Route recommendation method and device, electronic equipment and readable storage medium

Abstract

The invention discloses a route recommendation method and device, electronic equipment and a readable storage medium, and belongs to the technical field of data processing. The method comprises the steps of obtaining at least one route to be recommended and first information, wherein the first information comprises at least one of the following items: route state information provided by at least two applications and historical preferences of a user; based on the at least one to-be-recommended route and the first information, determining a first recommended route; and outputting a first recommendation scheme, wherein the first recommendation scheme comprises the first recommendation route.

Description

Technical Field

[0001] The present application belongs to the field of data processing technology, and specifically relates to a route recommendation method, device, electronic device and readable storage medium. Background Art

[0002] With the development of science and technology, the types of artificial intelligence (AI) software (applications) are increasing, and their functions are becoming more and more powerful. It has become an indispensable part of people's lives and work.

[0003] Currently, when planning a travel route, users typically need to check travel information on different apps or websites. For example, users check the weather in a weather app, traffic in a map app, and route feedback in a social app. Users plan their routes based on the information retrieved from these different apps. However, this information is fragmented, requiring users to switch between multiple apps or websites to retrieve different travel information. This often results in low route planning accuracy. Summary of the Invention

[0004] The purpose of the embodiments of the present application is to provide a route recommendation method, device, electronic device and readable storage medium, which can improve the accuracy of route planning.

[0005] In a first aspect, an embodiment of the present application provides a route recommendation method, the method comprising:

[0006] Obtaining at least one route to be recommended and first information, wherein the first information includes at least one of the following: route status information provided by at least two applications and a user's historical preferences;

[0007] determining a first recommended route based on the at least one route to be recommended and the first information;

[0008] A first recommendation plan is output, where the first recommendation plan includes the first recommended route.

[0009] In a second aspect, an embodiment of the present application provides a route recommendation device, comprising:

[0010] A first acquisition module is configured to acquire at least one route to be recommended and first information, wherein the first information includes at least one of the following: route status information provided by at least two applications, and a user's historical preferences;

[0011] A first determining module, configured to determine a first recommended route based on the at least one route to be recommended and the first information;

[0012] The first output module is configured to output a first recommendation plan, where the first recommendation plan includes the first recommended route.

[0013] In a third aspect, an embodiment of the present application provides an electronic device comprising a processor and a memory, wherein the memory stores programs or instructions that can be run on the processor, and when the programs or instructions are executed by the processor, the steps of the method described in the first aspect are implemented.

[0014] In a fourth aspect, an embodiment of the present application provides a readable storage medium, on which a program or instruction is stored. When the program or instruction is executed by a processor, the steps of the method described in the first aspect are implemented.

[0015] In a fifth aspect, an embodiment of the present application provides a chip, which includes a processor and a communication interface, wherein the communication interface is coupled to the processor, the communication interface is used to transmit image data, and the processor is used to run programs or instructions to implement the method described in the first aspect.

[0016] In a sixth aspect, an embodiment of the present application provides a computer program product, which is stored in a storage medium and executed by at least one processor to implement the method described in the first aspect.

[0017] In an embodiment of the present application, route status information provided by at least two applications and / or the user's historical preferences can be directly obtained, and the route status information provided by at least two applications and / or the user's historical preferences can be used to determine and output a first recommended route to implement route planning. In this way, during the route planning process, the user does not need to switch between at least two applications to query different travel information, thereby improving the efficiency and accuracy of information acquisition, and using the route status information provided by at least two applications and / or the user's historical preferences to determine the first recommended route to implement route planning, thereby improving the accuracy of route planning. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 is a flow chart of a route recommendation method provided in an embodiment of the present application;

[0019] Figure 2 This is a schematic diagram of a hiking route planning principle provided by an embodiment of the present application;

[0020] Figure 3 This is an interface provided by an embodiment of the present application when the screen of an electronic device is off (off screen) or locked;

[0021] Figure 4 This is an interface provided by an embodiment of the present application in the standby state of an electronic device;

[0022] Figure 5This is a route recommendation interface diagram of an artificial intelligence software provided in an embodiment of the present application;

[0023] Figure 6 This is one of the interactive diagrams of a route recommendation solution provided in an embodiment of the present application;

[0024] Figure 7 This is one of the principle diagrams of a route recommendation solution provided in an embodiment of the present application;

[0025] Figure 8 This is the second interactive diagram of a route recommendation solution provided in an embodiment of the present application;

[0026] Figure 9 This is the second schematic diagram of a route recommendation solution provided in an embodiment of the present application;

[0027] Figure 10 This is the third interactive diagram of a route recommendation solution provided in an embodiment of the present application;

[0028] Figure 11 This is the third schematic diagram of a route recommendation solution provided in an embodiment of the present application;

[0029] Figure 12 This is a module diagram of a route recommendation device provided in an embodiment of the present application;

[0030] Figure 13 is a schematic structural diagram of an electronic device provided in an embodiment of the present application;

[0031] Figure 14 This is a schematic diagram of the hardware structure of the electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0032] The following will be combined with the accompanying drawings in the embodiments of the present application to clearly describe the technical solutions in the embodiments of the present application. Obviously, the embodiments described are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field are within the scope of protection of this application.

[0033] The terms "first," "second," and the like in the specification of this application are used to distinguish similar objects, and are not used to describe a specific order or precedence. It should be understood that the terms used in this manner are interchangeable where appropriate, so that the embodiments of this application can be implemented in an order other than that illustrated or described herein, and that the objects distinguished by "first," "second," and the like are generally of the same type, and do not limit the number of objects; for example, the first object can be one or more. Furthermore, the term "and / or" in this specification indicates at least one of the connected objects, and the character " / " generally indicates that the objects connected are in an "or" relationship.

[0034] The video generation unit provided in the embodiment of the present application is described in detail below through specific embodiments and their application scenarios in conjunction with the accompanying drawings.

[0035] like Figure 1 As shown, the present application provides a route recommendation method according to an embodiment. The method can be executed by an electronic device, and specifically can be implemented by an artificial intelligence application in the electronic device. The method includes:

[0036] Step 101: Obtain at least one route to be recommended and first information, where the first information includes at least one of the following: route status information provided by at least two applications, and a user's historical preferences.

