40 results about "Itinerary planning" patented technology

The invention provides a business travel management system and method, and relates to the technical field of enterprise management, a route is planned through an itinerary planning module, business trips are on business according to the planned route, and the business trips are positioned through a positioning module; the method comprises the following steps: acquiring positioning information of a business tripper through a trajectory analysis module, acquiring a trajectory of the business tripper according to the positioning information, analyzing a staying place and time corresponding to the staying place, and acquiring a consumption level of the staying place; a business tripper reports a bill, the bill reported by the business tripper is received through a fee auditing module, the bill place, the bill time and the bill amount are identified, the bill place, the bill time and the bill amount are compared with the staying place, the time corresponding to the staying place and the consumption level of the staying place, and the abnormal bill is marked. The business travel management system solves the problem that existing business travel management is time-consuming and labor-consuming, and is suitable for business travel management of enterprises.

The invention provides an itinerary planning method, device and equipment for a specific crowd and a medium, and the method comprises the steps: firstly obtaining the health condition of the specific crowd and itinerary information containing a plurality of itinerary points, obtaining the current itinerary point in real time after a user starts the itinerary, calculating and updating the health condition by means of intelligent wearable equipment, and if the health condition does not meet a preset requirement, executing the step 2; the travel information is adjusted, the adjustment comprises at least one operation of travel point sequence adjustment, travel point addition and deletion and single-point travel plan modification, and finally the adjusted travel is displayed through a human-computer interaction interface in a graphic identification, text prompt or information comparison mode; the travel can be flexibly adjusted according to the health condition of the specific crowd, the adjustment result is presented in a visual mode, and double guarantees are provided for travel safety and personalized experience.

In order to solve the problems of low resource utilization efficiency and insufficient personalized service in the prior art, the invention discloses an itinerary planning method, system, equipment and medium based on a guided local search algorithm, and relates to the technical field of big data analysis and artificial intelligence, and the method comprises the steps: obtaining and preprocessing scenic spot data and traffic data; filling a playing list based on the scenic spots selected by the tourists, the scenic spot data and the traffic data; and planning a travel for the travel list based on a guided local search algorithm. Multi-source data including scenic spot opening and closing time, recommended travel duration, geographic position, scenic spot labels and the like are integrated, real-time analysis and intelligent decision are performed by applying an advanced artificial intelligence technology, high-quality travel recommendation service is provided for tourists, personalized requirements of the tourists can be met, the utilization efficiency of tourism resources can be improved, and the tourism experience of the tourists can be improved. Efficient sharing and intelligent analysis of tourism information are realized, and powerful support is provided for tourism decision making.

The invention provides a multi-destination travel itinerary planning method, system and device and a storage medium. The method comprises the following steps: receiving a travel planning request of a user; based on keywords in the tourism planning request, matching a plurality of related scenic spots and tourism destination cities to which the scenic spots belong; at least according to the traffic information between the tourism destination cities, generating a tourism sequence based on the tourism destination city playing sequence, inter-city traffic planning between the tourism destination cities and tourism sub-planning of each tourism destination city, and obtaining daily tourism tracks, daily accommodation hotels and scenic spot routes; and generating a travel itinerary plan according to the daily travel track, the scenic spot itinerary, the daily accommodation hotel and the inter-city traffic plan, and feeding back the travel itinerary plan to the user. According to the invention, travel, accommodation and travel time arrangement and route planning schemes in the travel itinerary of the user can be finely designed, the travel time cost of the user is reduced, and the experience in the travel itinerary is improved.

The invention discloses an air travel plan and service customization system, and particularly relates to the technical field of big data, the air travel plan and service customization system comprises a user terminal module, an intelligent travel planning engine and a service integration platform, and the user terminal module is connected to the intelligent travel planning engine and the service integration platform through the Internet. A travel demand and a current position of a user are obtained through a travel preference input module and a positioning module of a user terminal module, a dynamic scheme is generated in combination with a flight dynamic database, a hotel resource pool and a scenic spot ticket API under an intelligent travel planning engine, and after the user confirms a travel, the travel demand and the current position of the user are obtained. The service integration platform synchronously books air tickets and hotels and generates electronic certificates, when flights are delayed, alternative traffic scheme calculation is automatically triggered, travel nodes are dynamically connected to map navigation service, and the travel state of a user is updated in real time.

