Information recommendation processing method and device, electronic device and computer program product

Abstract

The embodiment of the invention provides an information recommendation processing method and device, an electronic device and a computer program product, and the method comprises the steps: obtaining input task information which is used for determining a to-be-executed target task; candidate recommendation information matched with the target task and obtained through searching in multiple applications is obtained, a set of candidate recommendation information is obtained, and the multiple applications are the applications allowed to execute the target task; and displaying at least part of the recommendation information in the group of candidate recommendation information, so that the problems of operation and processing complexity of a plurality of applications in related technologies can be solved, the recommendation information matched with the plurality of applications is recommended based on the input task information, and the operation complexity of the plurality of applications is reduced.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of wireless communication technology, and more specifically, to an information recommendation processing method, device, electronic device, and computer program product. Background Art

[0002] Mobile terminal applications are constantly developing, and users need to select application services that suit them from a large amount of information, which is a problem that current smart terminals need to solve. Artificial intelligence technology is advancing by leaps and bounds. How to use artificial intelligence technology to process information and apply it to terminal products to reduce the user's operating burden.

[0003] There is no solution yet for the relatively complex problem of operating multiple applications in the related art. Summary of the invention

[0004] The embodiments of the present application provide an information recommendation processing method, device, electronic device and computer program product to at least solve the problem of operating multiple applications and processing more complex problems in the related art.

[0005] According to an embodiment of the present application, a method for processing information recommendation is provided, which is applied to a mobile terminal, and the method includes:

[0006] Acquire input task information, wherein the task information is used to determine a target task to be performed;

[0007] Acquire candidate recommendation information that matches the target task and is obtained by searching in multiple applications to obtain a group of candidate recommendation information, wherein the multiple applications are applications that are allowed to execute the target task;

[0008] At least part of the set of candidate recommendation information is displayed.

[0009] According to another embodiment of the present application, there is also provided an information recommendation processing device, which is applied to a mobile terminal, and the device includes:

[0010] A first acquisition module, used to acquire input task information, wherein the task information is used to determine a target task to be executed;

[0011] A second acquisition module is used to acquire candidate recommendation information matching the target task obtained by searching in multiple applications to obtain a group of candidate recommendation information, wherein the multiple applications are applications that are allowed to execute the target task;

[0012] The display module is used to display at least part of the recommended information in the set of candidate recommended information.

[0013] According to another embodiment of the present application, a computer program product is provided, including computer program instructions, wherein the computer program instructions enable a computer to implement the steps in any of the above method embodiments.

[0014] According to another embodiment of the present application, a computer-readable storage medium is provided, in which a computer program is stored, wherein the computer program is configured to execute the steps of any of the above method embodiments when run.

[0015] According to another embodiment of the present application, an electronic device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor is configured to run the computer program to execute the steps in any one of the above method embodiments.

[0016] In an embodiment of the present application, input task information is obtained, wherein the task information is used to determine a target task to be executed; candidate recommendation information matching the target task obtained by searching in multiple applications is obtained to obtain a group of candidate recommendation information, wherein the multiple applications are applications that allow the target task to be executed; at least part of the recommendation information in the group of candidate recommendation information is displayed, which can solve the problem of operating multiple applications and handling more complex problems in related technologies, and recommends recommendation information matching multiple applications based on the input task information, thereby reducing the operating complexity of multiple applications. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 It is a hardware structure block diagram of a mobile terminal of the information recommendation processing method of an embodiment of the present application;

[0018] Figure 2 is a flowchart of an information recommendation processing method according to an embodiment of the present application;

[0019] Figure 3 is a flowchart of an information recommendation processing method according to an optional embodiment of the present application;

[0020] Figure 4 is a flow chart of mobile terminal recommendation information according to an embodiment of the present application;

[0021] Figure 5 is a schematic diagram of the recommendation information processing of this embodiment;

[0022] Figure 6 A block diagram of an information recommendation processing device according to an embodiment of the present application;

[0023] Figure 7 A block diagram of an information recommendation processing device according to an optional embodiment of the present application. DETAILED DESCRIPTION

[0024] The embodiments of the present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0025] It should be noted that the terms "first", "second", etc. in the specification and claims of this application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence.

