Information recommendation method and device, electronic equipment and storage medium

Abstract

The present disclosure relates to an information recommendation method and device, an electronic device and a storage medium. The method comprises: receiving information recommendation requests for a target medium from multiple request terminals; when none of the recommendation parameters included in the recommendation requests meets a target recommendation parameter of the target medium, performing aggregation processing on each of the recommendation parameters to obtain an aggregated recommendation parameter; and in a case where the aggregated recommendation parameter meets the target recommendation parameter, recommending information to be recommended to each of the request terminals. In this way, multiple request terminals that do not meet the target recommendation parameter are aggregated, and in a case where the aggregated recommendation parameter meets the target recommendation parameter, information to be recommended is recommended to each of the request terminals, so that each of the request terminals matches more information recommendation opportunities, system performance waste is avoided, and information recommendation efficiency is improved.

Description

Technical Field

[0001] This disclosure relates to the field of Internet technology, and in particular to information recommendation methods, devices, electronic devices, and storage media. Background Technology

[0002] With the development of internet technology, information promotion via the internet has become a new form of information dissemination. In the promotion of products, novels, and applications, media platforms often need to recommend the content.

[0003] Merchants provide relevant recommendation parameters to media platforms. Only when these parameters meet the set conditions can they obtain the opportunity to have their promotional content recommended. However, due to the limited resources of media platforms, even after providing the relevant recommendation parameters, merchants may still be unable to find more recommendation opportunities. This renders the merchant's initial recommendation processing ineffective, resulting in wasted system performance and low information recommendation efficiency. Summary of the Invention

[0004] This disclosure provides information recommendation methods, apparatus, electronic devices, and storage media to at least address the problem of low text and image matching accuracy in related technologies. The technical solution of this disclosure is as follows:

[0005] According to a first aspect of the present disclosure, an information recommendation method is provided, the method comprising:

[0006] Receive multiple requests from clients for information recommendations related to the target media;

[0007] When none of the recommendation parameters included in the recommendation request meet the target recommendation parameters of the target media, the multiple recommendation parameters are aggregated to obtain aggregated recommendation parameters.

[0008] If the aggregated recommendation parameters meet the target recommendation parameters, the information to be recommended for each of the requesting parties is recommended.

[0009] Optionally, the step of recommending the information to be recommended for each of the requesting ends includes:

[0010] The first piece of information to be recommended is recommended on the page of the target media, and the second piece of information to be recommended is recommended on the subordinate page of the first piece of information to be recommended;

[0011] Wherein, the first information to be recommended and the second information to be recommended are the information to be recommended corresponding to each of the requesting ends.

[0012] Optionally, the first and / or second information to be recommended includes a task to be performed. After recommending the first information to be recommended on the page of the target media and recommending the second information to be recommended on the subordinate page of the first information to be recommended, the method further includes:

[0013] Determine whether the task to be executed is to be executed;

[0014] If so, virtual resources of corresponding value are allocated from the remaining resources to the execution entity of the task to be executed, where the remaining resources are the margin between the aggregated recommendation parameters and the target recommendation parameters.

[0015] Optionally, the second recommended information includes a task to be executed, which is a target application installation task. Before recommending the second recommended information on the subordinate page of the first recommended information, the following steps are also included:

[0016] Using a pre-installed target plugin, a list of applications in the current terminal device is obtained to form a first list; the target plugin is installed on the requesting end corresponding to the first information to be recommended.

[0017] Determining whether the task to be executed is to be executed includes:

[0018] The target plugin is used to obtain the application list in the terminal device again, resulting in a second list;

[0019] Based on the second list and the first list, determine whether the target application installation task is executed.

[0020] Optionally, before recommending the first piece of information to be recommended on the target media's page and recommending the second piece of information to be recommended on the next-level page of the first piece of information to be recommended, the method further includes:

[0021] The conversion efficiency ranking of the multiple requesting ends is determined based on historical data;

[0022] The request terminals ranked in the top N by conversion efficiency are determined as the first request terminals, and the remaining request terminals other than the first request terminals are determined as the second request terminals, where N≥1;

[0023] The step of recommending first recommended information on the target media's page and recommending second recommended information on the subordinate page of the first recommended information includes:

[0024] The first piece of information to be recommended from the first requesting party is recommended on the page of the target media, and the second piece of information to be recommended from the second requesting party is recommended on the subordinate page of the first piece of information to be recommended.

