CN113950678A

CN113950678A - Application pushing method and related device

Info

Publication number: CN113950678A
Application number: CN201980097278.6A
Authority: CN
Inventors: 王小龙
Original assignee: Guangdong Oppo Mobile Telecommunications Corp Ltd; Shenzhen Huantai Technology Co Ltd
Current assignee: Guangdong Oppo Mobile Telecommunications Corp Ltd; Shenzhen Huantai Technology Co Ltd
Priority date: 2019-07-26
Filing date: 2019-07-26
Publication date: 2022-01-18
Also published as: WO2021016760A1

Abstract

An application pushing method and a related device are applied to a server, and the method comprises the following steps: determining a target application type with target user interest degree greater than preset interest degree (S101); acquiring a plurality of applications of which the application types are the target application types in an application store, and acquiring comment information of the plurality of applications (S102); determining a target application according to the comment information of the plurality of applications (S103); outputting a push message recommending downloading of the target application through the electronic device held by the target user, wherein the push message comprises a download link and introduction information of the target application (S104). The method is beneficial to recommending the application suitable for the user to use for the user.

Description

Application pushing method and related device

Technical Field

The application relates to the technical field of mobile terminals, in particular to an application pushing method and a related device.

Background

With the widespread application of mobile terminals such as smart phones, smart phones can support more and more applications and have more and more powerful functions, and smart phones develop towards diversification and personalization directions and become indispensable electronic products in user life. The application store is provided with various types of applications for the user to select and download, but the application store cannot intelligently perform statistical learning according to the applications downloaded by the user, so that the applications suitable for the user to use are obtained and recommended to the user, or the recommended applications are not suitable for the user, so that the downloading amount of the application store cannot be improved.

Disclosure of Invention

The embodiment of the application pushing method and the related device are beneficial to recommending applications suitable for users for the users.

In a first aspect, an embodiment of the present application provides an application pushing method, which is applied to a server, and the method includes:

determining a target application type with target user interest degree greater than preset interest degree;

acquiring a plurality of applications of which the application types are the target application types in an application store, and acquiring comment information of the plurality of applications;

determining a target application according to the comment information of the plurality of applications;

and outputting a push message recommending the downloading of the target application through the electronic equipment held by the target user, wherein the push message comprises a downloading link and introduction information of the target application.

In a second aspect, the embodiment of the present application provides an application push apparatus, which is applied to a server, and includes a processing unit and a communication unit, wherein,

the processing unit is used for determining the target application type of which the target user interest degree is greater than the preset interest degree; the application type of the application store is the target application type, and comment information of the applications is acquired; and determining a target application according to the comment information of the plurality of applications; and outputting a push message for recommending the user to download the target application through the communication unit, wherein the push message comprises a download link and introduction information of the target application.

In a third aspect, an embodiment of the present application provides an electronic device, including a controller, a memory, a communication interface, and one or more programs, where the one or more programs are stored in the memory and configured to be executed by the controller, and the program includes instructions for executing steps in any method of the first aspect of the embodiment of the present application.

In a fourth aspect, the present application provides a computer-readable storage medium, where the computer-readable storage medium stores a computer program for electronic data exchange, where the computer program makes a computer perform part or all of the steps described in any one of the methods of the first aspect of the present application.

In a fifth aspect, the present application provides a computer program product, wherein the computer program product includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to cause a computer to perform some or all of the steps as described in any one of the methods of the first aspect of the embodiments of the present application. The computer program product may be a software installation package.

It can be seen that, in the embodiment of the application, a server first determines a target application type of which an interest degree of a target user is greater than a preset interest degree, then acquires a plurality of applications of which application types in an application store are the target application type, acquires comment information of the plurality of applications, then determines a target application according to the comment information of the plurality of applications, and finally outputs a push message recommending downloading of the target application through an electronic device held by the target user, where the push message includes a download link and introduction information of the target application. The server can intelligently determine the target application type which is interested by the target user, and can determine the target application which is suitable for the target user according to the comment information of the plurality of applications of which the application types are the target application types, so that the push information aiming at the target application is output through the electronic equipment held by the target user, the target user can select whether to download the target application after seeing the push information, the reliability of application push is improved, and the application download amount of an application store is favorably improved.

Drawings

In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.

Fig. 1A is a schematic structural diagram of an electronic device according to an embodiment of the present disclosure;

fig. 1B is a schematic flowchart of an application pushing method according to an embodiment of the present application;

fig. 2 is a schematic flowchart of another application pushing method provided in an embodiment of the present application;

fig. 3 is a schematic flowchart of another application pushing method provided in an embodiment of the present application;

fig. 4 is a schematic structural diagram of an electronic device provided in an embodiment of the present application;

fig. 5 is a block diagram illustrating functional units of an application pushing apparatus according to an embodiment of the present disclosure.

Detailed Description

In order to make the technical solutions of the present application better understood, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.

The terms "first," "second," and the like in the description and claims of the present application and in the above-described drawings are used for distinguishing between different objects and not for describing a particular order. Furthermore, the terms "include" and "have," as well as any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those steps or elements listed, but may alternatively include other steps or elements not listed, or inherent to such process, method, article, or apparatus.

Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein can be combined with other embodiments.