[0037] The first information can also be understood as information that can affect the selection of the recommended route. At least two applications can be the executors of the method, that is, applications installed in the electronic device, and the route status information provided by the at least two applications can be obtained. It should be noted that the route status information is the route status information corresponding to at least one route to be recommended. In addition, the at least one route to be recommended can be at least one route to be recommended of the above-mentioned user (also referred to as the first user), and the user's historical preferences can also be referred to as the first user's historical preferences, that is, in this embodiment, it can be a route recommended to the user. It should also be noted that the user's historical preferences can be user preferences determined by statistical analysis of the user's historical behavior data.

[0038] Step 102: Determine a first recommended route based on the at least one route to be recommended and the first information.

[0039] It should be noted that the first recommended route may be selected from at least one recommended route, or may be selected from multiple routes provided by an application that provides route planning (which may be referred to as a first application, for example, including but not limited to travel applications, map applications, etc., and is not specifically limited in this embodiment). Furthermore, it should be noted that the at least one recommended route may also be provided by an application that provides route planning, and the multiple routes may differ from the at least one recommended route in part or in whole. Furthermore, the first recommended route may be understood to be the user's recommended route.

[0040] Step 103: Output a first recommendation plan, where the first recommendation plan includes the first recommended route.

[0041] The first recommended solution is output to implement route recommendation, and the user can determine whether to choose the first recommended route for travel based on the first recommended route in the first recommended solution. In addition, the first recommended solution can be understood as the user's recommended solution, that is, a route is recommended to the user.

[0042] In an embodiment of the present application, in an embodiment of the present application, route status information provided by at least two applications and / or the user's historical preferences can be directly obtained, and the route status information provided by at least two applications and / or the user's historical preferences can be used to determine and output a first recommended route to implement route planning. In this way, during the route planning process, the user does not need to switch between at least two applications to query different travel information, thereby improving the efficiency and accuracy of information acquisition, and using the route status information provided by at least two applications and / or the user's historical preferences to determine the first recommended route to implement route planning, thereby improving the accuracy of route planning.

[0043] In some embodiments, obtaining at least one route to be recommended includes at least one of the following:

[0044] Obtaining a first recommendation request, and in response to the first recommendation request, calling an application programming interface (API) of a map application to obtain the at least one route to be recommended; wherein the first recommendation request carries a first time and a first destination;

[0045] Obtaining a second recommendation request, obtaining historical behavior data of the user in response to the second recommendation request, and determining the at least one route to be recommended based on the historical behavior data;

[0046] At least one historically recommended route within a preset historical time period is obtained, and the at least one route to be recommended is determined based on the at least one historically recommended route, wherein the at least one route to be recommended includes at least one of the at least one historically recommended route.

[0047] In this embodiment, a user can actively request route recommendations or passively obtain recommended routes. In one example, when a user actively requests route recommendations, the user can enter a recommendation request. In this way, the recommendation request entered by the user can be obtained. In response to the recommendation request, at least one to-be-recommended route and first information can be obtained. Based on the first information, a first recommended route can be determined from the at least one to-be-recommended route, and the first recommended route can be recommended to the user. For example, the recommendation request (first recommendation request, second recommendation request) can be a recommendation request entered by the user in the route recommendation interface.

[0048] It should be noted that the recommendation request may be the above-mentioned first recommendation request, which carries the first time and the first destination input by the user. After obtaining the first recommendation request, in response to the first recommendation request, the application programming interface (API) of the map application may be called to obtain at least one recommended route to the first destination at the first time provided by the map application, that is, each of the at least one recommended route is a route to the first destination at the first time, that is, the destination of each recommended route is the first destination. The recommendation request may also be the above-mentioned second recommendation request (which may carry a user identifier). In this example, the user does not need to enter the time and destination, that is, the second recommendation request may not carry the first time and the first destination. In response to the second recommendation request, the historical behavior data of the user corresponding to the user identifier carried therein may be obtained, and the at least one recommended route may be determined based on the historical behavior data. As an example, historical behavior data may include, but is not limited to, historical travel data (e.g., historical travel routes, frequently visited route types (e.g., route types with more than a preset number of trips, etc.), frequently visited attraction types (e.g., attraction types with more than a preset number of trips), transportation methods of historical travel routes, weather of historical travel routes, hiking time of historical travel routes, surrounding service information of historical travel routes, etc.), and determining at least one route to be recommended based on the historical behavior data may include determining the user's historical preferences (e.g., route difficulty preferences, transportation method preferences, etc.) based on the historical behavior data, and determining at least one route to be recommended from routes provided by the network based on the historical preferences. As an example, the process of determining at least one route to be recommended from routes provided by the network based on historical preferences may include: obtaining routes provided by the network, and determining at least one route to be recommended from the routes provided by the network based on historical preferences and status information of the routes provided by the network (route status information); or, determining at least one route from the routes provided by the network based on historical preferences, and determining at least one route to be recommended from the at least one route based on the route status information of the at least one route, etc. In addition, it should be noted that a route may have been recommended to the user in the preset historical time period, that is, a historical recommended route for the user already exists. In the process of the user passively obtaining the recommended route, at least one historical recommended route for the user in the preset historical time period can be obtained (it can be a route recommended to the user in the preset historical time period, or a route recommended to the user in the preset historical time period and selected by the user, etc.). At least one of the at least one historical recommended routes can be used as at least one route to be recommended, and the first information of the route to be recommended can be used to generate a first recommended route, and the first recommended route can be recommended to the user.

[0049] In this embodiment, at least one recommended route can be obtained by any of the three methods mentioned above. In this way, the first recommended route is determined based on the obtained at least one recommended route and the first information, and the route planning is completed, thereby improving the flexibility of route planning.

[0050] In some embodiments, the route status information includes at least two of the following:

[0051] Weather information;

[0052] Traffic information;

[0053] Route feedback information of at least one user;

[0054] Surrounding service information.

