Display method, device and electronic equipment

Abstract

The present application discloses a display method, device and electronic device, belonging to the field of communication technology. The method mainly includes receiving a first input to a first platform, the first platform provides information of multiple applications; in response to the first input, obtaining first information of a first account, the first account is an account for logging into the first platform, the first information includes the first account and the first payment information of the first application in multiple applications; according to the first information, determining the payment status information corresponding to the first account, the payment status information is used to characterize the probability value of predicting the occurrence of payment behavior between the first account and the application; displaying a first interface, the first interface includes resource information corresponding to the target application in multiple applications, and the target probability value of the occurrence of payment behavior between the target application and the first account meets the preset conditions.

Description

Technical Field

[0001] The present application belongs to the field of communication technology, and specifically relates to a display method, device and electronic equipment. Background Art

[0002] With the rapid development of communication technology, online games have become an important choice for people's daily entertainment. Online game players are not only interested in free games provided by online game platforms, but also have a demand for paid online games.

[0003] Currently, if users want to view or obtain paid online game information, they need to search for the required online game information in the massive online games provided by the online game platform, pay for it and download it. As a result, for users, it is difficult to obtain the online game information they are interested in in a timely manner while increasing the number of user operations; for the platform, it is difficult to make personalized recommendations to users. Summary of the invention

[0004] The purpose of the embodiments of the present application is to provide a display method, device, equipment and storage medium, which can solve the problem that users currently have complex operations and cannot obtain online game information in a timely manner during the process of obtaining paid online game information.

[0005] In a first aspect, an embodiment of the present application provides a display method, which is applied to an electronic device. The method may include:

[0006] receiving a first input to a first platform, the first platform providing information of a plurality of applications;

[0007] In response to the first input, first information of a first account is obtained, where the first account is an account for logging into the first platform, and the first information includes first payment information of the first account and a first application among the multiple applications;

[0008] Determine payment status information corresponding to the first account according to the first information, where the payment status information is used to characterize a probability value of predicting that a payment behavior occurs between the first account and the application program;

[0009] The first interface is displayed, and the first interface includes resource information corresponding to a target application among multiple applications, and a target probability value of a payment behavior between the target application and the first account meets a preset condition.

[0010] In a second aspect, an embodiment of the present application provides a display device, which is applied to an electronic device, and the device may include:

[0011] A receiving module, configured to receive a first input to a first platform, wherein the first platform provides information of a plurality of applications;

[0012] An acquisition module, configured to acquire first information of a first account in response to a first input, where the first account is an account for logging into the first platform, and the first information includes first payment information of the first account and a first application among the multiple applications;

[0013] A determination module, configured to determine payment status information corresponding to the first account based on the first information, wherein the payment status information is used to characterize and predict the probability of a payment behavior between the first account and the application program;

[0014] The display module is used to display a first interface, wherein the first interface includes resource information corresponding to a target application among multiple applications, and a target probability value of a payment behavior between the target application and the first account meets a preset condition.

[0015] In a third aspect, an embodiment of the present application provides an electronic device, which includes a processor, a memory, and a program or instruction stored in the memory and executable on the processor, and when the program or instruction is executed by the processor, the steps of the display method shown in the first aspect are implemented.

[0016] In a fourth aspect, an embodiment of the present application provides a readable storage medium, on which a program or instruction is stored, and when the program or instruction is executed by a processor, the steps of the display method shown in the first aspect are implemented.

[0017] In a fifth aspect, an embodiment of the present application provides a chip, the chip including a processor and a communication interface, the communication interface and the processor are coupled, and the processor is used to run programs or instructions to implement the steps of the display method shown in the first aspect.

[0018] In an embodiment of the present application, by responding to a first input to a first platform, first information of a first account logging into the first platform is obtained, wherein the first information includes first payment information of the first account and the first application among multiple applications provided by the first platform. Next, payment status information corresponding to the first account is determined according to the first information, and the payment status information is used to characterize the probability value of predicting the occurrence of payment behavior between the first account and the application. Then, a first interface including resource information corresponding to a target application in multiple applications is displayed, wherein the target probability value of the occurrence of payment behavior between the target application and the first account meets a preset condition. Thus, by installing the first application and obtaining payment information between the user and the first application, based on the payment information, the payment behavior of the user and the resource information of other applications provided by the platform is predicted, and the resource information of the application that meets the preset condition is recommended to the user. For the user, there is no need to search for the required paid resources in the massive resources provided by the platform, which reduces the user's operations while allowing the user to promptly learn about the paid resources of interest. For the platform, personalized recommendations of resources can be made to the user to provide user experience. In addition, for application providers, it can improve the user stickiness of the application, and better update the application information according to the user's payment behavior, while increasing the provider's profits and updating the application's resource information according to user needs. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 A schematic diagram of a display architecture provided in an embodiment of the present application;

[0020] Figure 2 A schematic diagram of a display interface interaction provided in an embodiment of the present application;

[0021] Figure 3 A flow chart of a display method provided in an embodiment of the present application;

[0022] Figure 4 A schematic diagram of determining a preset period provided in an embodiment of the present application;

[0023] Figure 5 A schematic diagram of determining an importance value provided in an embodiment of the present application;

[0024] Figure 6 A schematic diagram of the structure of a display device provided in an embodiment of the present application;

[0025] Figure 7 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application;

[0026] Figure 8 A schematic diagram of the hardware structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0027] The following will be combined with the drawings in the embodiments of the present application to clearly describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments in the present application belong to the scope of protection of this application.

