WO2015131803A1 - Application recommending method and system - Google Patents

Application recommending method and system Download PDF

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Publication number
WO2015131803A1
WO2015131803A1 PCT/CN2015/073561 CN2015073561W WO2015131803A1 WO 2015131803 A1 WO2015131803 A1 WO 2015131803A1 CN 2015073561 W CN2015073561 W CN 2015073561W WO 2015131803 A1 WO2015131803 A1 WO 2015131803A1
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WO
WIPO (PCT)
Prior art keywords
application
application categories
browser
applications
web page
Prior art date
Application number
PCT/CN2015/073561
Other languages
French (fr)
Inventor
Xiaodan LIN
Original Assignee
Tencent Technology (Shenzhen) Company Limited
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by Tencent Technology (Shenzhen) Company Limited filed Critical Tencent Technology (Shenzhen) Company Limited
Publication of WO2015131803A1 publication Critical patent/WO2015131803A1/en

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    • 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

Definitions

  • the present disclosure relates to the field of computer technologies, and in particular, to an application recommending method and system.
  • APPs applications
  • Application operators generally promote applications by presenting related information to users in many ways, for example, by presenting information related to the applications to be promoted by means of web page content in websites, pop-up advertisements in web pages, and interfaces of various clients.
  • application recommendation information in various forms is disturbance to users to some extent.
  • users are less likely to accept the recommended applications. Therefore, pushing a massive amount of information related to applications without targeting at specific user groups is a waste of network bandwidth and computer system resources.
  • An exemplary application recommending method includes:
  • An exemplary application recommending system includes:
  • an accessed application acquiring module configured to acquire web page applications accessed through a browser
  • an accessed category acquiring module configured to acquire application categories to which the web page applications belong to obtain the application categories accessed through the browser
  • a category extracting module configured to calculate access indexes corresponding to the application categories accessed through the browser, and extract a preset number of the application categories having the access indexes that rank higher;
  • an application information acquiring module configured to acquire information about applications corresponding to the extracted application categories
  • an information pushing module configured to push the acquired information about the applications.
  • FIG. 1 is a schematic flowchart of an application recommending method according to an embodiment
  • FIG. 2 is a schematic flowchart of S106 in FIG. 1;
  • FIG. 3 is a schematic flowchart of S202 in FIG. 2 according to an embodiment
  • FIG. 4 is a schematic structural diagram of an application recommending system according to an embodiment
  • FIG. 5 is a schematic structural diagram of a category extracting module according to an embodiment
  • FIG. 6 is a schematic structural diagram of an application information acquiring module according to an embodiment
  • FIG. 7 is a schematic structural diagram of an application recommending system according to an embodiment
  • FIG. 8 is a schematic structural diagram of an application recommending system according to an embodiment
  • FIG. 9 is an architectural diagram of a computer system capable of implementing an embodiment of the present invention.
  • FIG. 10 is an architectural diagram of a server and a client capable of implementing an embodiment of the present invention.
  • FIG. 9 depicts an exemplary environment 600 incorporating exemplary application recommending methods and systems in accordance with various disclosed embodiments.
  • the environment 600 can include a server 604, a terminal 606, and a communication network 602.
  • the server 604 and the terminal 606 may be coupled through the communication network 602 for information exchange.
  • any number of terminals 606 or servers 604 may be included, and other devices may also be included.
  • the communication network 602 may include any appropriate type of communication network for providing network connections to the server 604 and terminal 606 or among multiple servers 604 or terminals 606.
  • the communication network 602 may include the Internet or other types of computer networks or telecommunication networks, either wired or wireless.
  • a terminal may refer to any appropriate user terminal with certain computing capabilities, e.g., a personal computer (PC), a work station computer, a hand-held computing device (e.g., a tablet), a mobile terminal (e.g., a mobile phone or a smart phone), or any other client-side computing device.
  • PC personal computer
  • work station computer e.g., a work station computer
  • hand-held computing device e.g., a tablet
  • a mobile terminal e.g., a mobile phone or a smart phone
  • a server may refer to one or more server computers configured to provide certain server functionalities, e.g., acquire web page applications accessed through a browser; acquire application categories to which the web page applications belong to obtain the application categories accessed through the browser; calculate access indexes corresponding to the application categories accessed through the browser, and extract a preset number of the application categories having the access indexes that rank higher; acquire information about applications corresponding to the extracted application categories; and push the acquired information about the applications.
  • a server may also include one or more processors to execute computer programs in parallel.
  • FIG. 10 shows a block diagram of an exemplary computing system 700 (or computer system 700) capable of implementing the server 604 and/or the terminal 606.
  • the exemplary computer system 700 may include a processor 702, a storage medium 704, a monitor 706, a communication module 708, a database 710, peripherals 712, and one or more bus 714 to couple the devices together. Certain devices may be omitted and other devices may be included.
  • the processor 702 can include any appropriate processor or processors. Further, the processor 702 can include multiple cores for multi-thread or parallel processing.
  • the storage medium 704 may include memory modules, e.g., Read-Only Memory (ROM), Random Access Memory (RAM), and flash memory modules, and mass storages, e.g., CD-ROM, U-disk, removable hard disk, etc.
  • the storage medium 704 may store computer programs for implementing various processes, when executed by the processor 702.
  • the monitor 706 may include display devices for displaying contents in the computing system 700.
  • the peripherals 712 may include I/O devices such as keyboard and mouse.
  • the communication module 708 may include network devices for establishing connections through the communication network 602.
  • the database 710 may include one or more databases for storing certain data and for performing certain operations on the stored data, e.g., access indexes corresponding to the application categories accessed through the browser, a preset number of the application categories having the access indexes that rank higher; information about applications corresponding to the extracted application categories; and the acquired information to be pushed about the applications.
  • the terminal 606 may cause the server 604 to perform certain actions, e.g., acquire web page applications accessed through a browser; acquire application categories to which the web page applications belong to obtain the application categories accessed through the browser; calculate access indexes corresponding to the application categories accessed through the browser, and extract a preset number of the application categories having the access indexes that rank higher; acquire information about applications corresponding to the extracted application categories; and push the acquired information about the applications.
  • the server 604 may be configured to provide structures and functions for such actions and operations.
  • a terminal involved in the disclosed methods and systems can include the terminal 606, while a server involved in the disclosed methods and systems can include the server 604.
  • the methods and systems disclosed in accordance with various embodiments can be executed by a computer system.
  • the disclosed methods and systems can be implemented by a server.
  • an application recommending method implemented by the server 604, includes:
  • S102 Acquire web page applications accessed through a browser.
  • the applications may be web page applications (Web apps), which may be operated through a web page browser on the Internet or an enterprise Intranet.
  • Web apps web page applications
  • a web page application is written in a web language (e.g., programming languages such as HTML, JavaScript, and Java), and generally needs to be accessed through a browser.
