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

Abstract

Provided in the present disclosure are an information recommendation processing method and apparatus, and an electronic apparatus and a computer program product. The method comprises: acquiring task information which is input, wherein the task information is used for determining a target task to be executed; acquiring candidate recommendation information which matches the target task and is obtained by searching among a plurality of applications, so as to obtain a group of pieces of candidate recommendation information, wherein the plurality of applications are applications allowed to execute the target task; and displaying at least some of the recommendation information in the group of pieces of candidate recommendation information.

Description

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

[0001] Cross-reference to Related Applications

[0002] The present disclosure is based on Chinese Patent Application No. 2024113026450 entitled "Information recommendation processing method and device, electronic device, and computer program product" filed on September 18, 2024, and claims priority to the patent application, the disclosure of which is incorporated herein in its entirety by reference. TECHNICAL FIELD

[0003] Embodiments of the present disclosure relate to the technical field of wireless communication, in particular, to an information recommendation processing method, device, electronic device, and computer program product. BACKGROUND

[0004] With the continuous development of mobile terminal applications, users need to select suitable application services from a large amount of information, which is a problem that needs to be solved for current smart terminals. Artificial intelligence technology is developing rapidly. How to process information through artificial intelligence technology and apply it to terminal products to reduce user operation burden is a problem that needs to be solved.

[0005] For the problem of operating multiple applications and processing complexity in related technologies, no solution has been proposed. SUMMARY

[0006] Embodiments of the present disclosure 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 complexity in related technologies.

[0007] According to one embodiment of the present disclosure, an information recommendation processing method is provided, applied to a mobile terminal, the method comprising:

[0008] obtaining input task information, wherein the task information is used to determine a target task to be executed;

[0009] obtaining candidate recommendation information matched with the target task searched in multiple applications to obtain a group of candidate recommendation information, wherein the multiple applications are applications that allow the target task to be executed;

[0010] displaying at least part of the recommendation information in the group of candidate recommendation information.

[0011] According to another embodiment of the present disclosure, an information recommendation processing device is also provided, applied to a mobile terminal, the device comprising:

[0012] a first obtaining module configured to obtain input task information, wherein the task information is used to determine a target task to be executed;

[0013] The second obtaining module is configured to obtain candidate recommendation information matched with the target task searched in a plurality of applications, to obtain a group of candidate recommendation information, wherein the plurality of applications are applications allowing the target task to be executed;

[0014] The display module is configured to display at least part of the recommendation information in the group of candidate recommendation information.

[0015] According to still another embodiment of the present disclosure, a computer program product is also provided, which includes computer program instructions, wherein the computer program instructions enable a computer to implement the steps in any of the above method embodiments.

[0016] According to still another embodiment of the present disclosure, a computer readable storage medium is also provided, which stores a computer program, wherein the computer program is configured to execute the steps in any of the above method embodiments when running.

[0017] According to still another embodiment of the present disclosure, an electronic device is also provided, which includes a memory and a processor, the memory stores a computer program, and the processor is configured to run the computer program to execute the steps in any of the above method embodiments. BRIEF DESCRIPTION OF DRAWINGS

[0018] FIG. 1 is a hardware structure block diagram of a mobile terminal of an information recommendation processing method according to an embodiment of the present disclosure;

[0019] FIG. 2 is a flowchart of an information recommendation processing method according to an embodiment of the present disclosure;

[0020] FIG. 3 is a flowchart of an information recommendation processing method according to an optional embodiment of the present disclosure;

[0021] FIG. 4 is a flowchart of a mobile terminal recommendation information according to an embodiment of the present disclosure;

[0022] FIG. 5 is a schematic diagram of recommendation information processing according to the present embodiment;

[0023] FIG. 6 is a block diagram of an information recommendation processing device according to an embodiment of the present disclosure;

[0024] FIG. 7 is a block diagram of an information recommendation processing device according to an optional embodiment of the present disclosure. DETAILED DESCRIPTION

[0025] Embodiments of the present disclosure will be described in detail below with reference to the accompanying drawings and in conjunction with embodiments.

[0026] It should be noted that the terms "first", "second", etc. in the specification and claims of the present disclosure and the above-mentioned drawings are used to distinguish similar objects, and do not necessarily describe a specific order or sequence.