[0026] The method embodiments provided in the embodiments of the present application can be executed in a mobile terminal or a similar computing device. Taking running on a mobile terminal as an example, Figure 1 is a hardware structure block diagram of a mobile terminal of the information recommendation processing method of an embodiment of the present application, such as Figure 1 As shown, the mobile terminal may include one or more ( Figure 1 Only one is shown in the figure) a processor 102 (the processor 102 may include but is not limited to a processing device such as a microprocessor MCU or a programmable logic device) and a memory 104 for storing data, wherein the mobile terminal may also include a transmission device 106 and an input / output device 108 for communication functions. It can be understood by those skilled in the art that Figure 1 The structure shown is only for illustration and does not limit the structure of the mobile terminal. Figure 1 More or fewer components as shown, or with Figure 1 Different configurations shown.

[0027] The memory 104 can be used to store computer programs, for example, software programs and modules of application software, such as the computer program corresponding to the information recommendation processing method in the embodiment of the present application. The processor 102 executes various functional applications and single board matching by running the computer program stored in the memory 104, that is, to implement the above method. The memory 104 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include a memory remotely arranged relative to the processor 102, and these remote memories may be connected to the mobile terminal via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0028] The transmission device 106 is used to receive or send data via a network. The specific example of the above network may include a wireless network provided by a communication provider of the mobile terminal. In one example, the transmission device 106 includes a network adapter (Network Interface Controller, referred to as NIC), which can be connected to other network devices through a base station so as to communicate with the Internet. In one example, the transmission device 106 can be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0029] In this embodiment, a method for processing information recommendation running on the above mobile terminal is provided. Figure 2 is a flowchart of an information recommendation processing method according to an embodiment of the present application. Figure 2 As shown, applied to a mobile terminal, the process includes the following steps:

[0030] Step S202, obtaining input task information, where the task information is used to determine the target task to be executed;

[0031] Step S204, obtaining candidate recommendation information matching the target task obtained by searching in multiple applications, and obtaining a group of candidate recommendation information, wherein the multiple applications are applications that are allowed to execute the target task;

[0032] Step S206: display at least part of a set of candidate recommendation information.

[0033] Through the above steps S202 to S206, the problem of operating multiple applications and handling relatively complex problems in related technologies can be solved, and recommendation information matching multiple applications is recommended based on the input task information, thereby reducing the complexity of operating multiple applications.

[0034] Among them, the execution subject of the above steps can be a mobile terminal or other devices, but is not limited to this. The above steps of obtaining task information, searching for matching applications and obtaining candidate recommendation information, and displaying recommendation results. Execute in order, that is, only after obtaining the task information input by the user, can the target task to be executed be determined, and then the candidate recommendation information matching the target task can be obtained, and finally at least part of the recommendation information is displayed. The displayed content can be determined according to the user's choice, or according to certain preset rules, such as sorting the candidate recommendation information first, and displaying a certain number of recommended information with the highest sorting. The recommended information can be a list or different tabs.

[0035] Before obtaining candidate recommendation information, it is necessary to determine the specific target task based on the task information and filter out applications that can perform the task from the application set. This step is the key to ensuring the accuracy of the recommendation information. Figure 3is a flowchart of an information recommendation processing method according to an optional embodiment of the present application. Figure 3 As shown, the method also includes:

[0036] S302, determining a target task according to the task information;

[0037] S304: Determine, in the application set, a plurality of applications that are allowed to execute the target task.

[0038] Through the above S302 to S304, it is possible to avoid searching for irrelevant applications, thereby improving search efficiency and recommendation accuracy. For example, when a user searches for "nearby food", only catering, map and review applications are searched, without involving news or game applications.

