WO2017045532A1

WO2017045532A1 - Application program classification display method and apparatus

Info

Publication number: WO2017045532A1
Application number: PCT/CN2016/097702
Authority: WO
Inventors: 陈勇
Original assignee: 北京金山安全软件有限公司
Priority date: 2015-09-17
Filing date: 2016-08-31
Publication date: 2017-03-23
Also published as: CN105224614A

Abstract

An application program classification display method and apparatus. The application program classification display method comprises: acquiring source data, wherein the source data comprises log data and application program information data (S11); extracting key information from the log data, and acquiring at least one type of user behaviour data (S12); according to the at least one type of user behaviour data and the application program information data, determining a popularity value of an application program classification (S13); and according to the popularity value of the application program classification, sorting and displaying the application program classification (S14). The method can realize the automatic classification and display of an application program.

Description

Application classification method and device

Cross-reference to related applications

The present application is based on a Chinese patent application filed on Jan. 17, 2015, the entire disclosure of which is hereby incorporated by reference.

Technical field

The present invention relates to the field of communications technologies, and in particular, to a method and apparatus for displaying application classification.

Background technique

With the continuous development and popularization of mobile smartphones, applications on mobile smartphones are also emerging. Users can search for the required applications by searching for keywords, and then install the corresponding applications.

In order to facilitate the user to quickly find the desired application, a variety of application categories can be displayed on the page, and the user can click on the application classification to select an application under the application classification.

In the prior art, the classification and presentation of applications is based on manual operations, lacking automated classification and presentation solutions.

Summary of the invention

The present invention aims to solve at least one of the technical problems in the related art to some extent.

To this end, it is an object of the present invention to provide a display method for application classification that enables classification and presentation of automated applications.

Another object of the present invention is to provide a display device for application classification.

In order to achieve the above object, a method for displaying an application classification according to an embodiment of the present invention includes: acquiring source data, the source data including log data and application information data; and extracting key information of the log data, Obtaining at least one type of user behavior data; determining, according to the at least one of the user behavior data and the application information data, a popularity value of the application classification; and the application according to the popularity value of the application classification Sort and sort by category.

Optionally, performing key information extraction on the log data, and acquiring at least one type of user behavior data, including: acquiring user behavior category information; determining corresponding log data according to the user behavior category information; and from the corresponding log Extracting key information from the data; obtaining at least one type of user behavior data according to the extracted key information.

Optionally, the user behavior category information includes: searching, clicking, and installing, where the log data is: user search log data, user click log data, and user installation log data, where the corresponding log data is used. Extracting key information, including: when the log data is user search log data, extracting a user ID and a search keyword, Obtaining user search data; or, when the log data is a user clicking log data, extracting user ID, search keyword, and clicked application information to obtain user click data; or, when the log data is user installed When the log data is extracted, the user ID, the search keyword, and the information of the installed application are extracted to obtain user installation data.

Optionally, the determining, according to the at least one type of user behavior data and the application information data, the popularity value of each application classification, including: determining each according to the at least one type of user behavior data a heat value of the application; determining, according to the application information data, an application classification to which each application belongs; determining a heat value of the application classification according to a heat value of each application classified by each application .

Optionally, determining, according to the at least one type of user behavior data, a heat value of each application, including: determining, according to the at least one type of user behavior data, each search keyword under each application The heat value; determining the heat value of the application according to the heat value of each search keyword under each application.

Optionally, determining, according to the at least one type of user behavior data, a heat value of each search keyword under each application, including: determining each application according to the at least one type of user behavior data The PV heat value and the UV heat value of each search keyword are determined; and according to the PV heat value and the UV heat value, the heat value of each search keyword under each application is determined.

Optionally, the at least one type of user behavior data includes: user search data, user click data, and user installation data, and determining, according to the at least one type of user behavior data, each search key under each application The PV heat value and the UV heat value of the word include: determining a search PV value and a search UV value according to the user search data, determining a click PV value and a click UV value according to the user click data, and installing data according to the user Determining the installation PV value and installing the UV value; determining the PV heat value of each search keyword under each application according to the search PV value, the click PV value, and the installation PV value; searching for the UV value, clicking the UV according to the search Value and install UV values to determine the UV heat value for each search keyword under each application.

Optionally, the determining, according to the PV heat value and the UV heat value, a heat value of each search keyword in each application, including: a PV heat value of all search keywords under each application The product of the heat value of the UV heat is determined as the heat value of the search keyword.

Optionally, determining, according to the popularity value of each search keyword under each application, the heat value of the application, including: accumulating sum of heat values of all search keywords under each application , determined as the heat value of the application.

Optionally, determining the popularity value of the application classification according to the heat value of each application classified by each application, including: accumulating the heat value of each application under each application classification. And determine the heat value that is classified for the application.

Optionally, the sorting and displaying the application categories according to the heat value classified by the application, including: the order of the heat values sorted according to the application from high to low, to the application Sort by category; After sorting the application categories, select a preset number of application categories and display them.

The method for displaying an application classification proposed by the first aspect of the present invention obtains user behavior data and application information data, and determines a heat value of the application classification according to the user behavior data and the application information data, and classifies according to the application program. The popularity value sorts and displays the application classification, and does not need to rely on manual operation, so that the problems existing in the manual mode can be solved, and the classification and presentation of the automated application can be realized.

In order to achieve the above object, an apparatus for displaying an application classification according to a second aspect of the present invention includes: an obtaining module, configured to acquire source data, the source data includes log data and application program information; and an extraction module, configured to: Performing key information extraction on the log data to obtain at least one type of user behavior data; and determining a module, configured to determine a heat value of the application classification according to the at least one type of user behavior data and the application information data; The display module sorts and displays the application classification according to the popularity value of the application classification.