[0055] It is understood that the route status information provided by the at least two applications may include at least two of the following: weather information provided by a weather service application; traffic information and / or surrounding service information provided by a map application; and route feedback information from at least one user provided by an information interaction application (e.g., a social application (platform), a forum application, a communication community application, or the aforementioned artificial intelligence application). For example, the weather service application's API may be called to obtain weather information, the map application's API may be called to obtain traffic information and / or surrounding service information, and the social platform's API may be called to obtain route feedback information from at least one user. The at least one user may be understood as a user who has entered route feedback information for at least one recommended route in the information interaction application. If the at least one recommended route includes at least one of the at least one historically recommended routes, the at least one user may include the first user. In other cases (e.g., if the at least one recommended route is determined in response to a first recommendation request, or if the at least one recommended route is determined in response to a second recommendation request, etc.), the at least one user may or may not include the first user. As an example, route feedback information may include, but is not limited to, reviews, suggestions, and other information. As an example, surrounding service information may include, but is not limited to, information about restaurants, accommodations, shops, and attractions.

[0056] It should be noted that, for each of at least one to-be-recommended route, the route feedback information of at least one user may be feedback information of at least one user on the to-be-recommended route. As an example, it may include preliminary feedback information before traveling along the to-be-recommended route, mid-way feedback information during the trip along the route in the to-be-recommended route, and feedback information after completing the trip along the route in the to-be-recommended route.

[0057] That is, in this embodiment, in the process of recommending a route, at least two factors of the route such as weather, traffic, surrounding services, route feedback information, etc. may be considered to make the recommended route more compatible with the route status information and recommend a more suitable route.

[0058] As an example, before obtaining at least one route to be recommended and the first information, the method may further include:

[0059] Receiving a wake-up instruction input by a user, and waking up the artificial intelligence application in response to the wake-up instruction;

[0060] When the artificial intelligence application is awake, a route recommendation interface is displayed, the route recommendation interface including at least one of the following: an input box and a first control corresponding to the input box; a second control; and a third control, wherein the first control prompts for input of a time and a destination, the second control prompts for a recommended travel route (e.g., a recommended hiking route), and the third control prompts for starting planning (starting route planning).

[0061] In this embodiment, obtaining a first recommendation request may include: receiving a first time and a first destination input by a user in an input box of a route recommendation interface, receiving a first input to the first control (e.g., a click), and generating a first recommendation request in response to the first input. Obtaining a second recommendation request may include: receiving a second input to the second control (e.g., a click) from the user, and generating a second recommendation request in response to the second input. Obtaining at least one historical recommended route within a preset historical time period may include: receiving a third input to a third control (e.g., a click) from the user, and obtaining at least one historical recommended route within a preset historical time period in response to the third input. That is, in this embodiment, the user can select a route recommendation method by selecting the controls in the interface, that is, the user can select any of the three methods mentioned above, so that route recommendations can be made to the user in a selected manner, thereby improving the flexibility of route recommendations.

[0062] In some embodiments, the first information includes the route status information and the user's historical preferences, the at least one to-be-recommended route includes at least one historically recommended route within a preset time period, and the route status information includes route feedback information of the user on the at least one historically recommended route;

[0063] The determining a first recommended route based on the at least one to-be-recommended route and the first information includes:

[0064] updating the user's historical preferences according to route feedback information input by the user for the at least one historical recommended route to obtain updated historical preferences;

[0065] The first recommended route is generated based on the updated historical preference.

[0066] It will be understood that in this embodiment, users passively obtain recommended routes, and historically recommended routes may differ from the user's desired route, i.e., not meet the user's expectations. Alternatively, historically recommended routes may meet the user's expectations. Users can provide relevant feedback on historically recommended routes. For example, if a route does not meet the user's expectations, the user can enter negative feedback and route suggestions. If a route does meet the user's expectations, the user can enter positive feedback. In this way, the route feedback information entered by the user for at least one historically recommended route can be used to update the user's historical preferences, obtaining the user's updated historical preferences. Using the user's updated historical preferences, a first recommended route is generated, which better meets the user's expectations. As an example, the first recommended route in this embodiment can be a route determined from the multiple routes described above based on the updated historical preferences. As an example, the recommendation model can be used to determine the first recommended route. Before determining the first recommended route based on the updated historical preferences, the recommendation model can be updated according to the route feedback information input by the user for the at least one historical recommended route. In this way, in the process of determining the first recommended route based on the updated historical preferences, the first recommended route can be determined based on the updated historical preferences through the updated recommendation model, thereby improving the route recommendation effect.

[0067] In some embodiments, after outputting the first recommended solution, the method further includes:

[0068] Receive demand feedback information input by users;

[0069] Based on the demand feedback information, updating the first recommendation solution;

[0070] Output the updated first recommended solution.

[0071] After the first recommended route is recommended, if the user is not satisfied with the recommended first recommended route, the user can put forward corresponding requirements, that is, the user can input the demand feedback information. In this way, after receiving the demand feedback information, the recommendation scheme can be adjusted. For example, the first recommended route in the first recommendation scheme can be updated. If the first recommendation scheme includes recommended information on route status information, the recommended information on route status information in the first recommendation scheme can also be updated. If the first recommendation scheme includes route status information, the recommended information on route status information in the first recommendation scheme can also be updated. Then, the updated first recommendation scheme is output and recommended to the user to meet the user's needs. As an example, outputting the updated first recommendation scheme may include at least one of the following: voice broadcasting of the updated first recommendation scheme; text display of the updated first recommendation scheme; display of an image including the updated first recommendation scheme; and presentation of the updated first recommendation scheme through map mode. This improves the flexibility of scheme recommendation.

[0072] In some embodiments, the first information includes the route status information;

[0073] The method further includes: determining suggestion information corresponding to the route status information;

[0074] The first recommendation scheme also includes the suggestion information.