[0028] The terms "first", "second", etc. in the specification and claims of the present application are used to distinguish similar objects, and are not used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable under appropriate circumstances, so that the embodiments of the present application can be implemented in an order other than those illustrated or described here, and the objects distinguished by "first", "second", etc. are generally of one type, and the number of objects is not limited. For example, the first object can be one or more. In addition, "and / or" in the specification and claims represents at least one of the connected objects, and the character " / " generally indicates that the objects associated with each other are in an "or" relationship.

[0029] Based on this, the following Figure 1-Figure 2 , the display method provided in the embodiment of the present application is described in detail through specific embodiments and their application scenarios.

[0030] The present application embodiment proposes a display architecture, such as Figure 1 As shown, the display architecture may include an electronic device 10. A first platform such as an application store provided by an operating system is set in the electronic device 10, and the first platform provides resource information of multiple applications, such as download links of game applications, game wallpapers related to the application, game themes, game-related comics, etc. In addition, a user holding the electronic device 10 can log in to the first platform through a first account.

[0031] Based on Figure 1 The architecture shown in the embodiment of the present application is described based on the electronic device 10.

[0032] like Figure 2 As shown, the user can click on the icon of the first platform displayed on the electronic device 10 to start the first platform. The first platform provides the user with resource information of multiple applications such as download links of game applications, game wallpapers related to the application, game themes, game-related comics and other resource information.

[0033] Based on this, when the electronic device 10 receives the first input to the first platform, in response to the first input, the first information of the first account is obtained, the first account is the account of the user to log in to the first platform through the electronic device 10, the first information may include the first payment information of the first account and the first application among the multiple applications, and the first payment information may include the payment frequency and the payment interaction amount value. Among them, the payment frequency is such as the frequency of the user purchasing resources in the game application A through the first account, or the frequency of the user purchasing other game applications through the first account, and the payment interaction amount value is the amount of the user purchasing resources in the game application A through the first account.

[0034] Next, the electronic device 10 determines the payment status information corresponding to the first account based on the first information, and the payment status information is used to characterize the probability value of predicting the payment behavior between the first account and the application. For example, based on the information that the user purchases resources in game application A, or based on the information that the user purchases game application A through the first account and installs the game application A on the electronic device 10 after the payment is completed, the probability value of the first account purchasing resources in game application B is predicted, or the probability of the user purchasing game application B through the first account and installing the game application B on the electronic device 10 after the payment is completed is predicted.

[0035] Then, the first interface is displayed, which includes resource information corresponding to the target application among multiple applications, such as the download link of the target application, the wallpaper of the target application, and the comics of the target application. The target probability value of the payment behavior between the target application and the first account meets the preset conditions. For example, when the target application is a game application B, the target probability value of the payment behavior between the game application B and the first account is greater than or equal to a preset threshold.

[0036] Thus, by having the user install the first application and obtaining the payment information between the user and the first application, and based on the payment information, predicting the payment behavior of the user and the resource information of other applications provided by the platform, the resource information of the application that meets the preset conditions is recommended to the user. For the user, there is no need to search for the required paid resources in the massive resources provided by the platform, which reduces the user's operations and enables the user to promptly learn about the paid resources of interest. For the platform, personalized recommendations of resources can be made to the user to provide a better user experience. In addition, for the provider of the application, the user stickiness of the application can be improved, and the information of the application can be better updated according to the user's payment behavior, so that the resource information of the application can be updated according to the user's needs while increasing the provider's profits.

[0037] Based on this, the display method provided in the embodiment of the present application can be applied to the above-mentioned scenario of recommending paid games in the application store provided in the electronic device, and can also be applied to a certain application X provided in the electronic device to obtain the payment information of the user for the paid resource 1 in the application X, and based on the first payment information, recommend the paid resource 2 in the application X to the user.

[0038] According to the above architecture and application scenarios, the following are combined Figure 3 The display method provided in the embodiment of the present application is described in detail.

[0039] Figure 3 A flowchart of a display method provided in an embodiment of the present application.