  • web page applications with shortcuts added to the browser can be acquired.
  • shortcuts of the web page applications to the browser for example, add bookmarks or quick links of the web page applications, and add the web page applications to the favorites list of the browser.
  • a user can conveniently access the web page applications with the shortcuts, and these web page applications are usually applications that the user is interested in and accesses frequently.
  • the web page applications include but are not limited to:
  • the web page applications with access frequencies to which through the browser satisfy a preset condition can be acquired.
  • the preset condition may be a preset threshold, for example, three times per month.
  • the web page applications with access frequencies to which through the browser reach the preset threshold may be acquired.
  • the preset condition may also be a preset number of access frequencies that rank higher. In S102, the preset number of web page applications with the access frequencies that rank higher may be acquired.
  • the web page applications with shortcuts added to the browser and the web page applications with access frequencies to which through the browser satisfy the preset condition may be acquired.
  • the web page applications with shortcuts added to the browser or with access frequencies to which through the browser satisfy the preset condition are acquired, so as to acquire the web page applications that the user is interested in from the web page applications accessed by the user.
  • web page applications that the user is more interested in can be acquired according to the web page applications that the user is interested in later.
  • S104 Acquire application categories to which the web page applications accessed through the browser belong to obtain the application categories accessed through the browser.
  • the application category of each web page application accessed through the browser may be acquired.
  • the application categories may be set in advance, the web page applications corresponding to the application categories are then set, and the corresponding relations between the application categories and the web page applications are stored.
  • the application categories may be set according to application categories input by the user, and the web page applications corresponding to the application categories may be set according to the web page applications corresponding to the application categories input by the user.
  • the following application categories may be set: entertainment, tools, social, music, efficiency, life, reference, travel, sports, navigation, news, finance, photography, food, and transportation, and it may be set that web page applications corresponding to the application category of music include Grooveshark, Pandora, and the like.
  • the corresponding application categories can be found according to the web page applications acquired in S102 based on the corresponding relations between the application categories and the web page applications stored in advance, and the application categories to which the web page applications belong are marked.
  • the application categories can be set in advance, and key words corresponding to the application categories are recorded.
  • the application categories can be set according to the application categories input by the user.
  • the user may search names of the application categories, and then high-frequency words in the search results are recorded.
  • the obtained high-frequency words are used as the key words corresponding to the application categories.
  • corresponding relations between the application categories and the key words are stored.
  • pages of the web page applications are accessed and high-frequency words in the pages of the web page applications are extracted, and then the extracted high-frequency words are compared with the key words corresponding to the application categories.
  • the application category having the highest matching degree is acquired and used as the application category to which the web page application belongs.
  • the application categories accessed through the browser can be obtained by acquiring a set of application categories to which all web page applications accessed through the browser belong.
  • S106 Calculate access indexes corresponding to the application categories accessed through the browser, and extract a preset number of the application categories having the access indexes that rank higher.
  • S106 includes the following:
  • S202 Calculate access durations corresponding to the application categories accessed through the browser, and extract the preset number of the application categories corresponding to the access durations that rank higher.
  • the calculating access durations corresponding to the application categories accessed through the browser includes:
  • S302 Acquire the access durations of the web page applications according to access histories to the web page applications.
  • the application recommending method further includes a process for forming the access histories to the web page applications, which includes: monitoring and recording start time and end time of accessing the web page applications through the browser to obtain the access histories to the web page applications.
  • the access duration of a web page application can be obtained by calculating separate access durations of the web page application according to the start time and end time of each access to the web page application in the access history of the web page application, and summing the separate access durations.
  • S304 Sum the access durations of the web page applications in the same application category to obtain the access durations corresponding to various application categories.
  • the application categories can be sorted in a descending order according to the corresponding access durations, and the preset number of the application categories that rank higher in the sequence of application categories sorted in the descending order according to the access durations are extracted.
  • S204 Calculate quantities of the web page applications in the application categories accessed through the browser, and extract the preset number of the application categories in which the quantities rank higher.
  • the application categories can be sorted in a descending order according to the quantities of the web page applications therein, and the preset number of the application categories that rank higher in the sequence of application categories sorted in the descending order according to the quantities of the web page applications therein are extracted.
  • S106 may include only S202 or only S204.
  • the application categories that the user is interested in can be obtained by acquiring the application categories with longer access durations or including more web page applications accessed through the browser.
  • the application categories that the user is more interested in can be acquired by acquiring the common application categories of the application categories with longer access durations and the application categories including more web page applications accessed through the browser.
  • the application recommending method further includes: setting the application categories in advance, setting the applications corresponding to the application categories, and storing the corresponding relations between the application categories and the applications.
  • the application categories may be set according to application categories input by the user, and the applications corresponding to the application categories may be set according to the applications corresponding to the application categories input by the user.
  • the application recommending method further includes: setting the application categories, searching names of the application categories, extracting the applications in the search results, and storing the corresponding relations between the application categories and the extracted applications.
  • the application categories can be set according to the application categories input by the user.
  • the information about the applications acquired in S108 includes names, icons, download addresses or download links, introductions, and the like of the applications.
  • S108 includes: acquiring information about web page applications that are not accessed through the browser corresponding to the extracted application categories.
  • the web page applications that have been accessed through the browser can be acquired.
  • the applications corresponding to the application categories extracted in S106 are found according to the corresponding relations between the application categories and the applications stored in advance, and the web page applications that have been accessed through the browser are filtered out to obtain the web page applications that are not accessed through the browser. Additionally or alternatively, the information related to the obtained web page applications is acquired.
  • S108 includes: acquiring information about applications that are not installed at a local end of the browser corresponding to the extracted application categories.
  • the local end of the browser refers to a device on which the browser runs.
  • the applications that have been installed at the local end of the browser can be acquired.
  • the applications corresponding to the application categories extracted in S106 are found according to the corresponding relations between the application categories and the applications stored in advance, and the applications that have been installed at the local end of the browser are filtered out to obtain the applications that are not installed at the local end of the browser. Additionally or alternatively, the information related to the obtained web page applications is acquired.
  • S108 includes: acquiring information about web page applications that are not accessed through the browser corresponding to the extracted application categories, and acquiring information about applications that are not installed at a local end of the browser corresponding to the extracted application categories.
  • the browser acquires the web page applications accessed through the browser, and sends the information about the acquired web page applications to a server.
  • the server acquires the application categories to which the web page applications belong, obtains the application categories accessed through the browser, calculates the access indexes corresponding to the application categories accessed through the browser, extracts the predetermined number of the application categories having the access indexes that rank higher, obtains information about the applications corresponding to the extracted application categories, and further delivers the acquired information about the applications to the browser.
  • the application recommending method further includes: presenting the information about the applications by means of the browser.
  • a pop-up window may be generated by the browser, and the information about the applications is displayed in the pop-up window; alternatively, the information about the applications may be loaded to the web page content and presented by means of the browser.