The invention relates to the technical field of computers, in particular to a tourism service intelligent recommendation management system and method based on artificial intelligence, in the system, a demand adaptation recommendation module generates a tourism spot travel planning route adaptation result of a user based on a to-be-executed travel planning scenic spot deviation sequence and a travel execution feature set; and extracting dining planning information in the travel route planning route of the scenic spot of the user, locking a dining adaptive area of the user, and generating a space-time matching set of the travel route and the dining reservation. According to the method, user behavior preference characteristics are analyzed in combination with behavior density space-time distribution data of each scenic spot; therefore, the stay behavior vector feature information of the user in the travel planning route of each scenic spot in the to-be-executed travel planning scenic spot deviation sequence is obtained, and data support is provided for the subsequent dynamic generation of the travel spot travel planning route adaptation result of the user and the space-time matching set of the travel route and catering reservation.

The invention is suitable for the technical field of itinerary recommendation, and provides a collaborative recommendation method and system for a tourist self-created itinerary and an official selected itinerary, and the method comprises the steps: obtaining behavior data of the user self-created itinerary, multi-dimensional evaluation data of the official selected itinerary, and environment context data; the user interest matching degree is calculated according to the behavior data, a travel freedom degree index is generated based on modification frequency, cooperation modes are analyzed and determined through preset conditions in combination with the environment context data, and the cooperation modes comprise a user dominant mode, an official dominant mode, a balanced cooperation mode, a theme guide mode and a real-time emergency mode; according to the cooperation mode, a corresponding recommendation strategy is adopted to adjust a user self-created journey; and generating an optimized journey scheme, carrying out visual display, and updating user data and an official data source. According to the invention, efficient cooperation of diversified travel itinerary schemes is realized, and the intelligent level and user experience of travel itinerary planning are effectively improved.

The embodiment of the invention provides an information processing method and related equipment, and the method comprises the steps: displaying a service interface, and displaying received itinerary planning request information in the form of a first session message in the service interface; in response to the itinerary planning request information, itinerary planning information and at least two browsing modes are output, any browsing mode is used for performing simplified display on the itinerary planning information, and the itinerary planning information and the at least two browsing modes are displayed on the service interface in the form of a second session message; and in response to the triggering of any browsing mode, presenting the itinerary plan in the itinerary planning information according to the triggered browsing mode. According to the embodiment of the invention, the travel route planning content can be displayed in a simplified manner, the information density is reduced, and the reading experience of a user is improved.

1. The name of the design product: itinerary planning graphical user interface for 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: interface change state diagram 4. 5. The use of the graphical user interface: the interface is used to set the itinerary date. 6. The human-computer interaction mode of the graphical user interface: in the main view, when the user clicks the dot control on the right side of "DAY 1", enter interface change state diagram 1; when the user clicks the "set specific date" control in the pop-up window, enter interface change state diagram 2; when the user clicks the selected "1" date control, enter interface change state diagram 3; when the user clicks the "OK" control, enter interface change state diagram 4.

The invention relates to the technical field of itinerary planning, in particular to an itinerary planning method, which comprises the following steps: acquiring a user demand, and extracting keywords and conditions of the user demand; obtaining display information according to the keywords, and performing resource matching according to conditions and preset elements; calling a preset template to generate a travel itinerary; generating an itinerary quotation for the itinerary according to a resource matching result; and receiving travel confirmation information, judging whether a clustering condition is met, and if yes, synchronizing the travel itinerary data to the first platform to enable the first platform to execute a reservation process. According to the travel agency quotation method, keywords and conditions required by the user are obtained, the travel itinerary of the user is planned, the corresponding travel itinerary is generated through the preset template, and at least one travel quotation is generated for the travel itinerary according to the resource matching result, so that the manpower, material and time costs of the travel agency are reduced.