[0040] like Figure 3 As shown, the display method can be applied to Figure 1 to Figure 2 The electronic device shown, based on this, can specifically include the following steps:

[0041] Step 310, receiving a first input to a first platform, the first platform providing information of a plurality of applications. Step 320, in response to the first input, obtaining first information of a first account, the first account being an account for logging into the first platform, the first information including first payment information of the first account and the first application among the plurality of applications. Step 330, determining payment status information corresponding to the first account based on the first information, the payment status information being used to characterize the probability value of predicting payment behavior between the first account and the application. Step 340, displaying a first interface, the first interface including resource information corresponding to a target application among the plurality of applications, the target probability value of payment behavior between the target application and the first account meeting a preset condition.

[0042] In this way, by having the user install the first application and obtaining the payment information between the user and the first application, and based on the payment information, predicting the payment behavior of the user and the resource information of other applications provided by the platform, the resource information of the application that meets the preset conditions is recommended to the user. For the user, there is no need to search for the required paid resources in the massive resources provided by the platform, which reduces the user's operations and enables the user to promptly learn about the paid resources of interest. For the platform, personalized recommendations of resources can be made to the user to provide a better user experience. In addition, for the provider of the application, the user stickiness of the application can be improved, and the information of the application can be better updated according to the user's payment behavior, so that the resource information of the application can be updated according to the user's needs while increasing the profit of the provider.

[0043] The above steps are described in detail below:

[0044] In one or more optional embodiments, involving step 320, the first information may specifically include: first payment information between the first account and the first application among the multiple applications, first account information of the first account, and first application information of the first application.

[0045] The first account information includes but is not limited to: user identification number such as mobile phone number, gender, age, and device information of the electronic device that downloaded the first application. The first application information includes but is not limited to: application identification number of the user logging into the first application such as game ID when the first application is a game application, game category corresponding to the first application, and charging functions involved in the first application. The first payment information may include but is not limited to: payment frequency of the first account such as the number of times the user paid to purchase resource information through the first account within six months, payment interaction amount such as the amount of resource information purchased by the user through the first account within six months, the number of times the first application is started, the paid resource sequence such as the arrangement sequence of multiple first applications, the first application charging frequency such as the number of times the first application is charged within six months, the first application charging amount, and the user retention rate of the first application.

[0046] Next, step 330 is involved. In one or more optional embodiments, step 330 may specifically include:

[0047] The first account information, the first application information and the first payment information are input into a target recommendation model to obtain payment status information, wherein the target recommendation model is determined by the second account information of the second account with payment behavior in the first platform within a preset period, the second application information of the second application with payment behavior in multiple applications, and the second payment information of the second account and the second application.

[0048] Based on this, before executing the above-mentioned steps of inputting the first account information, the first application information and the first payment information into the target recommendation model to obtain the payment status information, the display method provided in the embodiment of the present application may also include training the initial recommendation model to obtain the target recommendation model, thereby, the trained target recommendation model can be obtained through the following steps.

[0049] First, the electronic device 10 calculates the preset period for users to obtain paid applications (or paid resources in applications) on the first platform, i.e., the user payment period. Further, the electronic device 10 collects the application download and payment data of users on the first platform, and counts the percentage of the cumulative number of payments for the application per day within 60 natural days after the user downloads the application. In this way, the following can be obtained: Figure 4The cumulative payment curve shown in FIG. 1 shows that the horizontal axis of the curve represents the time (day) after the application is downloaded, from 0 natural days to 30 natural days, and the vertical axis represents the cumulative payment ratio (pay rate). Figure 4 As we know, the cumulative number of payments within 15 natural days after downloading the application accounts for 95% of the total number of payments within 60 natural days after downloading the application, which shows that most of the user's payment behavior is concentrated within 15 natural days. Based on this, the training samples for inputting the initial recommendation model provided in the embodiment of the present application can use an observation period that can cover 95% of the user's payment behavior within 60 natural days after downloading the application as the payment period of the application after downloading, that is, 15 natural days after the user downloads the application as the payment period.

[0050] Next, the electronic device 10 constructs training samples and sample labels based on the user's application downloading behavior in the first platform as the full set of training samples, that is, samples with payment behavior within 15 natural days after the user downloads the application are positive samples, and vice versa. Here, in the embodiment of the present application, an observation period that can cover 95% of the user's payment behavior within 60 natural days after downloading the application is used as the payment period of the downloaded application, that is, 15 natural days after the user downloads the application is used as the payment period. Therefore, in the case where the application is a game application, the payment period is reasonably defined, which solves the current problem that the payment period is short and less payment data is obtained, and the period definition is long, information is delayed, resulting in inaccurate predictions of the recommendation model after training.

