in a browser and obtain a web application with a browser access frequency meeting a preset condition.
In the embodiment, the web application programs which are more interested in the web application programs accessed by the user are obtained by obtaining the web application programs added with the quick access mode in the browser or the access frequency of the browser meets the preset condition, so that the web application programs which are more interested in the user can be conveniently obtained in the following steps according to the web application programs which are more interested in the user.
The access category acquiring module 20 is configured to acquire a program category to which a web application accessed by a browser belongs, and acquire the program category accessed by the browser.
First, the access category acquisition module 20 may acquire a program category to which each web application accessed by the browser belongs.
In one embodiment, the application recommendation system further includes a category setting module, a corresponding web application setting module, and a first storage module (not shown in the figure), wherein: the category setting module is used for presetting program categories. The corresponding webpage application program setting module is used for setting the webpage application programs corresponding to the program categories. The first storage module is used for storing the corresponding relation between the program category and the webpage application program. The program type can be set according to the program type input by the user, and the webpage application program corresponding to the program type can also be set according to the webpage application program corresponding to the program type input by the user. For example, the category setting module may set a plurality of program categories as follows: entertainment, tools, social contact, music, efficiency, life, reference, travel, sports, navigation, news, finance, photography, food, travel, etc., the corresponding web application setting module can set the web applications corresponding to the music program categories to include: "cool me music", "thousands of silent listening", etc. The access category acquiring module 20 may search a corresponding program category from the correspondence between the pre-stored program categories and the web application programs according to the web application programs acquired by the access program acquiring module 10, and mark the program category to which the web application program belongs.
In another embodiment, the application recommendation system further includes a category setting module, a corresponding keyword statistics module, and a second storage module (not shown in the figure). The category setting module is as described above. In one embodiment, the corresponding keyword counting module may perform searching according to the program category name, count high-frequency words in the search result, and use the obtained high-frequency words as the keywords corresponding to the program category. The second storage module is used for storing the corresponding relation between the program category and the corresponding keyword. The access category obtaining module 20 may access a page of the web application, extract high-frequency words in the page of the web application, match the extracted high-frequency words with keywords corresponding to each program category, and obtain the program category corresponding to the highest matching degree as the program category to which the web application belongs.
Further, the access category obtaining module 20 obtains a set of program categories to which all web applications accessed by the browser belong, so as to obtain the program categories accessed by the browser.
The category extraction module 30 is configured to count access indicators corresponding to program categories accessed by the browser, and extract a preset number of program categories before the access indicators.
As shown in fig. 5, in one embodiment, the category extraction module 30 includes a first category extraction module 320, a second category extraction module 340, and a common category acquisition module 360, wherein:
the first category extraction module 320 is configured to count access durations corresponding to program categories accessed by the browser, and extract a preset number of program categories before the corresponding access durations.
In one embodiment, the first category extracting module 320 may obtain the access duration of the web application according to the access record of the web application,
in this embodiment, the application recommendation system further includes an access record generation module (not shown in the figure) for forming an access record of the web application. In one embodiment, the access record generating module is used for monitoring and recording the starting time and the ending time of the browser accessing the web application to obtain the web application access record.
The first category extracting module 320 may calculate the access duration of each time of the web application according to the start time and the result time of each time of the web application being accessed in the web application access record, and accumulate the access duration of each time to obtain the access duration of the web application.
Further, the first category extracting module 320 may accumulate the access durations of the web applications belonging to the same program category to obtain the access durations corresponding to the program categories.
Further, the first category extracting module 320 may arrange the program categories in a descending order according to the corresponding access durations, and extract a preset number of program categories positioned at the top in the program category sequence arranged in the descending order according to the access durations.
The second category extraction module 340 is configured to count the number of web applications included in each program category accessed by the browser, and extract a preset number of program categories with a top number.
The second category extraction module 340 may sort the program categories in a descending order according to the number of included web applications, and extract a preset number of program categories positioned at the top in the sequence of program categories sorted in a descending order according to the number of included web applications.
The common category acquiring module 360 is configured to acquire a common program category from the program categories extracted by the first category extracting module 320 and the second category extracting module 340.
In one embodiment, the category extraction module 30 may include only the first category extraction module 320 or only the second category extraction module 340. In the above embodiment, the program category in which the user is interested may be obtained by obtaining the program category with a longer access time or the program category with a larger number of web applications accessed by the browser.
The above-described embodiment of acquiring the common program category in the program category having a longer access time and the program category including the program category having a larger number of web applications accessed by the browser can acquire the program category in which the user is more interested.