[0025] Optionally, recommending first recommended information on the target media's page and recommending second recommended information on the next-level page of the first recommended information includes:

[0026] The first piece of information to be recommended from the first requesting party is recommended on the page of the target media, and the second piece of information to be recommended from the second requesting party and the third piece of information to be recommended from the first requesting party are recommended on the subordinate page of the first piece of information to be recommended.

[0027] Optionally, the display parameters of the third recommended information are determined by the difference between the recommendation parameters of the second requesting end and the virtual resources allocated by the second requesting end to the execution entity. The display parameters include at least the display content and the size of the display window.

[0028] According to a second aspect of the present disclosure, an information recommendation apparatus is provided, the apparatus comprising:

[0029] The receiving module is configured to receive information recommendation requests for the target media from multiple requesting clients;

[0030] The aggregation processing module is configured to perform aggregation processing on multiple recommendation parameters to obtain aggregated recommendation parameters when none of the recommendation parameters included in the recommendation request meet the target recommendation parameters of the target media.

[0031] The recommendation module is configured to recommend information to be recommended by each of the requesting clients when the aggregated recommendation parameters meet the target recommendation parameters.

[0032] Optionally, the recommendation module is specifically configured to execute:

[0033] The first piece of information to be recommended is recommended on the page of the target media, and the second piece of information to be recommended is recommended on the subordinate page of the first piece of information to be recommended;

[0034] Wherein, the first information to be recommended and the second information to be recommended are the information to be recommended corresponding to each of the requesting ends.

[0035] Optionally, the first and / or second information to be recommended includes a task to be performed, and the device further includes:

[0036] The execution determination module is configured to determine whether the task to be executed is to be executed.

[0037] The allocation module is configured to allocate virtual resources of corresponding value from the remaining resources to the execution entity of the task to be executed if the execution is true. The remaining resources are the margin between the aggregated recommendation parameters and the target recommendation parameters.

[0038] Optionally, the second recommendation information includes a task to be executed, which is a target application installation task, and the device further includes:

[0039] The first list acquisition module is configured to use a pre-installed target plugin to acquire a list of applications in the current terminal device, thereby obtaining a first list; the target plugin is installed on the requesting end corresponding to the first information to be recommended.

[0040] The execution determination module is specifically configured to execute:

[0041] The target plugin is used to obtain the application list in the terminal device again, resulting in a second list;

[0042] Based on the second list and the first list, determine whether the target application installation task is executed.

[0043] Optionally, the device further includes:

[0044] The sorting determination module is configured to perform a sorting based on historical data to determine the conversion efficiency of the multiple requesting ends;

[0045] The request end determination module is configured to determine the request ends that rank in the top N by conversion efficiency as the first request end, and determine the remaining request ends other than the first request end as the second request end, where N≥1;

[0046] The recommendation module is further configured to execute:

[0047] The first piece of information to be recommended from the first requesting party is recommended on the page of the target media, and the second piece of information to be recommended from the second requesting party is recommended on the subordinate page of the first piece of information to be recommended.

[0048] Optionally, the recommendation module is further configured to perform:

[0049] The first piece of information to be recommended from the first requesting party is recommended on the page of the target media, and the second piece of information to be recommended from the second requesting party and the third piece of information to be recommended from the first requesting party are recommended on the subordinate page of the first piece of information to be recommended.

[0050] According to a third aspect of the present disclosure, an electronic device is provided, comprising:

[0051] processor;

[0052] Memory used to store the processor's executable instructions;

[0053] The processor is configured to execute the instructions to implement the information recommendation method as described in the first aspect.

[0054] According to a fourth aspect of the present disclosure, a computer-readable storage medium is provided that, when instructions in the computer-readable storage medium are executed by a processor of a server, enables the server to perform the information recommendation method as described in the first aspect.

[0055] According to a fifth aspect of the present disclosure, a computer program product is provided, including a computer program / instructions, wherein the computer program / instructions, when executed by a processor, implement the information recommendation method described in the first aspect.