[0027] The method embodiments provided in the embodiments of the present disclosure can be executed in a mobile terminal or similar computing device. Taking the case of running on a mobile terminal, Fig. 1 is a hardware structure block diagram of a mobile terminal of the information recommendation processing method according to the embodiments of the present disclosure. As shown in Fig. 1, the mobile terminal can include one or more (only one is shown in Fig. 1) processors 102 (the processor 102 can include but is not limited to a processing device such as a microprocessor MCU or programmable logic device) and a memory 104 for storing data, wherein the above-mentioned mobile terminal can further include a transmission device 106 for communication function and an input / output device 108. Those skilled in the art can understand that the structure shown in Fig. 1 is only schematic, which does not limit the structure of the above-mentioned mobile terminal. For example, the mobile terminal can further include more or less components than those shown in Fig. 1, or have a different configuration from that shown in Fig. 1.

[0028] The memory 104 can be used to store computer programs, for example, software programs of application software and modules, such as the computer program corresponding to the information recommendation processing method in the embodiments of the present disclosure. The processor 102 executes various functions of the application and single board matching by running the computer program stored in the memory 104, that is, implements the above-mentioned method. The memory 104 can include a high-speed random access memory, and can further include a non-volatile memory, such as one or more magnetic storage devices, flash memories, or other non-volatile solid-state memories. In some examples, the memory 104 can further include a memory remotely arranged with respect to the processor 102, which can be connected to the mobile terminal through 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 a combination thereof.

[0029] The transmission device 106 is used to receive or send data via a network. Specific examples of the above-mentioned network can include a wireless network provided by a communication provider of the mobile terminal. In one example, the transmission device 106 includes a network adapter (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 in a wireless manner.

[0030] In the present embodiment, an information recommendation processing method running on the above-mentioned mobile terminal is provided. Fig. 2 is a flow chart of the information recommendation processing method according to the embodiments of the present disclosure, as shown in Fig. 2, applied to a mobile terminal, the flow includes the following steps:

[0031] S202, obtain input task information, the task information is used for determining a target task to be executed;

[0032] S204, obtain candidate recommendation information matched with the target task searched in a plurality of applications, obtain a set of candidate recommendation information, and the plurality of applications are applications allowing the target task to be executed;

[0033] S206, display at least part of the recommendation information in the set of candidate recommendation information.

[0034] Through the above S202 to S206, the problem that the operation of the plurality of applications is complex in the related art can be solved, the plurality of application matched recommendation information is recommended based on the input task information, and the operation complexity of the plurality of applications is reduced.

[0035] The execution subject of the above S202 to S206 can be a mobile terminal or the like, but is not limited thereto. The above obtaining task information, searching for matched applications and obtaining candidate recommendation information, and displaying recommendation results are executed in sequence, that is, the target task to be executed can be determined after the task information input by the user is obtained, then the candidate recommendation information matched with the target task can be obtained, and finally at least part of the recommendation information is displayed. The content displayed can be determined according to the selection of the user, or can be determined according to a certain preset rule, for example, the candidate recommendation information is sorted, and a certain number of recommendation information with high ranking is displayed. The recommendation information can be a list or different tabs.

[0036] Before obtaining the candidate recommendation information, the specific target task needs to be determined according to the task information, and the application capable of executing the task is screened from the application set. This step is the key to ensure the accuracy of the recommendation information. FIG. 3 is a flowchart of an information recommendation processing method according to an optional embodiment of the present disclosure, as shown in FIG. 3, the method further comprises:

[0037] S302, determining the target task according to the task information;

[0038] S304, determining a plurality of applications allowing the target task to be executed in the application set.

[0039] Through the above S302 to S304, the search of irrelevant applications can be avoided, the search efficiency and the accuracy of the recommendation are improved, for example, when the user searches for “nearby food”, only the search is performed from the catering, map and review applications, and the news or game applications are not involved.

[0040] In an embodiment, S302 can include: performing semantic recognition on the task information to obtain a semantic recognition result, i.e., directly determining the target task based on the task information; in a case where the semantic recognition result represents the target semantic, determining the target semantic as the target task, or in a case where the semantic recognition result does not accurately represent the target semantic, determining at least one of the location information of the target terminal and the user label information and the target semantic as the target task. The target task is determined through semantic recognition, and if the recognition result is not clear, the user location and personalized label information can be combined to further clarify. This implementation realizes the attention to the personalized needs of the user and the flexibility in processing uncertain tasks. This method can better understand the real needs of the user, and even if the user input information is incomplete or ambiguous, it can provide more accurate recommendations by combining location information and user preferences, for example, the user inputs “I want to eat”, and the system can recommend nearby restaurants through the current location and historical dining preferences of the user.

