Travel route planning method and device

Abstract

The invention discloses a tour route planning method and device, and the method comprises the steps: obtaining the search information of a user for a tour demand, displaying the scenic spot information of to-be-recommended scenic spots to the user according to the search information, and determining a target scenic spot which the user is interested in from the to-be-recommended scenic spots. And inputting the search information and first information corresponding to the target scenic spot into a preset artificial intelligence model to obtain a first tour route output by the preset artificial intelligence model, and then adjusting the first tour route according to a preset knowledge base to obtain a second tour route. Namely, the artificial intelligence model can generate the personalized tour route according to the user demand, and meanwhile, the user record information in the preset knowledge base can be referred to when the tour route is recommended, so that the accuracy of the recommended tour route is improved, and the information of the tour route is enriched. Through the mode, the user does not need to spend a lot of time to research the travel strategy, and the travel experience of the user is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of computer processing, in particular to a travel route planning method and device. BACKGROUND

[0002] At present, a user needs to spend a lot of time and energy to plan a travel route before going out. This not only occupies a lot of time, but also may affect the travel experience due to poor planning.

[0003] Therefore, how to quickly obtain a personalized travel route is a technical problem to be solved. SUMMARY

[0004] Therefore, the present application provides a travel route planning method and device to quickly provide a user with an accurate and creative personalized travel route planning and improve the user's travel experience.

[0005] To solve the above problems, the technical scheme provided by the present application is as follows:

[0006] In the first aspect of the present application, a travel route planning method is provided, which comprises:

[0007] In response to search information of a user for travel needs, the method displays scenic spot information of a to-be-recommended scenic spot;

[0008] The method determines a target scenic spot in the to-be-recommended scenic spot that is interesting to the user;

[0009] The method inputs the search information and the scenic spot information of the target scenic spot into a preset artificial intelligence model to output a first travel route;

[0010] The method adjusts the first travel route according to a preset knowledge base to obtain a second travel route; the preset knowledge base records user record information of a visiting user of each preset scenic spot.

[0011] In the second aspect of the present application, a travel route planning device is provided, which comprises:

[0012] A display unit is configured to display scenic spot information of a to-be-recommended scenic spot in response to search information of a user for travel needs;

[0013] A determination unit is configured to determine a target scenic spot in the to-be-recommended scenic spot that is interesting to the user;

[0014] An acquisition unit is further configured to input the search information and the scenic spot information of the target scenic spot into a preset artificial intelligence model to output a first travel route;

[0015] The acquisition unit is further configured to adjust the first travel route according to a preset knowledge base to obtain a second travel route, wherein the preset knowledge base records user record information of users who have visited each preset scenic spot.

[0016] In a third aspect of the present application, an electronic device is provided, comprising: one or more processors; a storage device having one or more programs stored thereon,

[0017] When the one or more programs are executed by the one or more processors, the one or more processors implement the travel route planning method of the first aspect.

[0018] In a fourth aspect of the present application, a computer readable storage medium is provided, having a computer program stored thereon, which, when executed by a processor, implements the travel route planning method of the first aspect.

[0019] In a fifth aspect of the present application, a computer program product is provided, which, when executed on a computer, causes the computer to implement the travel route planning method of the first aspect.

[0020] Therefore, the present application has the following beneficial effects:

[0021] The present application provides a travel route planning method, which responds to the search information of the user for travel needs, displays the scenic spot information of the to-be-recommended scenic spot to the user, and then determines the target scenic spot of interest to the user in the to-be-recommended scenic spot. The search information and the scenic spot information of the target scenic spot are input into a preset artificial intelligence model, and a first travel route is output, that is, the preset artificial intelligence model is used to generate a first travel route that meets the user's travel needs by referring to the search information and the scenic spot information of the target scenic spot. Then, the first travel route is adjusted according to a preset knowledge base to obtain a second travel route. Since the preset knowledge base records user record information of users who have visited each preset scenic spot, the first travel route is adjusted by using the user record information stored in the preset knowledge base, which improves the accuracy of the recommended travel route and enriches the information of the preset scenic spot on the travel route, helping the user to better understand the preset scenic spot.

[0022] It can be seen that, by the technical solution provided by the present application, personalized travel routes can be quickly provided for users based on user needs and real records shared by other users, without the user spending a lot of time researching travel strategies, thereby improving the user's travel experience. BRIEF DESCRIPTION OF DRAWINGS

[0023] Figure 1 A travel route planning method flowchart is provided for the embodiments of the present application;

[0024] Figure 2A travel route planning framework provided for an embodiment of the present application;

[0025] Figure 3 A travel route planning device structure schematic diagram provided for an embodiment of the present application;

[0026] Figure 4 An electronic device structure schematic diagram provided for an embodiment of the present application. DETAILED DESCRIPTION

[0027] In order to make the above-mentioned purposes, features and advantages of the present application more obvious and easy to understand, the embodiments of the present application will be further described in detail below with reference to the drawings and specific embodiments.

[0028] At present, users need to spend a lot of time researching strategies before going out, and many times the complex itinerary planning makes many users step back, affecting the user's travel.

[0029] Based on this, the present application provides a travel route planning scheme, which can quickly provide accurate and creative personalized travel route planning for users based on search information reflecting user travel needs, preset artificial intelligence models and preset knowledge bases and other information, without users spending a lot of time researching strategies, improving the decision-making efficiency before traveling and the user travel experience.