Electronic devices may include various handheld devices, vehicle-mounted devices, wearable devices (e.g., smartwatches, smartbands, pedometers, etc.), computing devices or other processing devices connected to wireless modems, as well as various forms of User Equipment (UE), Mobile Stations (MS), terminal Equipment (terminal device), and so forth, having wireless communication capabilities. For convenience of description, the above-mentioned devices are collectively referred to as electronic devices.

The following describes embodiments of the present application in detail.

Referring to fig. 1A, fig. 1A is a schematic structural diagram of an electronic device 100 according to an embodiment of the present disclosure, where the electronic device 100 includes: the mobile terminal comprises a shell 110, a circuit board 120 arranged in the shell 110, a touch display screen 130 and a camera 140 which are arranged on the shell 110, wherein a processor 121 and a memory 122 are arranged on the circuit board 120, the memory 122 is connected with the processor 121, and the processor 121 is connected with the touch display screen 130; wherein the content of the first and second substances,

the touch display screen 130 is configured to display a push message of the target application;

the memory 122 is used for storing a download link and introduction information of the target application;

the processor 121 is configured to determine a target application type of which target user interest degree is greater than a preset interest degree; the application type of the application store is the target application type, and comment information of the applications is acquired; and determining a target application according to the comment information of the plurality of applications; and the push message is used for outputting a push message for recommending downloading of the target application through the electronic equipment held by the target user, and the push message comprises a downloading link and introduction information of the target application.

Referring to fig. 1B, fig. 1B is a schematic flowchart of an application pushing method applied to a server according to an embodiment of the present application. As shown in the figure, the push method of the application includes:

s101, the server determines the target application type of which the target user interest degree is greater than the preset interest degree.

The server is a server corresponding to the application store, the merchant of the application store has various types of applications, the server can determine a target application type in which the target application is interested according to information such as an application download record of target electronic equipment held by a user or a footprint of the user when browsing the application store, that is, an application type in which the user interest degree is greater than a preset interest degree, the target application type may be a game application type, a social application type, a video application type, and the like, and the target application type may include multiple application types.

S102, the server obtains a plurality of applications with the application types being the target application types in the application stores, and obtains comment information of the plurality of applications.

The server may obtain a plurality of applications in the application store, where the application type is a target application type, and the number of the plurality of applications may be preset by the user, for example, the target application type is a game application type, and the plurality of applications may be game applications of top ten of the download amount, or top ten game applications with the highest score, or all game applications developed by a certain game developer that the user likes. Furthermore, comment information of the plurality of applications may be further acquired.

S103, the server determines a target application according to the comment information of the plurality of applications.

The server can conduct semantic analysis according to the comment information of the multiple applications, or determine the target application from the multiple applications by combining all records of the user when the user uses the application store at ordinary times, or combining the current network environment where the electronic device is located, namely the traffic environment or the WIFI environment and the like, so that the target application can be pushed to the electronic device according to the target application.

S104, the server outputs a push message recommending the downloading of the target application through the electronic equipment held by the target user, wherein the push message comprises a downloading link and introduction information of the target application.

The server sends the push message of the target application to the electronic equipment, the push message for downloading the target application is output and displayed through the electronic equipment, and a target user holding the electronic equipment can determine whether the target application needs to be downloaded according to the download link and the introduction information of the target application, so that application push of the target user is achieved.

It can be seen that, in the embodiment of the application, a server first determines a target application type of which an interest degree of a target user is greater than a preset interest degree, then obtains a plurality of applications of which application types in an application store are the target application type, obtains comment information of the plurality of applications, then determines a target application according to the comment information of the plurality of applications, and finally outputs a push message recommending downloading of the target application through an electronic device held by the target user, where the push message includes a download link and introduction information of the target application. The server can intelligently determine the target application type which is interested by the target user, and can determine the target application which is suitable for the target user according to the comment information of the plurality of applications of which the application types are the target application types, so that the push information aiming at the target application is output through the electronic equipment held by the target user, the target user can select whether to download the target application after seeing the push information, the reliability of application push is improved, and the application download amount of an application store is favorably improved.

In one possible example, the determining the type of the target application with the target user interestingness greater than the preset interestingness includes: determining application types of a plurality of applications downloaded from the application store by the electronic equipment, and determining the number of applications corresponding to each application type; and determining the target application type with the user interest degree larger than the preset interest degree according to the application quantity of each application type.

Wherein, when determining that the target application type with the user interest degree greater than the preset interest degree is, the server may first determine the application types of the multiple applications downloaded by the electronic device from the application store, and determine the application number corresponding to each application type, and determine the target application type with the user interest degree greater than the preset interest degree according to the application number of each application type, for example, the target application type may be the highest number of applications downloaded among the multiple application types, or the highest downloading frequency, for example, application type a corresponds to 8 applications, application type B corresponds to 5 applications, application type C corresponds to 4 applications, application type a may be taken as the target application type, and when detecting the downloading duration of the 8 applications of application type a, that is, the time period from the time when the downloading of the first application is completed to the time when the downloading of the last application is completed, the download duration of the application type B is 4 months, the download duration corresponding to the application type B is 2 months, and the download duration of the application type C is 2 months, most of the application type B can be the target application type, and the more the application of a certain application type is downloaded, the more the application type is not indicative of the user's interest in the application type.