[0041] In an embodiment, the application can also be determined by the task type or task description information, which depends on the pre-established correspondence between the applications in the application set and the task type. This ensures the pertinence of the recommended information and the selectivity of the application, avoiding the interference of irrelevant applications. S304 can include one of the following: obtaining the task type of the target task, selecting an application in the application set that allows the execution of the task of the task type, and determining the selected application as the plurality of 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 the task of the corresponding task type, for example, the task information is a backpack, the target task is to buy a backpack, the task type is shopping, and the applications that allow the execution of shopping include application 1 and application 2; obtaining the 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 plurality of 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 that matches travel includes a certain map and a certain travel APP. This method can ensure the rationality of the search range, avoid blind search, and improve the pertinence of the recommended information, for example, when searching for “flights from location 1 to location 2”, only search from airlines and travel booking applications, without involving other types of applications.

[0042] In an embodiment, the way of obtaining the candidate recommendation information includes displaying application windows and searching for matching information. This process involves multi-application parallel processing, improving the efficiency of information acquisition. Correspondingly, S204 can include: displaying an application window of each of the plurality of applications; and displaying the candidate recommendation information matching the target task obtained by searching in each of the plurality of applications. This method can provide an intuitive display of multi-application search results, allowing users to see the recommendation information from different applications at the same time, facilitating quick comparison and selection. For example, when searching for "weekend activities", users can see recommendations from multiple applications such as social media, entertainment, and travel.

[0043] In another embodiment, the specific scenarios and methods of obtaining candidate recommendation information are further refined, including starting the application to obtain information in the application non-running state, or calling the pre-configured application interface to obtain information. S204 can include one of the following: in the case where none of the plurality of applications is running, running the plurality of applications and obtaining the candidate recommendation information matching the target task obtained by searching in each of the plurality of applications to obtain a set of candidate recommendation information; or in the case where a first part of the plurality of applications is not running and a second part of the plurality of applications is running, running the first part of the plurality of applications and obtaining the candidate recommendation information matching the target task obtained by searching in the plurality of applications in the case where the first part of the plurality of applications and the second part of the plurality of applications are running to obtain a set of candidate recommendation information; and calling a pre-configured application interface in the plurality of applications to obtain the candidate recommendation information matching the target task obtained by searching in the plurality of applications to obtain a set of candidate recommendation information. By automatically running the application or calling the application interface to obtain the recommendation information, the user's operation steps can be reduced, providing a more convenient and fast search experience. For example, after the user inputs "weather forecast", the system automatically obtains information from the weather application without the user manually opening the application.

[0044] In an embodiment, when displaying the recommendation information, an application identifier or a recommendation priority identifier can be attached to help users quickly identify the source or priority of the recommendation information. This enhances the readability of the recommendation information and the convenience of user selection. S206 can include at least one of the following: displaying an application identifier corresponding to each of the at least part of the recommendation information, wherein the application represented by each application identifier is the application used to search for the corresponding recommendation information in the at least part of the recommendation information; and displaying a recommendation priority identifier corresponding to each of the at least part of the recommendation information, wherein the recommendation priority identifier is used to represent the recommendation priority of the corresponding recommendation information in the at least part of the recommendation information. This method can help users quickly identify the source and importance of the recommendation information, such as displaying application identifiers such as "certain group" and "certain review", as well as recommendation priorities determined based on user historical behavior and application credibility, allowing users to trust the recommendation results more.

[0045] In another embodiment, after the user selects the recommended information, an application page related to the information can be displayed, and the task execution can be directly performed. The user operation process can be simplified, and the efficiency of task execution can be improved. The above S206 can further include: in a case where target recommended information in at least part of the recommended information is selected, displaying a page for executing a target task in a target application, wherein the target recommended information is candidate recommended information matched with the target task searched in the target application. This method can realize seamless jumping, and the user can directly enter a specific page of the application from the recommended information, for example, clicking a "book" button in the recommended information to directly jump to a booking page, which greatly improves the convenience of operation and user experience.

[0046] Embodiments of the present disclosure can analyze user intent by AI technology through user operation of a mobile phone, input of task information, starting of multiple similar applications in multiple windows, or search of related information to obtain candidate recommended information required by the user. User individual characteristics and information such as a current environment position of the user are analyzed to give a ranking most suitable for the user for selection by the user.