[0056] The technical solutions provided by the embodiments of this disclosure bring at least the following beneficial effects:

[0057] In embodiments of this disclosure, multiple requesting clients receive information recommendation requests for a target media. When none of the recommendation parameters included in the request meet the target recommendation parameters of the target media, the recommendation parameters are aggregated to obtain aggregated recommendation parameters. If the aggregated recommendation parameters meet the target recommendation parameters, the information to be recommended from each requesting client is recommended. In this way, multiple requesting clients that do not meet the target recommendation parameters are aggregated, and the information to be recommended from each requesting client is recommended only when the aggregated recommendation parameters meet the target recommendation parameters. This allows each requesting client to have more information recommendation opportunities, avoids wasting system performance, and improves information recommendation efficiency.

[0058] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure. Attached Figure Description

[0059] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this disclosure and, together with the description, serve to explain the principles of this disclosure, and are not intended to unduly limit this disclosure.

[0060] Figure 1 This is a flowchart illustrating the steps of a first information recommendation method according to an exemplary embodiment;

[0061] Figure 2 This is a schematic diagram illustrating the first and second information to be recommended according to an exemplary embodiment.

[0062] Figure 3 This is a flowchart illustrating the steps of a second information recommendation method according to an exemplary embodiment;

[0063] Figure 4This is a flowchart illustrating the steps of a third information recommendation method according to an exemplary embodiment;

[0064] Figure 5 This is a structural block diagram of an information recommendation device according to an exemplary embodiment;

[0065] Figure 6 This is a block diagram illustrating an electronic device for information recommendation according to an exemplary embodiment. Detailed Implementation

[0066] To enable those skilled in the art to better understand the technical solutions of this disclosure, the technical solutions in the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings.

[0067] It should be noted that the terms "first," "second," etc., used in the specification, claims, and accompanying drawings of this disclosure are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this disclosure described herein can be implemented in orders other than those illustrated or described herein. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this disclosure. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this disclosure as detailed in the appended claims.

[0068] Figure 1 This is a flowchart illustrating the steps of a first information recommendation method according to an exemplary embodiment, such as... Figure 1 As shown, the method includes the following steps.

[0069] In step S11, multiple requesting parties receive information recommendation requests for the target media.

[0070] The system architecture of this solution is a three-party platform, including the alliance platform, the demand side, and multiple media platforms. The demand side consists of the entities that need resources, namely merchants who want to promote content on the media platforms. The media platforms are the entities that supply resources, and these platforms include various media platforms such as websites and applications (APPs).

[0071] The affiliate platform is a resource aggregation platform, serving as a common path for media platforms to reach both new and existing users on the demand side and achieve expected conversions. The main business logic of the affiliate platform is resource and budget matching. The affiliate platform is the implementing entity for this solution.

[0072] The alliance platform receives information recommendation requests from various demanders. These requests may include recommendation parameters and the identifier of the requested media platform. The alliance platform then aggregates these requests according to the requested media platform and categorizes them accordingly.

[0073] In this embodiment of the disclosure, the target media is one of multiple media platforms, and the demand side can initiate an information recommendation request to it. In this embodiment of the invention, the demand side that initiates the information recommendation request is the requesting side.

[0074] In step S12, when none of the recommendation parameters included in the recommendation request meet the target recommendation parameters of the target media, the multiple recommendation parameters are aggregated to obtain aggregated recommendation parameters.

[0075] Because the target media has limited resources, it has certain conditions for recommending information to the requesting client. When the recommendation parameters provided by the requesting client do not meet the target recommendation parameters, the target media will not give the requesting client the opportunity to recommend matching information. Generally, the target recommendation parameters are calculated using the CPA (Cost Per Activity) method.

[0076] The alliance platform obtains recommendation parameters from recommendation requests. If the recommendation parameters provided by multiple requesting parties do not meet the target recommendation parameters, then according to traditional methods, these requesting parties will not be able to obtain information recommendation opportunities from the target media.

[0077] This solution aggregates recommendation parameters from multiple request endpoints to calculate aggregated recommendation parameters. These aggregated recommendation parameters can be obtained by summing multiple recommendation parameters. For example, the aggregated recommendation parameters can be obtained by calculating the sum or weighted sum of multiple recommendation parameters. Specifically, each request endpoint is pre-weighted according to its conversion efficiency, and then the multiple recommendation parameters and their corresponding weights are weighted and summed to obtain the weighted sum.

[0078] For example, requester A has a recommended parameter of 4, requester B has a recommended parameter of 8, requester C has a recommended parameter of 3, and requester D has a recommended parameter of 1. The target recommended parameter for the target media is 10. Thus, none of the recommended parameters from any of the requesters meet the target recommended parameter. In this case, the recommended parameters from each requester are aggregated, and the sum of the multiple recommended parameters is calculated, resulting in an aggregated recommended parameter of 16.