Optionally, the extraction module includes:

a first obtaining unit, configured to acquire user behavior category information;

a first determining unit, configured to determine corresponding log data according to the user behavior category information;

a first extracting unit, configured to extract key information from the corresponding log data;

And a second acquiring unit, configured to obtain at least one type of user behavior data according to the extracted key information.

Optionally, the user behavior category information includes: searching, clicking, and installing, where the log data is: user search log data, user click log data, and user installation log data, where the first extracting unit is specifically used when The log data is when the user searches for the log data, extracts the user ID and the search keyword to obtain the user search data; or, when the log data is the user clicks the log data, extracts the user ID, the search keyword, and the clicked application. Program information to obtain user click data; or, when the log data is user installation log data, extract user ID, search keyword, and installed application information to obtain user installation data.

Optionally, the determining module includes:

a second determining unit, configured to determine a heat value of each application according to the at least one type of user behavior data;

a third determining unit, configured to determine, according to the application information data, an application classification to which each application belongs;

And a fourth determining unit, configured to determine a heat value of the application classification according to a heat value of each application classified by each application.

Optionally, the second determining unit is specifically configured to determine, according to the at least one type of user behavior data, a heat value of each search keyword under each application; each search according to each application The heat value of the keyword determines the heat value of the application.

Optionally, the second determining unit is further configured to determine, according to the at least one type of user behavior data, a PV heat value and a UV heat value of each search keyword in each application; according to the PV heat Value and the UV heat The value determines the popularity value of each search keyword under each application.

Optionally, the at least one user behavior data includes: user search data, user click data, and user installation data, and the second determining unit is further configured to determine a search PV value and search for the UV according to the user search data. a value, determining a click PV value and a click UV value according to the user click data, and, according to the user installation data, determining an installation PV value and installing a UV value; according to the searching PV value, clicking a PV value, and installing a PV value, A PV heat value for each search keyword under each application is determined; a UV heat value for each search keyword under each application is determined based on the search UV value, the click UV value, and the installed UV value.

Optionally, the second determining unit is further configured to determine a product of a PV heat value and a UV heat value of each search keyword under each application as a heat value of the search keyword.

Optionally, the second determining unit is further configured to determine, as a heat value of the application, an accumulated sum of heat values of all search keywords under each application.

Optionally, the fourth determining unit is specifically configured to determine an accumulated sum of heat values of all applications in each application category, and determine the heat value classified by the application.

Optionally, the display module is specifically configured to sort the application classification according to a heat value of the application classification from high to low; and select a preset number in the sorted application classification. The application is classified and displayed.

The device for displaying the application classification according to the embodiment of the second aspect of the present invention obtains the user behavior data and the application information data, and determines the heat value of the application classification according to the user behavior data and the application information data, and classifies according to the application program. The popularity value sorts and displays the application classification, and does not need to rely on manual operation, so that the problems existing in the manual mode can be solved, and the classification and presentation of the automated application can be realized.

In order to achieve the above object, a client device according to a third aspect of the present invention includes: a housing, a processor, a memory, a circuit board, and a power supply circuit, wherein the circuit board is disposed inside the space enclosed by the housing, and the processor And the memory is disposed on the circuit board; the power circuit is configured to supply power to each circuit or device of the client device; the memory is used to store the executable program code; and the processor is operable to read the executable program code stored in the memory. Executing a program corresponding to the program code, for performing: acquiring source data, the source data includes log data and application information data; performing key information extraction on the log data, and acquiring at least one type of user behavior data; Determining at least one of user behavior data and the application information data, determining a popularity value of the application classification; sorting and displaying the application classification according to the popularity value of the application classification.

Optionally, the user behavior category information includes: searching, clicking, and installing, and the log data is: a user: Searching the log data, the user clicking the log data and the user installation log data, the extracting the key information from the corresponding log data, including: when the log data is the user search log data, extracting the user ID and the search keyword, To obtain user search data; or, when the log data is a user click log data, extract user ID, search keyword, and clicked application information to obtain user click data; or, when the log data is a user When the log data is installed, the user ID, the search keyword, and the installed application information are extracted to obtain the user installation data.

Optionally, the determining, according to the PV heat value and the UV heat value, a heat value of each search keyword in each application, including: a PV heat of each search keyword under each application The product of the value and the UV heat value is determined as the heat value of the search keyword.

Optionally, determining the popularity value of the application classification according to the heat value of each application classified by each application, including: accumulating the sum of the heat values of all applications under each application classification. Determine the heat value that is classified for the application.

Optionally, the sorting and displaying the application categories according to the heat value classified by the application, including: the order of the heat values sorted according to the application from high to low, to the application Sorting by category; selecting a preset number of application categories in the sorted application category for display.

The client device according to the embodiment of the third aspect of the present invention obtains the user behavior data and the application information data, and determines the heat value of the application classification according to the user behavior data and the application information data, and classifies the heat value according to the application program. Sorting and displaying application categories does not require manual operations, so that problems with manual methods can be solved, and automated application classification and presentation can be realized.

A fourth aspect of the present invention provides a computer readable storage medium having instructions stored therein, when a processor of a terminal executes the instruction, the terminal performs a display method of the application classification as described above.

A fifth aspect of the present invention provides a computer program that, when run on a processor, performs a display method of application classification as described above.

The additional aspects and advantages of the invention will be set forth in part in the description which follows.

DRAWINGS

The above and/or additional aspects and advantages of the present invention will become apparent and readily understood from

1 is a schematic flow chart of a method for displaying an application classification according to an embodiment of the present invention;

2 is an overall architectural diagram of a method for displaying an application classification in an embodiment of the present invention;

3 is a schematic flowchart of a method for displaying an application classification according to another embodiment of the present invention;

4 is a schematic flowchart of a log scanning storage module in an embodiment of the present invention;

FIG. 5 is a schematic flowchart of a method for displaying an application classification according to another embodiment of the present invention; FIG.