[0039] In one embodiment, the above step S302 may specifically include: performing semantic recognition on the task information to obtain a semantic recognition result, that is, the target task can be directly determined based on the task information; when the semantic recognition result represents the target semantics, the target semantics is determined as the target task, or, when the semantic recognition result does not accurately represent the target semantics, at least one of the location information of the target terminal and the user tag information is determined as the target task with the target semantics. The target task is determined by semantic recognition. If the recognition result is unclear, it can be further clarified by combining information such as the user location and personalized tags. This achieves attention to the personalized needs of users and flexibility in handling uncertain tasks. This method can better understand the real needs of users. Even if the information entered by the user is incomplete or vague, it can provide more accurate recommendations by combining location information and user preferences. For example, if the user enters "I want to eat", the system can recommend nearby restaurants based on the user's current location and historical dining preferences.

[0040] In one embodiment, the execution application can also be determined by the task type or task description information, which depends on the pre-correspondence between the application and the task type in the application set. This step ensures the pertinence of the recommended information and the selectivity of the application, and avoids the interference of irrelevant applications. The above step S304 can specifically include one of the following: obtaining the task type of the target task, selecting an application that allows the execution of tasks of the task type in the application set, and determining the selected application as multiple applications, wherein each application in the application set has a pre-established correspondence with at least one task type, and each application in the application set is set to allow the execution of tasks of the corresponding task type, for example, the task information is a school bag, the target task is to buy a school bag, the task type is shopping, and the applications allowed to execute shopping include application 1 and application 2; obtaining the task description information of the target task, selecting an application whose application description information matches the task description information in the application set, and determining the selected application as multiple applications, for example, the task information is location 1, the target task is to go to location 1, the task description information of the target task is to travel to location 1, and the application description information matches travel with a certain map and a certain travel APP. This approach can ensure the rationality of the search scope, avoid blind search, and improve the pertinence of recommended information. For example, when searching for "flights from location 1 to location 2", only airlines and travel booking applications are searched, without involving other types of applications.

[0041] In one embodiment, a method for obtaining candidate recommendation information includes displaying an application window and searching for matching information. This process involves parallel processing of multiple applications, which improves the efficiency of information acquisition. Correspondingly, the above step S204 may specifically include: displaying the application window of each application in multiple applications; displaying candidate recommendation information matching the target task obtained by searching in each application. This method can provide an intuitive display of multi-application search results, and users can see the recommendation information of different applications at the same time, which is convenient for quick comparison and selection. For example, when searching for "weekend activities", recommendations from multiple applications such as social, entertainment and travel can be seen.

[0042] In another embodiment, the specific scenarios and methods for obtaining candidate recommendation information are further refined, including starting an application to obtain information when the application is not running, or calling a preconfigured application interface to obtain information. The above step S204 may specifically include one of the following: when multiple applications are not running, running multiple applications, and obtaining candidate recommendation information matching the target task searched in each of the multiple applications to obtain a set of candidate recommendation information; or when the first part of the multiple applications is not running and the second part of the multiple applications is running, running the first part of the applications, and when both the first part of the applications and the second part of the applications are running, obtaining candidate recommendation information matching the target task searched in multiple applications to obtain a set of candidate recommendation information; calling a preconfigured application interface in multiple applications to obtain candidate recommendation information matching the target task searched in multiple applications to obtain a set of candidate recommendation information. By automatically running applications or calling application interfaces to obtain recommended information, the user's operation steps can be reduced, providing a more convenient and fast search experience. For example, after the user enters "weather forecast", the system automatically obtains information from the weather application without the user manually opening the application.

