Vehicle-mounted application recommendation method and device combined with virtual assistant, equipment, medium and product

Abstract

The invention discloses a vehicle-mounted application recommendation method and device combined with a virtual assistant, equipment, a medium and a product. Acquiring scene information of the current scene, wherein the scene information comprises user state information in the vehicle and environment information outside the vehicle; according to the scene information, based on a preset recommendation strategy, generating a recommendation list of vehicle-mounted applications for the current scene; according to the use condition of the vehicle-mounted application in the recommendation list by the user in a set time period, determining the score of the virtual assistant; and updating the virtual assistant and a preset recommendation strategy according to the integral. According to the technical scheme, the utilization rate of the vehicle-mounted application and the interactivity of the vehicle-mounted entertainment system are effectively improved.

Description

Technical Field

[0001] Embodiments of the present invention relate to the field of vehicle technology, and in particular, to a method, device, equipment, medium and product for recommending in-vehicle applications in combination with a virtual assistant. Background Art

[0002] With the rapid development of the automotive industry and intelligent technology, in-car entertainment systems have become the key to improving the driving experience. Modern in-car entertainment systems integrate navigation, music, video, voice assistant and other functions, and use advanced technologies such as GPS, AI and 5G to provide convenient services for drivers and passengers, making the in-car space a new place for entertainment and leisure.

[0003] However, despite the significant technological progress of in-vehicle entertainment systems, existing in-vehicle entertainment systems on the market still face the problems of insufficient interactive experience and low utilization rate of in-vehicle applications in the in-vehicle entertainment systems. Summary of the invention

[0004] The present invention provides a method, device, equipment, medium and product for recommending in-vehicle applications in combination with a virtual assistant, so as to solve the problems of insufficient interactive experience and low utilization rate of in-vehicle applications in existing in-vehicle entertainment systems.

[0005] According to one aspect of the present invention, a method for recommending in-vehicle applications in combination with a virtual assistant is provided, comprising:

[0006] Acquire scene information of the current scene, wherein the scene information includes user status information inside the vehicle and environment information outside the vehicle;

[0007] According to the scenario information, based on a preset recommendation strategy, a recommendation list of in-vehicle applications for the current scenario is generated;

[0008] Determining the points of the virtual assistant according to the user's usage of the in-vehicle applications in the recommendation list within a set time period;

[0009] The virtual assistant and the preset recommendation strategy are updated according to the points.

[0010] According to another aspect of the present invention, there is provided a vehicle-mounted application recommendation device combined with a virtual assistant, comprising:

[0011] An information acquisition module is used to acquire scene information of the current scene, wherein the scene information includes user status information inside the vehicle and environment information outside the vehicle;

[0012] A list generation module, used to generate a recommendation list of vehicle-mounted applications for the current scenario based on the scenario information and a preset recommendation strategy;

[0013] A points determination module, used to determine the points of the virtual assistant according to the user's usage of the in-vehicle applications in the recommendation list within a set time period;

[0014] A strategy updating module is used to update the virtual assistant and the preset recommendation strategy according to the points.

[0015] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0016] at least one processor; and

[0017] a memory communicatively connected to the at least one processor; wherein,

[0018] The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the in-vehicle application recommendation method combined with a virtual assistant as described in any embodiment of the present invention.

[0019] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the in-vehicle application recommendation method combined with a virtual assistant as described in any embodiment of the present invention when executed.

[0020] According to another aspect of the present invention, a computer program product is provided, which includes a computer program. When the computer program is executed by a processor, it implements the in-vehicle application recommendation method combined with a virtual assistant as described in any embodiment of the present invention.

[0021] The technical solution provided by the embodiment of the present invention obtains scene information of the current scene, wherein the scene information includes user status information in the car and environmental information outside the car; generates a recommendation list of in-vehicle applications for the current scene based on the scene information and a preset recommendation strategy; determines the points of the virtual assistant based on the user's use of the in-vehicle applications in the recommendation list within a set time period; and updates the virtual assistant and the preset recommendation strategy based on the points. A recommendation list of in-vehicle applications for the current scene is generated through the scene information of the current scene, so that the in-vehicle applications recommended in the recommendation list are more in line with the actual needs of the user, thereby effectively improving the usage rate of the in-vehicle applications. At the same time, points are awarded after the user uses the recommended in-vehicle applications, and the virtual assistant and recommendation strategy are continuously updated through these points, which not only encourages users to use the recommended in-vehicle applications more frequently, but also significantly improves the interactivity of the in-vehicle entertainment system.