6 is a schematic flowchart of a method for displaying an application classification according to another embodiment of the present invention;

7 is a schematic flow chart of a sorting data creation module in an embodiment of the present invention;

8 is a diagram showing an example of searching for hot word block classification and sorting results in an embodiment of the present invention;

FIG. 9 is a schematic structural diagram of an apparatus for displaying an application classification according to another embodiment of the present invention; FIG.

FIG. 10 is a schematic structural diagram of an apparatus for displaying an application classification according to another embodiment of the present invention; FIG.

FIG. 11 is a schematic structural diagram of an embodiment of a client device according to the present invention.

detailed description

The embodiments of the present invention are described in detail below, and the examples of the embodiments are illustrated in the drawings, wherein the same or similar reference numerals are used to refer to the same or similar elements or elements having the same or similar functions. The following is described by referring to the figures. The examples are intended to be illustrative, and not to limit the invention. Rather, the invention is to cover all modifications, modifications and equivalents within the spirit and scope of the appended claims.

FIG. 1 is a schematic flowchart of a method for displaying an application classification according to an embodiment of the present invention, where the method includes:

S11: Acquire source data, where the source data includes log data and application information data.

The log data may include at least one of user search log data, user click log data, and user installation log data. Specifically, different log data can be obtained from the corresponding user log, for example, obtaining user search log data from the user search log; obtaining user click log data from the user click log; and obtaining user installation log data from the user installation log .

The user search log data is used to record the data of the user search history. For example, the user search log data may record the information of the user and the information of the search history corresponding to the user, where the user information may be a user identifier (user ID). The information of the user's search history may include search keywords, and may also include other information such as the search engine used and the search time. In the search, the search box may be used as an entry, and the input content is a search keyword; the user ID is used to uniquely identify the user, for example, the mobile phone number is usually used as the user ID on the mobile smart phone.

The user clicks the log data to record the data of the user's click history. For example, the user clicks on the log data to record the information of the user and the click history of the user. The user's information may be the user identifier (user ID) and the user. The click history information can include clicked apps, searched keywords, and other information such as click time.

The user installation log data is used to record the data of the user installation history. For example, the user installation log data may record the information of the user and the installation history information of the user, where the user information may be a user identifier (user ID). The user's installation history information may include installed applications, searched keywords, and other information such as installation time.

The application information data may be obtained from configuration information of the application, for example, the application information data may include: a category of the application, and may further include one or more of an application name, a description, a star rating, and an installation address. item.

S12: Perform key information extraction on the log data to obtain at least one type of user behavior data.

The user behavior data includes user search data, user click data, and user installation data.

Referring to FIG. 2, the log data includes user search log data, user click log data, and user installation log data as an example. After the data source 21 is determined, the log scan storage module 22 may extract key information from the log data to obtain user behavior data. twenty three.

The user search data records the user ID and the search keyword corresponding to the user ID; the user clicks the data to record the user ID, the search keyword corresponding to the user ID, and the information of the clicked application; the user ID stores the user ID and the user The search keyword corresponding to the ID and the information of the installed application.

In an embodiment, referring to FIG. 3, step S12 may specifically include:

S121: Acquire user behavior category information.

The data obtained by the data source module may include user behavior category information to determine user behavior category information. Specifically, the user behavior category information may include at least one of a search, a click, and an installation.

S122: Determine corresponding log data according to the user behavior category information.

The log corresponding to the behavior category may be determined according to the obtained user behavior category information. For example, referring to FIG. 4, the data source 41 includes user behavior category information, and the log scan storage module 42 may determine the user according to the user behavior category information. The behavior category, and the corresponding log data is obtained according to the user behavior category. For example, when the user behavior category information is a search, it may be determined that the corresponding log data is user search log data; when the user behavior category information is clicked, it may be determined that the corresponding log data is the user click log data; when the user behavior category information is When installing, you can determine that the corresponding log data is user installation log data.

S123: Extract key information from the corresponding log data.

Specifically, referring to FIG. 4, the log scan storage module 42 may extract corresponding key information from the log data, for example, when the log data is user search log data, extract a user ID and a search keyword; or, The log data is information for extracting a user ID, a search keyword, and a clicked application when the user clicks the log data (referred to as a click app); or, when the log data is user installed log data, extracting a user ID, searching Keyword and information about the installed application (referred to as the install app).

S124: Obtain at least one type of user behavior data according to the extracted key information.

The user behavior data may include: user search data, user click data, and user installation data.

Specifically, the corresponding user behavior data 43 can be composed of key information extracted from the log data. For example, referring to FIG. 4, the user search data is composed of the user ID and the search keyword; the user click data is composed of the user ID, the search keyword, and the information of the clicked application; the user ID, the search keyword, and the installed application The information constitutes user installation data.

S13: Determine a heat value of the application classification according to the at least one type of user behavior data and the application information data.

Among them, the heat value is a digital measure of the heat, and the heat can reflect the degree of user demand for the corresponding information. For example, the heat of the application can indicate the degree to which the application is welcomed by the user and/or is concerned by the user, and the heat of the application classification. It can indicate the extent to which the application classification is welcomed by the user and/or is of interest to the user.

Specifically, for an application classification, the heat value of each application included in the application classification may be determined, and then the heat value of the application classification is determined according to the heat value of each application, where each application The heat value can be determined according to the heat of the search keyword corresponding to the application. For example, referring to FIG. 2, after the user behavior data 23 is obtained, the processing may be performed by the sort data creation module 24 to obtain a heat value of 25, wherein the heat value is 25 packets. The search keyword heat value, the application (app) heat value and the application classification heat value (referred to as the classification heat value).

