Travel planning method and device, equipment, storage medium and program product

Abstract

The invention provides a travel planning method, device and equipment, a storage medium and a program product, relates to the technical field of aviation travel services, and aims to provide a coherent one-stop travel route planning service, simplify the planning process and improve the planning efficiency. The method comprises the following steps: acquiring travel demand information of a user; based on the travel demand information of the user, performing keyword search and matching on the data in the database to obtain at least one travel planning scheme meeting the travel demand; the database comprises data matched with the travel demand information of the user; and sorting the at least one travel planning scheme to obtain an optimal travel planning scheme.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of air travel services, and particularly relates to a travel planning method and device, equipment, a storage medium and a program product. BACKGROUND

[0002] The existing one-stop air travel mode usually only focuses on the process optimization in a single module such as ticket booking, hotel check-in or ground transportation, and cannot realize data intercommunication and intelligent collaboration between modules. Such isolated service state affects the coherence experience and planning efficiency of user travel. SUMMARY

[0003] The present application aims to provide a travel planning method, device, equipment, storage medium and program product, which aims to provide a coherent one-stop travel planning service, simplify the planning process and improve the planning efficiency.

[0004] To achieve the above-mentioned purpose, the embodiments of the present application provide the following technical solutions: In a first aspect, the present application provides a travel planning method, comprising: obtaining travel demand information of a user; performing keyword search and matching on data in a database based on the travel demand information of the user to obtain at least one travel planning scheme meeting the travel demand; the database comprising data matching the travel demand information of the user; and sorting the at least one travel planning scheme to obtain an optimal travel planning scheme.

[0005] The travel planning method provided by the present application first obtains the travel demand information of the user, extracts keywords therefrom and then matches the keywords with the data in the database to determine at least one travel planning scheme meeting the travel demand, and then selects the optimal travel planning scheme through sorting. It can be seen that the present application can automatically select the data matching the user demand from the database to generate a perfect travel planning scheme, without the need for the user to manually switch between multiple isolated application platforms to formulate a travel planning scheme, and can provide a coherent one-stop travel planning service, simplify the planning process and improve the planning efficiency.

[0006] In some embodiments, based on the travel demand information of the user, keyword search and matching are performed on the data in the database to obtain at least one travel planning scheme that meets the travel demand, including: classifying the travel demand information to obtain at least one type of travel demand information; for each type of travel demand information in the at least one type of travel demand information, based on each type of travel demand information, keyword search and matching are performed on the data in the database to obtain at least one travel planning information that meets each type of travel demand; wherein the database includes a database matched with the type of each type of travel demand information in the at least one type of travel demand information; based on the at least one travel planning information that meets each type of travel demand, a set of travel planning information that meets the at least one type of travel demand is obtained; the travel planning information in the set of travel planning information is combined to obtain at least one travel planning scheme.

[0007] In some embodiments, the at least one travel planning scheme is sorted to obtain an optimal travel planning scheme, including: using an intelligent algorithm model to comprehensively score and sort the at least one travel planning scheme according to multi-objective optimization parameters; wherein the multi-objective optimization parameters include: distance between scenic spots, user travel time, scenic spot opening time, and traffic convenience; from the sorting result, the travel planning scheme with the highest score is determined as the optimal travel planning scheme.

[0008] In some embodiments, the optimal travel planning scheme is fed back to the user, and the evaluation of the optimal travel planning scheme by the user is obtained; in the case that the user approves the optimal travel planning scheme, the traffic ticket information corresponding to the optimal travel planning scheme is sent to the user; in the case that the user does not approve the optimal travel planning scheme, the travel demand information of the user is reacquired, and the travel planning scheme is re-determined.

[0009] In some embodiments, the travel demand information of the user is obtained, including: obtaining the information related to travel input by the user under the dialogue guidance of the intelligent assistant system; based on the information related to travel input by the user, the travel demand information of the user is determined.

[0010] In some embodiments, the travel demand information of the user includes at least one of the following: departure and destination, user travel planning, traffic transfer mode, travel ticket purchase situation, hotel and scenic spot arrangement.

[0011] In a second aspect, the present application also provides a travel planning device, which comprises an acquisition module, a matching module and a sorting module; the acquisition module is configured to acquire travel demand information of a user; the matching module is configured to perform keyword search and matching on data in a database based on the travel demand information of the user, to obtain at least one travel planning scheme that meets the travel demand; the database comprises data that matches the travel demand information of the user; and the sorting module is configured to sort the at least one travel planning scheme to obtain an optimal travel planning scheme.

[0012] In a third aspect, the present application also provides an electronic device, which comprises a processor and a memory; the memory stores instructions executable by the processor; and the processor is configured to execute the instructions, so that the electronic device implements the method of the first aspect.

[0013] In a fourth aspect, the present application also provides a computer-readable storage medium, which comprises computer software instructions; and when the computer software instructions are run in an electronic device, the electronic device implements the method of the first aspect.

[0014] In a fifth aspect, the present application also provides a computer program product, which comprises a computer program; and when the computer program is run on an electronic device, the electronic device executes the method of the first aspect.

[0015] The beneficial effects of the second aspect to the fifth aspect described above can refer to the corresponding description of the first aspect, and will not be described again. BRIEF DESCRIPTION OF DRAWINGS

[0016] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced as follows. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can also be obtained by those skilled in the art without creative labor.