As can be seen, in this example, when determining the target application type with the target application interestingness greater than the preset interestingness, the application type of each application downloaded by the electronic device is determined first, and then the application number corresponding to each application type is determined, so that the target application type with the higher target user interestingness can be obtained more accurately according to the application number of each application type, and application push to the user according to the target application type is facilitated.

In one possible example, the determining a target application according to the comment information of the plurality of applications includes: semantic analysis is carried out on the comment information of each application in the multiple applications, and the feature information of the comment user is obtained; and acquiring pre-stored characteristic information of the target user, and selecting the application with the matching degree of the characteristic information of the comment user and the characteristic information of the target user higher than a first preset threshold value as the target application.

Wherein, the comment information of each application in the plurality of applications comprises the comments of the users for a plurality of days, the comment information of each application is semantically analyzed, the characteristic information of each application is determined, the characteristic information can comprise the annual salary information, professional information, hobby information and the like of the comment users, for example, the feature information of the comment users corresponding to the application 1 is that the user age groups are concentrated in 15-18 years, the feature information of the comment users corresponding to the application 2 is that the user age groups are concentrated in 19-25 years, the feature information of the comment users corresponding to the application 3 is that the user age groups are concentrated in 26-30 years, at this time, the pre-stored feature information of the target user can be obtained, thus, the application with the highest matching degree between the feature information of the comment user and the feature information of the target user is selected as the target application, for example, if the target user is 24 years old, the application 2 is selected as the target application.

As can be seen, in this example, semantic analysis is performed on the comment information of each application in the multiple applications, and the feature information of the comment user of each application can be determined, so that an application in which the matching degree between the feature information of the comment user and the feature information of the target user is greater than a first preset threshold can be selected as a target application.

In one possible example, the determining a target application according to the comment information of the plurality of applications includes: determining a plurality of user comments of each application in the plurality of applications according to the comment information of the plurality of applications; determining a keyword set of each application according to the plurality of user comments of each application, wherein keywords in the keyword set are words in a preset word set, and each keyword corresponds to one user comment; determining the number of good comments and the good comment rate of each application according to the keyword set of each application; and determining the target application according to the number of the good comments and the good comment rate of each application.

When the target application is determined from the multiple applications according to the comment information of each application, a keyword set for each application can be obtained according to the multiple user comments of each application, the words in the keyword set are words in a preset word set, the preset word set can be set in advance by a user, or the server provides some words for the user to select and then obtain the preset word set, each keyword corresponds to one user comment, and one user comment can include at least one keyword. In addition, the method can also realize that the bronze drum of the user searches the keyword to find the application corresponding to the keyword.

The evaluation number and the evaluation rate of each application can be determined according to the keyword set of each application, the more keywords in the keyword set corresponding to a certain application are, the more evaluation representing the application is, and the evaluation number of the application can be combined to determine the evaluation rate, so that the target application is determined.

As can be seen, in this example, after a certain application is downloaded, a user downloading the application may comment or evaluate the application, obtain a keyword set of each application after obtaining multiple user comments of each application in multiple applications, quickly determine the number of good comments and good frequency of each application according to the keyword set, select a target application that can be pushed and downloaded for a target user in combination with the user comments of each application, and help the target user to download a suitable application for good use.

In one possible example, the determining the number of good comments and the good comment rate of each application according to the keyword set of each application includes: detecting whether a first target vocabulary indicating user emotion is contained in the keyword set of each application; if yes, determining whether the emotion expressed by the first target vocabulary is positive emotion; if yes, determining that the user comment corresponding to the first target vocabulary is good comment, and determining the number of the first target vocabulary; and determining the number of good comments and the good comment rate of each application according to the number of the first target vocabulary of each application.

When the goodness quantity and the goodness frequency of each application are determined according to the keyword set of each application, whether the keyword set of each application contains a first target vocabulary indicating the emotion of the user, such as words which are like, good, difficult, happy, annoying, irritated and the like and can indicate the emotion of the user when the user uses the application is detected, if yes, whether the emotion expressed by the first target vocabulary is positive emotion is determined, if yes, the comment of the user corresponding to the first target vocabulary is determined to be good, so that the goodness quantity of the corresponding application can be determined according to the quantity of the first target vocabulary, and the goodness rate is calculated.

It can be seen that, in this example, the keyword set of each application may include words that may indicate user emotion, so that whether the emotion of the user in the application using process is positive emotion may be determined, if the emotion is positive emotion, it may be indicated that the words corresponding to the positive emotion are good opinion, good opinions in multiple user comments are quickly obtained according to the emotional tendency of the user, and the number of good opinions is determined, which is favorable for determining that the target application is suitable for the user to use in combination with the number and the frequency of good opinions of each application.

In one possible example, the determining the number of good comments and the good comment rate of each application according to the keyword set of each application includes: detecting whether a second target vocabulary indicating user behaviors is contained in the keyword set of each application; if yes, determining whether the user can use the application again according to the user behavior indicated by the second target vocabulary; if yes, determining that the user comment corresponding to the second target vocabulary is good comment, and determining the number of the second target vocabulary; and determining the number of good comments and the good comment rate of each application according to the number of the second target vocabulary of each application.