[0075] It should be understood that the suggestion information can be travel suggestions. For example, for weather information, corresponding clothing suggestions and equipment carrying suggestions can be given. For traffic information, corresponding transportation suggestions and clothing suggestions can be given. For surrounding service information, corresponding surrounding service stops and rest suggestions can be given. For route feedback information, corresponding suggestions can be given. For example, if the route feedback information of a certain route indicates that the route is difficult, a suggestion to wear sports shoes can be given. In this way, for the first recommended route, the suggestion information corresponding to the route status information of the first recommended route can be determined, so that when the user chooses the first recommended route to travel, he can also travel according to the suggestion information to improve the travel experience. As an example, the first recommendation plan can also include the estimated route difficulty and route duration of the first recommended route based on the user's physical fitness data.

[0076] In some embodiments, outputting the first recommendation includes at least one of the following:

[0077] Voice broadcast of the first recommended solution;

[0078] The text displays the first recommended solution;

[0079] displaying an image including the first recommendation;

[0080] The first recommended solution is presented in a map mode.

[0081] That is, in this embodiment, any of the above four methods can be used to output the first recommended solution to achieve the recommendation of the first recommended solution. While improving the flexibility of the solution recommendation, it can make it easier for users to understand the recommended solution and make more accurate and satisfactory solution decisions.

[0082] As an example, the target output method selected by the user from the above four output methods (voice broadcast, text display, image display, and map mode presentation) can be obtained, and the first recommended solution can be output. In this way, the user can select the output method according to needs, and the first recommended solution can be output in the target output method selected by the user to meet the user's needs.

[0083] The process of the above method is described in detail below with some specific embodiments. Taking hiking route recommendation in a hiking scenario as an example, artificial intelligence software can be understood as an intelligent system that can understand user intentions and provide services.

[0084] First, the relevant background technology is introduced.

[0085] Currently, when planning a route, hiking enthusiasts often need to separately query weather forecasts, route status, traffic conditions, restaurants, accommodations, and other information. This information is scattered across different platforms, making the query process cumbersome and the user experience poor. Hiking or travel planning applications in related technologies typically only provide static routes or simple guides, lacking dynamic updates and intelligent recommendations, making it difficult to meet users' personalized needs. First, information fragmentation: users need to switch between multiple applications or websites to obtain information on weather, road conditions, traffic, restaurants, accommodations, and other information, resulting in low information acquisition efficiency. Second, there is a lack of personalized suggestions: the recommendations provided by related applications are often too general and cannot provide customized services based on the user's personal preferences and actual conditions. Third, the interactive experience is poor: the user interface is complex, the operation steps are cumbersome, and the user experience is poor.

[0086] Based on this, the embodiment of the present application provides a comprehensive hiking planning system based on an intelligent assistant (artificial intelligence software), which provides users with a one-stop hiking planning service through multimodal human-computer interaction (which can simultaneously support multiple input and output modes of interaction, such as voice, text, and images, so that users can communicate with the system more naturally). The intelligent assistant can communicate with users in various forms such as voice, text, and pictures, dynamically integrate the latest hiking feedback information from information interaction applications such as social platforms and outdoor communities, and access API services such as weather and maps to achieve a mode that combines active push and active query, and make personalized recommendations based on user historical behavior data. The solution provided in the embodiment of the present application can achieve but is not limited to the following:

[0087] Real-time information integration: Unify and process real-time information from multiple sources, including social reviews, user feedback, weather data, and traffic conditions;

[0088] Multimodal interactive experience: Users can express their needs by voice or input scenarios through text or photos, allowing AI software to more flexibly understand user intent.

[0089] Intelligent decision support: Based on multi-dimensional data analysis, it provides users with scientific decision support;

[0090] Personalized recommendations: Based on the user's past hiking records and explicit preferences, intelligent algorithms are used to generate route plans that are highly consistent with individual needs;

[0091] Dynamic learning and optimization: The system can continuously adjust and optimize the recommendation model based on user interaction feedback to improve service accuracy and user satisfaction.

[0092] The specific technical details of the solution provided in the embodiments of this application include but are not limited to the following:

[0093] Multimodal interactive access: Users interact with AI applications through their mobile phone apps' multimodal interfaces (supporting voice, text, and image input). For example, a user can voice-inform "I want to hike to XX scenic spot" or upload a picture of their current location and surroundings, which the system then analyzes and identifies. The AI ​​application can proactively push route recommendations to users or quickly inquire about their preferences.

[0094] Hiking feedback data integration: The AI ​​application backend captures real-time data from social platforms, outdoor forums, and hiking enthusiast communities, collecting the latest reviews of target routes, difficulty feedback, landscape descriptions, and crowd conditions. After processing this unstructured data, the system summarizes key information such as route difficulty, scenic reviews, and peak traffic flow for planning reference.

[0095] Weather Information Acquisition: The system accesses the Weather Service API (Weather Application API) to obtain real-time weather information for the target hiking area and time period, including temperature, precipitation, wind speed, humidity, etc. Based on weather conditions, the AI ​​software provides users with clothing and equipment recommendations, such as timely reminders to bring rain gear or sunscreen;

[0096] Map and surrounding information query: By calling the map API, the system generates a transportation route plan for the user and retrieves information on points of interest (POIs), such as restaurants and rest areas, near the starting and ending points of the hike. For example, some map Places APIs provide detailed location data and intelligent search capabilities, including whether reservations are required, average cost, and special dishes. Artificial intelligence applications use this information to recommend suitable dining stops and rest plans.

[0097] Personalized Recommendation Generation: The system records and analyzes users' past hiking history (e.g., frequently visited route types, hiking duration, favorite landscapes, etc.) and explicit preferences (e.g., difficulty level, preferred transportation method). Leveraging recommendation algorithms, it generates personalized route and service combination recommendations. Modern recommendation systems widely utilize artificial intelligence to learn from individual user preferences and behaviors, delivering the most relevant items to them.

[0098] Two-way interaction and model optimization: The system supports both user-initiated queries (users can ask the AI ​​application for weather, route updates, etc. at any time) and proactive push notifications (with user permission, the AI ​​application regularly pushes the latest route and equipment recommendations). Every user response (such as accepting / rejecting a recommended route, asking further questions) is fed back into the learning model, continuously optimizing recommendations and enhancing its intelligence.