[0079] In step S13, if the aggregated recommendation parameters meet the target recommendation parameters, the information to be recommended for each of the requesting ends is recommended.

[0080] Determine the relationship between the aggregated recommendation parameters and the target recommendation parameters. If the aggregated recommendation parameters are greater than or equal to the target recommendation parameters, then the aggregated recommendation parameters are determined to satisfy the target recommendation parameters, and the recommended information for each requesting end corresponding to the aggregated recommendation parameters is recommended.

[0081] Specifically, based on the recommended parameters of each requester, the requesters can be combined in such a way that the aggregated recommended parameters are greater than or equal to the target recommended parameters, so as to obtain as many combinations as possible that satisfy the target recommended parameters.

[0082] In this way, when there are multiple requesters whose recommended parameters do not meet the target recommended parameters, the requesters can be combined according to the principle that the aggregated recommended parameters are greater than or equal to the target recommended parameters. This ensures that each requester in the combination has the opportunity to receive information recommendations from the target media, thus maximizing the rational use of the media platform's resources.

[0083] Furthermore, if the aggregated recommendation parameter is less than the recommendation parameter, it is determined that the aggregated recommendation parameter does not meet the target recommendation parameter, and each requesting end cannot obtain the recommendation qualification of the target media.

[0084] In summary, in the embodiments of this disclosure, multiple requesting clients receive information recommendation requests for a target media. When none of the recommendation parameters included in the request meet the target recommendation parameters of the target media, the recommendation parameters are aggregated to obtain aggregated recommendation parameters. If the aggregated recommendation parameters meet the target recommendation parameters, the information to be recommended from each requesting client is recommended. In this way, multiple requesting clients that do not meet the target recommendation parameters are aggregated, and the information to be recommended from each requesting client is recommended only when the aggregated recommendation parameters meet the target recommendation parameters. This allows each requesting client to have more information recommendation opportunities, avoids wasting system performance, and improves information recommendation efficiency.

[0085] In one possible implementation, recommending the information to be recommended to each of the requesting ends includes step S131:

[0086] In step S131, a first piece of information to be recommended is recommended on the page of the target media, and a second piece of information to be recommended is recommended on the subordinate page of the first piece of information to be recommended; wherein the first piece of information to be recommended and the second piece of information to be recommended are the information to be recommended corresponding to each of the requesting ends.

[0087] In this embodiment of the disclosure, recommending first recommended information on the target media's page allows users to view the first recommended information while browsing the target media page, thereby fulfilling the purpose of information promotion for the requesting end corresponding to the first recommended information. Furthermore, when a user clicks to enter a sub-page of the first recommended information, they can also see second recommended information on the sub-page, fulfilling the purpose of information promotion for the requesting end corresponding to the second recommended information.

[0088] Specifically, both the first and second information to be recommended can include recommendation information corresponding to at least one requester. For example, the first information to be recommended includes recommendation information from requester A, and the second information to be recommended includes recommendation information from requesters B, C, and D.

[0089] In this way, by using the target media's page as the entry page, as long as the aggregated recommendation parameters of multiple requesting parties meet the target recommendation parameters, the lower-level pages of the entry page can be used to recommend the information to be recommended to multiple requesting parties at the same time, providing more requesting parties with information recommendation opportunities and improving information recommendation efficiency.

[0090] Figure 2 This is a schematic diagram illustrating the first and second information to be recommended according to an exemplary embodiment.

[0091] Reference Figure 2 The left image shows the target media's webpage, which contains the first piece of information to be recommended. Users can access the next page of this first piece of information by clicking a button or performing a task within it. Figure 2 The image on the right in the image shows a second set of recommended information on this subordinate page.

[0092] The first piece of information to be recommended can be the information to be recommended from one of the multiple requesting clients, and the second piece of information to be recommended can be the information to be recommended from the other requesting clients. For example, the first piece of information to be recommended includes the information to be recommended from requesting client A, and the second piece of information to be recommended includes the information to be recommended from requesting clients B, C, and D.