In an embodiment, referring to FIG. 5, step S13 may specifically include:

S131: Determine a heat value of each application according to the at least one type of user behavior data.

The heat value of each search keyword in each application may be determined according to the user behavior data; and the heat value of the application is determined according to the heat value of each search keyword in each application. .

In an embodiment, referring to FIG. 6, corresponding to an application, determining the heat value of the application may specifically include:

S61: Acquire user behavior data, including user search data, user click data, and user installation data.

For example, referring to FIG. 7, the classification heat generation value is calculated by the ranking data creation module 74.

S62: Obtain a Page View (PV) value and a User View (UV) value according to the user behavior data.

The PV value includes the search PV value, the PV (App Keyword Click Page View, AKCPV) value, and the PV (App Keyword Install Page View, AKIPV) value. The UV value includes searching for the UV value and clicking the UV (App Keyword Click User View). , AKCUV) value and install UV (App Keyword Install User View, AKIUV) value.

Wherein, referring to FIG. 7, the search PV value and the search UV value may be determined according to the user search data, and the click PV (AKCPV) value and the click UV (AKCUV) value are determined according to the user click data, and are installed according to the user. Data, determine the installed PV (AKIPV) value and install the UV (AKIUV) value.

Specifically, the user search data can be counted, and the search PV of each search keyword is obtained, and the search UV is obtained.

Click on PV (App Keyword Click Page View, AKCPV) refers to the click PV of the search keyword calculated according to each application; click UV (App Keyword Click User View, AKCUV) refers to the search based on each application. Keyword Click Page (AKIPV) refers to the installation PV of the search keyword calculated according to each application; App (Open Key App Install, AKIUV) refers to each The application counts the installed keywords of the search UV.

You can first count the number of applications from the user click data, and then click the PV and click UV of the search keyword for each application to get AKCPV and AKCUV respectively.

You can first count the number of applications from the user installation data, and then according to each application statistics search keyword installation PV and install UV, get AKIPV and AKIUV respectively.

S63: Determine, according to the search PV value, the click PV value, and the installed PV value, a PV heat value of each search keyword under the application, and determine, according to the search UV value, the click UV value, and the installed UV value. The UV heat value of each search keyword under the application.

Referring to Figure 7, the search PV value is represented by the search PV, the search UV value is represented by the search UV, the click PV value is represented by AKCPV, the click UV value is represented by AKCUV, the installed PV value is represented by AKIPV, and the installed UV value is represented by AKIUV, then By obtaining the PV heat value of each search keyword under the application (App) according to the search PV, AKCPV and AKIPV, the UV heat of each search keyword under the application (App) can be obtained according to the search UV, AKCUV and AKIUV. value.

Specifically, the PV heat value of each search keyword under the application is calculated by the following formula:

PV heat value = AKCPV / search PV + AKIPV / AKCPV

The UV heat value of each search keyword under the application is calculated by the following formula:

UV heat value = AKCUV / search UV + AKIUV / AKCUV

S64: Determine a heat value of the search keyword according to a PV heat value and a UV heat value of each search keyword.

Referring to FIG. 7, the heat value of the search keyword is represented by the final heat value of the search keyword, and then the PV heat value of each search keyword under the application (App) and each search under the application (App) may be used. The UV heat value of the keyword is obtained as the final heat value of each search keyword under the application (App).

The product of the PV heat value and the UV heat value of each search keyword may be determined as the heat value of the search keyword.

Specifically, the heat value of each search keyword under the application is obtained from the PV heat value and the UV heat value of the search keyword by the following formula:

Search word heat value = PV heat value * UV heat value

S65: Determine the heat value of the application according to the heat value of each search keyword under the application.

Referring to FIG. 7, an application (App) popularity value can be obtained based on the final heat value of each search keyword under the application (App).

The sum of the heat values of each of the search keywords under the application may be determined as the heat value of the application. Specifically, the heat value of the application is determined by the following formula:

Application heat value = ∑ (the heat value of each search keyword under the application)

S132: Determine, according to the application information data, an application classification to which each application belongs.

Among them, the application can be classified according to its function and domain characteristics, such as "educational class", "game class", "tool class" and so on.

Specifically, the application information data includes an application category, and may further include data such as a name, a description, and the like, wherein the application classification to which the application belongs may be determined according to the category in the application information data.

For example, referring to FIG. 7, the category to which the App belongs may be checked according to the application information data (App information data). When the application classification to which the application belongs may be determined according to the App information data, the classification may be determined, and the corresponding classification may be determined. For example, it belongs to a game class or a tool class.

S133: Determine a heat value of the application classification according to a heat value of each application classified by each application.

Referring to FIG. 7, after determining the App heat value and checking the category to which the App belongs and having the classification, the classification heat value can be determined.

Specifically, the accumulated sum of the heat values of each application under each application classification may be determined as the heat value of the application classification.

For example, the "game class" application includes application A, application B, and application C, and the "game class" application classification heat value = application A heat value + application B heat value + application Program C heat value.

For example, after determining the classification of the application to which the application belongs, when the classification has a heat value, the heat value of the classification may be updated, and the initial heat value of each classification may be set to 0, and each time after determining After the heat value of an application under the classification, the newly determined application heat value plus the original heat value can be used to obtain the updated classification heat value. For example, the currently processed application is D, the application D belongs to the tool class, and the updated heat value of the application class of the tool class = the heat value before the update + the heat value of the application D.

S14: Sort and display the application classification according to the heat value classified by the application.

Referring to FIG. 2, after the classification heat value is obtained, the application classifications are sorted and displayed can be represented by the search hot word block classification and ranking module 26.