[0030] Specifically, the above-mentioned scheme can be realized through an intelligent tourism service platform. The intelligent tourism service platform has space-time memory capability (corresponding to the preset knowledge base) and AI perception planning capability, and the platform collects a large amount of real experience and marked information shared by users, so that new users can easily refer to the footprints and experiences of others by standing on the shoulders of giants. Then, according to the user's interest and demand (such as the desired destination, the expected play days, etc.), a personalized travel plan is customized.

[0031] The above-mentioned platform will realize the above-mentioned functions based on the Artificial Intelligence Generated Content (AIGC) model and Artificial Intelligence Agent (AI Agent) in artificial intelligence technology.

[0032] Among them, AIGC generates various types of content by using artificial intelligence technology, including text, images, audio and video, etc., which improves work efficiency and reduces cost.

[0033] An AI Agent is an intelligent entity capable of perceiving its environment, making decisions, and executing actions. It is typically based on machine learning and artificial intelligence technologies, possessing autonomy and adaptability, and can learn and improve autonomously in specific tasks or domains. The working principle of an AI Agent mainly includes the following four parts:

[0034] Perception: AI initially establishes its perception of the external world through hardware such as sensors, cameras, and microphones. Inputs: The perceived information is input into the system.

[0035] Information processing (Brain): can be understood as a general large model plus N professional knowledge bases, used to process information.

[0036] Includes the following systems:

[0037] Information storage-related memory systems include storage and memory, used to store long-term and short-term data.

[0038] Knowledge base: It can diagnose the current state and subsequent treatment based on symptoms.

[0039] To facilitate understanding of this application, the technical solution provided in this application will be described in detail below with reference to the accompanying drawings.

[0040] See Figure 1 The figure is a flowchart of a travel route planning method provided in an embodiment of this application, as shown below. Figure 1 As shown, the method includes:

[0041] S101: In response to user search information regarding travel needs, display attraction information for recommended attractions.

[0042] In this embodiment, to provide personalized recommendations based on users' travel needs, search information input by users regarding their travel needs is obtained. This search information can be travel inquiries entered by users through a smart tourism service platform, reflecting their travel requirements. For example, a user might enter "Summer is here, where is a good place to escape the heat?" through the platform.

[0043] In this embodiment, the intelligent tourism service platform can store a large amount of scenic spot information of scenic spots. After obtaining the search information reflecting the user's travel demand, the intelligent tourism service platform screens the to-be-recommended scenic spots that meet the user's travel demand from the large amount of scenic spots stored in the intelligent routing service platform according to the search information, and displays the scenic spot information of the to-be-recommended scenic spots to the user, so that the user can understand the related information of each to-be-recommended scenic spot. The scenic spot information can include images, text introduction and other information of the scenic spot. The image data of the scenic spot can be uploaded by the related personnel of the scenic spot, or can be shared by other users who have visited the scenic spot.

[0044] Specifically, S101 can be implemented in the following way:

[0045] One way is to determine candidate scenic spots based on the search information, delete the visited scenic spots from the candidate scenic spots based on the historical travel data of the user, obtain the to-be-recommended scenic spots, obtain the scenic spot information of the to-be-recommended scenic spots, and display the scenic spot information of the to-be-recommended scenic spots. The historical travel data can be the data of the user's last travel, which includes the identification of the visited scenic spots. When determining the to-be-recommended scenic spots, the user's last traveled scenic spots are removed from the recommended candidate scenic spots according to the historical travel data, and then the remaining candidate scenic spots are used as the to-be-recommended scenic spots.

[0046] Specifically, when displaying the scenic spot information of the to-be-recommended scenic spots to the user, in order to facilitate the user to browse the scenic spot information of each to-be-recommended scenic spot, a video stream can be generated using the scenic spot information of all to-be-recommended scenic spots. In this way, the user can view the scenic spot information of each scenic spot through the video stream without manually switching the scenic spot information of different recommended scenic spots.

[0047] Another way is to screen the to-be-traveled route that meets the user's travel demand from the set of travel routes based on the search information, take the scenic spots on the to-be-traveled route as the to-be-recommended scenic spots, obtain the scenic spot information of the to-be-recommended scenic spots, and display the scenic spot information of the to-be-recommended scenic spots to the user. The set of travel routes is a large number of travel routes of users collected by the intelligent tourism service platform in advance. By collecting in advance, the set of travel routes can search the travel route that matches the user's travel demand from the existing set of travel routes, and take the scenic spots on the travel route as the to-be-recommended scenic spots to achieve fast recommendation.

[0048] S102: Determine the target scenic spot of interest to the user in the to-be-recommended scenic spots.

[0049] After displaying the scenic spot information of the to-be-recommended scenic spots to the user, the target scenic spot of interest to the user can be determined from the multiple recommended scenic spots based on the triggering operation of the user for each recommended scenic spot.

[0050] The operation triggered by the user for the recommended scenic spot includes one or more of a browsing operation, a marking operation, and a deleting operation. Under the browsing operation, browsing data is generated, which can include browsing duration, browsing frequency, and the like. The browsing data can reflect the travel preferences of the user.