[0093] In one possible implementation, the first and / or second information to be recommended includes a task to be performed. After recommending the first information to be recommended on the page of the target media and recommending the second information to be recommended on a subordinate page of the first information to be recommended, the method further includes:

[0094] Step S14: Determine whether the task to be executed is to be executed;

[0095] Step S15: If yes, then allocate virtual resources of corresponding value from the remaining resources to the execution entity of the task to be executed, where the remaining resources are the margin when the aggregated recommendation parameters exceed the target recommendation parameters.

[0096] In steps S14-S15, to improve the conversion effect of information recommendation, a task to be performed can be added to the first or second information to be recommended. This task may include application installation, viewing, registration, etc.

[0097] If the aggregated recommendation parameter is greater than or equal to the target recommendation parameter, the portion of the aggregated recommendation parameter exceeding the target recommendation parameter is considered surplus resources. These surplus resources can be used as a reward for the entity that completes the task; that is, the virtual resources corresponding to the surplus resources can be allocated to the entity that completes the task. This entity can be a user.

[0098] In this way, this solution can provide information recommendation opportunities to each requesting end without increasing the recommendation parameters of each requesting end, and can also return some of the remaining resources to the executing entity to incentivize the executing entity to complete the tasks to be performed, thereby increasing the executing entity's enthusiasm for completing the tasks to be performed, and thus improving the conversion effect of information promotion by each requesting end.

[0099] Figure 3 This is a flowchart illustrating the steps of a second information recommendation method according to an exemplary embodiment, such as... Figure 3 As shown, the method includes the following steps.

[0100] In step S21, multiple requesting parties receive information recommendation requests for the target media.

[0101] In this embodiment of the disclosure, step S21 can refer to step S11, and will not be repeated here.

[0102] In step S22, when none of the recommendation parameters included in the recommendation request meet the target recommendation parameters of the target media, the multiple recommendation parameters are aggregated to obtain aggregated recommendation parameters.

[0103] In this embodiment of the disclosure, step S22 can refer to step S12, and will not be repeated here.

[0104] In step S23, if the aggregated recommendation parameters meet the target recommendation parameters, the conversion efficiency ranking of the multiple request ends is determined based on historical data.

[0105] Historical data can include the content and location of recommended information from a period of time prior to the current time, as well as the corresponding conversion efficiency. Multiple requests are categorized based on similar recommended content and location, and the conversion efficiency of requests within each category is ranked according to their respective conversion efficiencies.

[0106] In step S24, the request terminals ranked in the top N by conversion efficiency are determined as the first request terminals, and the remaining request terminals other than the first request terminals are determined as the second request terminals, where N≥1.

[0107] The top N requesters with the highest conversion rates are designated as the first requester, and the remaining requesters are designated as the second requester. The affiliate platform will then match different information recommendation positions for the first and second requesters.

[0108] In one possible implementation, based on the attribute information of the plurality of requesting ends, a first requesting end suitable for display on the page of the target media is determined from the plurality of requesting ends, and a second requesting end suitable for display on the subordinate receiving page is determined.

[0109] Unlike steps S23 and S24, this method determines the first and second requesting ends based on the attribute information of the requesting end, which is another method for determining the first and second requesting ends.

[0110] In this embodiment, the attribute information of the requesting end includes the product category, conversion mode, and content of the information to be recommended. This attribute information can be input into a pre-trained model to determine the recommendation position of the information to be recommended on the requesting end, such as the target media page or a subordinate landing page. This allows for the determination of a first requesting end suitable for display on the target media page and a second requesting end suitable for display on a subordinate landing page from multiple requesting ends.

[0111] In this way, based on the attribute information of the requesting end, the first requesting end suitable for display on the target media page and the second requesting end suitable for display on the subordinate page can be determined, which can match more suitable recommendation positions for multiple requesting ends and improve the efficiency of information recommendation.

[0112] After step S24, step S25 or step S26 can be performed.

[0113] In step S25, the first recommended information from the first requesting party is recommended on the page of the target media, and the second recommended information from the second requesting party is recommended on the subordinate page of the first recommended information.

[0114] In this embodiment of the disclosure, the first requesting end is a requesting end with higher conversion efficiency, and the second requesting end is a requesting end with lower conversion efficiency. Setting the first information to be recommended on the target media page for recommendation can obtain higher page views, maximize the conversion efficiency of the first information to be recommended, and thus improve the overall conversion efficiency.

[0115] In step S26, the first recommended information from the first requesting end is recommended on the page of the target media, and the second recommended information from the second requesting end and the third recommended information from the first requesting end are recommended on the subordinate page of the first recommended information.