When the good comment quantity and the good frequency of each application are determined according to the keyword set of each application, whether the keyword set of each application contains a second target vocabulary indicating user behaviors, such as vocabularies with sensitive response, multiple functions, good operation, or stuck, still click, long waiting time, pit abandoning, unloading and the like is detected, whether the user can respond again is determined according to the user behaviors indicated by the second target vocabulary, and if yes, the user comment corresponding to the second target vocabulary is determined to be good comment, so that the good comment quantity and the good frequency of each application can be determined according to the quantity of the second target vocabulary.

It can be seen that in this example, the keyword set of each application may contain a vocabulary that may indicate the behavior of the user, so that the behavior of the user in using the application may be determined to determine whether the user will use the application again, and if so, the vocabulary may be indicated as good, and if not, the vocabulary may be indicated as bad. And determining the favorable comment and the favorable comment quantity in the multiple user comments of the application according to whether the user continues to use the application or not, and combining the favorable comment quantity and the favorable frequency of each application, so that the determined target application is suitable for the user to use.

In one possible example, the determining the target application according to the number of good comments and the good comment rate of each application includes sorting the plurality of applications in an order from the number of good comments to the number of good comments of each application, so as to obtain a first sorting; sequencing the plurality of applications according to the sequence of the high rating rate to the low rating rate of each application to obtain a second sequence; selecting at least one application from the plurality of applications as the target application according to the first ranking and the second ranking.

Wherein, each application is ranked according to the order of the number of good comments of each application from high to low to obtain a first ranking, and each application is ranked according to the order of the good frequency of each application from high to low to obtain a second ranking, for example, the number of comments of application 1 is 100, the number of good comments is 70, the good comment rate is 70%, the number of comments of application 2 is 150, the number of good comments is 60, the good comment rate is 40%, the number of comments of application 3 is 300, the number of good comments is 90, the good comment rate is 30%, the ranking is performed according to the number of good comments of each application, the obtained first ranking is application 3, application 1, application 2, and ranking according to the good frequency of each application, the obtained second ranking is application 1, application 2, and application 3, it can be seen that the number of good comments is probably because the users who comment are more frequently, and can not represent that the user really is satisfied with the application, the high rating may be due to fewer users reviewing and not representing that the user is really satisfied with the application.

As can be seen, in this example, after the number of good comments and the rate of good comments of each application are determined, the plurality of applications may be sorted according to the number of good comments to obtain a first sort, the plurality of applications may be sorted according to the good frequency to obtain a second sort, and the target application is selected from the plurality of applications by combining the first sort and the second sort, which is beneficial to improving reliability and comprehensiveness of target application selection.

In one possible example, the selecting at least one application from the plurality of applications as the target application according to the first ordering and the second ordering includes: and selecting the application with the smallest sum of the ranking in the first ranking and the ranking in the second ranking as the target application, or selecting at least one application with the ranking in the first ranking larger than a second preset threshold value and the ranking in the second ranking larger than a third preset threshold value as the target application.

Wherein, in the first sequence of application 3, application 1, application 2, and the second sequence of application 1, application 2, and application 3, if the application with the smallest sum of the rank in the first sequence and the rank in the second sequence is selected as the target application, the target application is application 1, if the application with the rank in the first sequence greater than a second preset threshold value, such as the application with the first rank, is selected, and in the second sequence, the rank in the second sequence greater than a third preset threshold value, such as the application with the first rank, the target application is application 1 and application 3.

In this example, when the target application is selected, the application with the smallest ranking between the first ranking and the second ranking may be selected, or the application with the ranking greater than the second preset threshold in the first ranking and the application with the ranking greater than the third preset threshold in the second ranking may be selected, so that the selected target application may be more favored and more frequent than other applications.

In one possible example, after sending the push message that recommends the user to download the target application, the method further comprises: and when the electronic equipment is detected to start the application store application, displaying the target application and/or an application similar to the target application on a home page of the application store.

After the target application is determined, the server sends a push message of the target application to the electronic equipment to recommend the user to download the target application, and can also update the data of the home page of the application store, so that the electronic equipment can see the target application displayed on the home page of the application store or an application similar to the target application when the application store is started. The push message of the target application only comprises a download link and brief introduction information of the target application, and the target user can see more detailed introduction information of the target application at the application store.

As can be seen, in this example, not only the target application may be pushed to the user through the electronic device, but also the user may view the target application on the home page of the application store, so that more detailed information of the target application may be obtained, and the user may select whether the target application needs to be downloaded again.

Referring to fig. 2, fig. 2 is a schematic flowchart of an application push method provided in the embodiment of the present application, and the application push method is applied to a server, consistent with the embodiment shown in fig. 1B. As shown in the figure, the push method of the application includes:

s201, the server determines application types of a plurality of applications downloaded from the application store by the electronic equipment and determines the number of applications corresponding to each application type.

S202, the server determines the target application type with the user interest degree larger than the preset interest degree according to the application quantity of each application type.

S203, the server acquires a plurality of applications of which the application types are the target application types in the application store, and acquires comment information of the plurality of applications.

S204, the server determines the target application according to the comment information of the plurality of applications.