  • an application recommending system includes an accessed application acquiring module 10, an accessed category acquiring module 20, a category extracting module 30, an application information acquiring module 40, and an information pushing module 50.
  • the accessed application acquiring module 10 is configured to acquire web page applications accessed through a browser.
  • the accessed application acquiring module 10 is configured to acquire web page applications with shortcuts added to the browser.
  • shortcuts of the web page applications to the browser for example, add bookmarks or quick links of the web page applications, and add the web page applications to the favorites list of the browser.
  • a user can conveniently access the web page applications with the shortcuts, and these web page applications are usually applications that the user is interested in and accesses frequently.
  • the accessed application acquiring module 10 is configured to acquire web page applications with access frequencies to which through the browser satisfy a preset condition.
  • the preset condition may be a preset threshold, for example, three times per month.
  • the accessed application acquiring module 10 is configured to acquire the web page applications with access frequencies to which through the browser reach the preset threshold.
  • the preset condition may also be a preset number of access frequencies that rank higher.
  • the accessed application acquiring module 10 is configured to acquire the preset number of web page applications with the access frequencies that rank higher.
  • the accessed application acquiring module 10 is configured to acquire the web page applications with shortcuts added to the browser and the web page applications with access frequencies to which through the browser satisfy the preset condition.
  • the web page applications with shortcuts added to the browser or with access frequencies to which through the browser satisfy the preset condition are acquired, so as to acquire the web page applications that the user is interested in from the web page applications accessed by the user.
  • web page applications that the user is more interested in can be acquired according to the web page applications that the user is interested in later.
  • the accessed category acquiring module 20 is configured to acquire application categories to which the web page applications accessed through the browser belong to obtain the application categories accessed through the browser.
  • the accessed category acquiring module 20 may acquire the application category of each web page application accessed through the browser.
  • the application recommending system further includes a category setting module, a corresponding web page application setting module, and a first storage module (not shown).
  • the category setting module is configured to set the application categories in advance.
  • the corresponding web page application setting module is configured to set the web page applications corresponding to the application categories.
  • the first storage module is configured to store corresponding relations between the application categories and the web page applications.
  • the application categories may be set according to application categories input by the user, and the web page applications corresponding to the application categories may be set according to the web page applications corresponding to the application categories input by the user.
  • the category setting module may sets the following application categories: entertainment, tools, social, music, efficiency, life, reference, travel, sports, navigation, news, finance, photography, food, and transportation
  • the corresponding web page application setting module may set that web page applications corresponding to the application category of music include Grooveshark, Pandora, and the like.
  • the accessed category acquiring module 20 may search for the corresponding application categories according to the web page applications acquired by the accessed application acquiring module 10 based on the corresponding relations between the application categories and the web page applications stored in advance, and mark the application categories to which the web page applications belong.
  • the application recommending system may further include a category setting module, a corresponding key word recording module, and a second storage module (not shown).
  • the category setting module is as described above.
  • the corresponding key word recording module may search names of the application categories, record high-frequency words in the search results, and use the obtained high-frequency words as the key words corresponding to the application categories.
  • the second storage module is configured to store corresponding relations between the application categories and the corresponding key words.
  • the accessed category acquiring module 20 may access pages of the web page applications, extract high-frequency words in the pages of the web page applications, compare the extracted high-frequency words with the key words corresponding to the application categories, acquire the application category having the highest matching degree and use the application category as the application category to which a web page application belongs.
  • the accessed category acquiring module 20 obtains the application categories accessed through the browser by acquiring a set of application categories to which all web page applications accessed through the browser belong.
  • the category extracting module 30 is configured to calculate access indexes corresponding to the application categories accessed through the browser, and extract a preset number of the application categories having the access indexes that rank higher.
  • the category extracting module 30 includes a first category extracting module 320, a second category extracting module 340, and a common category extracting module 360.
  • the first category extracting module 320 is configured to calculate access durations corresponding to the application categories accessed through the browser, and extract the preset number of the application categories corresponding to the access durations that rank higher.
  • the first category extracting module 320 may acquire the access durations of the web page applications according to access histories to the web page applications.
  • the application recommending system further includes an access history generating module (not shown), configured to generate the access histories to the web page applications.
  • the access history generating module is configured to monitor and record start time and end time of accessing the web page applications through the browser to obtain the access histories to the web page applications.
  • the first category extracting module 320 may obtain the access duration of a web page application by calculating separate access durations of the web page application according to the start time and end time of each access to the web page application in the access history of the web page application, and summing the separate access durations.
  • the first category extracting module 320 may sum the access durations of the web page applications in the same application category to obtain the access durations corresponding to various application categories.
  • the first category extracting module 320 may sort the application categories in a descending order according to the corresponding access durations, and extract the preset number of the application categories that rank higher in the sequence of application categories sorted in the descending order according to the access durations.
  • the second category extracting module 340 is configured to calculate quantities of the web page applications in the application categories accessed through the browser, and extract the preset number of the application categories in which the quantities rank higher.
  • the second category extracting module 340 may sort the application categories in a descending order according to the quantities of the web page applications therein, and extract the preset number of the application categories that rank higher in the sequence of application categories sorted in the descending order according to the quantities of the web page applications therein.
  • the common category extracting module 360 is configured to extract common application categories from the application categories extracted by the first category extracting module 320 and the second category extracting module 340.
  • the category extracting module 30 may include only the first category extracting module 320 or only the second category extracting module 340.
  • the application categories that the user is interested in can be obtained by acquiring the application categories with longer access durations or including more web page applications accessed through the browser.
  • the application categories that the user is more interested in can be acquired by acquiring the common application categories of the application categories with longer access durations and the application categories including more web page applications accessed through the browser.
  • the application information acquiring module 40 is configured to acquire information about applications corresponding to the extracted application categories.
  • the application recommending system further includes a category setting module, a corresponding application setting module, and a third storage module (not shown).
  • the category setting module is as described above.
  • the corresponding application setting module is configured to set the applications corresponding to the application categories.
  • the third storage module is configured to store corresponding relations between the application categories and the applications.
  • the applications corresponding to the application categories may also be set according to the applications corresponding to the application categories input by the user.
  • the application recommending system further includes a category setting module, a searching and result extracting module, and a fourth storage module (not shown).
  • the category setting module is as described above.
  • the searching and result extracting module is configured to search names of the application categories, extract the applications in the search results, and store corresponding relations between the application categories and the extracted applications.
  • the information about the applications acquired by the application information acquiring module 40 includes names, icons, download addresses or download links, introductions, and the like of the applications.
  • the application information acquiring module 40 includes a not-accessed application information acquiring module 402 and a not-installed application information acquiring module 404.
  • the not-accessed application information acquiring module 402 is configured to acquire information about web page applications that are not accessed through the browser corresponding to the extracted application categories.