The program information acquisition module 40 acquires information of the application program corresponding to the extracted program category.
In one embodiment, the application recommendation system further includes a category setting module, a corresponding application setting module, and a third storage module (not shown in the figure), wherein: the category setting module is as described above. The corresponding application program setting module is used for setting the application programs corresponding to the program categories. The third storage module is used for storing the corresponding relation between the program category and the application program. The application program corresponding to the program type can also be set according to the application program corresponding to the program type input by the user.
In another embodiment, in an embodiment, the application recommendation system further includes a category setting module, a search and result extraction module, and a fourth storage module (not shown in the figure), wherein: the category setting module is as described above. The search and result extraction module is used for searching according to the program category name, extracting the application programs in the search result and storing the corresponding relation between the program category and the extracted application programs.
The information of the application acquired by the program information acquiring module 40 includes the name, icon, download address or download link, and profile content of the application.
As shown in fig. 6, in one embodiment, program information acquisition module 40 includes an unaccessed program information acquisition module 402 and an uninstalled program information acquisition module 404, where:
the unaccessed program information obtaining module 402 is configured to obtain information of a web application that has not been accessed by the browser and corresponds to the extracted program type.
The unaccessed program information obtaining module 402 can obtain the web application programs that have been accessed by the browser, search for the application programs corresponding to the program categories extracted by the category extraction module 30 from the pre-stored correspondence between the program categories and the application programs, and filter out the web application programs that have been accessed by the browser to obtain the web application programs that have not been accessed by the browser; further, the obtained related information of the webpage application program is obtained.
The uninstalled program information obtaining module 404 is configured to obtain information of an application program that is not installed locally in the browser and corresponds to the extracted program category.
Browser-local refers to a device on which the browser is running. The uninstalled program information obtaining module 404 may obtain the locally installed application program of the browser, search for the application program corresponding to the program category extracted in step S106 from the correspondence between the pre-stored program categories and the application programs, and filter out the locally installed application program of the browser, to obtain the locally uninstalled application program of the browser; further, the obtained related information of the webpage application program is obtained.
In one embodiment, program information acquisition module 40 may include only the un-accessed program information acquisition module 402 or only the un-installed program information acquisition module 404.
The information pushing module 50 is used for pushing the obtained information of the application program.
As shown in fig. 7, in an embodiment, the access program obtaining module 10 runs on a browser, the access category obtaining module 20, the category extracting module 30, the program information obtaining module 40, and the information pushing module 50 run on a server, and the application recommendation system further includes a sending module 60 running on the browser, and configured to send the information of the web application obtained by the access program obtaining module 10 to the server. In this embodiment, the information pushing module 50 is configured to send the information of the web application acquired by the program information acquiring module 40 to the browser.
As shown in fig. 8, in an embodiment, the application recommendation system further includes a presentation module 70 running on the browser, and configured to present information of the application sent by the information pushing module 50. In one embodiment, presentation module 70 may generate a pop-up window in which information for the application is displayed; alternatively, information for the application may be loaded into the web page content and exposed.
The application program recommendation method and the application program recommendation system acquire the program types to which the webpage application programs accessed by the browser belong, count the access indexes corresponding to the program types accessed by the browser, acquire the information of the application programs corresponding to the program types with the access indexes before, and recommend the information of the application programs to a user; the webpage application programs accessed by the browser are webpage application programs used by a user, the program category with the front access index can represent the category of the webpage application programs interested by the user, the application program recommending method and the application program recommending system can count the program category of the webpage application programs interested by the user in the webpage application programs used by the user, acquire the information of the webpage application programs corresponding to the program category interested by the user, recommend the information of the webpage application programs to the user, have high probability of receiving the webpage application programs, and can improve the network bandwidth and the system resource utilization rate compared with the method and the system which can massively push the relevant information of the application programs under the condition that a specific target push user group does not exist.
FIG. 9 is a block diagram of a computer system 1000 upon which embodiments of the present invention may be implemented. The computer system 1000 is only one example of a suitable computing environment for the invention and is not intended to suggest any limitation as to the scope of use of the invention. Neither should the computer system 1000 be interpreted as having a dependency or requirement relating to a combination of one or more components of the exemplary computer system 1000 illustrated.
The computer system 1000 shown in FIG. 9 is one example of a computer system suitable for use with the invention. Other architectures with different subsystem configurations may also be used. Devices such as desktop, notebook, tablet computers, and the like, as are well known to those of ordinary skill, may be suitable for use with some embodiments of the present invention. But are not limited to, the devices listed above.