[0051] Furthermore, the electronic device 10 obtains a training sample. The training sample may include the second account information of the second account with payment behavior in the first platform within a preset period, the second application information of the second application with payment behavior in multiple applications, and the second payment information of the second account and the second application. Further, the electronic device 10 obtains the second account information of the second account corresponding to multiple users who have agreed to the information collection authorization in the first platform and the second payment information of the second account and the second application. Among them, the second account information includes but is not limited to: user identification number such as mobile phone number, gender, age, device information of the electronic device that downloads the first application. The second payment information includes but is not limited to: the payment frequency of the second account such as the number of times the user pays for resource information through the second account within half a year, the payment interaction limit value such as the amount of resource information purchased by the user through the second account within half a year, the number of times the application is started, the paid resource sequence such as the arrangement sequence of multiple applications, the application charging frequency such as the number of times the application is charged within half a year, the application charging limit value, and the user retention rate of the application. In addition, the electronic device 10 can also obtain second application information of a second application with payment behavior among the multiple applications provided in the first platform. The second application information is the application identification number of the user logging into the second application, such as the game ID when the second application is a game application, the game category corresponding to the second application, and the charging function involved in the second application.

[0052] Based on this, before inputting into the initial recommendation model, the above training samples need to be processed with feature transformation to obtain a 64-bit integer corresponding to each information, and then the 64-bit integer corresponding to each information is vectorized to obtain an 8-bit or 16-bit vector, that is, high-dimensional sparse features are converted into low-dimensional dense features, which is convenient for subsequent recommendation model processing. Among them, single-value features such as user identification number and application identification number are directly vectorized, and multi-value features such as resource sequence and application charging frequency can be embedded (embedding) processing.

[0053] It should be noted that in order to improve the accuracy of the training recommendation model and reduce the amount of calculation for the training recommendation model, the embodiments of the present application adopt different processing methods to perform feature processing on the training samples involved above. Among them, the application charging amount value in the second payment information, the user retention rate of the application, etc. can be processed by data discretization (or quantile segmentation). The second account information and the second application information are cross-processed, such as the user identification number and the application identification number of the user logging in to the second application are cross-processed, and the paid resource sequence and the category of the application provided by the first platform are cross-processed.

[0054] Then, since the initial recommendation model provided in the embodiment of the present application includes at least two parallel sub-models, namely the first initial recommendation model and the second initial recommendation model, the paid resource sequence in the second payment information involved above can be processed separately, such as performing an attention mechanism on the paid resource sequence. The attention mechanism performs a weighted summation on the vector corresponding to each information in the training sample, such as Figure 5 As shown, query is the application identification number of the second application, key is the user's historical payment resource sequence, such as the application identification number of each application in the multiple applications that the user has historically paid for, by calculating the similarity between the application identification number of the second application and the application identification number of each application, different weights are assigned to the application identification number of each application that the user has historically paid for, and the application identification numbers of these applications that the user has historically paid for are weighted and summed to obtain the weighted value of the application feature of the user's historical payment.

[0055] Based on this, the initial recommendation model in the embodiment of the present application can be a deep factor machine model, wherein the first initial recommendation model can be a factor vector machine part, namely FM, and the second initial recommendation model can be a deep part, namely DNN. In this way, according to the first preset feature domain, the vector corresponding to the second account information after the vectorization processing and the vector corresponding to the second application information are spliced, and the spliced ​​vector is input into the FM part. And, according to the second preset feature domain, the vector corresponding to the second application information after the vectorization processing and the vector corresponding to the second payment information are spliced, and the spliced ​​vector is input into the DNN part. In this way, based on the sum of the prediction results of the two parts, the prediction result of the deep factor machine model is obtained, and by calculating the loss between the predicted value and the actual value, the model is iteratively trained until the first initial model meets the first preset condition and the second initial model meets the second preset condition, and the target recommendation model is determined.

[0056] In this way, based on the target recommendation model completed by the training involved above, the target recommendation model includes a first recommendation model obtained by training the first initial model and a second recommendation model obtained by training the second initial model. Thus, the payment status information corresponding to the first account can be determined through the following steps 3301 and 3302.

[0057] Step 3301, input the first account information and the first application information into the first recommendation model to obtain a first probability value of payment behavior between the first account and the application; and input the first application information and the first payment information into the second recommendation model to obtain a second probability value of payment behavior between the first account and the application.

[0058] Step 3302, summarizing the first probability value and the second probability value to obtain payment status information.

[0059] Based on this, in one or more optional embodiments, the step of determining the first probability value in step 3301 may specifically include:

[0060] Step 33011: Determine a first importance value of a third application corresponding to the first application based on the first account information and the first application information.

[0061] Step 33012: Calculate a first probability value of a payment behavior between the first account and the third application based on the first importance value corresponding to the third application.

[0062] Further, in another or more optional embodiments, the step 33011 may specifically include steps 401 and 402.

[0063] Step 401: Determine a third application corresponding to the first application based on the similarity between the first account information and each second account information.

[0064] Among them, the third application can be determined in the following manner: matching the first account information with each second account information to obtain the similarity between the first account information and each second account information; screening out a first similarity that is greater than or equal to a first preset similarity from the similarities between the first account information and each second account information; determining an application that has payment behavior with the third account as the third application, and the third account corresponds to the first similarity.