S205, the server outputs a push message recommending downloading of the target application through the electronic equipment held by the target user, wherein the push message comprises a downloading link and introduction information of the target application.

In addition, when the target application type with the target application interestingness larger than the preset interestingness is determined, the application type of each application downloaded by the electronic equipment is determined, and then the application number corresponding to each application type is determined, so that the target application type with the higher target user interestingness can be obtained accurately according to the application number of each application type, and application pushing can be conducted on the target application type to the user.

Referring to fig. 3, fig. 3 is a schematic flowchart of an application pushing method according to an embodiment of the present application, and the application pushing method is applied to a server, consistent with the embodiments shown in fig. 1B and fig. 2. As shown in the figure, the push method of the application includes:

s301, the server determines application types of a plurality of applications downloaded from the application store by the electronic equipment, and determines the number of applications corresponding to each application type.

S302, the server determines the target application type with the user interest degree larger than the preset interest degree according to the application quantity of each application type.

S303, the server acquires a plurality of applications of which the application types are the target application types in the application stores, and acquires comment information of the plurality of applications.

S304, the server determines a plurality of user comments of each application in the plurality of applications according to the comment information of the plurality of applications.

S305, the server determines a keyword set of each application according to the user comments of each application, wherein the keywords in the keyword set are words in a preset word set, and each keyword corresponds to one user comment.

S306, the server determines the number of good comments and the good comment rate of each application according to the keyword set of each application.

S307, the server determines the target application according to the number of the good comments and the good comment rate of each application.

S308, the server outputs a push message recommending downloading of the target application through the electronic equipment held by the target user, wherein the push message comprises a downloading link and introduction information of the target application.

In addition, after a certain application is downloaded, a user downloading the application can comment or evaluate the application, a keyword set of each application is obtained after a plurality of user comments of each application in a plurality of applications are obtained, the number of good comments and the good frequency of each application can be rapidly determined according to the keyword set, the target application capable of being pushed and downloaded is selected for the target user in combination with the user comments of each application, and the downloading of the target user to the application suitable for good use is facilitated.

Consistent with the embodiments shown in fig. 1B, fig. 2, and fig. 3, please refer to fig. 4, and fig. 4 is a schematic structural diagram of an electronic device 400 provided in the embodiments of the present application, where the electronic device 400 runs one or more application programs and an operating system, and as shown, the electronic device 400 includes a processor 410, a memory 420, a communication interface 430, and one or more programs 421, where the one or more programs 421 are stored in the memory 420 and configured to be executed by the processor 410, and the one or more programs 421 include instructions for performing the following steps;

In one possible example, in the aspect of determining that the target user interest level is greater than the target application type of the preset interest level, the instructions in the program are specifically configured to: determining application types of a plurality of applications downloaded from the application store by the electronic equipment, and determining the number of applications corresponding to each application type; and determining the target application type with the user interest degree larger than the preset interest degree according to the application quantity of each application type.

In one possible example, in the determining a target application from the comment information of the plurality of applications, the instructions in the program are specifically configured to: semantic analysis is carried out on the comment information of each application in the multiple applications, and the feature information of the comment user is obtained; and acquiring pre-stored characteristic information of the target user, and selecting the application with the matching degree of the characteristic information of the comment user and the characteristic information of the target user higher than a first preset threshold value as the target application.

In one possible example, in the determining a target application from the comment information of the plurality of applications, the instructions in the program are specifically configured to: determining a plurality of user comments of each application in the plurality of applications according to the comment information of the plurality of applications; determining a keyword set of each application according to the plurality of user comments of each application, wherein keywords in the keyword set are words in a preset word set, and each keyword corresponds to one user comment; determining the number of good comments and the good comment rate of each application according to the keyword set of each application; and determining the target application according to the number of the good comments and the good comment rate of each application.

In one possible example, in the determining of the number of good comments and the good comment rate of each application according to the keyword set of each application, the instructions in the program are specifically configured to: detecting whether a first target vocabulary indicating user emotion is contained in the keyword set of each application; if yes, determining whether the emotion expressed by the first target vocabulary is positive emotion; if yes, determining that the user comment corresponding to the first target vocabulary is good comment, and determining the number of the first target vocabulary; and determining the number of good comments and the good comment rate of each application according to the number of the first target vocabulary of each application.

In one possible example, in the determining of the number of good comments and the good comment rate of each application according to the keyword set of each application, the instructions in the program are specifically configured to: detecting whether a second target vocabulary indicating user behaviors is contained in the keyword set of each application; if yes, determining whether the user can use the application again according to the user behavior indicated by the second target vocabulary; if yes, determining that the user comment corresponding to the second target vocabulary is good comment, and determining the number of the second target vocabulary; and determining the number of good comments and the good comment rate of each application according to the number of the second target vocabulary of each application.

In one possible example, in the aspect of determining the target application according to the number of good comments and the good comment rate of each application, the instructions in the program are specifically configured to: sequencing the plurality of applications according to the sequence of the number of the good comments of each application from most to least to obtain a first sequence; sequencing the plurality of applications according to the sequence of the high rating rate to the low rating rate of each application to obtain a second sequence; selecting at least one application from the plurality of applications as the target application according to the first ranking and the second ranking.