As shown in fig. 9, the computer system 1000 includes a processor 1010, a memory 1020, and a system bus 1022. Various system components including the memory 1020 and the processor 1010 are connected to the system bus 1022. The processor 1010 is hardware for executing computer program instructions through basic arithmetic and logical operations in a computer system. Memory 1020 is a physical device used for temporarily or permanently storing computing programs or data (e.g., program state information). The system bus 1020 may be any of several types of bus structures including a memory bus or memory controller, a peripheral bus, and a local bus. The processor 1010 and the memory 1020 may be in data communication via a system bus 1022. Wherein memory 1020 includes Read Only Memory (ROM) or flash memory (neither shown), and Random Access Memory (RAM), which typically refers to main memory loaded with an operating system and application programs.
The computer system 1000 also includes a display interface 1030 (e.g., a graphics processing unit), a display device 1040 (e.g., a liquid crystal display), an audio interface 1050 (e.g., a sound card), and an audio device 1060 (e.g., speakers). Display device 1040 and audio device 1060 are media devices for experiencing multimedia content.
It should be noted that other computer systems, including more or less subsystems than computer system 1000, can also be suitable for use with the invention. For example, the computer system 1000 may include a bluetooth unit capable of exchanging data over short distances, an image sensor for taking pictures, and an accelerometer for measuring acceleration.
As described in detail above, the computer system 1000 adapted to the present invention can perform the designated operations of the application program recommendation method. The computer system 1000 performs these operations in the form of software instructions executed by the processor 1010 in a computer-readable medium. These software instructions may be read into memory 1020 from storage device 1070 or from another device via local network interface 1100. The software instructions stored in the memory 1020 cause the processor 1010 to perform the application recommendation method described above. Furthermore, the present invention can be implemented by hardware circuits or by a combination of hardware circuits and software instructions. Thus, implementations of the invention are not limited to any specific combination of hardware circuitry and software.
The above-mentioned embodiments only express several embodiments of the present invention, and the description thereof is more specific and detailed, but not construed as limiting the scope of the present invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the inventive concept, which falls within the scope of the present invention. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (8)
1. An application program recommendation method, comprising the steps of:
acquiring a webpage application program added with a quick access mode in a browser and a webpage application program with a browser access frequency meeting a preset condition;
acquiring the program type of the webpage application program to obtain the program type accessed by the browser;
counting access indexes corresponding to the program categories accessed by the browser, and extracting the program categories with the preset number of access indexes, wherein the program categories comprise: counting the access time length corresponding to the program category, accumulating the access time lengths of the webpage application programs belonging to the same program category to obtain the access time length corresponding to each program category, and extracting the program categories with the preset number of the access time lengths before the corresponding access time lengths; counting the number of the webpage application programs included in the program categories, and extracting the program categories with the preset number which is the top number; acquiring a common program category in the program categories extracted twice;
monitoring and recording the starting time and the ending time of the browser for accessing the webpage application program to obtain a webpage application program access record;
acquiring information of application programs corresponding to the extracted program types, wherein the information of webpage application programs which are not visited by the browser and correspond to the extracted program types and/or the information of application programs which are not installed locally in the browser and correspond to the extracted program types;
and pushing the acquired information of the application program to the browser, and loading and displaying the pushed information of the application program into webpage content through the browser.
2. The application program recommendation method according to claim 1, wherein the added shortcut access mode comprises at least one of the following modes: added as a bookmark or quick link, added to the browser favorites.
3. The method for recommending application programs according to claim 1, wherein the step of counting access indicators corresponding to the program categories accessed by the browser and extracting a preset number of program categories with the access indicators in front comprises:
counting access duration corresponding to the program categories, and extracting the program categories with preset number before the corresponding access duration; or the like, or, alternatively,
and counting the number of the webpage application programs included in the program categories, and extracting the program categories with the preset number at the top.