[0065] Step 402: Calculate a first importance value of the third application program according to the first application information and the third application information of the third application program.

[0066] Furthermore, the first application information is matched with the third application information of the third application to obtain the similarity between the first application and the third application; and the first importance value of the third application is determined based on the similarity between the first application and the third application.

[0067] Based on this, in one or more optional embodiments, the steps involved in determining the second probability value in step 3301 may specifically include steps 33013 to 33015.

[0068] Step 33013: Determine a third application corresponding to the first application based on the first application information and the application information of each application among the multiple applications.

[0069] Furthermore, the first application information can be matched with the application information of each application in the multiple applications to obtain the similarity between the first application and each application; a second similarity greater than or equal to a second preset similarity can be filtered out from the similarity between the first application and each application; and the application corresponding to the second similarity can be determined as a third application.

[0070] Step 33014: Determine the second importance value of the third application based on the first payment information.

[0071] Further, in the case where the first payment information includes a payment frequency and a payment interaction limit value, the second importance value of the third application is calculated according to the frequency value corresponding to the payment frequency and the resource value corresponding to the payment interaction limit value.

[0072] It should be noted that, in addition to determining the second importance value based on the first payment information, the second importance value of the third application may also be calculated based on the first payment information and the second similarity.

[0073] Step 33015, calculating a second probability value of payment behavior between the first account and the application based on the third application and the second importance value.

[0074] It should be noted that the above method of determining the second importance value can determine the second importance value by one of the above methods or by multiple methods to improve the accuracy of the payment status information. In addition, the first probability value and the second probability value can be calculated at the same time, or the first probability value can be calculated first and then the second probability value. Of course, the second probability value can also be calculated first and then the first probability value. Here, the embodiment of the present application does not limit the order of calculating the first probability value and the second probability value.

[0075] In summary, the display method provided in the embodiment of the present application obtains the first information of the first account logged in to the first platform by responding to the first input to the first platform, wherein the first information includes the first payment information of the first account and the first application among the multiple applications provided by the first platform. Then, according to the first information, the payment status information corresponding to the first account is determined, and the payment status information is used to characterize the probability value of predicting the payment behavior between the first account and the application. Then, the first interface including the resource information corresponding to the target application among the multiple applications is displayed, and the target probability value of the payment behavior between the target application and the first account meets the preset conditions. Thus, by installing the first application and obtaining the payment information between the user and the first application, and based on the payment information, predicting the payment behavior of the user and the resource information of other applications provided by the platform, and recommending the resource information of the application that meets the preset conditions to the user. For the user, there is no need to find the required paid resources in the massive resources provided by the platform, which reduces the user's operations and enables the user to promptly know the paid resources of interest. For the platform, personalized recommendations of resources can be made to the user to provide user experience. In addition, for application providers, it can improve the user stickiness of the application, and better update the application information according to the user's payment behavior, while increasing the provider's profits and updating the application's resource information according to user needs.

[0076] It should be noted that the display method provided in the embodiment of the present application can be executed by a display device or a display module in the display device for executing the display method. In the embodiment of the present application, the display device provided in the embodiment of the present application is described by taking the display device executing the display method as an example.

[0077] Based on the same inventive concept, the present application also provides a display device. Figure 6 Provide detailed explanation.

[0078] Figure 6 A schematic diagram of the structure of a display device provided in an embodiment of the present application.

[0079] like Figure 6 As shown, the display device 60 is applied to Figure 1 to Figure 2 The electronic device shown may specifically include:

[0080] The receiving module 601 is used to receive a first input to a first platform, where the first platform provides information of a plurality of applications;

[0081] An acquisition module 602 is configured to acquire first information of a first account in response to a first input, where the first account is an account for logging into the first platform, and the first information includes first payment information of the first account and a first application among the multiple applications;

[0082] A determination module 603, configured to determine payment status information corresponding to the first account based on the first information, wherein the payment status information is used to characterize and predict the probability of a payment behavior between the first account and the application program;

[0083] The display module 604 is used to display a first interface, where the first interface includes resource information corresponding to a target application among multiple applications, and a target probability value of a payment behavior between the target application and the first account meets a preset condition.

[0084] Thus, the user installs the first application and obtains the payment information between the user and the first application, and based on the payment information, predicts the payment behavior of the user and the resource information of other applications provided by the platform, and recommends the resource information of the application that meets the preset conditions to the user. For the user, there is no need to search for the required paid resources in the massive resources provided by the platform, which reduces the user's operations and enables the user to promptly learn about the paid resources of interest. For the platform, personalized recommendations of resources can be made to the user to provide a better user experience. In addition, for the provider of the application, the user stickiness of the application can be improved, and the information of the application can be better updated according to the user's payment behavior, so that the resource information of the application can be updated according to the user's needs while increasing the profit of the provider.