In one possible example, in the aspect that at least one application is selected from the plurality of applications as the target application according to the first ordering and the second ordering, the instructions in the program are specifically configured to: and selecting the application with the smallest sum of the ranking in the first ranking and the ranking in the second ranking as the target application, or selecting at least one application with the ranking in the first ranking larger than a second preset threshold value and the ranking in the second ranking larger than a third preset threshold value as the target application.

In one possible example, after sending the push message that recommends the user to download the target application, the instructions in the program are specifically configured to: and when the electronic equipment is detected to start the application store application, displaying the target application and/or an application similar to the target application on a home page of the application store.

The above description has introduced the solution of the embodiment of the present application mainly from the perspective of the method-side implementation process. It is understood that the electronic device comprises corresponding hardware structures and/or software modules for performing the respective functions in order to realize the above-mentioned functions. Those of skill in the art would readily appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as hardware or combinations of hardware and computer software. Whether a function is performed as hardware or computer software drives hardware depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.

In the embodiment of the present application, the electronic device may be divided into the functional units according to the method example, for example, each functional unit may be divided corresponding to each function, or two or more functions may be integrated into one control unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit. It should be noted that the division of the units in the embodiment of the present application is schematic, and is only one logical function division, and in actual implementation, there may be another division manner.

Fig. 5 is a block diagram of functional units of the apparatus 500 according to the embodiment of the present application. The application pushing device 500 is applied to a server, and the application pushing device 500 includes a processing unit 501 and a communication unit 502, where:

the processing unit 501 is configured to determine a target application type of which target user interest degree is greater than a preset interest degree; the application type of the application store is the target application type, and comment information of the applications is acquired; and determining a target application according to the comment information of the plurality of applications; and a push message for outputting a recommendation that the user download the target application through the communication unit 502, wherein the push message includes a download link and introduction information of the target application.

In a possible example, in terms of determining that the target user interest level is greater than the target application type of the preset interest level, the processing unit 501 is specifically configured to: determining application types of a plurality of applications downloaded from the application store by target electronic equipment held by the target user, and determining the number of applications corresponding to each application type; and the target application type with the user interest degree larger than the preset interest degree is determined according to the application quantity of each application type.

In one possible example, in the aspect of determining the target application according to the comment information of the multiple applications, the processing unit 501 is specifically configured to: semantic analysis is carried out on the comment information of each application in the multiple applications, and the feature information of the comment user is obtained; and the application is used for acquiring the pre-stored characteristic information of the target user and determining that the application with the matching degree of the characteristic information of the comment user and the characteristic information of the target user higher than a first preset threshold value is the target application.

In one possible example, in the aspect of determining the target application according to the comment information of the multiple applications, the processing unit 501 is specifically configured to: determining a plurality of user comments of each application in the plurality of applications according to the comment information of the plurality of applications; the keyword set of each application is determined according to the user comments of each application, wherein the keywords in the keyword set are words in a preset word set, and each keyword corresponds to one user comment; the keyword set is used for determining the number of the good comments and the good comment rate of each application according to the keyword set of each application; and determining the target application according to the number of good comments and the good comment rate of each application.

In a possible example, in the aspect of determining the number of good comments and the good comment rate of each application according to the keyword set of each application, the processing unit 501 is specifically configured to: detecting whether a first target vocabulary indicating user emotion is contained in the keyword set of each application; if yes, determining whether the emotion expressed by the first target vocabulary is positive emotion; if yes, determining that the user comment corresponding to the first target vocabulary is good comment, and determining the number of the first target vocabulary; and the method is used for determining the number of good comments and the good comment rate of each application according to the number of the first target vocabulary of each application.

In a possible example, in the aspect of determining the number of good comments and the good comment rate of each application according to the keyword set of each application, the processing unit 501 is specifically configured to: detecting whether a second target vocabulary indicating user behaviors is contained in the keyword set of each application; if yes, determining whether the user can use the application again according to the user behavior indicated by the second target vocabulary; if yes, determining that the user comment corresponding to the second target vocabulary is good comment, and determining the number of the second target vocabulary; and the method is used for determining the number of the good comments and the good comment rate of each application according to the number of the second target vocabulary of each application.

In one possible example, in the aspect of determining the target application according to the number of good comments and the good comment rate of each application, the processing unit 501 is specifically configured to: sequencing the plurality of applications according to the sequence of the number of the good comments of each application from most to least to obtain a first sequence; the application ranking module is used for ranking the plurality of applications according to the order of the good rating of each application from high to low to obtain a second ranking; and means for selecting at least one application from the plurality of applications as the target application according to the first and second rankings.

In one possible example, in the aspect that at least one application is selected from the multiple applications as the target application according to the first ordering and the second ordering, the processing unit 501 is specifically configured to: and selecting the application with the smallest sum of the ranking in the first ranking and the ranking in the second ranking as the target application, or selecting at least one application with the ranking in the first ranking larger than a second preset threshold value and the ranking in the second ranking larger than a third preset threshold value as the target application.

In a possible example, after sending the push message recommending the user to download the target application, the processing unit 501 is specifically configured to: and when the electronic equipment is detected to start the application store, displaying the target application and/or an application similar to the target application on a home page of the application store.