4. An application recommendation system, comprising:
the access program acquisition module is used for acquiring the webpage application program added with the quick access mode in the browser and the webpage application program with the browser access frequency meeting the preset conditions;
the access category acquisition module is used for acquiring the program category to which the webpage application program belongs to obtain the program category accessed by the browser;
the category extraction module is used for counting access indexes corresponding to the program categories accessed by the browser and extracting the program categories with the access indexes higher than the access indexes by a preset number, and the category extraction module comprises a first category extraction module, a second category extraction module and a public category acquisition module, wherein: the first class extraction module is used for counting the access time length corresponding to the program class, accumulating the access time lengths of the webpage application programs belonging to the same program class to obtain the access time length corresponding to each program class, and extracting the program classes with the preset number, wherein the corresponding access time lengths are earlier than the preset number; the second category extraction module is used for counting the number of the webpage application programs included in the program categories and extracting the program categories with the preset number which is higher than the preset number; the public category acquisition module acquires a public program category in the program categories extracted by the first category extraction module and the second category extraction module;
the access record generating module is used for monitoring and recording the starting time and the ending time of the browser for accessing the webpage application program to obtain the access record of the webpage application program;
the program information acquisition module is used for acquiring information of an application program corresponding to the extracted program type, acquiring information of a webpage application program which is not visited by the browser and corresponds to the extracted program type, and acquiring information of an application program which is not installed locally in the browser and corresponds to the extracted program type;
and the information pushing module is used for pushing the acquired information of the application program to the browser, and loading and displaying the pushed information of the application program into webpage content through the browser.
5. The application recommendation system according to claim 4, wherein the access program obtaining module is configured to obtain the web application to which the shortcut access mode is added in the browser, and/or,
the method is used for acquiring the webpage application program with the browser access frequency meeting the preset conditions.
6. The application recommendation system of claim 4 wherein the category extraction module comprises a first category extraction module or a second category extraction module, wherein:
the first type extraction module is used for counting the access duration corresponding to the program type and extracting the program types with the preset number before the corresponding access duration;
the second category extraction module is used for counting the number of the webpage application programs included in the program categories and extracting the program categories with the preset number in front.
7. A computer-readable storage medium, having stored thereon a computer program which, when executed by a processor, causes the processor to carry out the steps of the application recommendation method of any one of claims 1 to 3.
8. A computer arrangement, comprising a storage medium and a processor, the storage medium having a computer program stored thereon, the computer program, when executed by the processor, causing the processor to carry out the steps of the application recommendation method of any one of claims 1 to 3.
Priority Applications (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201410081705.0A CN104899220B (en) | 2014-03-06 | 2014-03-06 | Application program recommendation method and system |
| PCT/CN2015/073561 WO2015131803A1 (en) | 2014-03-06 | 2015-03-03 | Application recommending method and system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201410081705.0A CN104899220B (en) | 2014-03-06 | 2014-03-06 | Application program recommendation method and system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN104899220A CN104899220A (en) | 2015-09-09 |
| CN104899220B true CN104899220B (en) | 2021-06-25 |
Family
ID=54031887
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201410081705.0A Active CN104899220B (en) | 2014-03-06 | 2014-03-06 | Application program recommendation method and system |
Country Status (2)
| Country | Link |
|---|---|
| CN (1) | CN104899220B (en) |
| WO (1) | WO2015131803A1 (en) |
Families Citing this family (17)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107463574A (en) * | 2016-06-02 | 2017-12-12 | 广州市动景计算机科技有限公司 | Content information provides method, equipment, browser, electronic equipment and server |
| CN107844495B (en) * | 2016-09-19 | 2022-11-22 | 北京搜狗科技发展有限公司 | Application program recommendation method and device and electronic equipment |
| CN108614848B (en) * | 2017-01-11 | 2023-09-19 | 北京搜狗科技发展有限公司 | Application program recommendation method, device and equipment |