Specifically, the application classification may be sorted according to the order of the heat values of the application classification from high to low, and the preset application number is selected and displayed in the sorted application classification. The preset number is, for example, five.

For example, referring to Figure 8, five application categories are selected for display based on the heat value of the application classification from high to low. The application classifications from high to low are Skype, Path, Defend the ra, Mobile Alarm System and See Films Online Free.

In this embodiment, the user behavior data and the application information data are obtained, and the heat value of the application classification is determined according to the user behavior data and the application information data, and the application classification is sorted and displayed according to the popularity value of the application classification, It is necessary to rely on manual operation, so that the problems existing in the manual mode can be solved, and the classification and presentation of the automated application can be realized. Further, in this embodiment, the heat value of the search keyword is determined by the user's search, click and installation behavior, the heat value of the application is determined according to the heat value of the search keyword, and the heat of the application classification is determined according to the heat value of the application. Values, which determine the heat value of the final application classification based on user behavior, thereby improving accuracy, stability, and timeliness.

FIG. 9 is a schematic structural diagram of an apparatus for displaying an application classification according to another embodiment of the present invention. The apparatus 90 includes an obtaining module 91, an extracting module 92, a determining module 93, and a display module 94.

The obtaining module 91 is configured to acquire source data, and the source data includes log data and application information data.

The extracting module 92 is configured to perform key information extraction on the log data to obtain at least one type of user behavior data.

In an embodiment, referring to FIG. 10, the extraction module 92 includes:

The first obtaining unit 921 is configured to acquire user behavior category information.

The first determining unit 922 is configured to determine corresponding log data according to the user behavior category information;

The log corresponding to the behavior category may be determined according to the obtained user behavior category information. For example, referring to FIG. 4, the data source 41 includes user behavior category information, and the log scan storage module 42 may determine the user according to the user behavior category information. The behavior category, and the corresponding log data is obtained according to the user behavior category. For example, when the user behavior class When the information is search, it may be determined that the corresponding log data is user search log data; when the user behavior category information is clicked, it may be determined that the corresponding log data is the user click log data; when the user behavior category information is installed, it may be determined The corresponding log data is the user installation log data.

a first extracting unit 923, configured to extract key information from the corresponding log data;

The second obtaining unit 924 is configured to obtain at least one type of user behavior data according to the extracted key information.

In another embodiment, the user behavior category information includes: searching, clicking, and installing, and the log data is: user search log data, user click log data, and user installation log data, and the first extracting unit is specifically used. When the log data is the user search log data, extracting the user ID and the search keyword to obtain the user search data; or, when the log data is the user clicking the log data, extracting the user ID, the search keyword, and Clicking on the information of the application to obtain the user click data; or, when the log data is the user installation log data, extracting the user ID, the search keyword, and the information of the installed application to obtain the user installation data.

The determining module 93 is configured to determine a heat value of the application classification according to the at least one of the user behavior data and the application information data.

Specifically, for an application classification, the heat value of each application included in the application classification may be determined, and then the heat value of the application classification is determined according to the heat value of each application, where each application The heat value can be determined according to the heat of the search keyword corresponding to the application. For example, referring to FIG. 2, after the user behavior data 23 is acquired, the ranking data creation module 24 may perform processing to obtain a heat value 25, wherein the heat value 25 includes a search keyword popularity value, an application (app) popularity value, and an application. Program classification heat value (referred to as classification heat value).

In another embodiment, referring to FIG. 10, the determining module 93 includes:

a second determining unit 931, configured to determine a heat value of each application according to the at least one type of user behavior data;

a third determining unit 932, configured to determine, according to the application information data, an application classification to which each application belongs;

The fourth determining unit 933 is configured to determine a heat value of the application classification according to a heat value of each application classified by each application.

In another embodiment, the second determining unit 931 is specifically configured to determine, according to the at least one type of user behavior data, a heat value of each search keyword under each application; according to each application The heat value of each search keyword determines the heat value of the application.

In another embodiment, the second determining unit 931 is further configured to obtain a Page View (PV) value and a User View (UV) value according to at least one type of user behavior data.

Wherein, the PV value includes searching for the PV value, and clicking the PV (App Keyword Click Page View, AKCPV) value to And install the PV (App Keyword Install Page View, AKIPV) value, the UV value includes searching for UV value, clicking UV (App Keyword Click User View, AKCUV) value, and installing UV (App Keyword Install User View, AKIUV) value.

Click on PV (App Keyword Click Page View, AKCPV) refers to the click PV of the search keyword calculated according to each application; click UV (App Keyword Click User View, AKCUV) refers to the search based on each application. The keyword PV (App Keyword Install Page View, AKIPV) refers to the installation PV of the search keyword calculated according to each application; the installation of UV (App Keyword Install User View, AKIUV) refers to each The application counts the installed keywords of the search UV.

Determining a PV heat value of each search keyword under the application according to the search PV value, a click PV value, and an installation PV value, and determining the application according to the search UV value, the click UV value, and the installed UV value. The UV heat value of each search keyword under the program.

Based on the PV heat value and the UV heat value, a heat value for each search keyword under each application is determined.

In another embodiment, the at least one user behavior data includes: user search data, user click data and user installation data, and the second determining unit 931 is further specifically configured to search data according to the at least one type of user. Determining a search PV value and searching for a UV value, determining a click PV value and a click UV value according to the user click data, and determining an installation PV value and installing a UV value according to the user installation data;

PV heat value = AKCPV / search PV + AKIPV / AKCPV

UV heat value = AKCUV / search UV + AKIUV / AKCUV

Determining a PV heat value of each search keyword under each application according to the search PV value, the click PV value, and the installation PV value;

Based on the search UV value, the click UV value, and the installed UV value, the UV heat value for each search keyword under each application is determined.