[0043] In one embodiment, when displaying the recommended information, an application identifier or a recommendation priority identifier may be attached to help the user quickly identify the source or priority of the recommended information. This enhances the readability of the recommended information and the convenience of user selection. The above step S206 may specifically include at least one of the following: displaying the application identifier corresponding to each piece of recommended information in at least part of the recommended information, wherein the application represented by each application identifier is an application used to search for the corresponding recommended information in at least part of the recommended information; displaying the recommendation priority identifier corresponding to each piece of recommended information in at least part of the recommended information, wherein the recommendation priority identifier is used to indicate the recommendation priority of the corresponding recommended information in at least part of the recommended information. This method can help users quickly identify the source and importance of the recommended information, such as displaying application identifiers such as "a certain group" and "a certain review", as well as the recommendation priority determined based on the user's historical behavior and the reputation of the application, so that users can trust the recommendation results more.

[0044] In another embodiment, after the user selects the recommended information, the application page related to the information can be displayed and the task can be executed directly. The user operation process can be simplified and the efficiency of task execution can be improved. The above step S206 can also specifically include: when the target recommended information in at least part of the recommended information is selected, displaying the page for executing the target task in the target application, wherein the target recommended information is the candidate recommended information that matches the target task and is searched in the target application. This method can achieve seamless jumps, and users can directly enter the specific page of the application from the recommended information. For example, click the "Book" button in the recommended information to jump directly to the booking page, which greatly improves the convenience of operation and user experience.

[0045] The embodiment of the present application allows the user to operate the mobile phone, input task information, analyze the user's intention through AI technology, start multiple similar applications in multiple windows, or search for relevant information to obtain the candidate recommendation information required by the user. It also analyzes the user's personalized characteristics, the current user's environment and location, and gives the most suitable ranking for the user for the user to choose.

[0046] For example, when a user gives a "return to the hotel" instruction at a certain location, the mobile terminal using the above solution provides multiple options such as bus, subway, taxi, etc., with corresponding time, price, and navigation route map for the user to choose. After the user makes a choice, if necessary, the next service link is entered, for example, if a taxi is selected, the patented artificial intelligence assistant executes the taxi order task. If the user is not satisfied with the result, the keyword can be revised and the output result can be analyzed again.

[0047] Figure 4 is a flow chart of mobile terminal recommendation information according to an embodiment of the present application, such as Figure 4 As shown, including:

[0048] Step S401, receiving task information input by a user;

[0049] Step S402, determining a target task corresponding to the task information, and determining a plurality of applications that are allowed to execute the target task;

[0050] Step S403, searching for the target task in multiple applications, obtaining matching candidate recommendation information, and obtaining a set of candidate recommendation information;

[0051] In the above step S403, the specific process of obtaining the matching candidate recommendation information is similar to the process of obtaining the candidate recommendation information matching the target task obtained by searching in each of the multiple applications, and will not be described in detail here.

[0052] Step S404, displaying a group of candidate recommendation information for the user to select;

[0053] Step S405, receiving the user's selection information, determining and executing the user's selection result;

[0054] Step S406, receiving the correction information input by the user, recommending a set of candidate recommendation information based on the corrected task information, determining the user's selection result based on the user's selection information, and executing the user's selection result.

[0055] On the display interface of the mobile terminal, the mobile terminal device can obtain the task information input by the user in the form of voice, text, or pictures. User personalized tags, environment, location and other tags define the user's personal preferences, as well as the user's current location, indoor and outdoor information. It is used to adjust the result sorting during artificial intelligence calculations.

[0056] Analyze the task information input by the user, extract keywords, analyze the task type through the artificial intelligence model, and start multiple similar applications or API interfaces to obtain information from each application. Output a set of candidate recommendation information that meets the user's needs (i.e., multiple candidate recommendation information), sort the set of candidate recommendation information, and recommend it to the user.