[0051] Specifically, when the user views the scenic spot information of the recommended scenic spot, the duration and frequency of the user browsing the scenic spot information of a recommended scenic spot are recorded. The recommended scenic spot corresponding to the scenic spot information with a browsing duration greater than a first preset duration and / or a browsing frequency greater than a first preset frequency is determined as the target scenic spot. And / or, in response to the marking operation triggered by the user for the first information, the recommended scenic spot corresponding to the marked scenic spot information is determined as the target scenic spot. The marking operation reflects the user's preference for the recommended scenic spot corresponding to the scenic spot information. In a specific implementation, the marking operation can be a collection operation triggered by the user for the scenic spot information of a recommended scenic spot, or adding a specific tag to the scenic spot information of a recommended scenic spot to express the user's willingness to go to the recommended scenic spot.

[0052] The browsing frequency refers to the number of times of viewing the scenic spot information corresponding to a recommended scenic spot within a certain period of time. For example, if the user views the image data of scenic spot A 3 times within a day, the browsing frequency is 3. The browsing duration refers to the total time from entering the page corresponding to the scenic spot information to leaving the page when the user views the scenic spot information of a recommended scenic spot. It should be noted that the browsing duration in this embodiment can refer to the maximum browsing duration in multiple browsing within a certain period of time, or the total browsing duration in multiple browsing within a certain period of time, which is not limited in this embodiment as long as the statistical granularity for each recommended scenic spot is the same.

[0053] That is, when the browsing duration of the user for the scenic spot information of a recommended scenic spot is greater than a first preset duration and / or the browsing frequency is greater than a first preset frequency, the recommended scenic spot is considered to be a scenic spot that the user wants to go to, and the scenic spot is taken as a target scenic spot. If there are some recommended scenic spots whose browsing duration is less than the first preset duration or whose browsing frequency is less than the first preset frequency, but the user triggers a marking operation for the scenic spot information of the recommended scenic spot, the marked recommended scenic spot is determined as the target scenic spot. In addition, if there are some recommended scenic spots whose browsing duration is greater than the first preset duration or whose browsing frequency is greater than the first preset frequency, but the user triggers a deleting operation for the scenic spot information of the recommended scenic spot, the recommended scenic spot will not be taken as a target scenic spot. That is, the user can express his / her travel needs through the marking operation.

[0054] S103: input the search information and the scenic spot information of the target scenic spot into a preset artificial intelligence model, and output a first travel route.

[0055] S104: adjusting the first travel route according to a preset knowledge base to obtain a second travel route.

[0056] After the target scenic spot is determined, the search information and the scenic spot information corresponding to the target scenic spot can be input into a preset artificial intelligence model, and the preset artificial intelligence model can intelligently analyze the travel demand of the user based on the input information to generate a first travel route that meets the travel demand of the user. The first travel route can include the travel order of the scenic spots, the travel time of each scenic spot, and the play duration, etc. The preset artificial intelligence model is a model for planning a travel route that is generated by pre-training. The model can be a language model based on deep learning, such as a convolutional neural network (CNN), a long short-term memory (LSTM), etc. Since the intelligent tourism service platform can collect user record information of visited scenic spots recorded by other users, in order to achieve accurate pushing, the first travel route generated will be adjusted according to a preset knowledge base (storing user record information) to obtain a second travel route, so as to display the second travel route to the user.

[0057] Specifically, S104 can be implemented as: for at least one travel scenic spot on the first travel route, obtaining the user record information corresponding to the travel scenic spot from the preset knowledge base; updating the scenic spot information of the travel scenic spot in the first travel route according to the user record information to obtain the second travel route. The scenic spot information of the travel scenic spot in the second travel route includes the user record information, which enriches the scenic spot information of the travel scenic spot and facilitates the user to learn more about the travel scenic spot in advance.

[0058] The preset knowledge base records the user record information of the visiting users of each preset scenic spot. The user record information can include positive evaluation, negative evaluation, recommendation index, etc. of other users for the preset scenic spot. In this way, the platform can adjust the preset scenic spot in the first travel route according to the footprints and / or travel experiences of others to obtain the second travel route. The second travel route can be completely the same as the first travel route, or the second travel route can delete scenic spots or adjust the scenic spot tour order based on the first travel route according to the user record information.

[0059] For example, the preset knowledge base includes user record information of visiting users of attractions 1-attraction N, wherein the first travel route includes attractions 2, 3 and 10. The user record information corresponding to attraction 2 is obtained from the preset knowledge base. If the user record information indicates that it is not recommended to visit attraction 2 in the case of limited play time, attraction 2 can be deleted from the first travel route. If the user record information includes a check-in location recommendation for attraction 2, the check-in location can be added to the attraction information of attraction 2 in the first travel route, so that the user can achieve accurate check-in. The same operation is performed for attractions 3 and 10.

[0060] In general, the preset artificial intelligence model can generate a plurality of first travel routes based on the input information. For each first travel route, the first travel route can be adjusted according to the preset knowledge base to obtain a second travel route, and the plurality of second travel routes can be displayed to the user. The user can select a second travel route as the final travel route.

[0061] In specific implementation, the preset artificial intelligence model can also optimize the first travel route based on information such as weather conditions, traffic conditions, attraction numbers, and attraction opening hours of the destination of each attraction on the first travel route, so as to recommend a better travel route to the user and avoid affecting the user's travel experience due to weather, traffic, etc.

[0062] Specifically, after outputting the first travel route, the method further includes: obtaining a first travel influencing factor of at least one travel attraction in the first travel route in a first time period; if the first travel influencing factor changes relative to a second travel influencing factor corresponding to a second time period, updating the first travel route based on the preset artificial intelligence model and the first travel influencing factor. The second time period is earlier than the first time period, the first travel route is determined based on the second travel influencing factor, and the travel influencing factor includes information such as weather conditions, traffic conditions, attraction numbers, and attraction opening hours of the destination. That is, to ensure that the user can obtain the optimal travel route, the first travel route can also be automatically updated according to the real-time changing data after obtaining the first travel route.

[0063] The first travel route is updated based on the preset artificial intelligence model and the first travel influencing factor, including: inputting the first travel influencing factor and the first travel route into the preset artificial intelligence model, and outputting a third travel route. That is, the preset artificial intelligence model updates the travel destination corresponding to the first travel influencing factor on the first travel route using the first travel influencing factor to obtain the third travel route. The third travel route is changed compared with the first travel route. The change can be that the third travel route does not include the travel destination corresponding to the first travel influencing factor, or the travel time of the travel destination corresponding to the first travel influencing factor on the third travel route is changed compared with the travel time on the first travel route.

[0064] It should be noted that when the third travel route does not include the travel destination corresponding to the first travel influencing factor, the change of the third travel route compared with the first travel route also includes adding other travel destinations in the third travel route to replace the deleted travel destination corresponding to the first travel influencing factor. For example, the outdoor hiking plan on the rainy day is updated to indoor activities to avoid the influence of weather on the travel experience.

[0065] When the travel time of the travel destination corresponding to the first travel influencing factor changes, the change of the third travel route compared with the first travel route also includes that the travel time of other travel destinations on the third travel route also changes compared with the first travel route.

[0066] In this embodiment, the platform determines whether to update the first travel route by judging whether the first travel influencing factor of a travel destination on the first travel route in the first time period and the second travel influencing factor corresponding to the second time period change. Specifically, the platform can obtain the first travel influencing factor of each travel destination on the first travel route in the first time period to determine whether to update the first travel route according to the first travel influencing factor of each travel destination. Alternatively, the platform can obtain the first travel influencing factor of a specific travel destination on the first travel route in the first time period to determine whether to update the first travel route according to the first travel influencing factor of the specific travel destination. The specific travel destination can refer to a travel destination with unpredictable travel influencing factors. In this way, the platform can determine whether to update the first travel route according to the first travel influencing factor of a small number of special travel destinations, reduce the above judgment operation, and improve work efficiency.

[0067] In this embodiment, after generating the first travel route, the platform can periodically obtain the first travel influencing factor of at least one travel attraction in the travel route (the travel route output by the preset artificial intelligence model) within a future time period. For example, after the preset artificial intelligence model outputs the travel route, the first travel influencing factor of at least one travel attraction in the travel route within the next 5 days is obtained every day. Alternatively, the same detection period can be set for each travel attraction in the travel route, or different detection periods can be set for different travel attractions in the travel route. For example, a shorter detection period is set for a travel attraction with frequent weather changes, and a longer detection period is set for a travel attraction with less weather changes.

[0068] Alternatively, when the platform detects that a travel attraction in the travel route has a typical event within a future time period, the first travel influencing factor of the travel attraction at the future time is obtained. The typical event can include severe weather, attraction closure or flow limitation, etc.

[0069] After obtaining the corresponding first travel influencing factor in the first time period, the first travel influencing factor corresponding to the first time period is compared with the second travel influencing factor corresponding to the second time period, and the processing measure can be selected according to the comparison result. For example, if the comparison result reflects that the travel influencing factors of the two time periods are different, the first travel route is updated immediately; or if the travel influencing factors of the two time periods are different and the difference is large, indicating that the user's travel will be greatly affected, the first travel route is updated so that the user can refer to the updated travel route; or if the travel influencing factors of the two time periods are different but the difference is small, indicating that the user's travel is less affected, the first travel route can be selected not to be updated to avoid frequent updates to disturb the user.

[0070] To further improve the user experience, after the second travel route is displayed to the user, the user can also be allowed to adjust the second travel route to obtain a travel route that meets the user's needs. Specifically, in response to the update operation triggered by the user on the second travel route, the second travel route is updated to obtain an updated second travel route. The update operation can include one or more of adding a travel attraction, deleting a travel attraction, and modifying the travel order of a travel attraction in the second travel route. That is, the user can adjust the second travel route, for example, adjust the travel order of the attractions, add attractions, delete attractions, etc., and the platform updates the second travel route according to the adjustment result to obtain a travel route that better meets the user's needs.

[0071] It can be seen that, by this embodiment, the search information and the scenic spots of interest to the user can be obtained, and the accurate and creative personalized travel route planning can be quickly provided for the user based on the above information, and the user no longer needs to spend a lot of time researching the guide. Moreover, the user can also correct the travel route according to the user's own needs, and improve the user experience.

[0072] In some embodiments, in order to further improve the user's travel experience and fully immerse in the trip without worrying about trivial details, a task list and / or a schedule can be determined and displayed based on the second travel route; or, the task list and / or the schedule are determined based on the second travel route, and services are booked for the user based on the task list and / or the schedule. The task list is used to prompt the user to book services, such as booking accommodation, scenic spot tickets, purchasing insurance, and purchasing related materials (medicine, clothes, and other living goods), and the schedule is used to indicate the daily travel route, so that the user can travel according to the schedule without planning the daily travel schedule.

[0073] Specifically, the platform can generate a task list and / or a schedule according to the second travel route, the travel date, and the weather at the destination, to customize the list of items needed for the user's travel. For example, clothing matching the local climate, essential common medicines, etc. In this way, the user only needs to travel according to the travel route indicated by the schedule, without being distracted by planning the daily travel route, improving the travel experience.

[0074] When booking accommodation for the user, historical accommodation information of the user can also be obtained, and the accommodation that meets the user's needs is booked based on the historical accommodation information. The historical accommodation information can include accommodation cost, accommodation type, etc., and the accommodation type can include homestay, hotel, resort, youth hostel, etc.

[0075] After obtaining the second travel route, images taken by the user during the travel can also be obtained, and a travel video is generated based on the images and target scripts. The target scripts are generated based on the content presented by the images. That is, during the trip, the user can upload the images taken during the trip through the platform, and the platform generates related scripts based on the images, and generates interesting videos based on the related scripts and images, to help the user record the story during the trip.

[0076] Or, generate a travel footprint based on the position information corresponding to the image; generate a footprint map based on the image and the travel footprint. Wherein, when the user uses the camera to shoot the image, the shooting time and the shooting location of the image will be recorded, based on which, the position information and the time information of the scenic spots reached by the user can be obtained through the shooting time and the shooting location corresponding to the image, the travel footprint is generated based on the position information, and the scenic spots reached in the travel footprint are sorted based on the time information, and the footprint map is generated according to the sorting result. At the same time, the footprint map can be displayed on the electronic map interface. That is, the embodiment records the unique pattern of the travel route by generating the footprint map. Wherein, the footprint map includes the scenic spot identifier of the scenic spot reached by the user, and the footprint map can be a 2D plane map or a 3D map. For the generated footprint map, the user can trigger a sharing operation to share the footprint map.

[0077] It should be noted that since the user travels according to the second travel route, the generated travel footprint matches the second travel route. Specifically, the matching can mean that the scenic spots in the travel footprint correspond one by one to the scenic spots on the second travel route, or the coincidence degree of the scenic spots in the travel footprint and the scenic spots on the second travel route is greater than a preset threshold, etc.

[0078] After sharing, in response to the user's triggering operation on a scenic spot identifier in the footprint map, the image corresponding to the scenic spot identifier is displayed. That is, through this way, not only the travel trajectory can be shared, but also the image data of each scenic spot in the travel trajectory can be shared, which facilitates other users to understand the characteristics of each scenic spot, and greatly enhances the intuitiveness and interestingness of the transmission of tourism information.

[0079] For the convenience of understanding the overall implementation framework of the present application, refer to Figure 2 the travel route planning framework diagram as shown. As Figure 2 shown, the following processing steps are included:

[0080] 1. The user inputs the search information "summer is coming, want to go on a trip" through the mobile phone client;

[0081] 2. Intelligent recommendation is performed based on the input information of the user, and the scenic spot information of the to-be-recommended scenic spot is displayed to the user, so that the user can mark the recommended scenic spot to obtain the target scenic spot interested by the user;

[0082] 3. The target scenic spot is submitted to the AI Agent module;

[0083] 4. The AI Agent module finds the user record information for the target scenic spot through the memory;

[0084] The memory can store user record information recorded by other users who have visited the scenic spot, so that the stored information is sent to the user when generating a travel route, enabling the user to learn more about the scenic spot.

[0085] 5. The AI Agent module generates a first travel route based on the search information and the scenic spot information of the target scenic spot, and updates the first travel route using the user record information of the target scenic spot found through the memory, to obtain a second travel route, and pushes the second travel route to the user.

[0086] 6. The user selects a target second travel route that meets their own preferences from the pushed second travel routes, and can adjust the target second travel route, to generate a final travel plan based on the user's adjustment.

[0087] 7. The intelligent assistant assists in booking tickets and hotels, and prompts the user to carry daily items according to the weather conditions.

[0088] 8. Through the transaction module, the relevant transactions of the above-mentioned booked tickets and hotels are completed.

[0089] The sound module, video module, 2D module, 3D module, and text module can help the user record points and events, generate interesting pictures and related texts, and generate (2D or 3D) footprint maps in combination with the user's footprint during the user's journey.

[0090] Specifically, each of the above modules realizes its respective function by calling the corresponding model in the model layer and reading the corresponding data from the data layer. The model layer includes a language model (LM), a stable diffusion (SD) model, a sound large model, a lip shape large model, etc. The data layer can include a vector database and a relational database (RDB), through which data related to travel can be stored. The SD model is a text-to-image generation model based on deep learning.

[0091] As can be seen, the above service platform uses advanced algorithm models to output a travel route based on user needs (such as desired destination, expected number of play days, etc.), and reference to other user footprints and experiences. At the same time, after generating the travel route, it also has a thoughtful full-process service function, including booking tickets for scenic spots along the way in advance, selecting suitable hotel accommodations, and customizing a detailed list of travel items for the user, such as clothing matching for local climate, essential common medicines, etc., striving to achieve seamless connection from planning to execution, enabling the user to fully immerse themselves in the beauty of the journey without worrying about trivial details.

[0092] Further, automatically update and adjust the travel plan according to real-time changing data (such as weather conditions), to ensure that the user obtains the latest optimal travel suggestion.

[0093] In addition, during the journey, by acquiring the images taken by the user, a short video with attractive tourist attractions is generated, greatly enhancing the intuitiveness and interest of the tourism information transmission.

[0094] Based on the above method embodiment, the application embodiment provides a travel route planning device and electronic equipment, which will be described below with reference to the accompanying drawings.

[0095] Referring to Figure 3 , the figure is a structure diagram of a travel route planning device provided by the application embodiment, as Figure 3 shown, the device 300 includes a display unit 301, a determination unit 302, and an acquisition unit 303.

[0096] The display unit 301 is configured to display the scenic spot information of the to-be-recommended scenic spot in response to the user's search information for travel needs;

[0097] The determination unit 302 is configured to determine a target scenic spot of interest to the user in the to-be-recommended scenic spot;

[0098] The acquisition unit 303 is configured to input the search information and the scenic spot information of the target scenic spot into a preset artificial intelligence model, and output a first travel route;

[0099] The acquisition unit 303 is further configured to adjust the first travel route according to a preset knowledge base to obtain a second travel route; the preset knowledge base records user record information of users visiting each preset scenic spot.

[0100] In a possible implementation, the device further includes an update unit.

[0101] The update unit is configured to, after outputting the first travel route, acquire a first travel influencing factor of at least one travel scenic spot in the first travel route within a first time period; if the first travel influencing factor changes relative to a second travel influencing factor corresponding to a second time period, update the first travel route based on the preset artificial intelligence model and the first travel influencing factor; wherein the second time period is earlier than the first time period, and the first travel route is determined based on the second travel influencing factor.

[0102] In a possible implementation, the update unit is specifically configured to input the first travel influencing factor and the first travel route into the preset artificial intelligence model, output a third travel route, and the third travel route changes compared with the first travel route.

[0103] In a possible implementation, the acquisition unit 303 is specifically configured to: acquire, from the preset knowledge base, user record information corresponding to at least one travel scenic spot on the first travel route; and update scenic spot information of the travel scenic spot in the first travel route according to the user record information, to obtain a second travel route, wherein the scenic spot information of the travel scenic spot in the second travel route includes the user record information.

[0104] In a possible implementation, the determination unit 302 is further configured to: after obtaining the second travel route, determine and display a task list and / or a schedule based on the second travel route; or determine a task list and / or a schedule based on the second travel route, and reserve a service for the user based on the task list and / or the schedule.

[0105] The task list is used to prompt the user to reserve a service, and the schedule is used to indicate a daily travel route.

[0106] In a possible implementation, the determination unit 302 is specifically configured to: acquire browsing data of the user for the scenic spot information, the browsing data including a browsing duration and / or a browsing frequency; determine a scenic spot with a browsing duration greater than a first preset duration and / or a browsing frequency greater than a first preset frequency as a target scenic spot; and / or, in response to a marking operation triggered by the user for the scenic spot information, determine a scenic spot corresponding to marked scenic spot information as a target scenic spot.

[0107] In a possible implementation, the display unit 301 is specifically configured to: determine a candidate scenic spot based on the search information; delete a visited scenic spot from the candidate scenic spot based on historical travel data of the user, to obtain a to-be-recommended scenic spot; acquire scenic spot information of the to-be-recommended scenic spot, and display the scenic spot information of the to-be-recommended scenic spot.

[0108] In a possible implementation, the apparatus further includes an update unit.

[0109] The update unit is specifically configured to: after displaying the second travel route to the user, in response to an update operation triggered by the user for the second travel route, update the second travel route to obtain an updated second travel route.

[0110] The update operation includes one or more of the following:

[0111] adding and / or deleting at least one travel scenic spot in the second travel route;

[0112] modify a travel order of at least one travel spot in the second travel route.

[0113] In a possible implementation, the apparatus further includes a generating unit.

[0114] The generating unit is configured to, after obtaining the second travel route, acquire an image captured by the user during the travel; generate a travel video based on the image and a target script, the target script being generated based on content presented by the image; or generate a travel footprint corresponding to the user based on position information of the image, the travel footprint matching the second travel route; and generate a footprint map based on the image and the travel footprint, the footprint map including a spot identifier of a spot visited by the user.

[0115] The specific implementation of each unit in the above embodiments can be referred to the related description in the method embodiments, and will not be described here again in this embodiment.

[0116] Based on the travel route planning method provided in the above method embodiments, the present application further provides an electronic device, including one or more processors; a storage device having one or more programs stored thereon, when the one or more programs are executed by the one or more processors, the one or more processors implement the travel route planning method described in any of the above embodiments.

[0117] Reference will be made to the following description of the embodiments of the present application. Figure 4 which shows a structural schematic diagram of an electronic device 400 suitable for implementing the embodiments of the present application. The terminal device in the embodiments of the present application can include but is not limited to mobile terminals such as mobile phones, notebook computers, digital broadcast receivers, PDAs (Personal Digital Assistant, personal digital assistants), PADs (portable android devices, tablet computers), PMPs (Portable Media Player, portable multimedia players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), and the like, as well as fixed terminals such as digital TVs, desktop computers, and the like. Figure 4 The electronic device shown is only an example, and should not bring any limitation to the functions and use range of the embodiments of the present application.

[0118] As Figure 4As shown, the electronic device 400 can include a processing device (e.g., a central processing unit, a graphics processing unit, etc.) 401 that can perform various appropriate actions and processes according to programs stored in a read-only memory (ROM) 402 or loaded into a random access memory (RAM) 403 from a storage device 408. Various programs and data required for the operation of the electronic device 400 are also stored in the RAM 403. The processing device 401, the ROM 402, and the RAM 403 are connected to each other through a bus 404. An input / output (I / O) interface 405 is also connected to the bus 404.

[0119] Generally, the following devices can be connected to the I / O interface 405: input devices 406 including, for example, a touch screen, a touch pad, a keyboard, a mouse, a camera, a microphone, an accelerometer, a gyroscope, etc.; output devices 407 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; storage devices 408 including, for example, a magnetic tape, a hard disk, etc.; and communication devices 409. The communication devices 409 can allow the electronic device 400 to communicate wirelessly or wired with other devices to exchange data. Although Figure 4 The electronic device 400 is shown with various devices, but it should be understood that not all of the shown devices are required to be implemented or present. More or fewer devices can alternatively be implemented or present.

[0120] In particular, the processes described above with reference to the flowcharts can be implemented as a computer software program according to embodiments of the present application. For example, embodiments of the present application include a computer program product comprising a computer program carried on a non-transitory computer readable medium, the computer program containing program code for performing the methods illustrated by the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network through the communication devices 409, or installed from the storage devices 408, or installed from the ROM 402. When the computer program is executed by the processing device 401, the above-mentioned functions defined in the methods of embodiments of the present application are performed.

[0121] The electronic device provided by embodiments of the present application and the travel route planning method provided by the above embodiments belong to the same inventive concept, and technical details not described in detail in the present embodiments can be referred to the above embodiments, and the present embodiments have the same beneficial effects as the above embodiments.

[0122] Based on the travel route planning method provided by the above method embodiments, the present embodiments provide a computer readable medium having a computer program stored thereon, wherein the program is executed by a processor to implement the travel route planning method according to any of the above embodiments.

[0123] It should be noted that the computer readable medium in the present application can be a computer readable signal medium or a computer readable storage medium or any combination of the two. The computer readable storage medium may, for example, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or apparatus, or any combination of the above. More specific examples of the computer readable storage medium can include, but are not limited to, an electrical connection having one or more wires, a portable computer diskette, 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 disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, the computer readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, device or apparatus. In the present application, the computer readable signal medium can include a data signal carried in a baseband or as a part of a carrier wave, which carries computer readable program code. Such a propagated data signal can take various forms, including but not limited to an electromagnetic signal, an optical signal or any suitable combination of the above. The computer readable signal medium can also be any computer readable medium other than the computer readable storage medium that can send, propagate or transmit the program for use by or in connection with an instruction execution system, device or apparatus. The program code contained in the computer readable medium can be transmitted by any suitable medium, including but not limited to a wire, a cable, a RF (radio frequency) or the like, or any suitable combination of the above.

[0124] In some embodiments, the client, server, or both can communicate using any current known or future developed network protocol, such as HTTP (Hyper Text Transfer Protocol), and can be interconnected with any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include local area networks ("LAN"), wide area networks ("WAN"), the Internet, and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any current known or future developed networks.

[0125] The computer readable medium described above can be included in the electronic device described above; or can exist separately from the electronic device and not be assembled into the electronic device.

[0126] The computer readable medium described above carries one or more programs, which when executed by the electronic device, cause the electronic device to perform the travel route planning method described above.

[0127] Computer program code for carrying out operations of the present application can be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C++ or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code can execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, 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 the connection can be made to an external computer (for example, through the Internet using an Internet Service Provider).

[0128] The computer program instructions can also be loaded onto a computer or other programmable information processing apparatus to cause a series of operations to be performed on the computer or other programmable information processing apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable information processing apparatus implement the functions / acts specified in the flowchart and / or block diagram block or blocks.

[0129] The units involved in the embodiments described in the present application can be implemented by software or by hardware. Among them, the name of the unit / module does not constitute a limitation to the unit itself in some cases. For example, the voice data acquisition module can also be described as a "data acquisition module".

[0130] The functions described above in the embodiments of the present application can be performed at least in part by one or more hardware logic components. For example, non-limiting examples of exemplary types of hardware logic components that can be used include field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), system on a chip (SOCs), complex programmable logic devices (CPLDs), etc.

[0131] In the context of this application, a machine-readable medium can be a tangible medium that contains or stores a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can include but is not limited to an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of the machine-readable storage medium will include one or more lines of electrical connections, portable computer disks, hard disk drives, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or Flash memory), optical fibers, portable compact disc read-only memories (CD-ROMs), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0132] It should be noted that the various embodiments described in this specification are progressive in nature, and each embodiment highlights the differences from other embodiments. The same or similar parts between embodiments can be mutually referred to. For the system or device disclosed in the embodiments, since it corresponds to the method disclosed in the embodiments, the description is relatively simple, and the relevant parts can be referred to the description of the method.

[0133] It should be understood that in this application, "at least one" means one or more, and "multiple" means two or more. "And / or" is used to describe the association relationship between the associated objects, which means that there can be three relationships, for example, "A and / or B" can represent: only A, only B, and A and B exist at the same time, where A and B can be singular or plural. The character " / " generally represents that the associated objects before and after are in an "or" relationship. "At least one of the following" or similar expressions means any combination of these items, including any combination of single or multiple items. For example, at least one of a, b or c can represent: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, and c can be single or multiple.