[0022] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0024] Figure 1 is a flow chart of a method for recommending in-vehicle applications in combination with a virtual assistant provided in Embodiment 1 of the present invention;

[0025] Figure 2 is a flow chart of a method for recommending in-vehicle applications in combination with a virtual assistant provided in Embodiment 2 of the present invention;

[0026] Figure 3 is a structural diagram of a vehicle-mounted application recommendation device combined with a virtual assistant provided in Embodiment 3 of the present invention;

[0027] Figure 4 It is a structural schematic diagram of an electronic device provided in Embodiment 4 of the present invention. DETAILED DESCRIPTION

[0028] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0029] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0030] Embodiment 1

[0031] Figure 1 This is a flow chart of a method for recommending in-vehicle applications in combination with a virtual assistant provided in the first embodiment of the present invention. This embodiment can be applied to the case of recommending in-vehicle applications in combination with a virtual assistant. The method can be executed by an in-vehicle application recommendation device in combination with a virtual assistant. The in-vehicle application recommendation device in combination with a virtual assistant can be implemented in the form of hardware and / or software. The in-vehicle application recommendation device in combination with a virtual assistant can be configured in an electronic device, which can be a vehicle. Figure 1 As shown, the method includes:

[0032] S110: Acquire scene information of the current scene, where the scene information includes user status information inside the vehicle and environment information outside the vehicle.

[0033] In this embodiment, the scene information of the current scene can be understood as the scene information at the current moment. The scene information includes the user status information inside the vehicle and the environmental information outside the vehicle. The user status information includes information such as the user's facial features, emotions, and heart rate. The environmental information includes information such as road conditions, vehicle distance, weather, and traffic signals.

[0034] Specifically, after the in-vehicle entertainment system is started, the environment information outside the vehicle at the current moment collected by the environment collection device outside the vehicle is obtained. At the same time, the user status information obtained by the user status detection device inside the vehicle after performing facial recognition, emotion analysis and physiological data detection on the user is obtained, wherein the physiological data may include the user's heart rate and skin temperature. It is worth noting that this embodiment does not limit the specific types of environment collection devices and user status detection devices. For example, the environment collection device may include sensors, cameras or radars. The user status detection device may be different types of sensors.

[0035] S120: Generate a recommendation list of in-vehicle applications for the current scenario according to the scenario information and based on a preset recommendation strategy.

[0036] In this embodiment, the preset recommendation strategy can be understood as a pre-set strategy for recommending in-vehicle applications. For example, the preset recommendation strategy can be a deep learning model, an ant colony optimization algorithm, or a machine learning algorithm (such as collaborative filtering, decision tree, and support vector machine, etc.), or a content-based recommendation algorithm. The recommendation list includes multiple in-vehicle applications. For example, the recommendation list can include, but is not limited to, in-vehicle applications such as music, navigation, and weather.

[0037] Specifically, the scene information is analyzed and data fusion is processed. Based on the processed data, a preset recommendation strategy is used to generate a recommendation list of in-vehicle applications for the current scene. The generated recommendation list is displayed on the in-vehicle display device for users to view and select.

[0038] S130. Determine the points of the virtual assistant according to the user's usage of the in-vehicle applications in the recommendation list within a set time period.

[0039] In this embodiment, the set time period can be understood as a pre-set time period, for example, the preset time period can be 20 minutes, one day or one week. The virtual assistant can be understood as a virtual assistant image set by the user according to personal preferences, and the virtual assistant can provide a variety of interaction methods, such as voice and gestures. The usage of the in-vehicle application can be understood as the interaction between the user and the in-vehicle application in the recommendation list. The points of the virtual assistant can be understood as a total reward or total feedback obtained by the user after using the in-vehicle application in the recommendation list within a predetermined period of time. This kind of points is an affirmation of the user's activity, participation and use of the in-vehicle application, which reflects the comprehensive results of the user's interaction with the in-vehicle application and the virtual assistant during this period. Users will increase their frequent use of the system because they get points when using the application, which effectively improves the overall user participation.