  • the not-accessed application information acquiring module 402 may acquire the web page applications that have been accessed through the browser, search for the applications corresponding to the application categories extracted by the category extracting module 30 according to the corresponding relations between the application categories and the applications stored in advance, and filter out the web page applications that have been accessed through the browser to obtain the web page applications that are not accessed through the browser. Additionally or alternatively, the not-accessed application information acquiring module 402 may acquire the information related to the obtained web page applications.
  • the not-installed application information acquiring module 404 is configured to acquire information about applications that are not installed at a local end of the browser corresponding to the extracted application categories.
  • the local end of the browser refers to a device on which the browser runs.
  • the not-installed application information acquiring module 404 may acquire the applications that have been installed at the local end of the browser can be acquired, search for the applications corresponding to the application categories extracted module 30 according to the corresponding relations between the application categories and the applications stored in advance, and filter out the applications that have been installed at the local end of the browser to obtain the applications that are not installed at the local end of the browser. Additionally or alternatively, not-installed application information acquiring module 404 may acquire the information related to the obtained web page applications.
  • the application information acquiring module 40 may include only the not-accessed application information acquiring module 402 or only the not-installed application information acquiring module 404.
  • the information pushing module 50 is configured to push the acquired information about the applications.
  • the accessed application acquiring module 10 runs on the browser, and the accessed category acquiring module 20, the category extracting module 30, the application information acquiring module 40, and the information pushing module 50 run on the server.
  • the application recommending system further includes a sending module 60 running on the browser, configured to send the information about the web page applications acquired by the accessed application acquiring module 10 to the server.
  • the information pushing module 50 is configured to deliver the information about the web page applications acquired by the application acquiring module 40 to the browser.
  • the application recommending system further includes a presenting module 70 running on the browser, configured to display the information about the applications delivered by the information pushing module 50.
  • the presenting module 70 may generate a pop-up window, and display the information about the applications in the pop-up window; alternatively, the presenting module 70 may load the information about the applications to the web page content to present the information about the applications.
  • application categories to which web page applications accessed through a browser belong are acquired, access indexes corresponding to the application categories accessed through the browser are calculated, information about applications corresponding to the application categories having the access indexes that rank higher is acquired, and the information about the applications is recommended to a user.
  • the web page applications accessed through the browser are web page applications that have been used by the user, and the application categories having the access indexes that rank higher may represent the categories to which the web page applications that the user is interested in belong.
  • the application recommending method and system can calculate the application categories to which the web page applications that the user is interested in belong, acquire information about web page applications corresponding to the application categories that the user is interested in, and recommend the information about the web page applications to the user.
  • the user is more likely to accept the recommended applications.
  • the method and system can improve utilization of network bandwidth and computer system resources.

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Abstract

An application recommending method includes: acquiring web page applications accessed through a browser; acquiring application categories to which the web page applications belong to obtain the application categories accessed through the browser; calculating access indexes corresponding to the application categories accessed through the browser, and extracting a preset number of the application categories having the access indexes that rank higher; acquiring information about applications corresponding to the extracted application categories; and pushing the acquired information about the applications.

Description

APPLICATION RECOMMENDING METHOD AND SYSTEM
FIELD OF THE TECHNOLOGY
The present disclosure relates to the field of computer technologies, and in particular, to an application recommending method and system.
BACKGROUND OF THE DISCLOSURE
The development of applications (APPs) depends on the number of and coverage on user groups, and needs promotion. Application operators generally promote applications by presenting related information to users in many ways, for example, by presenting information related to the applications to be promoted by means of web page content in websites, pop-up advertisements in web pages, and interfaces of various clients.
In one aspect, application recommendation information in various forms is disturbance to users to some extent. In another aspect, users are less likely to accept the recommended applications. Therefore, pushing a massive amount of information related to applications without targeting at specific user groups is a waste of network bandwidth and computer system resources.
SUMMARY
An exemplary application recommending method includes:
acquiring web page applications accessed through a browser;
acquiring application categories to which the web page applications belong to obtain the application categories accessed through the browser;
calculating access indexes corresponding to the application categories accessed through the browser, and extracting a preset number of the application categories having the access indexes that rank higher;
acquiring information about applications corresponding to the extracted application categories; and
pushing the acquired information about the applications.
An exemplary application recommending system includes:
an accessed application acquiring module, configured to acquire web page applications accessed through a browser;
an accessed category acquiring module, configured to acquire application categories to which the web page applications belong to obtain the application categories accessed through the browser;
a category extracting module, configured to calculate access indexes corresponding to the application categories accessed through the browser, and extract a preset number of the application categories having the access indexes that rank higher;
an application information acquiring module, configured to acquire information about applications corresponding to the extracted application categories; and
an information pushing module, configured to push the acquired information about the applications.
BRIEF DESCRIPTION OF THE DRAWINGS
FIG. 1 is a schematic flowchart of an application recommending method according to an embodiment;
FIG. 2 is a schematic flowchart of S106 in FIG. 1;
FIG. 3 is a schematic flowchart of S202 in FIG. 2 according to an embodiment;
FIG. 4 is a schematic structural diagram of an application recommending system according to an embodiment;
FIG. 5 is a schematic structural diagram of a category extracting module according to an embodiment;
FIG. 6 is a schematic structural diagram of an application information acquiring module according to an embodiment;
FIG. 7 is a schematic structural diagram of an application recommending system according to an embodiment;
FIG. 8 is a schematic structural diagram of an application recommending system according to an embodiment;
FIG. 9 is an architectural diagram of a computer system capable of implementing an embodiment of the present invention; and
FIG. 10 is an architectural diagram of a server and a client capable of implementing an embodiment of the present invention.
DESCRIPTION OF EMBODIMENTS
In order to make the objectives, technical solutions, and advantages of the present disclosure more comprehensible, the present disclosure 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 used for explaining the present disclosure, instead of limiting the present disclosure.
Unless the context clearly indicates otherwise, singular elements or components in the present disclosure may be in the plural and vice versa, which is not limited in the present disclosure. Although steps in the present disclosure are labeled with numbers, such numbers are not intended to limit the order of these steps. Unless the order of steps is explicitly stated or it is explicitly stated that a step needs to be performed on the basis of another step, the relative order of steps can be adjusted. It may be understood that, the term "and/or" used in the specification involves and includes any or all possible combinations of one or more associated listed items.
FIG. 9 depicts an exemplary environment 600 incorporating exemplary application recommending methods and systems in accordance with various disclosed embodiments. As shown in FIG. 9, the environment 600 can include a server 604, a terminal 606, and a communication network 602. The server 604 and the terminal 606 may be coupled through the communication network 602 for information exchange. Although only one terminal 606 and one server 604 are shown in the environment 600, any number of terminals 606 or servers 604 may be included, and other devices may also be included.