[0057] After obtaining multiple candidate recommendation information, select a priority recommendation rule according to user habits (for example, when shopping, the price of the product is prioritized, or the good reviews are prioritized, and the promotional coupons are prioritized; when driving, the distance is the shortest or the time is the shortest; when ordering food, a certain cuisine is prioritized or the time is the shortest), and list the sorting results. Analyze the sorting results and sort the results of multiple applications according to the recommendation rules. The user checks the sorted multiple candidate recommendation information and selects the recommendation information that is most suitable for him / her at the moment. The artificial intelligence assistant executes the recommendation information selected by the user. If the multiple recommended recommendation information does not meet the user's current expectations, the user can enter the correction information, and the artificial intelligence analysis and operation unit will reprocess the task information based on the new information entered by the user.

[0058] When executing a task, multiple recommendation information is output and recommended to the user. On the terminal device, it is shown that a task has at least one recommendation result (i.e., candidate recommendation information). Each recommendation result contains an information area for the user to judge, and a button for the user to select the recommendation result, or the information area itself is a button with a selection function. Furthermore, the input information can be corrected to correct the current information when it does not meet expectations. For example, the user inputs the task information "fan", and the recommended result does not find the required one. Enter the "blue" feature in the "correct input information" position, and the user will get the fan he needs.

[0059] Figure 5 is a schematic diagram of the recommendation information processing of this embodiment. Figure 5As shown, the user is traveling in a city and inputs "eat" into the mobile terminal. The mobile terminal analyzes the task information, extracts keywords, and determines that the user currently needs to eat. Start applications related to dining, such as application 1, application 2, application 3, etc., and find places to eat according to the user's current location. The smart device selects multiple restaurants that are close, reasonably priced, and well-reviewed by users (restaurant A, restaurant B, restaurant C, restaurant D, among which restaurant A and restaurant B are recommended by application 1, and the name of the application can be displayed) for the user to choose. After the user selects one, the smart device proceeds to the next step, reserving the restaurant location, navigating to the restaurant, recommending an order, etc.

[0060] Through the description of the above implementation methods, those skilled in the art can clearly understand that the method according to the above embodiment can be implemented by means of software plus a necessary general hardware platform, and of course can also be implemented by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, a magnetic disk, or an optical disk), and includes a number of instructions for enabling a terminal device (which can be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods described in each embodiment of the present invention.

[0061] In this embodiment, an information recommendation processing device is also provided, which is used to implement the above-mentioned embodiments and preferred implementation modes, and will not be repeated here. As used below, the term "module" can be a combination of software and / or hardware that implements a predetermined function. Although the device described in the following embodiments is preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceivable.

[0062] The present application also provides an information recommendation processing device. Figure 6 is a block diagram of an information recommendation processing device according to an embodiment of the present application, such as Figure 6 As shown, applied to a mobile terminal, the device includes:

[0063] A first acquisition module 62, used to acquire input task information, wherein the task information is used to determine a target task to be performed;

[0064] A second acquisition module 64 is used to acquire candidate recommendation information matching the target task obtained by searching in multiple applications, and obtain a group of candidate recommendation information, wherein the multiple applications are applications that allow the target task to be executed;

[0065] The display module 66 is configured to display at least part of the recommended information in the set of candidate recommended information.

[0066] Figure 7 is a block diagram of an information recommendation processing device according to an optional embodiment of the present application, such as Figure 7 As shown, the device also includes:

[0067] A determination module 72, configured to determine the target task according to the task information;

[0068] The execution module 74 is used to determine the multiple applications in the application set that are allowed to execute the target task.

[0069] In one embodiment, the determination module 72 is also used to perform semantic recognition on the task information to obtain a semantic recognition result; when the semantic recognition result represents the target semantics, the target semantics is determined as the target task; or, when the semantic recognition result does not accurately represent the target semantics, at least one of the location information and user tag information of the target terminal is determined together with the target semantics as the target task.