[0099] like Figure 2 The figure shows a schematic diagram of a hiking route planning principle provided by an embodiment of the present application. The user can input a recommendation request through multimodal interaction (i.e., the system supports multiple input and output modes of interaction, such as voice, text, images, etc., so that the user can communicate with the system more naturally). In response to the recommendation request, the artificial intelligence software can identify the user's intention and collect data. For example, the artificial intelligence software can collect information provided by third-party applications (e.g., social platforms, forums, weather applications, map applications, etc.) and determine the recommended route based on the information collected from the third-party applications (route status information), i.e., route generation. In addition, without the user actively inputting a recommendation request, a recommended route can also be generated based on user preferences through a recommendation algorithm. After the route is generated, a plan can be recommended to the user so that the user can choose a plan for hiking, etc.

[0100] The process of the route recommendation solution provided in the embodiment of the present application may specifically include:

[0101] First, if Figure 3 As shown in the figure, when the screen of the electronic device is off (off) or locked, the user can wake up the artificial intelligence software through voice, such as Figure 3 As shown, a keyboard 301 is provided for input, and the user can choose to input the hiking demand in text form, that is, by inputting the hiking demand in text form in the keyboard 301, and a voice input switch 302 is provided, and the user can choose to continue to input the hiking demand by voice; Figure 3In the function extension part 303, users can choose to take pictures, upload hiking route pictures, guide documents or execute other shortcut commands to allow the artificial intelligence software to perform more accurate analysis; in addition, the artificial intelligence software provides a shortcut command part 304. After the user trains the artificial intelligence software multiple times by planning hiking route requirements, the artificial intelligence software can generate personalized recommendation commands. Figure 4 As shown, when the electronic device is unlocked and in standby mode, the user can wake up the artificial intelligence software by voice or by directly clicking on the icon 401 of the artificial intelligence software.

[0102] Then, the artificial intelligence software can determine the recommended route and push the recommended solution to the user. For example, the artificial intelligence can collect information, organize and analyze the collected information, generate a recommended route, and recommend the recommended solution including the recommended route to the user. In this embodiment, you can enter the artificial intelligence software interface and click the route recommendation option in the interface to enter the route recommendation interface, such as Figure 5 As shown. Three interaction modes are provided, corresponding to three controls, namely the first control 501, the second control 502, and the third control 503. The user can choose the interaction mode, and the artificial intelligence software can generate routes and make recommendations based on the interaction mode selected by the user. The first interaction mode (corresponding to the first control 501) is that the user actively inputs, and the artificial intelligence software outputs a recommendation scheme (corresponding to the recommendation mode of the first recommendation request). The second interaction mode (corresponding to the second control 502) is that the artificial intelligence software outputs a recommendation scheme after receiving the second recommendation request. The third interaction mode (corresponding to the third control 503) is that the artificial intelligence software actively pushes the recommendation scheme. The first and second interaction modes are actively obtained by the user, and the third interaction mode is passively obtained by the user.

[0103] like Figure 6 As shown, for the first interaction mode: user input, artificial intelligence software output, that is, the user inputs the time and destination, and the artificial intelligence software gives a recommended solution.

[0104] A user can initiate a hiking plan request (the first recommendation request) through voice or text input, for example, "I'd like to hike Laoshan this weekend. Any suggestions?" The system activates artificial intelligence software, which responds to the user's request. The AI ​​software analyzes the user input, identifying the core intent (hiking plan) and key information (location: Laoshan, time: weekend). It then determines which service modules to invoke, including route information, weather forecast, and user profile analysis. The system then accesses the route database to obtain Laoshan hiking route information, the weather API to obtain weekend weather forecasts for the Laoshan area, social platform APIs to gather user reviews and road condition feedback from recent Laoshan hikes, the map API to retrieve transportation options to Laoshan, and the POI (Point of Interest) database to obtain information on nearby restaurants and rest facilities. Based on this information, the system generates a preliminary hiking plan (recommended plan). If the user has historical preferences, the system can combine this information with the user's historical preferences to create a personalized recommendation. Furthermore, the system can provide clothing recommendations based on weather conditions and estimate the appropriate route difficulty and duration based on the user's historical fitness data. The AI ​​software presents a recommended route to the user in natural language: "Laoshan will have sunny weather this weekend, with temperatures between 15 and 22°C, perfect for hiking. We recommend the Laoshan East Route, which is moderately difficult and takes approximately three hours. Crowds are currently moderate. Light sportswear, a hat, and sunscreen are recommended. Buses or subways are most convenient for reaching the area, but parking can be crowded. There are several well-rated restaurants nearby. Would you like more information?" Users can ask further questions or request adjustments to their route, such as "I'd like more detailed transportation information" or "Is there a less crowded route?" The AI ​​software adjusts its recommendations based on user feedback and provides more detailed information. After the user confirms the recommended route, the software provides a final summary and reminders.

[0105] like Figure 7 As shown in the figure, the specific process of implementing solution recommendation through the first interactive mode includes:

[0106] User-initiated dialogue: The user wakes up the AI ​​software and initiates a hiking plan request (the first recommendation request) through voice or text input;

[0107] Intent recognition and analysis: The system analyzes user input to identify the core intent (hiking plan) and key information (location, time);

[0108] Information collection and integration: The AI ​​software system uses route databases, weather APIs, social media APIs, traffic APIs, and databases to obtain hiking routes, weather forecasts, user reviews and road condition feedback, and information about nearby dining and rest facilities.

[0109] Plan generation and personalized recommendations: AI software integrates collected information to generate preliminary hiking plans and personalizes them based on user historical preferences.

[0110] Conversational response: AI software presents recommendations to users via voice or text.

[0111] User feedback and solution adjustments: Users raise further questions or request adjustments to the recommended solution;

[0112] The system provides the final adjusted recommendation plan and schedule reminder.

[0113] like Figure 8 As shown, for the second interaction method: artificial intelligence software recommends hiking plans.

[0114] The system records and analyzes the user's historical behavior data (for example, past hiking history (such as frequently visited route types, hiking duration, favorite landscapes, etc.) and historical preferences (such as physical condition, difficulty preference, and transportation mode preference), and uses the recommendation algorithm to generate a recommendation plan (for example, including personalized recommended routes and surrounding service information). The interactive diagram is shown in the figure below. Figure 8 shown.