[0085] The display device 60 is described in detail below, as shown below:

[0086] In one or more possible embodiments, the determination module 603 may be specifically configured to, when the first information further includes first account information of the first account and first application information of the first application, input the first account information, the first application information, and the first payment information into the target recommendation model to obtain payment status information; wherein,

[0087] The target recommendation model is determined by the second account information of the second account with payment behavior in the first platform within a preset period, the second application information of the second application with payment behavior in multiple applications, and the second payment information of the second account and the second application.

[0088] In another or more possible embodiments, the determination module 603 may be specifically used to, when the target recommendation model includes a first recommendation model and a second recommendation model, input the first account information and the first application information into the first recommendation model to obtain a first probability value of a payment behavior between the first account and the application; and input the first application information and the first payment information into the second recommendation model to obtain a second probability value of a payment behavior between the first account and the application;

[0089] The first probability value and the second probability value are aggregated to obtain payment status information.

[0090] Based on this, in one or more possible embodiments, the determination module 603 may be specifically used to determine, based on the first account information and the first application information, a first importance value of a third application corresponding to the first application; calculate, based on the third application and the first importance value, a first probability value of a payment behavior occurring between the first account and the third application; and,

[0091] Determine a third application corresponding to the first application according to the first application information and application information of each application among the plurality of applications;

[0092] determining a second importance value of a third application program based on the first payment information;

[0093] A second probability value of a payment behavior occurring between the first account and the application is calculated based on the third application and the second importance value.

[0094] Furthermore, the determination module 603 may be specifically configured to determine a third application corresponding to the first application according to the similarity between the first account information and each second account information;

[0095] A first importance value of the third application is calculated according to the first application information and the third application information of the third application.

[0096] In one or more possible embodiments, the determination module 603 may be specifically configured to match the first account information with each second account information to obtain a similarity between the first account information and each second account information;

[0097] Filtering out a first similarity greater than or equal to a first preset similarity from the similarities between the first account information and each second account information;

[0098] An application program having a payment behavior with a third account is determined as a third application program, and the third account corresponds to the first similarity.

[0099] In one or more further possible embodiments, the determination module 603 may be specifically configured to match the first application information with the third application information of the third application to obtain the similarity between the first application and the third application;

[0100] A first importance value of the third application is determined according to the similarity between the first application and the third application.

[0101] In one or more possible embodiments, the determination module 603 may be specifically configured to match the first application information with the application information of each application in the plurality of applications to obtain a similarity between the first application and each application;

[0102] Filtering out a second similarity greater than or equal to a second preset similarity from the similarities between the first application and each application;

[0103] The application corresponding to the second similarity is determined as the third application.

[0104] In one or more possible embodiments, the determination module 603 can be specifically used to calculate the second importance value of the third application based on the frequency value corresponding to the payment frequency and the resource value corresponding to the payment interaction limit value when the first payment information includes the payment frequency and the payment interaction limit value.

[0105] In still one or more possible embodiments, the determination module 603 may be specifically configured to calculate a second importance value of the third application program based on the first payment information and the second similarity.

[0106] The display device in the embodiment of the present application can be a device, or a component, integrated circuit, or chip in an electronic device. The device can be a mobile electronic device or a non-mobile electronic device. For example, the mobile electronic device can be a mobile phone, a tablet computer, a laptop computer, a PDA, an in-vehicle electronic device, a wearable device, an ultra-mobile personal computer (UMPC), a netbook, or a personal digital assistant (PDA), etc. The non-mobile electronic device can be a server, a network attached storage (NAS), a personal computer (PC), a television (TV), a teller machine or a self-service machine, etc., which is not specifically limited in the embodiment of the present application.

[0107] The display device in the embodiment of the present application may be a device having an operating system. The operating system may be an Android operating system, an IOS operating system, or other possible operating systems, which are not specifically limited in the embodiment of the present application.

[0108] The display device provided in the embodiment of the present application can achieve Figures 1 to 5 To avoid repetition, the various processes implemented by the method embodiment are not described here.

[0109] In an embodiment of the present application, by responding to a first input to a first platform, first information of a first account logging into the first platform is obtained, wherein the first information includes first payment information of the first account and the first application among multiple applications provided by the first platform. Next, payment status information corresponding to the first account is determined according to the first information, and the payment status information is used to characterize the probability value of predicting the occurrence of payment behavior between the first account and the application. Then, a first interface including resource information corresponding to a target application among multiple applications is displayed, wherein the target probability value of the occurrence of payment behavior between the target application and the first account meets a preset condition. Thus, by installing the first application and obtaining payment information between the user and the first application, and based on the payment information, the payment behavior of the user and the resource information of other applications provided by the platform is predicted, and the resource information of the application meeting the preset condition is recommended to the user. For the user, there is no need to search for the required paid resources in the massive resources provided by the platform, which reduces the user's operations while allowing the user to promptly learn about the paid resources of interest. For the platform, personalized recommendations of resources can be made to the user to provide user experience. In addition, for application providers, it can improve the user stickiness of the application, and better update the application information according to the user's payment behavior, while increasing the provider's profits and updating the application's resource information according to user needs.