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 invention discloses a multi-mode reinforcement learning dynamic travel itinerary planning system and method, and belongs to the technical field of artificial intelligence. The system comprises a multi-modal data input layer, a cognitive decision-making layer, a feedback optimization layer and a dynamic journey planning output layer. The core of the method is as follows: a cognitive decision-making layer cooperatively adopts a near-end strategy optimization PPO algorithm and a deep Q network DQN algorithm to respectively process continuous and discrete actions in a travel; the feedback optimization layer performs closed-loop optimization on the algorithm through a multi-dimensional reward function according to a travel execution result and user feedback; and the dynamic journey planning output layer dynamically adjusts the journey scheme based on the optimized decision and the real-time environment data. According to the method, the problems of static planning and single decision in the prior art are solved, and the individuation, flexibility and user satisfaction of route planning are remarkably improved through algorithm collaboration and dynamic response.

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.

The invention relates to the technical field of intelligent travel planning, and provides an intelligent travel itinerary planning method and device based on multi-data fusion application, and the method comprises the steps: reading real-time user data; extracting the stroke feature points and matching the stroke feature points with the last element of the reference stroke feature point queue; calculating a time adjustment amount and a scenic spot adjustment amount; if any adjustment amount exceeds the threshold value, an adjustment instruction is generated, the last element of the queue is removed, and then the real-time user data acquired by the multi-source data acquisition module is read; and otherwise, the last element is directly removed, and whether the time adjustment amount exceeds the first time threshold value and whether the scenic spot adjustment amount exceeds the first scenic spot threshold value are judged. The travel plan can be intelligently adjusted, the flexibility and personalization of travel planning are improved, time and scenic spot arrangement is optimized, and the user experience 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 relates to the technical field of intelligent travel and computer application, in particular to a travel itinerary planning auxiliary system and method, and the method comprises an initial travel itinerary planning module which is used for receiving a travel demand of a user and generating an initial travel itinerary plan; the user state sensing module is used for continuously acquiring and processing the physiological state data and the real-time geographic position of the user; the multi-source data acquisition module is used for acquiring dynamic data from an external data source according to the real-time geographic position; the travel planning module is used for performing travel re-planning according to the collected data and generating one or more optimized travel schemes; the dynamic adjustment and execution module is used for calling the travel route planning module according to a preset evaluation model; and receiving the optimized journey scheme generated by the journey planning module, and pushing the optimized journey scheme to a user. According to the method, the problems of poor experience and high health risk caused by the fact that the existing static travel planning cannot adapt to dynamic change in travel are solved.

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.

This application belongs to the field of data processing and relates to a method, system, computer equipment and storage medium for planning and pushing cultural and tourism itineraries. It aims to solve the technical problem that the existing technology only processes multimodal interactive data in isolation and labeling, without building a structured user memory association relationship that includes time-series association and scene association. As a result, itinerary planning does not match the user's overall preferences, multimedia push is blind, and it cannot meet the needs of personalized cultural and tourism services.

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 invention provides a travel itinerary planning method and system based on big data, and the method comprises the steps: firstly integrating tourism-related big data, including tourism destination resource data, user historical tourism data and tourism service supply data, and generating tourism preference matching data through correlation analysis; constructing a tourism scene interaction environment, obtaining user scene experience feedback information, adjusting preference weight distribution according to the feedback information, and generating an updated preference scene matching relationship; a preliminary travel route framework is generated in combination with the spatial distribution information of the travel destination resource data; and finally, importing the initial travel itinerary path framework into an interactive environment for simulation verification, optimizing a path node sequence, and outputting an interactive travel itinerary path, thereby realizing intelligence and individuation of travel itinerary 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 an itinerary planning method and device and electronic equipment, and belongs to the technical field of artificial intelligence. The itinerary planning method comprises the following steps: receiving a first input of a user to a road book interface; the road book interface comprises travel place detail information, and the travel place detail information comprises time information, weather information and traffic information of a plurality of travel places; and in response to the first input, displaying travel route planning information of the plurality of travel places.

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.