The communication network 602 may include any appropriate type of communication network for providing network connections to the server 604 and terminal 606 or among multiple servers 604 or terminals 606. For example, the communication network 602 may include the Internet or other types of computer networks or telecommunication networks, either wired or wireless.
A terminal, as used herein, may refer to any appropriate user terminal with certain computing capabilities, e.g., a personal computer (PC), a work station computer, a hand-held computing device (e.g., a tablet), a mobile terminal (e.g., a mobile phone or a smart phone), or any other client-side computing device.
A server, as used herein, may refer to one or more server computers configured to provide certain server functionalities, e.g., acquire web page applications accessed through a browser; acquire application categories to which the web page applications belong to obtain the application categories accessed through the browser; calculate access indexes corresponding to the application categories accessed through the browser, and extract a preset number of the application categories having the access indexes that rank higher; acquire information about applications corresponding to the extracted application categories; and push the acquired information about the applications. A server may also include one or more processors to execute computer programs in parallel.
The server 604 and the terminal 606 may be implemented on any appropriate computing platform. FIG. 10 shows a block diagram of an exemplary computing system 700 (or computer system 700) capable of implementing the server 604 and/or the terminal 606. As shown in FIG. 10, the exemplary computer system 700 may include a processor 702, a storage medium 704, a monitor 706, a communication module 708, a database 710, peripherals 712, and one or more bus 714 to couple the devices together. Certain devices may be omitted and other devices may be included.
The processor 702 can include any appropriate processor or processors. Further, the processor 702 can include multiple cores for multi-thread or parallel processing. The storage medium 704 may include memory modules, e.g., Read-Only Memory (ROM), Random Access Memory (RAM), and flash memory modules, and mass storages, e.g., CD-ROM, U-disk, removable hard disk, etc. The storage medium 704 may store computer programs for implementing various processes, when executed by the processor 702.
The monitor 706 may include display devices for displaying contents in the computing system 700. The peripherals 712 may include I/O devices such as keyboard and mouse.
Further, the communication module 708 may include network devices for establishing connections through the communication network 602. The database 710 may include one or more databases for storing certain data and for performing certain operations on the stored data, e.g., access indexes corresponding to the application categories accessed through the browser, a preset number of the application categories having the access indexes that rank higher; information about applications corresponding to the extracted application categories; and the acquired information to be pushed about the applications.
In operation, the terminal 606 may cause the server 604 to perform certain actions, e.g., acquire web page applications accessed through a browser; acquire application categories to which the web page applications belong to obtain the application categories accessed through the browser; calculate access indexes corresponding to the application categories accessed through the browser, and extract a preset number of the application categories having the access indexes that rank higher; acquire information about applications corresponding to the extracted application categories; and push the acquired information about the applications. The server 604 may be configured to provide structures and functions for such actions and operations.
In various embodiments, a terminal involved in the disclosed methods and systems can include the terminal 606, while a server involved in the disclosed methods and systems can include the server 604. The methods and systems disclosed in accordance with various embodiments can be executed by a computer system. In one embodiment, the disclosed methods and systems can be implemented by a server.
Various embodiments provide methods and systems for processing report information. The methods and systems are illustrated in various examples described herein.
In the embodiment shown in FIG. 1, an application recommending method, implemented by the server 604, includes:
S102: Acquire web page applications accessed through a browser.
In some embodiments, the applications may be web page applications (Web apps), which may be operated through a web page browser on the Internet or an enterprise Intranet. A web page application is written in a web language (e.g., programming languages such as HTML, JavaScript, and Java), and generally needs to be accessed through a browser. In some embodiments, web page applications with shortcuts added to the browser can be acquired. There are many ways to add shortcuts of the web page applications to the browser, for example, add bookmarks or quick links of the web page applications, and add the web page applications to the favorites list of the browser. A user can conveniently access the web page applications with the shortcuts, and these web page applications are usually applications that the user is interested in and accesses frequently.
The web page applications include but are not limited to:
Webmail, online shops, online auction, wiki, online forums, blogs, online games, and other applications.
In another embodiment, the web page applications with access frequencies to which through the browser satisfy a preset condition can be acquired. The preset condition may be a preset threshold, for example, three times per month. In S102, the web page applications with access frequencies to which through the browser reach the preset threshold may be acquired. The preset condition may also be a preset number of access frequencies that rank higher. In S102, the preset number of web page applications with the access frequencies that rank higher may be acquired.
In another embodiment, the web page applications with shortcuts added to the browser and the web page applications with access frequencies to which through the browser satisfy the preset condition may be acquired.
In the above embodiments, the web page applications with shortcuts added to the browser or with access frequencies to which through the browser satisfy the preset condition are acquired, so as to acquire the web page applications that the user is interested in from the web page applications accessed by the user. Hence, web page applications that the user is more interested in can be acquired according to the web page applications that the user is interested in later.
S104: Acquire application categories to which the web page applications accessed through the browser belong to obtain the application categories accessed through the browser.
Firstly, the application category of each web page application accessed through the browser may be acquired.
In one embodiment, the application categories may be set in advance, the web page applications corresponding to the application categories are then set, and the corresponding relations between the application categories and the web page applications are stored. The application categories may be set according to application categories input by the user, and the web page applications corresponding to the application categories may be set according to the web page applications corresponding to the application categories input by the user. For example, the following application categories may be set: entertainment, tools, social, music, efficiency, life, reference, travel, sports, navigation, news, finance, photography, food, and transportation, and it may be set that web page applications corresponding to the application category of music include Grooveshark, Pandora, and the like. In S104, the corresponding application categories can be found according to the web page applications acquired in S102 based on the corresponding relations between the application categories and the web page applications stored in advance, and the application categories to which the web page applications belong are marked.
In another embodiment, the application categories can be set in advance, and key words corresponding to the application categories are recorded. The application categories can be set according to the application categories input by the user. In one embodiment, the user may search names of the application categories, and then high-frequency words in the search results are recorded. The obtained high-frequency words are used as the key words corresponding to the application categories. Additionally or alternatively, corresponding relations between the application categories and the key words are stored. In S104, pages of the web page applications are accessed and high-frequency words in the pages of the web page applications are extracted, and then the extracted high-frequency words are compared with the key words corresponding to the application categories. For a web page application, the application category having the highest matching degree is acquired and used as the application category to which the web page application belongs.
Additionally or alternatively, the application categories accessed through the browser can be obtained by acquiring a set of application categories to which all web page applications accessed through the browser belong.
S106: Calculate access indexes corresponding to the application categories accessed through the browser, and extract a preset number of the application categories having the access indexes that rank higher.
As shown in FIG. 2, in one embodiment, S106 includes the following:
S202: Calculate access durations corresponding to the application categories accessed through the browser, and extract the preset number of the application categories corresponding to the access durations that rank higher.