[0110] Optional, such as Figure 7 As shown, an embodiment of the present application also provides an electronic device 70, including a processor 701, a memory 702, and a program or instruction stored in the memory 702 and executable on the processor 701. When the program or instruction is executed by the processor 701, each process of the above-mentioned display method embodiment is implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0111] It should be noted that the electronic devices in the embodiments of the present application include the above-mentioned mobile electronic devices and non-mobile electronic devices.

[0112] Figure 8 A schematic diagram of the hardware structure of an electronic device provided in an embodiment of the present application.

[0113] The electronic device 800 includes but is not limited to: a radio frequency unit 801, a network module 802, an audio output unit 803, an input unit 804, a sensor 805, a display unit 806, a user input unit 807, an interface unit 808, a memory 809, a processor 810 and a receiver 811 and other components.

[0114] Those skilled in the art will appreciate that the electronic device 800 may also include a power source (such as a battery) for supplying power to each component, and the power source may be logically connected to the processor 810 through a power management system, thereby implementing functions such as managing charging, discharging, and power consumption management through the power management system. Figure 8 The electronic device structure shown in the figure does not constitute a limitation on the electronic device. The electronic device may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently, which will not be described in detail here.

[0115] Among them, in the embodiment of the present application, the user input unit 807 is used to receive a first input to the first platform, and the first platform provides information of multiple applications. The processor 810 is used to obtain first information of the first account in response to the first input, and the first account is an account for logging into the first platform, and the first information includes first payment information of the first account and the first application among multiple applications. And the processor 810 is also used to determine the payment status information corresponding to the first account based on the first information, and the payment status information is used to characterize the probability value of predicting the occurrence of payment behavior between the first account and the application. The display unit 806 is used to display the first interface, and the first interface includes resource information corresponding to the target application among multiple applications, and the target probability value of the occurrence of payment behavior between the target application and the first account meets the preset conditions.

[0116] It should be understood that the input unit 804 may include a graphics processor (GPU) 8041 and a microphone 8042, and the graphics processor 8041 processes the image data of a static image or video obtained by an image capture device (such as a camera) in a video capture mode or an image capture mode. The display unit 806 may include a display panel, and the display panel may be configured in the form of a liquid crystal display, an organic light emitting diode, etc. The user input unit 807 includes a touch panel 8071 and other input devices 8072. The touch panel 8071 is also called a touch screen. The touch panel 8071 may include two parts: a touch detection device and a touch display. Other input devices 8072 may include, but are not limited to, a physical keyboard, function keys (such as a volume display button, a switch button, etc.), a trackball, a mouse, and a joystick, which will not be repeated here. The memory 809 may be used to store software programs and various data, including but not limited to applications and operating systems. The processor 810 may integrate an application processor and a modem processor, wherein the application processor mainly processes an operating system, a user interface, and applications, and the modem processor mainly processes wireless communications. It is understandable that the above-mentioned modem processor may not be integrated into the processor 810.

[0117] An embodiment of the present application also provides a readable storage medium, on which a program or instruction is stored. When the program or instruction is executed by a processor, the various processes of the above-mentioned display method embodiment are implemented and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0118] The processor is the processor in the electronic device in the above embodiment. The readable storage medium includes a computer readable storage medium, such as a computer read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0119] In addition, an embodiment of the present application further provides a chip, which includes a processor and a communication interface, the communication interface and the processor are coupled, and the processor is used to run programs or instructions to implement the various processes of the above-mentioned display method embodiment, and can achieve the same technical effect. To avoid repetition, it will not be repeated here.

[0120] It should be understood that the chip mentioned in the embodiments of the present application can also be called a system-level chip, a system chip, a chip system or a system-on-chip chip, etc.

[0121] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or device including the element.

[0122] In addition, it should be noted that the scope of the methods and devices in the embodiments of the present application is not limited to performing functions in the order shown or discussed, and may also include performing functions in a substantially simultaneous manner or in a reverse order according to the functions involved. For example, the described methods may be performed in an order different from that described, and various steps may be added, omitted, or combined. In addition, features described with reference to certain examples may be combined in other examples.

[0123] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a computer software product, which is stored in a storage medium (such as ROM / RAM, a disk, or an optical disk), and includes a number of instructions for a terminal (which can be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods of each embodiment of the present application.

[0124] The embodiments of the present application are described above in conjunction with the accompanying drawings, but the present application is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of the present application, ordinary technicians in this field can also make many forms without departing from the purpose of the present application and the scope of protection of the claims, all of which are within the protection of the present application.