[0040] Specifically, the user's usage of each in-vehicle application in the recommendation list within a set time period is detected in real time, where the usage may include but is not limited to the frequency, duration, and user feedback of the in-vehicle application; the points of each in-vehicle application are calculated based on the usage of each in-vehicle application, and then the points of each in-vehicle application are combined to determine the points of the virtual assistant. These points can not only be used as a measure of user activity, but can also be used to unlock new props, improve the image of the virtual assistant, and obtain the right to use specific functions, thereby further improving user satisfaction and loyalty to the in-vehicle application and the virtual assistant.

[0041] The points of the virtual assistant are determined by comprehensively calculating the points of each in-vehicle application. The points of the virtual assistant can be determined by adding up the points of each in-vehicle application or by taking a weighted sum of the points of each in-vehicle application.

[0042] S140: Update the virtual assistant and the preset recommendation strategy according to the points.

[0043] Specifically, for the update of the virtual assistant, in response to the user's point redemption operation, the props and / or functions that can be redeemed are presented to the user, and in response to the props and / or functions selected by the user, the corresponding props and / or functions are assigned to the virtual assistant. For the update of the preset recommendation strategy, when the points meet the preset conditions, it indicates that the preset recommendation strategy does not meet the user's current needs, and the preset recommendation strategy needs to be updated. Among them, the preset condition can be that when the points do not meet the preset threshold or are in the preset interval, the preset recommendation strategy is updated. The preset threshold is a preset value, and the preset interval is a preset interval range based on the actual situation.

[0044] Optionally, if the virtual assistant does not meet the preset conditions, indicating that the user is relatively satisfied with the preset recommendation strategy, the preset recommendation strategy may not be updated.

[0045] The technical solution provided in the implementation of the present invention is to obtain scene information of the current scene, wherein the scene information includes user status information in the car and environmental information outside the car; based on the scene information and based on a preset recommendation strategy, a recommendation list of in-car applications for the current scene is generated; based on the user's use of the in-car applications in the recommendation list within a set period of time, the points of the virtual assistant are determined; and based on the points, the virtual assistant and the preset recommendation strategy are updated. A recommendation list of in-car applications for the current scene is generated through the scene information of the current scene, so that the in-car applications recommended in the recommendation list are more in line with the actual needs of the user, thereby effectively improving the usage rate of the in-car applications. At the same time, points are awarded after the user uses the recommended in-car applications, and the virtual assistant and recommendation strategy are continuously updated through these points, which not only encourages users to use the recommended in-car applications more frequently, but also significantly improves the interactivity of the in-car entertainment system.

[0046] In some embodiments, the scenario information also includes at least one of the following: historical usage records of in-vehicle applications; user voice data; and user preference information.

[0047] In this embodiment, the historical usage records of the in-vehicle application can be understood as the historical data of the user using the in-vehicle application while the vehicle is driving. The user voice data can be understood as the voice commands and interaction records generated by the user when using the in-vehicle system. The user preference information can be understood as the personal preferences set by the user in the in-vehicle system, such as seat position, air conditioning temperature, favorite music type, etc. Through multi-source scene information, a solid data foundation is provided for realizing personalized recommendation lists, further improving the accuracy of recommendations.

[0048] In some embodiments, the in-vehicle application recommendation method in combination with a virtual assistant further includes: if the user starts the in-vehicle system for the first time, creating the virtual assistant according to the user operation.

[0049] Specifically, the in-vehicle system can be understood as an in-vehicle entertainment system. When it is determined that the user is starting the in-vehicle system for the first time, the system will guide the user through a series of setup steps to create their virtual assistant. For example, in this process, the user can customize the name, gender, age, language preference, and appearance of the virtual assistant according to their preferences. In addition, the user can also select key functions of the virtual assistant, such as navigation, music playback, and communication, and set privacy options to manage personal data. After completing these personalized settings, the virtual assistant will be activated and the user can interact with it through voice commands or touch screen. Through the above solution, a personalized user experience is provided, allowing users to enjoy a more interesting driving experience, effectively enhancing the user's interaction and satisfaction with the in-vehicle system.

[0050] In some embodiments, after generating a recommendation list of in-vehicle applications for the current scenario, it also includes: voice broadcasting the recommendation list through the virtual assistant.