[0116] In practical applications, to prevent the first requesting client from lacking incentive to recommend second recommended information on subordinate landing pages after being recommended on the target media's entry page, some recommended information can be allocated to the first requesting client on the subordinate landing page. This means adding a third recommended information corresponding to the first requesting client to the subordinate landing page. In this way, to gain the opportunity for recommendation, the first requesting client will recommend the second recommended information on the subordinate landing page, preventing the first requesting client from locking the entry page and protecting the rights of the second requesting client.

[0117] In one possible implementation, the display parameters of the third recommended information are determined by the difference between the recommendation parameters of the second requesting end and the virtual resources allocated by the second requesting end to the execution entity. The display parameters include at least the display content and the size of the display window.

[0118] When the lower-level receiving page includes a second piece of information to be recommended and a third piece of information to be recommended from the first requester, the alliance platform can calculate the difference between the recommendation parameters of the second requester and the virtual resources allocated to the execution entity, and use this difference as the basis for determining the display parameters of the third piece of information to be recommended.

[0119] In other words, the recommendation resources corresponding to the recommendation parameters of the second requesting end are partly allocated to the second information to be recommended and partly allocated to the third information to be recommended. The part of the recommendation resources allocated to the third information to be recommended determines the display method of the third information to be recommended, namely the display content, the size of the display window, and other display parameters.

[0120] The above rules provide a method and basis for the alliance platform to set the display parameters of third-party recommended information, further improving the efficiency of information recommendation.

[0121] Figure 4 This is a flowchart illustrating the steps of a third information recommendation method according to an exemplary embodiment, such as... Figure 4 As shown, the method includes the following steps.

[0122] In step S31, multiple requesting parties receive information recommendation requests for the target media.

[0123] In this embodiment of the disclosure, step S31 can refer to step S11, and will not be repeated here.

[0124] In step S32, when none of the recommendation parameters included in the recommendation request meet the target recommendation parameters of the target media, the multiple recommendation parameters are aggregated to obtain aggregated recommendation parameters.

[0125] In this embodiment of the disclosure, step S32 can refer to step S12, and will not be repeated here.

[0126] In step S33, if the second information to be recommended includes a task to be executed, and the task to be executed is a target application installation task, the application list in the current terminal device is obtained by using the pre-installed target plugin to obtain a first list; the target plugin is installed by the requesting end corresponding to the first information to be recommended.

[0127] To improve recommendation effectiveness and conversion efficiency, tasks to be performed can be added to the first or second list of items to be recommended. These tasks can include application installation, viewing, registration, etc.

[0128] By installing target plugins, such as the self-attribution SDK (Software Development Kit), the requesting end can obtain the channels through which users download the requesting end application, thereby determining whether the user's installation of the requesting end application is attributed to the first or second recommended information, and also knowing the target media that recommends the first or second recommended information.

[0129] Traditional methods require each requesting client to connect to the target plugin of the alliance platform so that each client can use the target plugin to detect the attribution of new application installations on the terminal. However, connecting to the target plugin requires deploying data interfaces, which is technically costly.

[0130] In this embodiment of the disclosure, since the second information to be recommended is located on the subordinate page of the first information to be recommended, the target plugin accessed by the request end of the first information to be recommended can be directly used to detect the execution status of the application installation task of the second information to be recommended. In this way, the request end of the second information to be recommended can obtain the attribution of the application installation without accessing the target plugin, thereby reducing the technical cost of the request end of the second information to be recommended.

[0131] Specifically, if the second set of recommended information includes tasks to be performed, the target plugin can be used to obtain a list of applications on the current user's terminal device before loading the second set of recommended information to obtain a first list for subsequent comparative analysis.

[0132] In step S34, if the aggregated recommendation parameters satisfy the target recommendation parameters, a first piece of information to be recommended is recommended on the page of the target media, and a second piece of information to be recommended is recommended on the subordinate page of the first piece of information to be recommended; wherein, the first piece of information to be recommended and the second piece of information to be recommended are respectively the information to be recommended corresponding to each of the requesting ends; the first piece of information to be recommended and / or the second piece of information to be recommended includes a task to be executed.

[0133] In this embodiment of the disclosure, the task to be performed included in the first and second recommended information is the installation task of the target application. Rewards for completing the task can be displayed on the first and second recommended information to incentivize the executing entity to perform the task.