As shown in FIG. 3, the calculating access durations corresponding to the application categories accessed through the browser includes:
S302: Acquire the access durations of the web page applications according to access histories to the web page applications.
In this embodiment, the application recommending method further includes a process for forming the access histories to the web page applications, which includes: monitoring and recording start time and end time of accessing the web page applications through the browser to obtain the access histories to the web page applications.
In S302, the access duration of a web page application can be obtained by calculating separate access durations of the web page application according to the start time and end time of each access to the web page application in the access history of the web page application, and summing the separate access durations.
S304: Sum the access durations of the web page applications in the same application category to obtain the access durations corresponding to various application categories.
Additionally or alternatively, the application categories can be sorted in a descending order according to the corresponding access durations, and the preset number of the application categories that rank higher in the sequence of application categories sorted in the descending order according to the access durations are extracted.
S204: Calculate quantities of the web page applications in the application categories accessed through the browser, and extract the preset number of the application categories in which the quantities rank higher.
The application categories can be sorted in a descending order according to the quantities of the web page applications therein, and the preset number of the application categories that rank higher in the sequence of application categories sorted in the descending order according to the quantities of the web page applications therein are extracted.
S206: Extract common application categories from the application categories extracted in the above two steps.
In one embodiment, S106 may include only S202 or only S204. In this embodiment, the application categories that the user is interested in can be obtained by acquiring the application categories with longer access durations or including more web page applications accessed through the browser.
In the above embodiment, the application categories that the user is more interested in can be acquired by acquiring the common application categories of the application categories with longer access durations and the application categories including more web page applications accessed through the browser.
S108: Acquire information about applications corresponding to the extracted application categories.
In one embodiment, before S108, the application recommending method further includes: setting the application categories in advance, setting the applications corresponding to the application categories, and storing the corresponding relations between the application categories and the applications. The application categories may be set according to application categories input by the user, and the applications corresponding to the application categories may be set according to the applications corresponding to the application categories input by the user. In another embodiment, before S108, the application recommending method further includes: setting the application categories, searching names of the application categories, extracting the applications in the search results, and storing the corresponding relations between the application categories and the extracted applications. Similarly, the application categories can be set according to the application categories input by the user.
The information about the applications acquired in S108 includes names, icons, download addresses or download links, introductions, and the like of the applications.
In one embodiment, S108 includes: acquiring information about web page applications that are not accessed through the browser corresponding to the extracted application categories.
The web page applications that have been accessed through the browser can be acquired. The applications corresponding to the application categories extracted in S106 are found according to the corresponding relations between the application categories and the applications stored in advance, and the web page applications that have been accessed through the browser are filtered out to obtain the web page applications that are not accessed through the browser. Additionally or alternatively, the information related to the obtained web page applications is acquired.
In another embodiment, S108 includes: acquiring information about applications that are not installed at a local end of the browser corresponding to the extracted application categories.
The local end of the browser refers to a device on which the browser runs. The applications that have been installed at the local end of the browser can be acquired. The applications corresponding to the application categories extracted in S106 are found according to the corresponding relations between the application categories and the applications stored in advance, and the applications that have been installed at the local end of the browser are filtered out to obtain the applications that are not installed at the local end of the browser. Additionally or alternatively, the information related to the obtained web page applications is acquired.
In another embodiment, S108 includes: acquiring information about web page applications that are not accessed through the browser corresponding to the extracted application categories, and acquiring information about applications that are not installed at a local end of the browser corresponding to the extracted application categories.
S110: Push the acquired information about the applications.
In one embodiment, the browser acquires the web page applications accessed through the browser, and sends the information about the acquired web page applications to a server. The server acquires the application categories to which the web page applications belong, obtains the application categories accessed through the browser, calculates the access indexes corresponding to the application categories accessed through the browser, extracts the predetermined number of the application categories having the access indexes that rank higher, obtains information about the applications corresponding to the extracted application categories, and further delivers the acquired information about the applications to the browser.
In one embodiment, the application recommending method further includes: presenting the information about the applications by means of the browser. In one embodiment, a pop-up window may be generated by the browser, and the information about the applications is displayed in the pop-up window; alternatively, the information about the applications may be loaded to the web page content and presented by means of the browser.
In the embodiment shown in FIG. 4, an application recommending system includes an accessed application acquiring module 10, an accessed category acquiring module 20, a category extracting module 30, an application information acquiring module 40, and an information pushing module 50.
The accessed application acquiring module 10 is configured to acquire web page applications accessed through a browser.
In one embodiment, the accessed application acquiring module 10 is configured to acquire web page applications with shortcuts added to the browser. There are many ways to add shortcuts of the web page applications to the browser, for example, add bookmarks or quick links of the web page applications, and add the web page applications to the favorites list of the browser. A user can conveniently access the web page applications with the shortcuts, and these web page applications are usually applications that the user is interested in and accesses frequently.
In another embodiment, the accessed application acquiring module 10 is configured to acquire web page applications with access frequencies to which through the browser satisfy a preset condition. The preset condition may be a preset threshold, for example, three times per month. The accessed application acquiring module 10 is configured to acquire the web page applications with access frequencies to which through the browser reach the preset threshold. The preset condition may also be a preset number of access frequencies that rank higher. The accessed application acquiring module 10 is configured to acquire the preset number of web page applications with the access frequencies that rank higher.
In another embodiment, the accessed application acquiring module 10 is configured to acquire the web page applications with shortcuts added to the browser and the web page applications with access frequencies to which through the browser satisfy the preset condition.
In the above embodiments, the web page applications with shortcuts added to the browser or with access frequencies to which through the browser satisfy the preset condition are acquired, so as to acquire the web page applications that the user is interested in from the web page applications accessed by the user. Hence, web page applications that the user is more interested in can be acquired according to the web page applications that the user is interested in later.
The accessed category acquiring module 20 is configured to acquire application categories to which the web page applications accessed through the browser belong to obtain the application categories accessed through the browser.
Firstly, the accessed category acquiring module 20 may acquire the application category of each web page application accessed through the browser.
In one embodiment, the application recommending system further includes a category setting module, a corresponding web page application setting module, and a first storage module (not shown). The category setting module is configured to set the application categories in advance. The corresponding web page application setting module is configured to set the web page applications corresponding to the application categories. The first storage module is configured to store corresponding relations between the application categories and the web page applications. The application categories may be set according to application categories input by the user, and the web page applications corresponding to the application categories may be set according to the web page applications corresponding to the application categories input by the user. For example, the category setting module may sets the following application categories: entertainment, tools, social, music, efficiency, life, reference, travel, sports, navigation, news, finance, photography, food, and transportation, and the corresponding web page application setting module may set that web page applications corresponding to the application category of music include Grooveshark, Pandora, and the like. The accessed category acquiring module 20 may search for the corresponding application categories according to the web page applications acquired by the accessed application acquiring module 10 based on the corresponding relations between the application categories and the web page applications stored in advance, and mark the application categories to which the web page applications belong.