The electronic device may further include a storage unit 503, the processing unit 501 and the communication unit 502 may be a controller or a processor, and the storage unit 503 may be a memory.

Embodiments of the present application also provide a computer storage medium, where the computer storage medium stores a computer program for electronic data exchange, and the computer program enables a computer to execute part or all of the steps of any one of the methods described in the above method embodiments, and the computer includes a mobile terminal.

Embodiments of the present application also provide a computer program product comprising a non-transitory computer readable storage medium storing a computer program operable to cause a computer to perform some or all of the steps of any of the methods as described in the above method embodiments. The computer program product may be a software installation package, the computer comprising a mobile terminal.

It should be noted that, for simplicity of description, the above-mentioned method embodiments are described as a series of acts or combination of acts, but those skilled in the art will recognize that the present application is not limited by the order of acts described, as some steps may occur in other orders or concurrently depending on the application. Further, those skilled in the art should also appreciate that the embodiments described in the specification are preferred embodiments and that the acts and modules referred to are not necessarily required in this application.

In the foregoing embodiments, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.

In the embodiments provided in the present application, it should be understood that the disclosed apparatus may be implemented in other manners. For example, the above-described embodiments of the apparatus are merely illustrative, and for example, the above-described division of the units is only one type of division of logical functions, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of some interfaces, devices or units, and may be an electric or other form.

The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.

In addition, each functional unit in the embodiments of the present application may be integrated into one control unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.

The integrated unit may be stored in a computer readable memory if it is implemented in the form of a software functional unit and sold or used as a stand-alone product. Based on such understanding, the technical solution of the present application may be substantially implemented or a part of or all or part of the technical solution contributing to the prior art may be embodied in the form of a software product stored in a memory, and including several instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the above-mentioned method of the embodiments of the present application. And the aforementioned memory comprises: a U-disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic or optical disk, and other various media capable of storing program codes.

Those skilled in the art will appreciate that all or part of the steps in the methods of the above embodiments may be implemented by associated hardware instructed by a program, which may be stored in a computer-readable memory, which may include: flash Memory disks, Read-Only memories (ROMs), Random Access Memories (RAMs), magnetic or optical disks, and the like.

The foregoing detailed description of the embodiments of the present application has been presented to illustrate the principles and implementations of the present application, and the above description of the embodiments is only provided to help understand the method and the core concept of the present application; meanwhile, for a person skilled in the art, according to the idea of the present application, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present application.

Claims

An application pushing method, applied to a server, the method comprising:

determining a target application type with target user interest degree greater than preset interest degree;

acquiring a plurality of applications of which the application types are the target application types in an application store, and acquiring comment information of the plurality of applications;

determining a target application according to the comment information of the plurality of applications;

and outputting a push message recommending the downloading of the target application through the electronic equipment held by the target user, wherein the push message comprises a downloading link and introduction information of the target application.
The method of claim 1, wherein the determining the target application type with the target user interest level greater than the preset interest level comprises:

determining application types of a plurality of applications downloaded from the application store by the electronic equipment, and determining the number of applications corresponding to each application type;

and determining the target application type with the user interest degree larger than the preset interest degree according to the application quantity of each application type.
The method of claim 1 or 2, wherein the determining a target application according to the comment information of the plurality of applications comprises:

semantic analysis is carried out on the comment information of each application in the multiple applications, and the feature information of the comment user is obtained;

and acquiring pre-stored characteristic information of the target user, and selecting the application with the matching degree of the characteristic information of the comment user and the characteristic information of the target user higher than a first preset threshold value as the target application.
The method of claim 1 or 2, wherein the determining a target application according to the comment information of the plurality of applications comprises:

determining a plurality of user comments of each application in the plurality of applications according to the comment information of the plurality of applications;

determining a keyword set of each application according to the plurality of user comments of each application, wherein keywords in the keyword set are words in a preset word set, and each keyword corresponds to one user comment;

determining the number of good comments and the good comment rate of each application according to the keyword set of each application;

and determining the target application according to the number of the good comments and the good comment rate of each application.
The method according to claim 4, wherein the determining the number of good comments and the good comments of each application according to the keyword set of each application comprises:

detecting whether a first target vocabulary indicating user emotion is contained in the keyword set of each application;

if yes, determining whether the emotion expressed by the first target vocabulary is positive emotion;

if yes, determining that the user comment corresponding to the first target vocabulary is good comment, and determining the number of the first target vocabulary;

and determining the number of good comments and the good comment rate of each application according to the number of the first target vocabulary of each application.
The method according to claim 4, wherein the determining the number of good comments and the good comments of each application according to the keyword set of each application comprises:

detecting whether a second target vocabulary indicating user behaviors is contained in the keyword set of each application;

if yes, determining whether the user can use the application again according to the user behavior indicated by the second target vocabulary;

if yes, determining that the user comment corresponding to the second target vocabulary is good comment, and determining the number of the second target vocabulary;

and determining the number of good comments and the good comment rate of each application according to the number of the second target vocabulary of each application.
The method of claim 4, wherein determining the target application according to the number of good comments and the good comment rate of each application comprises