[0051] Specifically, after generating the recommendation list, the virtual assistant in the vehicle system can use the voice broadcast function to broadcast the contents of the recommendation list to guide the user to make selections and operations, so that the user can obtain recommended information of vehicle applications without distracting driving attention, thereby improving driving safety and convenience.

[0052] In some embodiments, the points of the virtual assistant are determined based on the user's usage of the in-vehicle applications in the recommendation list within a set time period, including: determining the points of the virtual assistant based on the frequency and / or duration of use of the in-vehicle applications in the recommendation list by the user within a set time period.

[0053] Specifically, the user's usage frequency and / or usage duration of each in-vehicle application in the recommendation list within a set period of time is detected, and the points of each in-vehicle application are calculated according to the usage frequency and / or usage duration of each in-vehicle application using a preset scoring rule, and then the points of each in-vehicle application are combined to determine the points of the virtual assistant. The preset scoring rule may be a pre-set rule for calculating the points of each in-vehicle application.

[0054] For example, the preset points rule may include setting higher points for in-vehicle applications that are used less than a preset threshold when the usage time is the same, wherein the specific number of points set may be determined according to actual conditions. For example, for music applications and video applications, when the usage time is the same, if the video is used less frequently, higher points will be allocated to the video. This encourages users to explore infrequently used applications and enhances interaction with the in-vehicle system.

[0055] Optionally, if the detection finds that the usage frequencies of the first preset number of in-vehicle applications recommended in the recommendation list are significantly higher than other in-vehicle applications in the recommendation list, this indicates that the recommendation list meets the actual needs of the user. In this case, additional points can be added on top of the original points to allow the virtual assistant to obtain more points.

[0056] Optionally, additional points may be added based on the interaction between the user and the virtual assistant (such as question and answer or small talk, etc.) so that the virtual assistant can earn more points.

[0057] Optionally, a series of achievement goals can be pre-set, such as "Daily Navigation Expert", "Little Music Expert", etc. After the user achieves specific usage goals, he can get extra points.

[0058] Optionally, in order to enhance the user's social interaction, the user can also share the virtual assistant on social media. After detecting the user's operation of sharing the virtual assistant, multiple shareable social media are provided to the user so that the user can share the virtual assistant to the corresponding social media, thereby enhancing the user's social interaction.

[0059] Embodiment 2

[0060] Figure 2 This is a flowchart of a method for recommending in-vehicle applications in combination with a virtual assistant provided in the second embodiment of the present invention. This embodiment is optimized and expanded on the basis of the above-mentioned optional embodiments. Optionally, based on the points, the virtual assistant and the preset recommendation strategy are updated, including: updating the preset recommendation strategy based on the in-vehicle application from which the points are derived; presenting to the user the props and / or functions of the virtual assistant that match the in-vehicle application; and granting the virtual assistant corresponding props and / or functions when a user redeems any of the props and / or any of the functions.

[0061] like Figure 2 As shown, the method includes:

[0062] S210: Acquire scene information of the current scene, where the scene information includes user status information inside the vehicle and environment information outside the vehicle.

[0063] S220: Generate a recommendation list of in-vehicle applications for the current scenario based on the scenario information and a preset recommendation strategy.

[0064] S230: Determine the points of the virtual assistant according to the user's usage of the in-vehicle applications in the recommendation list within a set time period.

[0065] S240: Update the preset recommendation strategy according to the in-vehicle application from which the points are derived.

[0066] Specifically, since the contribution of each in-vehicle application to the points is different, it is necessary to determine the in-vehicle applications that are the source of the points, that is, to identify which in-vehicle applications contribute to the points of the virtual assistant. Further, determine whether the points of the virtual assistant are greater than the preset threshold. If the points of the virtual assistant are greater than the preset threshold, it means that the recommendation list generated according to the current preset recommendation strategy is suitable for the user. At this time, the preset recommendation strategy can be left unchanged; on the contrary, if the points of the virtual assistant do not reach the preset threshold, it is necessary to further analyze the correlation between the usage scenarios of these in-vehicle applications that contribute to the points and the personalized needs of the user, and then update the preset recommendation strategy based on the correlation. For example, if the preset recommendation strategy is a deep learning model, the correlation obtained by analysis is used as new training data to retrain and update the model.