In another embodiment, the application recommending system may further include a category setting module, a corresponding key word recording module, and a second storage module (not shown).The category setting module is as described above. In one embodiment, the corresponding key word recording module may search names of the application categories, record high-frequency words in the search results, and use the obtained high-frequency words as the key words corresponding to the application categories. The second storage module is configured to store corresponding relations between the application categories and the corresponding key words. The accessed category acquiring module 20 may access pages of the web page applications, extract high-frequency words in the pages of the web page applications, compare the extracted high-frequency words with the key words corresponding to the application categories, acquire the application category having the highest matching degree and use the application category as the application category to which a web page application belongs.
Additionally or alternatively, the accessed category acquiring module 20 obtains the application categories accessed through the browser by acquiring a set of application categories to which all web page applications accessed through the browser belong.
The category extracting module 30 is configured to calculate access indexes corresponding to the application categories accessed through the browser, and extract a preset number of the application categories having the access indexes that rank higher.
As shown in FIG. 5, in one embodiment, the category extracting module 30 includes a first category extracting module 320, a second category extracting module 340, and a common category extracting module 360.
The first category extracting module 320 is configured to calculate access durations corresponding to the application categories accessed through the browser, and extract the preset number of the application categories corresponding to the access durations that rank higher.
In one embodiment, the first category extracting module 320 may acquire the access durations of the web page applications according to access histories to the web page applications.
In this embodiment, the application recommending system further includes an access history generating module (not shown), configured to generate the access histories to the web page applications. In one embodiment, the access history generating module is configured to monitor and record start time and end time of accessing the web page applications through the browser to obtain the access histories to the web page applications.
The first category extracting module 320 may obtain the access duration of a web page application by calculating separate access durations of the web page application according to the start time and end time of each access to the web page application in the access history of the web page application, and summing the separate access durations.
Additionally or alternatively, the first category extracting module 320 may sum the access durations of the web page applications in the same application category to obtain the access durations corresponding to various application categories.
Additionally or alternatively, the first category extracting module 320 may sort the application categories in a descending order according to the corresponding access durations, and extract the preset number of the application categories that rank higher in the sequence of application categories sorted in the descending order according to the access durations.
The second category extracting module 340 is configured to calculate quantities of the web page applications in the application categories accessed through the browser, and extract the preset number of the application categories in which the quantities rank higher.
The second category extracting module 340 may sort the application categories in a descending order according to the quantities of the web page applications therein, and extract the preset number of the application categories that rank higher in the sequence of application categories sorted in the descending order according to the quantities of the web page applications therein.
The common category extracting module 360 is configured to extract common application categories from the application categories extracted by the first category extracting module 320 and the second category extracting module 340.
In one embodiment, the category extracting module 30 may include only the first category extracting module 320 or only the second category extracting module 340. In the above embodiment, the application categories that the user is interested in can be obtained by acquiring the application categories with longer access durations or including more web page applications accessed through the browser.
In the above embodiment, the application categories that the user is more interested in can be acquired by acquiring the common application categories of the application categories with longer access durations and the application categories including more web page applications accessed through the browser.
The application information acquiring module 40 is configured to acquire information about applications corresponding to the extracted application categories.
In one embodiment, the application recommending system further includes a category setting module, a corresponding application setting module, and a third storage module (not shown). The category setting module is as described above. The corresponding application setting module is configured to set the applications corresponding to the application categories. The third storage module is configured to store corresponding relations between the application categories and the applications. The applications corresponding to the application categories may also be set according to the applications corresponding to the application categories input by the user.
In another embodiment, the application recommending system further includes a category setting module, a searching and result extracting module, and a fourth storage module (not shown). The category setting module is as described above. The searching and result extracting module is configured to search names of the application categories, extract the applications in the search results, and store corresponding relations between the application categories and the extracted applications.
The information about the applications acquired by the application information acquiring module 40 includes names, icons, download addresses or download links, introductions, and the like of the applications.
As shown in FIG. 6, in one embodiment, the application information acquiring module 40 includes a not-accessed application information acquiring module 402 and a not-installed application information acquiring module 404.
The not-accessed application information acquiring module 402 is configured to acquire information about web page applications that are not accessed through the browser corresponding to the extracted application categories.
The not-accessed application information acquiring module 402 may acquire the web page applications that have been accessed through the browser, search for the applications corresponding to the application categories extracted by the category extracting module 30 according to the corresponding relations between the application categories and the applications stored in advance, and filter out the web page applications that have been accessed through the browser to obtain the web page applications that are not accessed through the browser. Additionally or alternatively, the not-accessed application information acquiring module 402 may acquire the information related to the obtained web page applications.
The not-installed application information acquiring module 404 is configured to acquire information about applications that are not installed at a local end of the browser corresponding to the extracted application categories.
The local end of the browser refers to a device on which the browser runs. The not-installed application information acquiring module 404 may acquire the applications that have been installed at the local end of the browser can be acquired, search for the applications corresponding to the application categories extracted module 30 according to the corresponding relations between the application categories and the applications stored in advance, and filter out the applications that have been installed at the local end of the browser to obtain the applications that are not installed at the local end of the browser. Additionally or alternatively, not-installed application information acquiring module 404 may acquire the information related to the obtained web page applications.
In one embodiment, the application information acquiring module 40 may include only the not-accessed application information acquiring module 402 or only the not-installed application information acquiring module 404.
The information pushing module 50 is configured to push the acquired information about the applications.
As shown in FIG. 7, in one embodiment, the accessed application acquiring module 10 runs on the browser, and the accessed category acquiring module 20, the category extracting module 30, the application information acquiring module 40, and the information pushing module 50 run on the server. In addition, the application recommending system further includes a sending module 60 running on the browser, configured to send the information about the web page applications acquired by the accessed application acquiring module 10 to the server. In this embodiment, the information pushing module 50 is configured to deliver the information about the web page applications acquired by the application acquiring module 40 to the browser.
As shown in FIG. 8, in one embodiment, the application recommending system further includes a presenting module 70 running on the browser, configured to display the information about the applications delivered by the information pushing module 50. In one embodiment, the presenting module 70 may generate a pop-up window, and display the information about the applications in the pop-up window; alternatively, the presenting module 70 may load the information about the applications to the web page content to present the information about the applications.
In the application recommending method and system, application categories to which web page applications accessed through a browser belong are acquired, access indexes corresponding to the application categories accessed through the browser are calculated, information about applications corresponding to the application categories having the access indexes that rank higher is acquired, and the information about the applications is recommended to a user. The web page applications accessed through the browser are web page applications that have been used by the user, and the application categories having the access indexes that rank higher may represent the categories to which the web page applications that the user is interested in belong. During the process that the user uses the web page applications, the application recommending method and system can calculate the application categories to which the web page applications that the user is interested in belong, acquire information about web page applications corresponding to the application categories that the user is interested in, and recommend the information about the web page applications to the user. The user is more likely to accept the recommended applications. Compared with pushing a massive amount of information related to applications without targeting at specific user groups, the method and system can improve utilization of network bandwidth and computer system resources.