Sequencing the plurality of applications according to the sequence of the number of the good comments of each application from most to least to obtain a first sequence;

sequencing the plurality of applications according to the sequence of the high rating rate to the low rating rate of each application to obtain a second sequence;

selecting at least one application from the plurality of applications as the target application according to the first ranking and the second ranking.
The method of claim 7, wherein the selecting at least one application from the plurality of applications as the target application according to the first ordering and the second ordering comprises:

selecting an application of the plurality of applications that has a smallest sum of the ranking in the first ordering and the ranking in the second ordering as the target application, or,

and selecting at least one application with the ranking in the first ranking larger than a second preset threshold value and the ranking in the second ranking larger than a third preset threshold value as the target application.
The method of any of claims 1-8, wherein after sending the push message that recommends the user to download the target application, the method further comprises:

and when the electronic equipment is detected to start the application store application, displaying the target application and/or an application similar to the target application on a home page of the application store.
An application push apparatus, applied to a server, comprising a processing unit and a communication unit, wherein,

the processing unit is used for determining the target application type of which the target user interest degree is greater than the preset interest degree; the application type of the application store is the target application type, and comment information of the applications is acquired; and determining a target application according to the comment information of the plurality of applications; and outputting a push message for recommending the user to download the target application through the communication unit, wherein the push message comprises a download link and introduction information of the target application.
The application pushing apparatus according to claim 10, wherein in the aspect of determining the type of the target application whose target user interest level is greater than a preset interest level, the processing unit is specifically configured to: determining application types of a plurality of applications downloaded from the application store by target electronic equipment held by the target user, and determining the number of applications corresponding to each application type; and the target application type with the user interest degree larger than the preset interest degree is determined according to the application quantity of each application type.
The application pushing device according to claim 10 or 11, wherein in the aspect of determining the target application according to the comment information of the plurality of applications, the processing unit is specifically configured to: semantic analysis is carried out on the comment information of each application in the multiple applications, and the feature information of the comment user is obtained; and the application is used for acquiring the pre-stored characteristic information of the target user and determining that the application with the matching degree of the characteristic information of the comment user and the characteristic information of the target user higher than a first preset threshold value is the target application.
The application pushing device according to claim 10 or 11, wherein in the aspect of determining the target application according to the comment information of the plurality of applications, the processing unit is specifically configured to: determining a plurality of user comments of each application in the plurality of applications according to the comment information of the plurality of applications; the keyword set of each application is determined according to the user comments of each application, wherein the keywords in the keyword set are words in a preset word set, and each keyword corresponds to one user comment; the keyword set is used for determining the number of the good comments and the good comment rate of each application according to the keyword set of each application; and determining the target application according to the number of good comments and the good comment rate of each application.
The application pushing apparatus according to claim 13, wherein in the determining of the number of good comments and the good comment of each application according to the keyword set of each application, the processing unit is specifically configured to: detecting whether a first target vocabulary indicating user emotion is contained in the keyword set of each application; if yes, determining whether the emotion expressed by the first target vocabulary is positive emotion;

if yes, determining that the user comment corresponding to the first target vocabulary is good comment, and determining the number of the first target vocabulary; and the method is used for determining the number of good comments and the good comment rate of each application according to the number of the first target vocabulary of each application.
The application pushing apparatus according to claim 13, wherein in the determining of the number of good comments and the good comment of each application according to the keyword set of each application, the processing unit is specifically configured to: detecting whether a second target vocabulary indicating user behaviors is contained in the keyword set of each application; if yes, determining whether the user can use the application again according to the user behavior indicated by the second target vocabulary; if yes, determining that the user comment corresponding to the second target vocabulary is good comment, and determining the number of the second target vocabulary; and the method is used for determining the number of the good comments and the good comment rate of each application according to the number of the second target vocabulary of each application.
The application pushing apparatus according to claim 13, wherein in the aspect of determining the target application according to the number of good comments and the good comment rate of each application, the processing unit is specifically configured to: sequencing the plurality of applications according to the sequence of the number of the good comments of each application from most to least to obtain a first sequence; the application ranking module is used for ranking the plurality of applications according to the order of the good rating of each application from high to low to obtain a second ranking; and means for selecting at least one application from the plurality of applications as the target application according to the first and second rankings.
The application pushing apparatus according to claim 16, wherein in the selecting at least one application from the plurality of applications as the target application according to the first ordering and the second ordering, the processing unit is specifically configured to: and selecting the application with the smallest sum of the ranking in the first ranking and the ranking in the second ranking as the target application, or selecting at least one application with the ranking in the first ranking larger than a second preset threshold value and the ranking in the second ranking larger than a third preset threshold value as the target application.
The application pushing device according to any one of claims 10 to 17, wherein after sending the push message that recommends the user to download the target application, the processing unit is specifically configured to: and when the electronic equipment is detected to start the application store, displaying the target application and/or an application similar to the target application on a home page of the application store.
An electronic device comprising a processor, a memory, a communication interface, and one or more programs stored in the memory and configured to be executed by the processor, the programs comprising instructions for performing the steps in the method of any of claims 1-9.
A computer-readable storage medium, characterized in that a computer program for electronic data exchange is stored, wherein the computer program causes a computer to perform the method according to any one of claims 1-9.