In another embodiment, the second determining unit 931 is further specifically configured to determine a product of a PV heat value and a UV heat value of each search keyword under each application as a heat value of the search keyword.

Search word heat value = PV heat value * UV heat value

In another embodiment, the second determining unit 931 is further specifically configured to determine an accumulated sum of the heat values of each search keyword under all applications as the heat value of the application.

Specifically, the heat value of the application is determined by the following formula:

In another embodiment, the fourth determining unit 933 is specifically configured to determine an accumulated sum of the heat values of each application under all application categories, and determine the heat value of the application classification.

The display module 94 sorts and displays the application categories according to the popularity values of the application classification.

The embodiment of the present invention further provides a client device. FIG. 11 is a schematic structural diagram of an embodiment of a client device according to the present invention. The client device includes a housing 51, a processor 52, a memory 53, a circuit board 54, and a power circuit. 55, wherein the circuit board 54 is disposed inside the space enclosed by the casing 51, the processor 52 and the memory 53 are disposed on the circuit board 54, and the power supply circuit 55 is configured to supply power to each circuit or device of the client device; For storing executable program code; the processor 52 runs a program corresponding to the executable program code by reading the executable program code stored in the memory 53 for performing the following steps:

S11': acquiring source data, the source data including log data and application information data.

S12': performing key information extraction on the log data to obtain at least one type of user behavior data.

In an embodiment, step S12' may specifically include:

S121': Acquire user behavior category information.

S122': determining corresponding log data according to the user behavior category information.

The log corresponding to the behavior category may be determined according to the obtained user behavior category information, for example, when When the user behavior category information is a search, it may be determined that the corresponding log data is user search log data; when the user behavior category information is clicked, it may be determined that the corresponding log data is the user click log data; when the user behavior category information is installed, It can be determined that the corresponding log data is user installation log data.

S123': extract key information from the corresponding log data.

Specifically, when the log data is user search log data, extracting a user ID and a search keyword; or, when the log data is a user clicking log data, extracting a user ID, a search keyword, and a clicked application Information (referred to as click app); or, when the log data is user installation log data, extract user ID, search keyword and installed application information (referred to as installation app).

S124': obtain at least one type of user behavior data according to the extracted key information.

Specifically, the corresponding user behavior data may be composed of key information extracted from the log data. For example, the user search data is composed of the user ID and the search keyword; the user click data is composed of the user ID, the search keyword, and the information of the clicked application; the user installation is composed of the user ID, the search keyword, and the information of the installed application. data.

S13': determining a heat value of the application classification according to the at least one of the user behavior data and the application information data.

Specifically, for an application classification, the heat value of each application included in the application classification may be determined, and then the heat value of the application classification is determined according to the heat value of each application, where each application The heat value can be determined according to the heat of the search keyword corresponding to the application.

In an embodiment, step S13' may specifically include:

S131': determining a heat value of each application according to the user behavior data.

In an embodiment, corresponding to an application, determining the heat value of the application may specifically include:

S61': Acquire user behavior data, including user search data, user click data, and user installation data.

S62': Obtain a Page View (PV) value and a User View (UV) value according to the user behavior data.

Wherein, the search PV value and the search UV value may be determined according to the user search data, the click PV (AKCPV) value and the click UV (AKCUV) value are determined according to the user click data, and the installation is determined according to the user installation data. PV (AKIPV) values and installed UV (AKIUV) values.

S63': determining, according to the search PV value, the click PV value, and the installed PV value, a PV heat value of each search keyword under the application, and, according to the search UV value, the click UV value, and the installed UV value, Determine the UV heat value for each search keyword under the application.

The search PV value is represented by the search PV, the search UV value is represented by the search UV, the click PV value is represented by AKCPV, the click UV value is represented by AKCUV, the installed PV value is represented by AKIPV, and the installed UV value is represented by AKIUV, which can be based on the search PV. AKCPV and AKIPV get the PV heat value of each search keyword under the application (App), and the UV heat value of each search keyword under the application (App) can be obtained according to the search UV, AKCUV and AKIUV.

PV heat value = AKCPV / search PV + AKIPV / AKCPV

UV heat value = AKCUV / search UV + AKIUV / AKCUV

S64': determining a heat value of the search keyword according to a PV heat value and a UV heat value of each search keyword.

The popularity value of the search keyword is expressed by the final heat value of the search keyword, and may be based on the PV heat value of each search keyword under the application (App) and the UV of each search keyword under the application (App). The heat value is the final heat value of each search keyword under the application (App).

Specifically, each of the applications is obtained from the PV heat value and the UV heat value of the search keyword by the following formula The heat value of the search keywords:

Search word heat value = PV heat value * UV heat value

S65': determining the heat value of the application according to the heat value of each search keyword under the application.

The application (App) popularity value can be derived from the final heat value of each search keyword under the application (App).

S132': Determine, according to the application information data, an application classification to which each application belongs.

For example, the category to which the App belongs may be checked according to the application information data (App information data). When the application classification to which the application belongs may be determined according to the App information data, the classification may be determined, and the corresponding classification may be determined, for example, belonging to Game class or tool class, etc.

S133': determining a heat value of the application classification according to a heat value of each application classified by each application.

After determining the App heat value and checking the category to which the App belongs and having a classification, the classification heat value can be determined.

S14': sort and display the application classification according to the popularity value of the application classification.

For example, based on the heat value of the application classification from high to low, select 5 application categories for display. The application classifications from high to low are Skype, Path, Defend the ra, Mobile Alarm System and See Films Online Free.