[0067] S250: Presenting props and / or functions of the virtual assistant that match the in-vehicle application to the user.

[0068] Specifically, after determining the in-vehicle applications that are the source of points, these in-vehicle applications are determined as target in-vehicle applications, and then based on the pre-set correspondence between the in-vehicle applications and the props, the props and / or functions of the virtual assistant corresponding to the target in-vehicle applications are presented to the user, so that the user can perform points redemption operations.

[0069] For example, Table 1 provides a correspondence between in-vehicle applications and props, as shown in Table 1, including multiple in-vehicle applications and props corresponding to each in-vehicle application. If the determined target in-vehicle applications are voice, music, and karaoke, the props presented to the user are voice props (such as baby voice, celebrity voice, cartoon character voice, etc.), ear props (such as headphones, ear shape, earrings, etc.) and mouth props (such as microphone, lip shape, lip color, etc.), so as to encourage users to explore and use more functions by binding specific props with in-vehicle applications.

[0070] Table 1 Correspondence between vehicle applications and props

[0071]

[0072]

[0073] S260: When a redemption operation of any of the props and / or any of the functions by the user is detected, the virtual assistant is given corresponding props and / or functions.

[0074] Specifically, the user redeems points based on the props and / or functions of the virtual assistant corresponding to the target in-vehicle application presented. After detecting the user's redemption operation, the user's virtual assistant is given corresponding props and functions, thereby enhancing the interactivity and practicality of the virtual assistant and improving the user experience.

[0075] The technical solution provided in the second embodiment of the present invention generates a personalized list of in-vehicle application recommendations by acquiring the scene information of the current scene, and after the user uses these in-vehicle applications within a set period of time, the virtual assistant is awarded points based on the usage, which not only encourages the user to explore more functions, but also can be used to update the recommendation strategy to make it more in line with user needs. In addition, by showing the user the virtual assistant props and functions that match the in-vehicle applications, the interactive experience is further enhanced. When the user performs the redemption operation, the virtual assistant will assign props and functions accordingly, which effectively promotes the in-depth interaction between the user and the in-vehicle system and improves the user satisfaction and experience.

[0076] Embodiment 3

[0077] Figure 3 is a schematic diagram of the structure of a vehicle-mounted application recommendation device combined with a virtual assistant provided in the third embodiment of the present invention. Figure 3 As shown, the device comprises:

[0078] An information acquisition module 31 is used to acquire scene information of a current scene, wherein the scene information includes user status information inside the vehicle and environment information outside the vehicle;

[0079] A list generating module 32, configured to generate a recommendation list of vehicle-mounted applications for the current scenario according to the scenario information and based on a preset recommendation strategy;

[0080] A points determination module 33, for determining the points of the virtual assistant according to the user's usage of the in-vehicle applications in the recommendation list within a set period of time;

[0081] The strategy updating module 34 is used to update the virtual assistant and the preset recommendation strategy according to the points.

[0082] The technical solution provided in the third embodiment of the present invention effectively improves the utilization rate of vehicle-mounted applications and the interactivity of the vehicle-mounted entertainment system.

[0083] The scene information also includes at least one of the following:

[0084] Historical usage records of in-vehicle applications; user voice data; user preference information.

[0085] Optionally, the in-vehicle application recommendation device combined with the virtual assistant also includes:

[0086] The assistant creation module is used to create the virtual assistant according to the user operation when the user starts the vehicle system for the first time.

[0087] Optionally, the in-vehicle application recommendation device combined with the virtual assistant also includes:

[0088] The voice broadcast module is used to voice broadcast the recommendation list through the virtual assistant.

[0089] Optionally, the points determination module is specifically used to determine the points of the virtual assistant based on the frequency and / or duration of use of the in-vehicle applications in the recommendation list by the user within a set time period.

[0090] Optional, policy update module, including:

[0091] A strategy updating unit, configured to update the preset recommendation strategy according to the vehicle-mounted application from which the points are derived;

[0092] a function presentation unit, configured to present to the user props and / or functions of the virtual assistant that match the in-vehicle application;

[0093] The function granting unit is used to grant the virtual assistant corresponding props and / or functions when detecting the user's redemption operation on any of the props and / or any of the functions.