Claims

1. A display method, characterized in that: include: receiving a first input to a first platform, the first platform providing information of a plurality of applications; In response to the first input, first information of a first account is obtained, where the first account is an account for logging into the first platform, and the first information includes first payment information of the first account and a first application among the multiple applications, first account information of the first account, and first application information of the first application; Inputting the first account information and the first application information into a first recommendation model of a target recommendation model to obtain a first probability value of a payment behavior between the first account and the application; and, inputting the first application information and the first payment information into a second recommendation model of the target recommendation model to obtain a second probability value of a payment behavior between the first account and the application program; Aggregating the first probability value and the second probability value to obtain payment status information corresponding to the first account, wherein the payment status information is used to represent a probability value for predicting that a payment behavior occurs between the first account and the application; Displaying a first interface, the first interface includes resource information corresponding to a target application among the multiple applications, and a target probability value of a payment behavior between the target application and the first account meets a preset condition; wherein, The step of inputting the first account information and the first application information into a first recommendation model of a target recommendation model to obtain a first probability value of a payment behavior between the first account and the application program; and inputting the first application information and the first payment information into a second recommendation model of the target recommendation model to obtain a second probability value of a payment behavior between the first account and the application program, includes: Determine, based on the first account information and the first application information, a first importance value of a third application corresponding to the first application; calculate, based on the third application and the first importance value, a first probability value of a payment behavior occurring between the first account and the third application; Determine a third application corresponding to the first application based on the first application information and the application information of each application among the multiple applications; determine a second importance value of the third application based on the first payment information; and calculate a second probability value of payment behavior between the first account and the third application based on the third application and the second importance value.

2. The method according to claim 1, characterized in that The target recommendation model is determined by the second account information of the second account with payment behavior in the first platform within a preset period, the second application information of the second application with payment behavior among the multiple applications, and the second payment information of the second account and the second application.

3. The method according to claim 1, characterized in that The determining, according to the first account information and the first application information, a first importance value of a third application corresponding to the first application includes: determining a third application corresponding to the first application according to the similarity between the first account information and each second account information; A first importance value of the third application is calculated according to the first application information and the third application information of the third application.

4. The method according to claim 3, characterized in that The determining, according to the similarity between the first account information and each second account information, a third application corresponding to the first application includes: Matching the first account information with each second account information to obtain a similarity between the first account information and each second account information; Filtering out a first similarity greater than or equal to a first preset similarity from the similarities between the first account information and each of the second account information; An application program having payment behavior with a third account is determined as the third application program, and the third account corresponds to the first similarity.

5. The method according to claim 3, characterized in that: The calculating, according to the first application information and the third application information of the third application, a first importance value of the third application includes: Matching the first application information with the third application information of the third application to obtain a similarity between the first application and the third application; A first importance value of the third application is determined according to the similarity between the first application and the third application.

6. The method according to claim 1, characterized in that The determining, according to the first application information and the application information of each application among the multiple applications, a third application corresponding to the first application includes: Matching the first application information with the application information of each application in the multiple applications to obtain a similarity between the first application and each application; Filtering out a second similarity greater than or equal to a second preset similarity from the similarities between the first application and each of the applications; The application corresponding to the second similarity is determined as the third application.

7. The method according to claim 1, characterized in that The first payment information includes a payment frequency and a payment interaction limit value; and determining the second importance value of the third application according to the first payment information includes: The second importance value of the third application is calculated according to the frequency value corresponding to the payment frequency and the resource value corresponding to the payment interaction limit value.

8. A display device, characterized in that: include: A receiving module, configured to receive a first input to a first platform, wherein the first platform provides information of a plurality of applications; an acquisition module, configured to acquire, in response to the first input, first information of a first account, where the first account is an account for logging into the first platform, and the first information includes first payment information of the first account and a first application program of the plurality of applications, first account information of the first account, and first application information of the first application program; a determination module, configured to input the first account information and the first application information into a first recommendation model of a target recommendation model, and obtain a first probability value of a payment behavior between the first account and the application program; and, inputting the first application information and the first payment information into a second recommendation model of the target recommendation model to obtain a second probability value of a payment behavior between the first account and the application program; Aggregating the first probability value and the second probability value to obtain payment status information corresponding to the first account, wherein the payment status information is used to characterize the probability of predicting that the first account and the application program will make a payment; The display module is used to display a first interface, wherein the first interface includes resource information corresponding to a target application program among the multiple applications, and a target probability value of a payment behavior between the target application program and the first account satisfies a preset condition; wherein The determination module is specifically configured to determine, based on the first account information and the first application information, a first importance value of a third application corresponding to the first application; and calculate, based on the third application and the first importance value, a first probability value of a payment behavior occurring between the first account and the third application; Determine a third application corresponding to the first application based on the first application information and the application information of each application among the multiple applications; determine a second importance value of the third application based on the first payment information; and calculate a second probability value of payment behavior between the first account and the third application based on the third application and the second importance value.

9. An electronic device, characterized in that: The method comprises a processor, a memory, and a program or instruction stored in the memory and executable on the processor, wherein the program or instruction, when executed by the processor, implements the steps of the display method according to any one of claims 1 to 7.

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