The client device exists in a variety of forms including, but not limited to:

(1) Mobile communication devices: These devices are characterized by mobile communication functions and are mainly aimed at providing voice and data communication. Such terminals include: smart phones (such as iPhone), multimedia phones, functional phones, and low-end phones.

(2) Ultra-mobile personal computer equipment: This type of equipment belongs to the category of personal computers, has computing and processing functions, and generally has mobile Internet access. Such terminals include: PDAs, MIDs, and UMPC devices, such as the iPad.

(3) Portable entertainment devices: These devices can display and play multimedia content. Such devices include: audio, video players (such as iPod), handheld game consoles, e-books, and smart toys and portable car navigation devices.

(4) Server: A device that provides computing services. The server consists of a processor, a hard disk, a memory, a system bus, etc. The server is similar to a general-purpose computer architecture, but because of the need to provide highly reliable services, processing power and stability High reliability in terms of reliability, security, scalability, and manageability.

(5) Other electronic devices with data interaction functions.

In addition, an embodiment of the present invention provides a storage medium, where the storage medium is used to store an application, and the application is used to execute a display method of an application classification according to an embodiment of the present invention at runtime. The display method of the application classification provided by the embodiment of the present invention may include:

Obtaining source data, the source data including log data and application information data;

Performing key information extraction on the log data to obtain at least one type of user behavior data;

Determining a heat value of the application classification according to the at least one type of user behavior data and the application information data;

The application categories are sorted and presented based on the popularity values of the application classification.

In addition, an embodiment of the present invention provides an application program, where the application is used to execute an application classification method according to an embodiment of the present invention at runtime. The display method of the application classification provided by the embodiment of the present invention may include:

It should be noted that in the description of the present invention, the terms "first", "second" and the like are used for descriptive purposes only, and are not to be construed as indicating or implying relative importance. Further, in the description of the present invention, the meaning of "a plurality" is two or more unless otherwise specified.

Any process or method description in the flowcharts or otherwise described herein may be understood to represent a module, segment or portion of code that includes one or more executable instructions for implementing the steps of a particular logical function or process. And the scope of the preferred embodiments of the invention includes additional implementations, in which the functions may be performed in a substantially simultaneous manner or in an opposite order depending on the functions involved, in the order shown or discussed. It will be understood by those skilled in the art to which the embodiments of the present invention pertain.

It should be understood that portions of the invention may be implemented in hardware, software, firmware or a combination thereof. In the above-described embodiments, multiple steps or methods may be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented by any one or combination of the following techniques well known in the art: having logic gates for implementing logic functions on data signals. Discrete logic circuits, application specific integrated circuits with suitable combinational logic gates, programmable gate arrays (PGAs), field programmable gate arrays (FPGAs), etc.

One of ordinary skill in the art can understand that all or part of the steps carried by the method of implementing the above embodiments can be completed by a program to instruct related hardware, and the program can be stored in a computer readable storage medium. When executed, one or a combination of the steps of the method embodiments is included.

In addition, each functional unit in each embodiment of the present invention may be integrated into one processing module, or each unit may exist physically separately, or two or more units may be integrated into one module. The above integrated modules can be implemented in the form of hardware or in the form of software functional modules. The integrated modules, if implemented in the form of software functional modules and sold or used as stand-alone products, may also be stored in a computer readable storage medium.

The above mentioned storage medium may be a read only memory, a magnetic disk or an optical disk or the like.

In the description of the present specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" and the like means a specific feature described in connection with the embodiment or example. A structure, material or feature is included in at least one embodiment or example of the invention. In the present specification, the schematic representation of the above terms does not necessarily mean the same embodiment or example. Moreover, the specific features, structures, materials or features described may be in any one Or combined in a suitable manner in various embodiments or examples.

Although the embodiments of the present invention have been shown and described, it is understood that the above-described embodiments are illustrative and are not to be construed as limiting the scope of the invention. The embodiments are subject to variations, modifications, substitutions and variations.

Claims

A method for displaying an application classification, comprising:

Obtaining source data, the source data including log data and application information data;

Performing key information extraction on the log data to obtain at least one type of user behavior data;

Determining a heat value of the application classification according to the at least one type of user behavior data and the application information data;

The application categories are sorted and presented based on the popularity values of the application classification.
The method according to claim 1, wherein extracting key information from the log data to obtain at least one type of user behavior data comprises:

Obtain user behavior category information;

Determining corresponding log data according to the user behavior category information;

Extracting key information from the corresponding log data;

At least one type of user behavior data is obtained based on the extracted key information.
The method according to claim 2, wherein the user behavior category information comprises: searching, clicking and installing, the log data is: user search log data, user click log data and user installation log data, Extracting key information from the corresponding log data, including:

When the log data is user search log data, extracting a user ID and a search keyword to obtain user search data; or

When the log data is the user clicking the log data, extracting the user ID, the search keyword, and the information of the clicked application to obtain the user click data; or

When the log data is user installation log data, information of the user ID, the search keyword, and the installed application is extracted to obtain user installation data.
The method according to any one of claims 1 to 3, wherein the determining, according to the at least one of user behavior data and the application information data, a heat value for each application classification, including :

Determining a heat value of each application according to the at least one type of user behavior data;

Determining, according to the application information data, an application classification to which each application belongs;

The heat value of the application classification is determined according to the heat value of each application under each application classification.
The method according to claim 4, wherein the determining the popularity value of each application according to the at least one user behavior data comprises:

Determining a heat value of each search keyword under each application according to the at least one type of user behavior data;

The heat value of the application is determined according to the heat value of each search keyword under each application.
The method according to claim 5, wherein the determining the popularity value of each search keyword under each application according to the at least one user behavior data comprises:

Determining a PV heat value and a UV heat value for each search keyword under each application according to the at least one type of user behavior data;