[0115] like Figure 9 As shown in the figure, the specific process of implementing solution recommendation through the second interactive mode includes:

[0116] User-initiated conversation: The user wakes up Xiao V and requests Xiao V to recommend a hiking route via voice or text.

[0117] Information collection and processing: Xiao V analyzes user preferences and historical data, and combines route status and user preferences to find in-depth search routes;

[0118] Information integration and visualization: Xiao V integrates weather, maps, and surrounding service information, returns hiking plans (hiking information), and presents the hiking plans in multimodal (voice, image, text) information;

[0119] User mode switching and interaction: Users switch between different interaction modes, such as switching from voice mode to map mode;

[0120] When a user requests a complete solution report, the artificial intelligence software will include the user's request in the database for analysis and provide a downloadable PDF report of the recommended solution for the user to download.

[0121] like Figure 10 As shown, for the third interaction method: artificial intelligence software actively pushes.

[0122] The system collects user feedback on the plan before, during, and after the hike (feedback results), identifies keywords and user sentiment, and compares the feedback results with the actual situation to evaluate the accuracy of the prediction. Based on the feedback results, the system iterates the algorithm and updates the recommendation model, learns user preferences, adjusts user preferences, and applies them to future plan push. Figure 10 shown.

[0123] like Figure 11 As shown in the figure, the specific process for implementing the recommended solution for the third interaction mode includes:

[0124] Initial hiking plan generation: Generate an initial hiking plan based on user historical behavior data and user preferences;

[0125] User feedback collection: Record feedback information based on users' initial feedback on the initial plan, mid-hike feedback, and post-hike feedback;

[0126] Feedback analysis and model update: The system analyzes user feedback information and updates the recommendation model

[0127] User profile update: Identify keywords and sentiment trends and update user profiles, such as updating user preferences;

[0128] Personalized plan adjustment: Using updated user preferences, proactively provide hiking plans that meet user preferences;

[0129] Push hiking plans: proactively push generated hiking plans to users.

[0130] The route recommendation scheme provided by the embodiments of this application can achieve:

[0131] Information integration and efficiency improvement: This embodiment of the application integrates various types of hiking-related information (routes, weather, transportation, restaurants, etc.) into a single platform and adopts a conversational human-computer interaction method, eliminating the need for users to switch between multiple applications. This greatly improves information acquisition efficiency and saves users time and energy in planning hiking activities. This information integration mechanism solves the problems of information fragmentation and low acquisition efficiency in related technologies.

[0132] Personalized experience and precise recommendations: The adaptive hiking planning system based on user feedback can learn user preferences and behavior patterns, and provide users with increasingly precise personalized hiking plans by continuously updating user profiles and recommendation algorithms. This personalized recommendation mechanism can significantly improve the user experience and make hiking plans more tailored to users' actual needs and abilities.

[0133] Multimodal Interaction and Information Visualization: This invention provides a multimodal interaction method that supports presenting hiking-related information in various formats, including voice, text, images, and maps. Users can choose different interaction methods as needed to obtain more intuitive and comprehensive hiking planning support. This flexible interaction method and information visualization makes complex hiking information easier to understand and use, improving user decision-making accuracy and satisfaction.

[0134] The route recommendation method provided in the embodiment of the present application can be executed by a route recommendation device. In the embodiment of the present application, the route recommendation device is used as an example to illustrate the route recommendation method provided in the embodiment of the present application.

[0135] like Figure 12 As shown, a route recommendation device 1200 according to an embodiment is provided, which can be used in an electronic device. The device 1200 includes:

[0136] A first acquisition module 1201 is configured to acquire at least one route to be recommended and first information, wherein the first information includes at least one of the following: route status information provided by at least two applications, and a user's historical preferences;

[0137] A first determining module 1202 is configured to determine a first recommended route based on the at least one route to be recommended and the first information;

[0138] The first output module 1203 is configured to output a first recommendation plan, where the first recommendation plan includes the first recommended route.

[0139] In some embodiments, obtaining at least one route to be recommended includes at least one of the following:

[0140] Obtaining a first recommendation request, and in response to the first recommendation request, calling an application programming interface (API) of a map application to obtain the at least one route to be recommended; wherein the first recommendation request carries a first time and a first destination, and each route to be recommended is a route to the first destination at the first time;

[0141] Obtaining a second recommendation request, obtaining historical behavior data of the user in response to the second recommendation request, and determining the at least one route to be recommended based on the historical behavior data;

[0142] At least one historically recommended route within a preset historical time period is obtained, and the at least one route to be recommended is determined based on the at least one historically recommended route, wherein the at least one route to be recommended includes at least one of the at least one historically recommended route.

[0143] In some embodiments, the first information includes the route status information and the user's historical preferences, the at least one to-be-recommended route includes at least one historically recommended route within a preset time period, and the route status information includes route feedback information of the user on the at least one historically recommended route;

[0144] The first determining module includes:

[0145] an updating unit, configured to update the user's historical preferences according to route feedback information input by the user for the at least one historical recommended route, to obtain updated historical preferences;

[0146] A generating unit is configured to generate the first recommended route based on the updated historical preference.

[0147] In some embodiments, the apparatus further comprises:

[0148] a receiving module, configured to receive demand feedback information input by a user after the first output module executes and outputs the first recommendation solution;

[0149] An updating module, configured to update the first recommendation solution based on the demand feedback information;

[0150] The second output module is used to output the updated first recommendation solution.

[0151] In some embodiments, the first information includes the route status information;

[0152] The device further comprises:

[0153] A second determining module is used to determine the suggestion information corresponding to the route status information;

[0154] The first recommendation scheme also includes the suggestion information.

[0155] In some embodiments, the route status information includes at least two of the following:

[0156] Weather information;

[0157] Traffic information;

[0158] Route feedback information of at least one user;

[0159] Surrounding service information.