The foregoing embodiments only describe several implementation manners of the present disclosure, and their description is specific and detailed, but cannot therefore be understood as a limitation to the patent scope of the present disclosure. It should be noted that a person of ordinary skill in the art may further make variations and improvements without departing from the conception of the present disclosure, and these all fall within the protection scope of the present disclosure. Therefore, the patent protection scope of the present disclosure should be subject to the appended claims.

Claims (15)

  1. An application recommending method, comprising:
    at a server having one or more processors and memory storing programs executed by the one or more processors;
    acquiring web page applications accessed through a browser;
    acquiring application categories to which the web page applications belong to obtain the application categories accessed through the browser;
    calculating access indexes corresponding to the application categories accessed through the browser, and extracting a preset number of the application categories having the access indexes that rank higher;
    acquiring information about applications corresponding to the extracted application categories; and
    pushing the acquired information about the applications.
  2. The application recommending method according to claim 1, wherein the acquiring web page applications accessed through a browser comprises:
    acquiring the web page applications with shortcuts added to the browser; and/or
    acquiring the web page applications with access frequencies to which through the browser satisfy a preset condition.
  3. The application recommending method according to claim 1, wherein the calculating access indexes corresponding to the application categories accessed through the browser, and extracting a preset number of the application categories having the access indexes that rank higher comprises:
    calculating access durations corresponding to the application categories, and extracting the preset number of the application categories corresponding to the access durations that rank higher; or
    calculating quantities of the web page applications in the application categories, and extracting the preset number of the application categories in which the quantities rank higher.
  4. The application recommending method according to claim 1, wherein the calculating access indexes corresponding to the application categories accessed through the browser, and extracting a preset number of the application categories having the access indexes that rank higher comprises:
    calculating access durations corresponding to the application categories, and extracting the preset number of the application categories corresponding to the access durations that rank higher;
    calculating quantities of the web page applications in the application categories, and extracting the preset number of the application categories in which the quantities rank higher; and
    extracting common application categories from the application categories extracted in the above two steps.
  5. The application recommending method according to claim 1, wherein the acquiring information about applications corresponding to the extracted application categories comprises:
    acquiring information about web page applications that are not accessed through the browser corresponding to the extracted application categories; and/or
    acquiring information about applications that are not installed at a local end of the browser corresponding to the extracted application categories.
  6. A server, comprising:
    one of more processors;
    memory; and
    one or more program modules stored in the memory and configured for execution by the one or more processors, the one or more program modules being within an application recommending system including:
    an accessed application acquiring module, configured to acquire web page applications accessed through a browser;
    an accessed category acquiring module, configured to acquire application categories to which the web page applications belong to obtain the application categories accessed through the browser;
    a category extracting module, configured to calculate access indexes corresponding to the application categories accessed through the browser, and extract a preset number of the application categories having the access indexes that rank higher;
    an application information acquiring module, configured to acquire information about applications corresponding to the extracted application categories; and
    an information pushing module, configured to push the acquired information about the applications.
  7. The server according to claim 6, wherein the accessed application acquiring module is configured to acquire the web page applications with shortcuts added to the browser; and/or
    configured to acquire the web page applications with access frequencies to which through the browser satisfy a preset condition.
  8. The application recommending system according to claim 6, the category extracting module comprising a first category extracting module or a second category extracting module, wherein:
    the first category extracting module is configured to calculate access durations corresponding to the application categories, and extract the preset number of the application categories corresponding to the access durations that rank higher; and
    the second category extracting module is configured to calculate quantities of the web page applications in the application categories, and extract the preset number of the application categories in which the quantities rank higher.
  9. The application recommending system according to claim 6, the category extracting module comprising a first category extracting module, a second category extracting module, and a common category extracting module, wherein:
    the first category extracting module is configured to calculate access durations corresponding to the application categories, and extract the preset number of the application categories corresponding to the access durations that rank higher;
    the second category extracting module is configured to calculate quantities of the web page applications in the application categories, and extract the preset number of the application categories in which the quantities rank higher; and
    the common category extracting module is configured to extract common application categories from the application categories extracted by the first category extracting module and the second category extracting module.
  10. The application recommending system according to claim 6, the application information acquiring module comprising a not-accessed application information acquiring module and/or a not-installed application information acquiring module, wherein:
    the not-accessed application information acquiring module is configured to acquire information about web page applications that are not accessed through the browser corresponding to the extracted application categories; and
    the not-installed application information acquiring module is configured to acquire information about applications that are not installed at a local end of the browser through the browser corresponding to the extracted application categories.
  11. A non-transitory computer readable storage medium having stored therein one or more instructions, which, when executed by a terminal, cause the server to:
    acquire web page applications accessed through a browser;
    acquire application categories to which the web page applications belong to obtain the application categories accessed through the browser;
    calculate access indexes corresponding to the application categories accessed through the browser, and extract a preset number of the application categories having the access indexes that rank higher;
    acquire information about applications corresponding to the extracted application categories; and
    push the acquired information about the applications.
  12. The computer readable storage medium according to claim 11, wherein the acquiring web page applications accessed through a browser comprises:
    acquiring the web page applications with shortcuts added to the browser; and/or
    acquiring the web page applications with access frequencies to which through the browser satisfy a preset condition.
  13. The computer readable storage medium according to claim 11, wherein the calculating access indexes corresponding to the application categories accessed through the browser, and extracting a preset number of the application categories having the access indexes that rank higher comprises:
    calculating access durations corresponding to the application categories, and extracting the preset number of the application categories corresponding to the access durations that rank higher; or
    calculating quantities of the web page applications in the application categories, and extracting the preset number of the application categories in which the quantities rank higher.
  14. The computer readable storage medium according to claim 11, wherein the calculating access indexes corresponding to the application categories accessed through the browser, and extracting a preset number of the application categories having the access indexes that rank higher comprises:
    calculating access durations corresponding to the application categories, and extracting the preset number of the application categories corresponding to the access durations that rank higher;
    calculating quantities of the web page applications in the application categories, and extracting the preset number of the application categories in which the quantities rank higher; and
    extracting common application categories from the application categories extracted in the above two steps.
  15. The computer readable storage medium according to claim 11, wherein the acquiring information about applications corresponding to the extracted application categories comprises:
    acquiring information about web page applications that are not accessed through the browser corresponding to the extracted application categories; and/or
    acquiring information about applications that are not installed at a local end of the browser corresponding to the extracted application categories.
PCT/CN2015/073561 2014-03-06 2015-03-03 Application recommending method and system WO2015131803A1 (en)

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