Based on the PV heat value and the UV heat value, a heat value for each search keyword under each application is determined.
The method of claim 6, wherein the at least one user behavior data comprises: user search data, user click data and user installation data, the determining according to the at least one user behavior data The PV heat value and UV heat value for each search keyword under each application, including:

Determining a search PV value and a search UV value according to the user search data, determining a click PV value and a click UV value according to the user click data, and determining an installation PV value and an installation UV value according to the user installation data;

Determining a PV heat value of each search keyword under each application according to the search PV value, the click PV value, and the installation PV value;

Based on the search UV value, the click UV value, and the installed UV value, the UV heat value for each search keyword under each application is determined.
The method according to claim 6 or 7, wherein the determining the heat value of each search keyword under each application according to the PV heat value and the UV heat value comprises:

The product of the PV heat value and the UV heat value of each search keyword under each application is determined as the heat value of the search keyword.
The method according to any one of claims 5-8, wherein the determining the popularity value of the application according to the popularity value of each search keyword under each application comprises:

The sum of the heat values of all the search keywords under each application is determined as the heat value of the application.
The method according to any one of claims 4-9, wherein the determining the popularity value of the application classification according to the heat value of each application classified by each application comprises:

The cumulative sum of the heat values of all applications under each application is determined and determined as the heat value of the application classification.
The method according to any one of claims 1 to 10, wherein the sorting and displaying the application classification according to the heat value classified by the application comprises:

Sorting the application categories according to the order of the heat values of the application classification from high to low;

Select a preset number of application categories in the sorted application category to display.
A display device for classifying an application, comprising:

An obtaining module, configured to acquire source data, where the source data includes log data and application information data;

An extracting module, configured to perform key information extraction on the log data, and obtain at least one type of user behavior data;

a determining module, configured to determine a heat value of the application classification according to the at least one type of user behavior data and the application information data;

The display module sorts and displays the application classification according to the popularity value of the application classification.
The apparatus according to claim 12, wherein the extraction module comprises:

a first obtaining unit, configured to acquire user behavior category information;

a first determining unit, configured to determine corresponding log data according to the user behavior category information;

a first extracting unit, configured to extract key information from the corresponding log data;

And a second acquiring unit, configured to obtain at least one type of user behavior data according to the extracted key information.
The device according to claim 13, wherein the user behavior category information comprises: searching, clicking, and installing, wherein the log data is: user search log data, user click log data, and user installation log data, The first extraction unit is specifically configured to:

When the log data is user search log data, extracting a user ID and a search keyword to obtain user search data; or

When the log data is the user clicking the log data, extracting the user ID, the search keyword, and the information of the clicked application to obtain the user click data; or

When the log data is user installation log data, information of the user ID, the search keyword, and the installed application is extracted to obtain user installation data.
The apparatus according to any one of claims 12-14, wherein the determining module comprises:

a second determining unit, configured to determine a heat value of each application according to the at least one type of user behavior data;

a third determining unit, configured to determine, according to the application information data, an application classification to which each application belongs;

And a fourth determining unit, configured to determine a heat value of the application classification according to a heat value of each application classified by each application.
The device according to claim 15, wherein the second determining unit is specifically configured to:

Determining a heat value of each search keyword under each application according to the at least one type of user behavior data;

The heat value of the application is determined according to the heat value of each search keyword under each application.
The apparatus according to claim 16, wherein the second determining unit is further specifically configured to:

Determining a PV heat value and a UV heat value for each search keyword under each application according to the at least one type of user behavior data;

Based on the PV heat value and the UV heat value, a heat value for each search keyword under each application is determined.
The apparatus according to claim 17, wherein the at least one type of user behavior data comprises: user search data, user click data and user installation data, and the second determining unit is further specifically configured to:

Determining a search PV value and a search UV value according to the user search data, determining a click PV value and a click UV value according to the user click data, and determining an installation PV value and an installation UV value according to the user installation data;

Determining a PV heat value of each search keyword under each application according to the search PV value, the click PV value, and the installation PV value;

Based on the search UV value, the click UV value, and the installed UV value, the UV heat value for each search keyword under each application is determined.
The device according to claim 17 or 18, wherein the second determining unit is further specifically configured to:

The product of the PV heat value and the UV heat value of each search keyword under each application is determined as the heat value of the search keyword.
The device according to any one of claims 16 to 19, wherein the second determining unit is further specifically configured to:

The sum of the heat values of all the search keywords under each application is determined as the heat value of the application.
The device according to any one of claims 15 to 19, wherein the fourth determining unit is specifically configured to:

The cumulative sum of the heat values of all applications under each application is determined and determined as the heat value of the application classification.
The device according to any one of claims 12 to 21, wherein the display module is specifically configured to:

Sorting the application categories according to the order of the heat values of the application classification from high to low;

Select a preset number of application categories in the sorted application category to display.
A client device, comprising: a housing, a processor, a memory, a circuit board, and a power supply circuit, wherein the circuit board is disposed inside a space enclosed by the housing, and the processor and the memory are disposed on the circuit board; a power circuit for powering various circuits or devices of the client device; a memory for storing executable program code; and a processor for executing a program corresponding to the executable program code by reading executable program code stored in the memory Used to perform the following steps:

Obtaining source data, the source data including log data and application information data;

Performing key information extraction on the log data to obtain at least one type of user behavior data;

Determining a heat value of the application classification according to the at least one type of user behavior data and the application information data;

The application categories are sorted and presented based on the popularity values of the application classification.
A computer readable storage medium having instructions stored therein, the terminal executing a method of displaying an application classification according to any one of claims 1-11 when a processor of the terminal executes the instruction.
A computer program, when executed on a processor, performs the display method of the application classification according to any one of claims 1-11.