[0047] For example, a user gives an instruction of "return to the hotel" at a certain place, and a mobile terminal using the above scheme gives multiple schemes such as bus, subway, and car, corresponding time, price, and navigation route map for selection by the user. After the user selects, if necessary, the next service link is entered, for example, the car is selected, and an artificial intelligence assistant of the present patent executes a car order task. Or the result is not satisfied, the keyword is revised again, and the output result is analyzed again.

[0048] FIG. 4 is a flowchart of recommended information of a mobile terminal according to an embodiment of the present disclosure, as shown in FIG. 4, including:

[0049] S401, receiving task information input by a user;

[0050] S402, determining a target task corresponding to the task information, and determining multiple applications allowed to execute the target task;

[0051] S403, searching for the target task in the multiple applications to obtain matched candidate recommended information, and obtaining a group of candidate recommended information;

[0052] In the above S403, the specific process of obtaining the matched candidate recommended information is of the same type as the process of obtaining the candidate recommended information matched with the target task in each of the multiple applications, which will not be described herein.

[0053] S404, displaying the group of candidate recommended information for selection by a user;

[0054] S405, receiving selection information of the user, and determining and executing a selection result of the user;

[0055] S406, receiving the user inputted correction information, recommending a group 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.

[0056] On the display interface of the mobile terminal, the mobile terminal device can obtain the user inputted task information in the form of voice, text, or picture, etc. The user's personalized tags, environment, location, etc. define the user's personal preference information and the user's current location information, indoor or outdoor, etc. The result ranking is adjusted when used for artificial intelligence operation.

[0057] The user inputted task information is analyzed, the keywords are extracted, the task type is analyzed by the artificial intelligence model, and multiple similar applications or API interfaces are started to obtain the application information. A group of candidate recommendation information (i.e. multiple candidate recommendation information) that meets the user's demand is outputted, and the group of candidate recommendation information is ranked and recommended to the user.

[0058] After obtaining the multiple candidate recommendation information, according to the user's habits, a certain priority recommendation rule is selected (for example, when shopping, the price is preferred, or the good comment is preferred, and the promotion coupon can be used first; when driving, the shortest distance or the shortest time; when ordering food, a certain cuisine is preferred or the shortest time is preferred), and the ranking result is listed. The ranking result is analyzed, and the results of multiple applications are ranked according to the recommendation rule. The user checks the multiple candidate recommendation information after ranking, and selects the recommendation information that is most suitable for the current self. The artificial intelligence assistant executes the user selected recommendation information. If the multiple recommended information does not meet the user's current expectation, the user can input the correction information, and the artificial intelligence analysis unit reprocesses the task information in combination with the user's new inputted information.

[0059] When performing the task, multiple recommendation information is outputted and recommended to the user. On the terminal device, there is at least more than one recommendation result (i.e. candidate recommendation information) for a task. 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. Further, the inputted information can be corrected, and the current information can be corrected when it does not meet the expectation. For example, the user inputted task information is "fan", and the recommendation result does not find the required one. The user inputs the "blue" feature in the "correct input information" position, and obtains the required fan.

[0060] Fig. 5 is a schematic diagram of the recommended information processing of the present embodiment. As shown in Fig. 5, a user is traveling in a city and inputs "dining" into the mobile terminal. The mobile terminal analyzes the task information, extracts the key words, and determines that the user currently needs to have a meal. The applications related to dining, such as application 1, application 2, and application 3, are started, and places where meals can be had are searched for according to the current location of the user. The intelligent device selects a plurality of restaurants (restaurant A, restaurant B, restaurant C, and restaurant D) that are close, have appropriate prices, and have good user evaluations (restaurant A and restaurant B are both recommended by application 1, and the name of the application can be displayed) for the user to select. After the user selects one, the intelligent device performs the next operation, reserves the location of the restaurant, navigates to the restaurant, and recommends ordering.

[0061] Those skilled in the art can clearly understand from the description of the above embodiments that the method according to the above embodiments can be realized by means of software and a general hardware platform as required, and of course can also be realized by hardware, but in many cases the former is a better embodiment. Based on such understanding, the technical solutions of the present disclosure can be embodied in the form of a software product, which is stored in a storage medium (such as a ROM / RAM, a magnetic disk, or an optical disk) and includes a plurality of instructions for causing a terminal device (which can be a mobile phone, a computer, a server, or a network device) to perform the methods described in the various embodiments of the present disclosure.

[0062] In the present embodiment, an information recommendation processing device is also provided, which is used to implement the above embodiments and preferred embodiments, and will not be described again. As used below, the term "module" can be a combination of software and / or hardware that implements a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, hardware or a combination of software and hardware is also possible and is contemplated.