[0160] The route recommendation device in the embodiments of the present application can be an electronic device or a component of an electronic device, such as an integrated circuit or chip. The electronic device can be a terminal or other device other than a terminal. The electronic device can be a mobile phone, tablet computer, laptop computer, PDA, in-vehicle electronic device, mobile internet device (MID), augmented reality (AR) / virtual reality (VR) device, robot, wearable device, ultra-mobile personal computer (UMPC), netbook, or personal digital assistant (PDA). It can also be a server, network attached storage (NAS), personal computer (PC), television, ATM, or self-service machine, etc., and the embodiments of the present application do not specifically limit this.

[0161] The route recommendation device in the embodiment of the present application may be a device having an operating system. The operating system may be an Android operating system, an iOS operating system, or other possible operating systems, which are not specifically limited in the embodiment of the present application.

[0162] The route recommendation device provided in the embodiment of the present application can implement each process implemented in the above route recommendation method embodiment, for example, it can implement Figures 1 to 11 To avoid repetition, the various processes implemented in the method embodiment are not described here.

[0163] Alternatively, as Figure 13 As shown, an embodiment of the present application further provides an electronic device 1300, including a processor 1301 and a memory 1302, wherein the memory 1302 stores programs or instructions that can be run on the processor 1301, and when the program or instructions are executed by the processor 1301, the various steps of the above-mentioned route recommendation method embodiment are implemented, and the same technical effect can be achieved. To avoid repetition, they will not be described here.

[0164] It should be noted that the electronic devices in the embodiments of the present application include the above-mentioned mobile electronic devices and non-mobile electronic devices.

[0165] Figure 14 A schematic diagram of the hardware structure of an electronic device implementing an embodiment of the present application.

[0166] The electronic device 1400 includes but is not limited to components such as a radio frequency unit 1401 , a network module 1402 , an audio output unit 1403 , an input unit 1404 , a sensor 1405 , a display unit 1406 , a user input unit 1407 , an interface unit 1408 , a memory 1409 , and a processor 1410 .

[0167] Those skilled in the art will understand that the electronic device 1400 may also include a power source (such as a battery) to power each component, and the power source may be logically connected to the processor 1410 through a power management system, thereby implementing functions such as charging, discharging, and power consumption management through the power management system. Figure 14 The electronic device structure shown in the figure does not constitute a limitation on the electronic device. The electronic device may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently, which will not be repeated here.

[0168] The processor 1410 is configured to:

[0169] Obtaining at least one route to be recommended and first information, wherein the first information includes at least one of the following: route status information provided by at least two applications and a user's historical preferences;

[0170] determining a first recommended route based on the at least one route to be recommended and the first information;

[0171] A first recommendation plan is output, where the first recommendation plan includes the first recommended route.

[0172] In some embodiments, obtaining at least one route to be recommended includes at least one of the following:

[0173] Obtaining a first recommendation request, and in response to the first recommendation request, calling an application programming interface (API) of a map application to obtain the at least one route to be recommended; wherein the first recommendation request carries a first time and a first destination, and each route to be recommended is a route to the first destination at the first time;

[0174] Obtaining a second recommendation request, obtaining historical behavior data of the user in response to the second recommendation request, and determining the at least one route to be recommended based on the historical behavior data;

[0175] At least one historically recommended route within a preset historical time period is obtained, and the at least one route to be recommended is determined based on the at least one historically recommended route, wherein the at least one route to be recommended includes at least one of the at least one historically recommended route.

[0176] In some embodiments, the first information includes the route status information and the user's historical preferences, the at least one to-be-recommended route includes at least one historically recommended route within a preset time period, and the route status information includes route feedback information of the user on the at least one historically recommended route;

[0177] The processor 1410 is specifically configured to:

[0178] updating the user's historical preferences according to route feedback information input by the user for the at least one historical recommended route to obtain updated historical preferences;

[0179] The first recommended route is generated based on the updated historical preference.

[0180] In some embodiments, the processor 1410 is further configured to:

[0181] After the first output module executes and outputs the first recommendation solution, receiving demand feedback information input by the user;

[0182] Based on the demand feedback information, updating the first recommendation solution;

[0183] Output the updated first recommended solution.

[0184] In some embodiments, the first information includes the route status information;

[0185] The processor 1410 is further configured to:

[0186] Determining suggestion information corresponding to the route status information;

[0187] The first recommendation scheme also includes the suggestion information.

[0188] In some embodiments, the route status information includes at least two of the following:

[0189] Weather information;

[0190] Traffic information;

[0191] Route feedback information of at least one user;

[0192] Surrounding service information.

[0193] It should be understood that in an embodiment of the present application, the input unit 1404 may include a graphics processing unit (GPU) 14041 and a microphone 14042, and the graphics processor 14041 processes the image data of a static picture or video obtained by an image capture device (such as a camera) in a video capture mode or an image capture mode. The display unit 1406 may include a display panel 14061, and the display panel 14061 may be configured in the form of a liquid crystal display, an organic light emitting diode, etc. The user input unit 1407 includes a touch panel 14071 and at least one of other input devices 14072. The touch panel 14071 is also called a touch screen. The touch panel 14071 may include two parts: a touch detection device and a touch controller. Other input devices 14072 may include, but are not limited to, a physical keyboard, function keys (such as volume control keys, switch keys, etc.), a trackball, a mouse, and an operating stick, which will not be repeated here.

[0194] Memory 1409 can be used to store software programs and various data. Memory 109 may primarily include a first storage area for storing programs or instructions and a second storage area for storing data. The first storage area may store an operating system, applications or instructions required for at least one function (such as a sound playback function, an image playback function, etc.). Furthermore, memory 109 may include volatile memory or non-volatile memory, or memory 1409 may include both volatile and non-volatile memory. The non-volatile memory may be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory may be a random access memory (RAM), a static random access memory (SRAM), a dynamic random access memory (DRAM), a synchronous dynamic random access memory (SDRAM), a double data rate synchronous dynamic random access memory (DDRSDRAM), an enhanced synchronous dynamic random access memory (ESDRAM), a synchronous link dynamic random access memory (SLDRAM), and a direct memory bus random access memory (DRRAM). The memory 109 in the embodiment of the present application includes but is not limited to these and any other suitable types of memory.