[0134] In step S35, the target plugin is used to obtain the application list in the terminal device again, resulting in a second list.

[0135] After recommending the first or second list of recommended information, the target plugin can be used to obtain the second list of applications on the terminal device.

[0136] In step S36, it is determined whether the target application installation task is executed based on the second list and the first list.

[0137] If the second list contains more target applications than the first list, it indicates that the executing entity performed the installation task for the target application in the first or second list of recommended information.

[0138] In step S37, if so, virtual resources of corresponding value are allocated from the remaining resources to the execution entity of the task to be executed, wherein the remaining resources are the margin when the aggregated recommendation parameters exceed the target recommendation parameters.

[0139] Since the aggregated recommended parameters only need to satisfy the target recommended parameters, if the aggregated recommended parameters are greater than the target recommended parameters, the difference between the two is the remaining resources, which can be allocated to the execution entities that complete the tasks to be executed.

[0140] In this way, this solution can ensure that each requesting end receives the requested recommendation opportunity without increasing the recommendation parameters of each requesting end. It can also return some of the remaining resources to the executing entity to incentivize the executing entity to complete the tasks to be performed, thereby increasing the executing entity's enthusiasm for completing the tasks to be performed and thus improving the conversion rate of recommendation information of each requesting end.

[0141] Furthermore, by utilizing the target plugin installed on the first requesting end, it can be determined whether the pending task has been completed. Since the second recommended information is located on the receiving page of the first requesting end, the target plugin installed on the first requesting end can be directly used to probe the execution status of the application installation task in the second recommended information. In this way, the second requesting end can obtain the attribution of application installation without installing the target plugin, thereby reducing the information recommendation cost for the second requesting end.

[0142] Figure 5 This is a structural block diagram illustrating an information recommendation device according to an exemplary embodiment. For example... Figure 4 As shown, the information recommendation device 40 includes:

[0143] The receiving module 41 is configured to receive multiple requesting clients for information recommendation requests related to the target media.

[0144] The aggregation processing module 42 is configured to perform aggregation processing on multiple recommendation parameters to obtain aggregated recommendation parameters when none of the recommendation parameters included in the recommendation request meet the target recommendation parameters of the target media.

[0145] The recommendation module 43 is configured to recommend the information to be recommended for each of the requesting ends when the aggregated recommendation parameters meet the target recommendation parameters.

[0146] Regarding the apparatus in the above embodiments, the specific manner in which each module performs its operation has been described in detail in the embodiments related to the method, and will not be elaborated upon here.

[0147] Figure 6 This is a block diagram illustrating an electronic device for information recommendation according to an exemplary embodiment. Its internal structure diagram can be as follows: Figure 6As shown, the server or electronic device includes a processor, memory, and a network interface connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The network interface of the server or electronic device is used to communicate with external terminals via a network connection. When the computer program is executed by the processor, it implements an information recommendation method.

[0148] Those skilled in the art will understand that Figure 6 The structure shown is merely a block diagram of a portion of the structure related to the present disclosure and does not constitute a limitation on the server or electronic device to which the present disclosure is applied. A specific server or electronic device may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0149] In an exemplary embodiment, a server or electronic device is also provided, including: a processor; and a memory for storing processor-executable instructions; wherein the processor is configured to execute the instructions to implement the information recommendation method as described in the embodiments of this disclosure.

[0150] In an exemplary embodiment, a computer-readable storage medium is also provided, which, when executed by a processor of a server or electronic device, enables the server or electronic device to perform the information recommendation method of the present disclosure embodiments. The computer-readable storage medium may be a ROM, random access memory (RAM), CD-ROM, magnetic tape, floppy disk, or optical data storage device, etc.

[0151] In an exemplary embodiment, a computer program product including instructions is also provided, which, when run on a computer, causes the computer to perform the information recommendation method of the present disclosure embodiments.

[0152] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. This computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and RAMbus dynamic RAM (RDRAM), etc.

[0153] Other embodiments of this disclosure will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this disclosure are indicated by the following claims.

[0154] It should be understood that this disclosure is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this disclosure is limited only by the appended claims.