[0094] The in-vehicle application recommendation device combined with a virtual assistant provided in an embodiment of the present invention can execute the in-vehicle application recommendation method combined with a virtual assistant provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0095] Embodiment 4

[0096] Figure 4 : is a structural schematic diagram of an electronic device provided in Embodiment 4 of the present invention. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workbenches, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0097] like Figure 4As shown, the electronic device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0098] A number of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0099] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as the in-vehicle application recommendation method in combination with a virtual assistant.

[0100] In some embodiments, the in-vehicle application recommendation method in combination with a virtual assistant may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the in-vehicle application recommendation method in combination with a virtual assistant described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to execute the in-vehicle application recommendation method in combination with a virtual assistant in any other appropriate manner (e.g., by means of firmware).

[0101] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0102] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0103] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0104] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0105] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0106] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0107] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0108] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

[0109] An embodiment of the present invention also provides a computer program product, including a computer program and / or instructions, which, when executed by a processor, implements the in-vehicle application recommendation method combined with a virtual assistant as provided in any embodiment of the present application.

[0110] In the process of implementation, the computer program product can be written in one or more programming languages ​​or a combination thereof to perform the computer program code of the present invention, including object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computer (for example, using an Internet service provider to connect through the Internet).

[0111] Note that the above are only preferred embodiments of the present invention and the technical principles used. Those skilled in the art will understand that the present invention is not limited to the specific embodiments herein, and that various obvious changes, readjustments and substitutions can be made by those skilled in the art without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in more detail through the above embodiments, the present invention is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the present invention, and the scope of the present invention is determined by the scope of the appended claims.

Claims

1. A method for recommending in-vehicle applications in combination with a virtual assistant, characterized in that: include: Acquire scene information of the current scene, wherein the scene information includes user status information inside the vehicle and environment information outside the vehicle; According to the scenario information, based on a preset recommendation strategy, a recommendation list of in-vehicle applications for the current scenario is generated; Determining the points of the virtual assistant according to the user's usage of the in-vehicle applications in the recommendation list within a set time period; The virtual assistant and the preset recommendation strategy are updated according to the points.

2. The method according to claim 1, characterized in that The scene information also includes at least one of the following: Historical usage records of in-vehicle applications; user voice data; user preference information.

3. The method according to claim 1, characterized in that Also includes: If the user starts the in-vehicle system for the first time, the virtual assistant is created according to the user operation.

4. The method according to claim 1, characterized in that: After generating a recommended list of in-vehicle applications for the current scenario, it also includes: The recommendation list is voice broadcasted through the virtual assistant.

5. The method according to claim 1, characterized in that Determining the points of the virtual assistant according to the user's usage of the in-vehicle applications in the recommendation list within a set period of time, including: The points of the virtual assistant are determined according to the frequency and / or duration of use of the in-vehicle applications in the recommendation list by the user within a set time period.

6. The method according to claim 1, characterized in that According to the points, updating the virtual assistant and the preset recommendation strategy includes: updating the preset recommendation strategy according to the in-vehicle application from which the points are derived; Presenting to the user props and / or functions of the virtual assistant that match the in-vehicle application; When a user's redemption operation for any of the props and / or any of the functions is detected, the virtual assistant is given the corresponding props and / or functions.

7. A vehicle-mounted application recommendation device combined with a virtual assistant, characterized in that: include: An information acquisition module is used to acquire scene information of the current scene, wherein the scene information includes user status information inside the vehicle and environment information outside the vehicle; A list generation module, used to generate a recommendation list of vehicle-mounted applications for the current scenario based on the scenario information and a preset recommendation strategy; A points determination module, used to determine the points of the virtual assistant according to the user's usage of the in-vehicle applications in the recommendation list within a set time period; A strategy updating module is used to update the virtual assistant and the preset recommendation strategy according to the points.

8. An electronic device, characterized in that: include: at least one processor; as well as a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the in-vehicle application recommendation method combined with a virtual assistant as described in any one of claims 1-6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method for recommending in-vehicle applications combined with a virtual assistant as described in any one of claims 1 to 6 is implemented.

10. A computer program product, characterized in that It includes a computer program / instruction, which, when executed by a processor, implements the in-vehicle application recommendation method combined with a virtual assistant as described in any one of claims 1-6.

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