[0195] Processor 110 may include one or more processing units; optionally, these may include, but are not limited to, applications and an operating system. Processor 1410 may integrate an application processor and a modem processor. The application processor primarily processes the operating system, user interface, and applications, while the modem processor primarily handles wireless communications. It is understood that the modem processor may not be integrated into processor 1410.

[0196] An embodiment of the present application also provides a readable storage medium, on which a program or instruction is stored. When the program or instruction is executed by a processor, the various processes of the above-mentioned route recommendation method embodiment are implemented and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0197] The processor is the processor in the electronic device in the above embodiment. The readable storage medium includes a computer readable storage medium, such as a computer read-only memory ROM, a random access memory RAM, a magnetic disk or an optical disk.

[0198] An embodiment of the present application further provides a chip including a processor and a communication interface, wherein the communication interface and the processor are coupled, the communication interface is used to transmit image data, and the processor is used to run programs or instructions to implement the various processes of the above-mentioned route recommendation method embodiment and achieve the same technical effect. To avoid repetition, they will not be described here.

[0199] It should be understood that the chip mentioned in the embodiments of the present application can also be called a system-level chip, a system chip, a chip system or a system-on-chip chip, etc.

[0200] An embodiment of the present application provides a computer program product, which is stored in a storage medium and executed by at least one processor to implement the various processes of the route recommendation method embodiment described above, and can achieve the same technical effect. To avoid repetition, it will not be described here.

[0201] It should be noted that, in this article, the terms "comprise", "include" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the statement "comprises a ..." does not exclude the presence of other identical elements in the process, method, article or device comprising the element. In addition, it should be noted that the scope of the methods and devices in the embodiments of the present application is not limited to performing functions in the order shown or discussed, and may also include performing functions in a substantially simultaneous manner or in the opposite order according to the functions involved. For example, the described method may be performed in an order different from that described, and various steps may also be added, omitted, or combined. In addition, the features described with reference to certain examples may be combined in other examples.

[0202] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus the necessary general hardware platform, and of course can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art can be embodied in the form of a computer software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), including a number of instructions for enabling a terminal (which can be a mobile phone, computer, server, or network device, etc.) to execute the methods described in each embodiment of the present application.

[0203] The embodiments of the present application are described above in conjunction with the accompanying drawings, but the present application is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of this application, ordinary technicians in this field can also make many forms without departing from the purpose of this application and the scope of protection of the claims, all of which are within the protection of this application.

Claims

1. A route recommendation method, characterized in that: The method comprises: Obtaining at least one route to be recommended and first information, wherein the first information includes at least one of the following: route status information provided by at least two applications and a user's historical preferences; determining a first recommended route based on the at least one route to be recommended and the first information; A first recommendation plan is output, where the first recommendation plan includes the first recommended route.

2. The method according to claim 1, characterized in that The obtaining of at least one route to be recommended includes at least one of the following: Obtaining a first recommendation request, and in response to the first recommendation request, calling an application programming interface (API) of a map application to obtain the at least one route to be recommended; wherein the first recommendation request carries a first time and a first destination, and each route to be recommended is a route to the first destination at the first time; Obtaining a second recommendation request, obtaining historical behavior data of the user in response to the second recommendation request, and determining the at least one route to be recommended based on the historical behavior data; At least one historically recommended route within a preset historical time period is obtained, and the at least one route to be recommended is determined based on the at least one historically recommended route, wherein the at least one route to be recommended includes at least one of the at least one historically recommended route.

3. The method according to claim 1, characterized in that The first information includes the route status information and the user's historical preferences, the at least one to-be-recommended route includes at least one historically recommended route within a preset time period, and the route status information includes route feedback information of the user on the at least one historically recommended route; The determining a first recommended route based on the at least one to-be-recommended route and the first information includes: updating the user's historical preferences according to route feedback information input by the user for the at least one historical recommended route to obtain updated historical preferences; The first recommended route is generated based on the updated historical preference.

4. The method according to any one of claims 1 to 3, characterized in that After outputting the first recommended solution, the method further includes: Receive demand feedback information input by users; Based on the demand feedback information, updating the first recommendation solution; Output the updated first recommended solution.

5. The method according to any one of claims 1 to 3, characterized in that The first information includes the route status information; The method further includes: determining suggestion information corresponding to the route status information; The first recommendation scheme also includes the suggestion information.

6. The method according to any one of claims 1 to 3, characterized in that The route status information includes at least two of the following: Weather information; Traffic information; Route feedback information of at least one user; Surrounding service information.

7. A route recommendation device, characterized in that: The device comprises: A first acquisition module is configured to acquire at least one route to be recommended and first information, wherein the first information includes at least one of the following: route status information provided by at least two applications, and a user's historical preferences; A first determining module, configured to determine a first recommended route based on the at least one route to be recommended and the first information; The first output module is configured to output a first recommendation plan, where the first recommendation plan includes the first recommended route.

8. The device according to claim 7, characterized in that The obtaining of at least one route to be recommended includes at least one of the following: Obtaining a first recommendation request, and in response to the first recommendation request, calling an application programming interface (API) of a map application to obtain the at least one route to be recommended; wherein the first recommendation request carries a first time and a first destination, and each route to be recommended is a route to the first destination at the first time; Obtaining a second recommendation request, obtaining historical behavior data of the user in response to the second recommendation request, and determining the at least one route to be recommended based on the historical behavior data; At least one historically recommended route within a preset historical time period is obtained, and the at least one route to be recommended is determined based on the at least one historically recommended route, wherein the at least one route to be recommended includes at least one of the at least one historically recommended route.

9. An electronic device, characterized in that: The method comprises a processor and a memory, wherein the memory stores a program or instruction that can be run on the processor, and when the program or instruction is executed by the processor, the steps of the route recommendation method according to any one of claims 1 to 6 are implemented.

10. A readable storage medium, characterized in that: The readable storage medium stores a program or instruction, and when the program or instruction is executed by the processor, the steps of the route recommendation method according to any one of claims 1 to 6 are implemented.

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