Claims

1. An information recommendation method, characterized in that, The method includes: Receive multiple requests from clients for information recommendations related to the target media; When none of the recommendation parameters included in the recommendation request meet the target recommendation parameters of the target media, the multiple recommendation parameters are aggregated to obtain aggregated recommendation parameters. If the aggregated recommendation parameters meet the target recommendation parameters, the information to be recommended for each of the requesting ends is recommended. The process of recommending the information to be recommended to each of the requesting clients includes: The first piece of information to be recommended is recommended on the page of the target media, and the second piece of information to be recommended is recommended on the subordinate page of the first piece of information to be recommended; The second list of recommended information includes a task to be performed, which is a target application installation task. Before recommending the second list of recommended information on the subordinate page of the first list of recommended information, it also includes: Using a pre-installed target plugin, a list of applications in the current terminal device is obtained to form a first list; the target plugin is installed on the requesting end corresponding to the first information to be recommended; the target plugin is used to detect the execution status of the application installation task of the second information to be recommended.

2. The method according to claim 1, characterized in that, The first information to be recommended and the second information to be recommended are the information to be recommended for each of the requesting ends.

3. The method according to claim 1, characterized in that, The first and / or second information to be recommended includes a task to be performed. After recommending the first information to be recommended on the page of the target media and recommending the second information to be recommended on the subordinate page of the first information to be recommended, the method further includes: Determine whether the task to be executed is to be executed; If so, virtual resources of corresponding value are allocated from the remaining resources to the execution entity of the task to be executed, where the remaining resources are the margin between the aggregated recommendation parameters and the target recommendation parameters.

4. The method according to claim 3, characterized in that, Determining whether the task to be executed is to be executed includes: The target plugin is used to obtain the application list in the terminal device again, resulting in a second list; Based on the second list and the first list, determine whether the target application installation task is executed.

5. The method according to claim 2, characterized in that, Before recommending the first piece of information to be recommended on the target media's page, and recommending the second piece of information to be recommended on the subordinate page of the first piece of information to be recommended, the method further includes: The conversion efficiency ranking of the multiple requesting ends is determined based on historical data; The request terminals ranked in the top N by conversion efficiency are determined as the first request terminals, and the remaining request terminals other than the first request terminals are determined as the second request terminals, where N≥1; The step of recommending first recommended information on the target media's page and recommending second recommended information on the subordinate page of the first recommended information includes: The first piece of information to be recommended from the first requesting party is recommended on the page of the target media, and the second piece of information to be recommended from the second requesting party is recommended on the subordinate page of the first piece of information to be recommended.

6. The method according to claim 5, characterized in that, The step of recommending first recommended information on the target media's page and recommending second recommended information on the subordinate page of the first recommended information includes: The first piece of information to be recommended from the first requesting party is recommended on the page of the target media, and the second piece of information to be recommended from the second requesting party and the third piece of information to be recommended from the first requesting party are recommended on the subordinate page of the first piece of information to be recommended.

7. The method according to claim 6, characterized in that, The display parameters of the third recommended information are determined by the difference between the recommendation parameters of the second requesting end and the virtual resources allocated by the second requesting end to the execution entity. The display parameters include at least the display content and the size of the display window.

8. An information recommendation device, characterized in that, The device includes: The receiving module is configured to receive information recommendation requests for the target media from multiple requesting clients; The aggregation processing module is configured to perform aggregation processing on multiple recommendation parameters to obtain aggregated recommendation parameters when none of the recommendation parameters included in the recommendation request meet the target recommendation parameters of the target media. The recommendation module is configured to recommend information to be recommended for each of the requesting clients when the aggregated recommendation parameters meet the target recommendation parameters. The recommendation module is specifically configured to execute: The first piece of information to be recommended is recommended on the page of the target media, and the second piece of information to be recommended is recommended on the subordinate page of the first piece of information to be recommended; The second list of recommended information includes a task to be executed, which is a target application installation task. The device is also configured to execute: Using a pre-installed target plugin, a list of applications in the current terminal device is obtained to form a first list; the target plugin is installed on the requesting end corresponding to the first information to be recommended; the target plugin is used to detect the execution status of the application installation task of the second information to be recommended.

9. An electronic device, characterized in that, include: processor; Memory used to store the processor's executable instructions; The processor is configured to execute the instructions to implement the information recommendation method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, When the instructions in the computer-readable storage medium are executed by the server's processor, the server is able to perform the information recommendation method as described in any one of claims 1 to 7.

11. A computer program product, comprising a computer program / instructions, characterized in that, When the computer program / instructions are executed by the processor, they implement the information recommendation method according to any one of claims 1 to 7.

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