[0070] In one embodiment, the execution module 74 is also used to determine the multiple applications in the application set that are allowed to execute the target task, including one of the following: obtaining the task type of the target task, selecting an application in the application set that is allowed to execute tasks of the task type, and determining the selected application as the multiple applications, wherein each application in the application set has a pre-established correspondence with at least one task type, and each application in the application set is set to allow execution of tasks of the corresponding task type; obtaining task description information of the target task, selecting an application in the application set whose application description information matches the task description information, and determining the selected application as the multiple applications.

[0071] In one embodiment, the second acquisition module 64 is further configured to display an application window of each application in the plurality of applications; and display candidate recommendation information matching the target task obtained by searching in each application.

[0072] In one embodiment, the second acquisition module 64 is also used to perform one of the following: when none of the multiple applications are being run, run the multiple applications, and obtain candidate recommendation information matching the target task that is searched in each of the multiple applications to obtain the set of candidate recommendation information; or when a first part of the applications in the multiple applications are not being run and a second part of the applications in the multiple applications are being run, run the first part of the applications, and when both the first part of the applications and the second part of the applications are being run, obtain candidate recommendation information matching the target task that is searched in the multiple applications to obtain the set of candidate recommendation information; call an application interface pre-configured in the multiple applications to obtain candidate recommendation information matching the target task that is searched in the multiple applications to obtain the set of candidate recommendation information.

[0073] In one embodiment, the display module 66 is further used to perform at least one of the following: displaying an application identifier corresponding to each piece of recommended information in the at least part of the recommended information, wherein the application represented by each of the application identifiers is an application used to search for the corresponding recommended information in the at least part of the recommended information; displaying a recommendation priority identifier corresponding to each piece of recommended information in the at least part of the recommended information, wherein the recommendation priority identifier is used to indicate the recommendation priority of the corresponding recommended information in the at least part of the recommended information.

[0074] In one embodiment, the display module 66 is also used to display a page for executing the target task in the target application when the target recommendation information in the at least part of the recommendation information is selected, wherein the target recommendation information is candidate recommendation information matching the target task obtained by searching in the target application.

[0075] An embodiment of the present application further provides a computer program product, including computer program instructions, wherein the computer program instructions enable a computer to implement the steps in any of the above method embodiments.

[0076] An embodiment of the present application further provides a computer-readable storage medium, in which a computer program is stored, wherein the computer program is configured to execute the steps of any of the above method embodiments when running.

[0077] In an exemplary embodiment, the computer-readable storage medium may include, but is not limited to, various media that can store computer programs, such as a USB flash drive, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk or an optical disk.

[0078] An embodiment of the present application further provides an electronic device, including a memory and a processor, wherein a computer program is stored in the memory, and the processor is configured to run the computer program to execute the steps in any one of the above method embodiments.

[0079] In an exemplary embodiment, the electronic device may further include a transmission device and an input / output device, wherein the transmission device is connected to the processor, and the input / output device is connected to the processor.

[0080] For specific examples in this embodiment, reference may be made to the examples described in the above embodiments and exemplary implementation modes, and this embodiment will not be described in detail herein.

[0081] Obviously, those skilled in the art should understand that the above modules or steps of the present application can be implemented by a general computing device, they can be concentrated on a single computing device, or distributed on a network composed of multiple computing devices, they can be implemented by a program code executable by a computing device, so that they can be stored in a storage device and executed by the computing device, and in some cases, the steps shown or described can be executed in a different order from that herein, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. Thus, the present application is not limited to any specific combination of hardware and software.

[0082] The above description is only the preferred embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the principles of the present application shall be included in the protection scope of the present application.

Claims

1. A method for information recommendation processing, characterized in that: Applied to a mobile terminal, the method comprises: Acquire input task information, wherein the task information is used to determine a target task to be performed; Acquire candidate recommendation information that matches the target task and is obtained by searching in multiple applications to obtain a group of candidate recommendation information, wherein the multiple applications are applications that are allowed to execute the target task; At least part of the set of candidate recommendation information is displayed.