| CN106933624A (en) * | 2017-02-22 | 2017-07-07 | 深圳充电网科技有限公司 | A kind of Intelligent hardware control system and control method |
| CN106960367A (en) * | 2017-03-31 | 2017-07-18 | 北京猎豹移动科技有限公司 | Promotion method, device and the server of application program |
| CN107704494B (en) * | 2017-08-24 | 2021-09-14 | 深圳市来玩科技有限公司 | User information collection method and system based on application software |
| CN107819845B (en) * | 2017-11-06 | 2021-01-26 | 阿里巴巴（中国）有限公司 | Light application pushing method and device and server |
| CN109040794B (en) * | 2018-08-01 | 2021-05-25 | 北京奇艺世纪科技有限公司 | Video website diversion method and device |
| CN109254781B (en) * | 2018-09-06 | 2022-11-01 | 上海尚往网络科技有限公司 | Method and equipment for installing application on user equipment |
| CN109543092A (en) * | 2018-09-27 | 2019-03-29 | 深圳壹账通智能科技有限公司 | Financial product recommended method, device, storage medium and computer equipment |
| CN110262810B (en) * | 2019-06-13 | 2023-05-09 | 上海掌门科技有限公司 | Method and device for installing application |
| US11194866B2 (en) | 2019-08-08 | 2021-12-07 | Google Llc | Low entropy browsing history for content quasi-personalization |
| CN115766253A (en) | 2019-08-08 | 2023-03-07 | 谷歌有限责任公司 | Low entropy browsing history for content quasi-personalization |
| CN110750720B (en) * | 2019-10-21 | 2023-04-28 | 上海嵩恒网络科技股份有限公司 | PC-based scene individual recommendation method and system |
| CN110909286A (en) * | 2019-10-23 | 2020-03-24 | 云深互联(北京)科技有限公司 | Method, system and equipment for processing browser data |
| CN113641408A (en) * | 2020-04-23 | 2021-11-12 | 百度在线网络技术（北京）有限公司 | Method and device for generating shortcut entrance |
| CN112883275B (en) * | 2021-03-17 | 2024-01-19 | 北京乐我无限科技有限责任公司 | Live broadcast room recommendation method, device, server and medium |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102811371A (en) * | 2012-07-10 | 2012-12-05 | Tcl集团股份有限公司 | Method, system and device for recommending intelligent television application program |
| CN103327102A (en) * | 2013-06-24 | 2013-09-25 | 北京小米科技有限责任公司 | Application program recommending method and device |
| CN103455559A (en) * | 2011-12-27 | 2013-12-18 | 北京奇虎科技有限公司 | Method and device for automatically recommending application |
| EP2684106A1 (en) * | 2011-03-10 | 2014-01-15 | Alibaba Group Holding Limited | Determining preferred categories based on user access attribute values |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102999588A (en) * | 2012-11-15 | 2013-03-27 | 广州华多网络科技有限公司 | Method and system for recommending multimedia applications |
-
2014
- 2014-03-06 CN CN201410081705.0A patent/CN104899220B/en active Active
-
2015
- 2015-03-03 WO PCT/CN2015/073561 patent/WO2015131803A1/en active Application Filing
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP2684106A1 (en) * | 2011-03-10 | 2014-01-15 | Alibaba Group Holding Limited | Determining preferred categories based on user access attribute values |
| CN103455559A (en) * | 2011-12-27 | 2013-12-18 | 北京奇虎科技有限公司 | Method and device for automatically recommending application |
| CN102811371A (en) * | 2012-07-10 | 2012-12-05 | Tcl集团股份有限公司 | Method, system and device for recommending intelligent television application program |
| CN103327102A (en) * | 2013-06-24 | 2013-09-25 | 北京小米科技有限责任公司 | Application program recommending method and device |
Also Published As
| Publication number | Publication date |
|---|---|
| WO2015131803A1 (en) | 2015-09-11 |
| CN104899220A (en) | 2015-09-09 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN104899220B (en) | Application program recommendation method and system | |
| US10140368B2 (en) | Method and apparatus for generating a recommendation page | |
| KR102455232B1 (en) | Method and electronic device for tab management based on context | |
| US20160179816A1 (en) | Near Real Time Auto-Suggest Search Results | |
| CN104703125B (en) | Information recommendation method, device and terminal based on instant messaging | |
| US9916364B2 (en) | Personalization of news articles based on news sources | |
| JP7119124B2 (en) | Action indicator for search behavior output element | |
| CN104572798A (en) | Method, equipment and system for processing webpage | |
| EP3230867B1 (en) | Browser provided website statistics | |
| CN103870553B (en) | A kind of input resource supplying method and system | |
| CN107239701B (en) | Method and device for identifying malicious website | |
| US11176143B2 (en) | Location-aware content detection | |
| US10061806B2 (en) | Presenting previously selected search results | |
| WO2015185020A1 (en) | Information category obtaining method and apparatus | |
| CN108334516B (en) | Information pushing method and device | |
| US20160371708A1 (en) | Method and apparatus for determining a user's level of interest in web-based content | |
| CN107526748B (en) | Method and equipment for identifying user click behavior | |
| CN109145307B (en) | User portrait recognition method, pushing method, device, equipment and storage medium | |
| CN105528247B (en) | Information processing method and client | |
| CN104392000B (en) | Determine the method and apparatus that mobile site captures quota | |
| CN105589870B (en) | Method and system for filtering webpage advertisements | |
| CN110825976B (en) | Website page detection method and device, electronic equipment and medium | |
| US9558167B2 (en) | Method, system and web server for adding related microblogs on webpage | |
| CN110674386B (en) | Resource recommendation method, device and storage medium | |
| US20190087421A1 (en) | Dynamic content suggestion in sparse traffic environment |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |