18 results about "Itinerary planning" patented technology

The embodiment of the invention provides an interaction method and device for route planning, equipment and a storage medium. The method comprises the following steps: acquiring user input associated with a travel task for a target application, wherein the user input comprises one or more travel requests for the travel task; invoking at least one travel reservation function by providing the user input to the large model, wherein the at least one travel reservation function is determined by the large model based on one or more parameters included in travel information associated with the travel task parsed from the user input. And in a session interface of the target application, presenting an itinerary planning result for the one or more travel requests, the itinerary planning result being generated by calling at least one itinerary reservation function to process the travel task. Through the process, the efficiency of route planning is improved.

The invention relates to an itinerary planning method and a vehicle-mounted system. The method comprises the following steps: when a multi-day journey planning request of a vehicle user is received, performing journey planning according to the multi-day journey planning request, generating a multi-day journey framework, acquiring target detailed journey content associated with a task of a daily journey, and filling the journey framework of the daily journey according to the target detailed journey content to obtain a multi-day journey framework; and generating an itinerary planning result of the multi-day itinerary planning request. Wherein the multi-day travel framework comprises a task of a daily travel and a travel framework. According to the route planning method, complex tasks are decomposed, and the planning capability and the success rate for complex schedule planning are improved. And moreover, the decomposed daily schedule planning tasks can be executed in parallel, so that the processing efficiency for complex schedule planning is greatly improved.

The invention discloses an AI-based personalized travel itinerary planning method and system, and electronic equipment, relates to the technical field of travel service, and aims to solve the problem of low accuracy and safety of itinerary planning. The method comprises the steps of obtaining cross-scene user behavior data including historical travel data, historical search data and social culture data, wherein the social culture data is used for indicating culture preference content published by a user on a social media platform; extracting feature vectors used for representing user interests and preferences from the cross-scene user behavior data; a dynamic risk score is predicted based on the response timeliness of a current risk event and a historical risk event including weather changes, traffic conditions and scenic spot people streams, the current risk event is an event affecting the trip feasibility, and the risk type of the current risk event is the same as that of the historical risk event; and fusing the feature vector and the dynamic risk score, and generating a personalized travel plan at least comprising destination information, traffic information and accommodation information.

This application relates to a trip planning method, apparatus, computer device, storage medium, and program product. The method includes: displaying a map page of the current trip; when a user leaves a target area, displaying a resource record entry on the map page; the target area is an area where resource expenditure can be triggered, and the resource record entry is used to input the amount of resource expenditure for this trip; adjusting the remaining trip amount based on the current remaining resources determined by the current resource expenditure amount, and displaying the adjusted trip. This method can improve trip planning speed.

The embodiment of the invention provides an interaction method and device for route planning, equipment and a storage medium. The method includes providing a user input associated with a travel task received in a target application to the large model. Obtaining a target itinerary planning result matched with the user input from the large model, the target itinerary planning result being determined from a plurality of candidate itinerary planning results based on the determined preference attribute of the user corresponding to the user input, the plurality of candidate travel planning results are generated at least according to travel modes between adjacent travel nodes, and the travel nodes comprise a travel starting point, a travel ending point and at least one intermediate node between the travel starting point and the travel ending point which are determined based on user input. And presenting the target journey planning result. Therefore, the efficiency of route planning is improved.

1. The name of the design product: AI travel planning graphical user interface of electronic device. 2. The use of the design product: an electronic device. 3. The design points of the design product: in the graphical user interface. 4. The picture or photo that best indicates the design points: front view. 5. The use of the graphical user interface: for displaying information and running programs, supporting manual selection of locations and generating travel routes using AI. 6. The change state of the graphical user interface: click the "AI travel planning" button in the middle area of the front view, enter interface change state figure 1; click the "+" button in the right area and the wish list icon button in the lower left area of interface change state figure 1, enter interface change state figure 2; select part of the route in interface change state figure 2 and click the "AI generated route" button, enter interface change state figure 3; click "generate result preview" in the bottom area of interface change state figure 3, enter interface change state figure 4; click the "confirm" button in the bottom area of interface change state figure 4, enter interface change state figure 5. The "X" and "copy" in the interface represent variable characters, and the single gray block represents the content screen.

The embodiment of the invention provides a task scheduling method and device for itinerary planning, a storage medium and a program product. In the scheme, firstly, based on multi-modal demand semantics, a system is enabled to adaptively identify an internal structure of a travel task, global complexity, real-time performance and a privacy level are intelligently mapped to a subtask level, and a'global demand-subtask constraint-end-edge-cloud node scheduling 'parameterized control link is formed; secondly, the reinforcement learning optimizer can dynamically adjust the scheduling weight, and strategy self-adaptive evolution is achieved. Furthermore, an execution-monitoring-feedback-rescheduling closed-loop system can be constructed, intelligent degradation and context snapshot migration are triggered when the node state deviates, seamless connection and continuous execution of a task chain among cross-hierarchy heterogeneous nodes are ensured, and finally, quick response is realized on the premise of ensuring the accuracy of a recommendation result of the travel information, so that the recommendation efficiency of the travel information is improved. And the system performance and the user experience can be balanced.

1. The name of the design product: the journey planning graphical user interface of an electronic device. 2. The use of the design product: an electronic device. 3. The design points of the design product: the graphical user interface. 4. The picture or photo that best indicates the design points: the front view. 5. The use of the graphical user interface: click the "login / register" button in the front view and log in to the account, enter the interface change state diagram 1; slide up the interface change state diagram 1, enter the interface change state diagram 2. The "X" and gray blocks in the front view, interface change state diagram 1 and interface change state diagram 2 are content screens. The front view reference diagram is the reference diagram of the front view, and the interface change state reference diagrams 1 and 2 are the reference diagrams of the interface change state diagrams 1 and 2 respectively.

The invention provides an itinerary planning method and device, electronic equipment, a storage medium and a program product, and relates to the technical field of machine learning, the method comprises the steps that user demand description and a large language model are acquired, and the large language model comprises an intention recognition sub-model, a candidate position retrieval sub-model and an itinerary planning sub-model; inputting the user demand description into an intention recognition sub-model for intention recognition, and obtaining a user travel intention corresponding to the user demand description; inputting a display demand and an implicit demand in the travel intention of the user into a candidate position retrieval sub-model for position retrieval, and obtaining a destination corresponding to the travel intention of the user and a candidate address list corresponding to the destination; and inputting the display demand, the implicit demand, the destination and the candidate address list into the itinerary planning sub-model for itinerary planning, and outputting itinerary planning information matched with the travel intention of the user, thereby automatically processing user demand description and itinerary planning, reducing time and cost of manual planning, and improving service efficiency.

The invention relates to the technical field of itinerary planning, and discloses an itinerary planning system based on a large model, and the system comprises a non-autonomous behavior recognition and preference purification module which outputs a purified behavior sequence reflecting the real preference of a user; the dynamic user state characterization module is used for mapping high-dimensional heterogeneous user features to a low-dimensional continuous potential space; the enhanced user portrait construction module is used for integrating regional culture priori knowledge and external ecological behavior signals; the system further comprises a travel generation and multi-constraint feasibility verification module based on a large model and a travel scheme interactive optimization and user feedback closed loop module. According to the scheme, the authenticity and feasibility of itinerary planning are improved, the accuracy of user portraits is enhanced by purifying non-autonomous behavior data, the recommendation adaptability is improved by fusing regional culture and external interest signals, dynamic budget and real-time resource verification are combined to guarantee that the scheme is executable, user interaction optimization and feedback closed loop are supported, and the user experience is improved. And personalized, practical and participatable intelligent travel service is realized.

The present disclosure provides a trip planning method and device, electronic equipment and storage medium, the trip planning method comprises: obtaining target trip information of a client; the target trip information comprises a trip departure location and a trip departure time; based on the target trip information, determining trip planning information of the client; the trip planning information comprises a car departure location and a car departure time; based on the trip planning information, generating car suggestion information. According to the embodiment of the present application, the corresponding car suggestion information can be automatically generated based on the target trip information of the client, the certainty of business travel is improved, and the client experience is enhanced.

The application discloses a tourism route planning method based on artificial intelligence and belongs to the technical field of route planning, and specifically comprises the following steps: obtaining historical route sequences of a group and corresponding route evaluation data, and constructing a route-evaluation mapping library; identifying a specific scenic spot based on the mapping library and extracting common behavior deviation characteristic values of a user after visiting the scenic spot; clustering the behavior characteristic values to obtain behavior characteristic clusters, and screening out subsequent scenic spots that bring higher experience feedback to each behavior characteristic cluster through statistical testing to form an association rule library; generating an initial route plan according to a current user request and the rule library; in the execution of the route, determining the deviation category to which the user belongs according to real-time collected user behavior data, querying the rule library according to the category to obtain an experience optimization decision set, and dynamically adjusting the remaining route. The application realizes the change from static resource matching to dynamic experience management, and effectively improves the personalization and satisfaction of tourism route planning.

The present application mainly relates to a personalized travel itinerary planning and management method, comprising the following steps: establishing travel itinerary time axis data; adding travel node data to the travel itinerary time axis data; adding node attribute data to each travel node data; adding node content data to each travel node data; booking the content items involved in the content item data; and marking the node content data after implementing the content items in the previous step. The present application enables users to plan and manage travel according to their personalized needs, and users can comprehensively plan and book travel through a single unified visual operation system during the travel planning and management process, and can also intuitively and concisely understand the relevant plan data and travel booking status of each link in the travel.

The invention discloses a travel itinerary planning method based on artificial intelligence, and belongs to the technical field of itinerary planning, and the method specifically comprises the steps: obtaining a historical itinerary sequence of a group and corresponding itinerary evaluation data, and constructing an itinerary-evaluation mapping library; identifying a specific scenic spot based on the mapping library, and extracting a cosexual behavior offset feature value after the user accesses the scenic spot; clustering is carried out according to the feature values to obtain behavior feature clusters, and subsequent scenic spots which bring higher experience feedback to the behavior feature clusters are screened out through statistical test to form an association rule base; generating an initial itinerary plan according to a current user request and the rule base; and in the travel execution process, the offset category of the travel is judged according to user behavior data collected in real time, the rule base is inquired according to the category to obtain an experience optimization decision set, and the remaining travel is dynamically adjusted. According to the invention, the transformation from static resource matching to dynamic experience management is realized, and the individuation and satisfaction of travel itinerary planning are effectively improved.

This invention discloses a multimodal cultural tourism knowledge retrieval enhancement method and an intelligent agent itinerary planning method based on a large language model. The retrieval enhancement method includes step S201, constructing a multimodal cultural tourism knowledge base, which includes travel product data, scenic spot real-time information, scenic area activity information, traffic and weather dynamic data, and tourist evaluation feedback information; step S202, constructing a retrieval enhancement framework based on a RESTful API interface and the MCP protocol; and step S203, using the retrieval enhancement framework to retrieve real-time cultural tourism data from the multimodal cultural tourism knowledge base. This invention, through a multimodal knowledge base and a dual-protocol retrieval framework, achieves real-time integration and related retrieval of scattered data, solving the problem of fragmented cultural tourism information and ensuring information timeliness.

The embodiment of the invention discloses a service interaction method, a method for realizing itinerary planning and a corresponding device. The service interaction method comprises the following steps: acquiring travel route planning description input by a user through a session interface; displaying state information of a plurality of stage tasks in the process of generating the itinerary planning document on the session interface, the plurality of stage tasks at least comprise a first stage task for analyzing the itinerary planning description to obtain constraint conditions of multiple dimensions; searching based on the constraint condition to obtain a second-stage task of service data corresponding to a plurality of itinerary elements, and generating a third-stage task of itinerary planning documents meeting the constraint condition based on the service data; and obtaining and displaying the itinerary planning document on the session interface. The itinerary planning document can be automatically generated based on the itinerary planning description input by the user, and the transparency and experience of the user interaction process are improved.

The invention relates to the technical field of travel itinerary automatic scheduling and optimization based on constrained programming, in particular to a travel itinerary intelligent scheduling method and system for multiple scenic spots of a travel destination. The method comprises the following steps: firstly, constructing a refined data model comprising scenic spot multi-entrance nodes, traffic cost, user preferences and time constraints; a scenic spot candidate set is obtained through ticket filtering and priority ranking preprocessing; then, a constraint planning theory is adopted to carry out deterministic solution on the multi-day journey, the open time window, multi-entrance mutual exclusion and secondary entrance complex reality constraint of the scenic spot are strictly processed, and the performability and stability of the solution are ensured; and finally, outputting an optimal travel plan according to a multi-target strategy. According to the invention, efficient and reliable intelligent journey planning meeting actual requirements is realized.

This specification provides a method and apparatus for displaying itineraries, a computing device, and a computer-readable storage medium. The method includes: displaying a itinerary point addition page; responding to an itinerary point addition operation on the itinerary point addition page, determining the end point of a first itinerary day and the start point of a second itinerary day as adjacent itinerary points, and displaying a itinerary details page. The first itinerary day and the second itinerary day are two itinerary days with sequentially adjacent itinerary times among multiple itinerary days. The itinerary details page includes information on each itinerary point in the multiple itinerary days and itinerary information between adjacent itinerary points. This method can improve itinerary planning effectiveness.