[0063] The present disclosure also provides an information recommendation processing device, and Fig. 6 is a block diagram of an information recommendation processing device according to an embodiment of the present disclosure. As shown in Fig. 6, the device is applied to a mobile terminal and includes:

[0064] A first obtaining module 62 is configured to obtain input task information, wherein the task information is used to determine a target task to be performed;

[0065] A second obtaining module 64 is configured to obtain candidate recommended information matched with the target task searched in a plurality of applications, to obtain a group of candidate recommended information, wherein the plurality of applications are applications that allow the target task to be performed;

[0066] A display module 66 is configured to display at least part of the recommended information in the group of candidate recommended information.

[0067] FIG. 7 is a block diagram of an information recommendation processing apparatus according to an optional embodiment of the present disclosure, as shown in FIG. 7, the apparatus further comprises:

[0068] A determination module 72, configured to determine the target task according to the task information.

[0069] An execution module 74, configured to determine the plurality of applications allowing execution of the target task in the application set.

[0070] In an embodiment, the determination module 72 is further configured to perform semantic recognition on the task information to obtain a semantic recognition result; in a case where the semantic recognition result represents a target semantic, determining the target semantic as the target task, or in a case where the semantic recognition result does not accurately represent a target semantic, determining at least one of position information and user tag information of the target terminal and the target semantic as the target task.

[0071] In an embodiment, the execution module 74 is further configured to determine the plurality of applications allowing execution of the target task in the application set, including one of the following: obtaining a task type of the target task, selecting an application allowing execution of a task of the task type in the application set, and determining the selected application as the plurality of 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 configured to allow execution of a task of a corresponding task type; obtaining 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 the plurality of applications.

[0072] In an embodiment, the second obtaining module 64 is further configured to display an application window of each application in the plurality of applications; and display the candidate recommendation information matched with the target task searched in the each application.

[0073] In an embodiment, the second obtaining module 64 is further configured to perform one of the following: in a case where none of the plurality of applications is running, running the plurality of applications and obtaining the candidate recommendation information matching the target task searched in each of the plurality of applications to obtain the set of candidate recommendation information; or in a case where a first part of the plurality of applications is not running and a second part of the plurality of applications is running, running the first part of the plurality of applications, and in a case where the first part of the plurality of applications and the second part of the plurality of applications are running, obtaining the candidate recommendation information matching the target task searched in the plurality of applications to obtain the set of candidate recommendation information; and invoking an application interface of the plurality of applications preconfigured to obtain the candidate recommendation information matching the target task searched in the plurality of applications to obtain the set of candidate recommendation information.

[0074] In an embodiment, the display module 66 is further configured to perform at least one of the following: displaying an application identifier corresponding to each of the at least part of the recommendation information, wherein each of the application identifiers represents an application used to search for the corresponding recommendation information in the at least part of the recommendation information; and displaying a recommendation priority identifier corresponding to each of the at least part of the recommendation information, wherein the recommendation priority identifier is used to represent a recommendation priority of the corresponding recommendation information in the at least part of the recommendation information.

[0075] In an embodiment, the display module 66 is further configured to display a page for executing the target task in a target application in a case where a 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 searched in the target application.

[0076] The embodiments of the present disclosure further provide 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.

[0077] The embodiments of the present disclosure further provide a computer readable storage medium, which stores a computer program, wherein the computer program is configured to execute the steps in any of the above method embodiments when running.

[0078] In an example embodiment, the above computer readable storage medium can include, but is not limited to, a U disk, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk or an optical disk, and various media that can store computer programs.

[0079] Embodiments of the present disclosure also provide an electronic device, comprising a memory and a processor, the memory storing a computer program, and the processor being configured to execute the computer program to perform the steps of any of the above method embodiments.

[0080] In an example embodiment, the above electronic device can further comprise a transmission device connected to the processor, and an input / output device connected to the processor.

[0081] The specific examples in the embodiments can refer to the examples described in the above embodiments and example implementations, which will not be repeated here.

[0082] Obviously, those skilled in the art should understand that the modules or steps of the present disclosure described above can be realized by general computing devices, which can be concentrated on a single computing device, or distributed on a network composed of multiple computing devices, which can be realized by program codes executable by computing devices, so that they can be stored in storage devices and executed by computing devices, and in some cases, the steps shown or described can be executed in different order, or they can be made into individual integrated circuit modules, or multiple modules or steps can be made into a single integrated circuit module. Thus, the present disclosure is not limited to any particular combination of hardware and software.