2. The method according to claim 1, characterized in that: Before obtaining candidate recommendation information matching the target task obtained by searching in multiple applications to obtain a set of candidate recommendation information, the method further includes: Determine the target task according to the task information; The plurality of applications that are allowed to execute the target task are determined in the application set.

3. The method according to claim 2, characterized in that Determining the target task according to the task information includes: Performing semantic recognition on the task information to obtain a semantic recognition result; In the case where the semantic recognition result indicates the target semantics, the target semantics is determined as the target task, or, In the case that the semantic recognition result does not accurately represent the target semantics, at least one of the location information and user tag information of the target terminal and the target semantics are determined as the target task.

4. The method according to claim 2, characterized in that: The determining, in the application set, the plurality of applications that are allowed to execute the target task comprises one of the following: Acquiring a task type of the target task, selecting an application from the application set that is allowed to execute tasks of the task type, and determining the selected application as the multiple applications, wherein each application in the application set has a pre-established corresponding relationship with at least one task type, and each application in the application set is set to be allowed to execute tasks of the corresponding task type; The task description information of the target task is obtained, an application whose application description information matches the task description information is selected from the application set, and the selected application is determined as the multiple applications.

5. The method according to claim 1, characterized in that The step of obtaining candidate recommendation information matching the target task obtained by searching each application in the plurality of applications to obtain a set of candidate recommendation information includes: displaying an application window of each application in the plurality of applications; The candidate recommendation information matching the target task obtained by searching in each application is displayed.

6. The method according to claim 1, characterized in that The step of obtaining candidate recommendation information matching the target task obtained by searching each application in the plurality of applications to obtain a set of candidate recommendation information includes one of the following: When none of the multiple applications are running, running the multiple applications, and obtaining candidate recommendation information matching the target task obtained by searching in each of the multiple applications, to obtain the set of candidate recommendation information; or, when a first part of the multiple applications is not being run and a second part of the multiple applications is being run, the first part of the applications is being run, and when both the first part of the applications and the second part of the applications are being run, candidate recommendation information matching the target task obtained by searching the multiple applications is obtained to obtain the set of candidate recommendation information; An application interface preconfigured in the multiple applications is called to obtain candidate recommendation information that matches the target task and is searched in the multiple applications, thereby obtaining the set of candidate recommendation information.

7. The method according to any one of claims 1 to 6, characterized in that The displaying of at least part of the recommended information in the set of candidate recommended information comprises at least one of the following: Displaying an application identifier corresponding to each piece of recommended information in the at least part of the recommended information, wherein the application represented by each application identifier is an application used to search for the corresponding recommended information in the at least part of the recommended information; A recommendation priority identifier corresponding to each piece of recommendation information in the at least part of the recommendation information is displayed, wherein the recommendation priority identifier is used to indicate the recommendation priority of the corresponding recommendation information in the at least part of the recommendation information.

8. The method according to any one of claims 1 to 6, characterized in that The displaying at least part of the recommended information in the set of candidate recommended information comprises: When target recommended information in the at least part of the recommended information is selected, a page for executing the target task in the target application is displayed, wherein the target recommended information is candidate recommended information matching the target task obtained by searching in the target application.

9. An information recommendation processing device, characterized in that: Applied to a mobile terminal, the device comprises: A first acquisition module, used to acquire input task information, wherein the task information is used to determine a target task to be executed; A second acquisition module is used to acquire candidate recommendation information matching the target task obtained by searching in multiple applications to obtain a group of candidate recommendation information, wherein the multiple applications are applications that are allowed to execute the target task; The display module is used to display at least part of the recommended information in the set of candidate recommended information.

10. An electronic device, characterized in that: The method comprises a memory and a processor, wherein the memory stores a computer program, and the processor is configured to run the computer program to execute the method according to any one of claims 1 to 8.

11. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 8 are implemented.

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