[0134] It is also to be noted that, as used in the specification and the appended claims, the singular forms "a," "an" and "the" include plural referents unless otherwise indicated. Furthermore, to the extent that the terms "including," "includes," "having," "has," "with," or "contains" are used in either the detailed description and the claims, such terms are intended to be inclusive in a manner similar to the term "comprising" as an open transition term without precluding any additional or other elements.

[0135] The embodiments disclosed herein can each be implemented as a method, apparatus, or article of manufacture using programming instructions. The embodiments disclosed herein can be implemented using software, firmware, hardware, or a combination thereof. The various elements of the disclosed embodiments, as well as the procedural aspects of the disclosed embodiments, can be implemented using a variety of programming instructions, software, firmware, or other programming instructions. In one embodiment, programming instructions are distributed via a computer medium, such as a compact disc, diskette, tape, file, or other computer medium. In another embodiment, programming instructions are downloaded into a computer from a network connection, such as the Internet, a local area network, a wide area network, or other network connection.

[0136] The above description of disclosed embodiments provides enough information to enable those with ordinary skill in the art to make and use the application. Various modifications to these embodiments will be readily apparent to those with ordinary skill in the art, and the generic principles defined herein can be applied to other embodiments without departing from the spirit or scope of the application. Accordingly, the application is not to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for planning travel routes, characterized in that, The method includes: In response to users' search information regarding their travel needs, display attraction information for recommended destinations; Identify the target attractions that the user is interested in from the list of attractions to be recommended; The search information and the attraction information of the target attraction are input into a preset artificial intelligence model, and a first travel route is output. The first travel route is adjusted according to a preset knowledge base to obtain a second travel route; the preset knowledge base contains user record information of users who have visited each preset scenic spot.

2. The method according to claim 1, characterized in that, After outputting the first travel route, the method further includes: Obtain the first travel influencing factor for at least one tourist attraction on the first travel route within the first time period; If the first travel influencing factor changes relative to the second travel influencing factor in the second time period, the first travel route is updated based on the preset artificial intelligence model and the first travel influencing factor. The second time period is earlier than the first time period, and the first travel route is determined based on the second travel influencing factor.

3. The method according to claim 2, characterized in that, The step of updating the first travel route based on the preset artificial intelligence model and the first travel influencing factors includes: The first travel influencing factor and the first travel route are input into the preset artificial intelligence model, and a third travel route is output, which is different from the first travel route.

4. The method according to claim 1, characterized in that, The step of adjusting the first travel route based on a preset knowledge base to obtain a second travel route includes: For at least one tourist attraction on the first travel route, retrieve the user record information corresponding to the tourist attraction from the preset knowledge base; The attraction information of the tourist attractions in the first travel route is updated based on the user record information to obtain a second travel route. The attraction information of the tourist attractions in the second travel route includes the user record information.

5. The method according to claim 1, characterized in that, After obtaining the second travel route, the method further includes: Based on the second travel route, determine and display a task list and / or schedule; or... A task list and / or schedule are determined based on the second travel route, and services are booked for the user based on the task list and / or the schedule; The task list is used to prompt the user to book services, and the schedule is used to indicate daily travel routes.

6. The method according to claim 1, characterized in that, The process of determining the target attractions that the user is interested in from the list of attractions to be recommended includes: Obtain the user's browsing data regarding the attraction information, the browsing data including browsing duration and / or browsing frequency; Recommended attractions whose browsing duration is greater than a first preset duration and / or whose browsing frequency is greater than a first preset frequency are identified as target attractions; And / or, In response to the user's marking operation on the attraction information, the attraction to be recommended corresponding to the marked attraction information is determined as the target attraction.

7. The method according to claim 1, characterized in that, The method of responding to a user's search information regarding travel needs and displaying attraction information for recommended destinations includes: Candidate attractions are determined based on the search information; Based on the user's historical travel data, deleted visited attractions from the candidate attractions and obtained attractions to be recommended. Obtain the attraction information of the attraction to be recommended, and display the attraction information of the attraction to be recommended.

8. The method according to claim 1, characterized in that, After showing the second travel route to the user, the method further includes: In response to the user's update operation triggered for the second travel route, the second travel route is updated to obtain the updated second travel route; The update operation includes one or more of the following: Add and / or delete at least one tourist attraction in the second travel route; Modify the order of at least one tourist attraction in the second travel route.

9. The method according to claim 1, characterized in that, After obtaining the second travel route, the method further includes: Acquire images taken by the user during their trip; A travel video is generated based on the image and the target text; the target text is generated based on the content presented in the image; or, the user's travel footprint is generated based on the location information of the image, and the travel footprint matches the second travel route; a footprint map is generated based on the image and the travel footprint, and the footprint map includes the attraction identifiers of the attractions visited by the user.

10. A travel route planning device, characterized in that, The device includes: The display unit is used to respond to users' search information regarding their travel needs and to display information about the attractions to be recommended. The determination unit is used to identify target attractions that the user is interested in from the attractions to be recommended. The acquisition unit is also used to input the search information and the attraction information of the target attraction into a preset artificial intelligence model and output a first travel route; The acquisition unit is further configured to adjust the first travel route according to a preset knowledge base to obtain a second travel route; the preset knowledge base contains user record information of users who have visited each preset scenic spot.

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