[0083] The above only describes the preferred embodiments of the present disclosure and is not intended to limit the present disclosure. Those skilled in the art can make various modifications and changes to the present disclosure. Any modification, equivalent replacement, improvement, etc. within the principles of the present disclosure shall be included in the protection scope of the present disclosure.

Claims

1. An information recommendation processing method applied to a mobile terminal, the method comprising: obtaining input task information, wherein the task information is used to determine a target task to be executed; obtaining candidate recommendation information matching the target task searched in a plurality of applications, to obtain a set of candidate recommendation information, wherein the plurality of applications are applications that allow the target task to be executed; displaying at least part of the candidate recommendation information in the set of candidate recommendation information.

2. The method of claim 1, wherein, Before the obtaining candidate recommendation information matching the target task searched in a plurality of applications, to obtain a set of candidate recommendation information, the method further comprises: determining the target task according to the task information; determining the plurality of applications that allow the target task to be executed in an application set.

3. The method of claim 2, wherein, The determining the target task according to the task information comprises: performing semantic recognition on the task information to obtain a semantic recognition result; in a case where the semantic recognition result represents a target semantic, determining the target semantic as the target task, or in a case where the semantic recognition result does not accurately represent a target semantic, determining at least one of location information of the target terminal and user label information as the target task.

4. The method of claim 2, wherein, The determining the plurality of applications that allow the target task to be executed in an application set comprises one of: obtaining a task type of the target task, selecting an application that allows a task of the task type to be executed in the application set, and determining the selected application as the plurality of 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 allow a task of a corresponding task type to be executed; obtaining 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 the plurality of applications.

5. The method of claim 1, wherein, The obtaining candidate recommendation information matching the target task searched in each application in the plurality of applications, to obtain a set of candidate recommendation information, comprises: displaying an application window of each application in the plurality of applications; displaying candidate recommendation information matching the target task searched in the each application.

6. The method of claim 1, wherein, The obtaining candidate recommendation information matching the target task searched in each application in the plurality of applications, to obtain a set of candidate recommendation information, comprises one of: in a case where none of the plurality of applications is running, running the plurality of applications, and obtaining candidate recommendation information matching the target task searched in each application in the plurality of applications, to obtain the set of candidate recommendation information; or in a case where a first part of the plurality of applications is not running and a second part of the plurality of applications is running, running the first part of the plurality of applications, and in a case where the first part of the plurality of applications and the second part of the plurality of applications are running, obtaining candidate recommendation information matching the target task searched in the plurality of applications, to obtain the set of candidate recommendation information; The preconfigured application interface in the plurality of applications is invoked to obtain candidate recommendation information matched with the target task searched in the plurality of applications, to obtain the set of candidate recommendation information.

7. The method of any one of claims 1 to 6, wherein, The displaying of at least part of the recommendation information in the set of candidate recommendation information comprises at least one of the following: displaying an application identifier corresponding to each of the at least part of the recommendation information, wherein the application represented by each of the application identifiers is an application used to search for the corresponding recommendation information in the at least part of the recommendation information; displaying a recommendation priority identifier corresponding to each of the at least part of the recommendation information, wherein the recommendation priority identifier is used to represent the recommendation priority of the corresponding recommendation information in the at least part of the recommendation information.

8. The method of any one of claims 1 to 6, wherein, The displaying of at least part of the recommendation information in the set of candidate recommendation information comprises: in a case where a target recommendation information in the at least part of the recommendation information is selected, displaying a page for executing the target task in a target application, wherein the target recommendation information is candidate recommendation information matched with the target task searched in the target application. 9.An information recommendation processing apparatus applied to a mobile terminal, the apparatus comprising: a first obtaining module configured to obtain input task information, wherein the task information is used to determine a target task to be executed; a second obtaining module configured to obtain candidate recommendation information matched with the target task searched in a plurality of applications, to obtain a set of candidate recommendation information, wherein the plurality of applications are applications allowing the target task to be executed; a display module configured to display at least part of the recommendation information in the set of candidate recommendation information. 10.An electronic apparatus comprising a memory and a processor, wherein the memory stores a computer program, and the processor is configured to execute the computer program to perform the method in any one of claims 1 to 8. 11.A computer program product comprising a computer program, wherein the computer program is executed by a processor to implement the steps of the method in any one of claims 1 to 8.

Images