[0017] Figure 1 Structure diagram of a travel planning system provided by the embodiments of the present application Figure 1 ; Figure 2 Flowchart of a travel planning method provided by the embodiments of the present application Figure 1 ; Figure 3 Flowchart of a travel planning method provided by the embodiments of the present application Figure 2 ; Figure 4 Flowchart of a travel planning method provided by the embodiments of the present application Figure 3 ; Figure 5A structure diagram of a travel planning system provided by an embodiment of the present application Figure 2 ; Figure 6 A structure diagram of a travel planning system provided by an embodiment of the present application Figure 3 ; Figure 7 A composition diagram of a travel planning device provided by an embodiment of the present application Figure 8 A structure diagram of an electronic device provided by an embodiment of the present application DETAILED DESCRIPTION

[0018] The technical solutions in the embodiments of the present application will be clearly and completely described with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative work fall within the protection scope of the present application.

[0019] It should be noted that, in the embodiments of the present application, the words such as "exemplarily" or "for example" are used to represent an example, illustration or description. Any embodiment or design scheme described as "exemplarily" or "for example" in the embodiments of the present application should not be interpreted as more preferred or more advantageous than other embodiments or design schemes. Rather, the words such as "exemplarily" or "for example" are intended to present the relevant concept in a specific manner.

[0020] In the embodiments of the present application, the terms "first", "second", "third", "fourth", "fifth", and "sixth" are used only for descriptive purposes, and should not be construed or implied to indicate or suggest relative importance or implicitly indicate the number of the indicated technical features. Therefore, the features limited by "first", "second", "third", "fourth", "fifth", and "sixth" can explicitly or implicitly include one or more of the features.

[0021] In the embodiments of the present application, the terms "include", "contain" or any other variants thereof are intended to cover non-exclusive inclusion, so that the process, method, article or device including a series of elements not only includes those elements, but also includes other elements not explicitly listed or inherent to such process, method, article or device. Without more limitations, the element limited by the statement "including one" does not exclude the presence of another identical element in the process, method, article or device including the element. For "A and / or B", the following three combinations are included: only A, only B, and the combination of A and B.

[0022] With the development of the aviation industry and the mobile Internet, the mobile intelligent travel mode has become the core business that airlines focus on promoting, and the mobile terminal application platform has been widely used in the aviation whole-process services such as flight query and check-in. However, the user's air travel is often associated with tourism, business and the like, so the user's demand is not limited to the link within the airport, but also extends to the travel plan, scenic spot selection and hotel reservation at the destination. The related technology fails to integrate the air travel with the overall travel plan of the user. This disconnection forces the user to go back and forth among multiple applications, repeatedly input information and manually splice, which is not only time-consuming and inefficient, but also easy to cause the final plan to be unsatisfactory due to connection errors, which seriously affects the overall travel experience.

[0023] Based on the above problems, the travel planning method provided by the present application first acquires the travel demand information of the user, extracts the keywords therefrom, and matches them with the data in the database, and then determines at least one travel planning scheme that can meet the travel demand, and selects the optimal travel planning scheme through sorting. It can be seen that the present application can automatically select the data matching the user's demand from the database to generate a perfect travel planning scheme, without the user manually switching between multiple isolated application platforms to develop a travel planning scheme, which can provide a coherent one-stop travel itinerary planning service, simplify the planning process and improve planning efficiency.

[0024] The system to which the travel planning method provided by the embodiments of the present application is applied will be described below in conjunction with specific embodiments and the accompanying drawings of the specification: The travel planning method provided by the embodiments of the present application can be applied to, for example, a travel planning system 100 as shown in the accompanying drawings. Figure 1 Please refer to Figure 1 The travel planning system 100 can include a user interaction device 101, a data processing device 102 and a planning scheme database 103. The data processing device 102 is in communication connection with the user interaction device 101 and the planning scheme database 103, respectively.

[0025] The user interaction device 101 is used to interact with the user. For example, the user interaction device 101 is used to receive and analyze the user's input to generate structured travel demand information.

[0026] For example, the user interaction device 101 can be a smart phone, a smart speaker, a car-mounted central control screen, a computer web client, etc., and the embodiments of the present application do not make any limitation on the specific form of the user interaction device 101.

[0027] The planning scheme database 103 stores a large amount of traffic data, scenic spot geographic location information, travel guide data, public transportation timetables, accommodation and catering information and user preference information, etc.

[0028] Exemplarily, the planning scheme database 103 can be a distributed database system or a cloud storage service, and the specific form of the planning scheme database 103 is not limited in the embodiments of the present application.

[0029] The keyword search engine and the intelligent algorithm model are deployed in the data processing apparatus 102. The data processing apparatus 102 retrieves and matches the planning scheme database 103 by calling the keyword search engine, generates a preliminary scheme set, calculates the optimal solution through the intelligent algorithm model, and finally returns the optimal travel planning scheme to the user interactive apparatus 101 to present to the user.

[0030] Exemplarily, the data processing apparatus 102 can be a server or a server cluster with strong computing power, and the specific form of the data processing apparatus 102 is not limited in the embodiments of the present application.

[0031] In other embodiments, the user interactive apparatus 101, the data processing apparatus 102 and the planning scheme database 103 can be integrated on the same device, or any one or two of the three are arranged in independent devices, and communicate through wired or wireless network, and the present application does not make any limitation.

[0032] The travel planning method provided by the embodiments of the present application is used to quickly match and recommend the optimal travel planning scheme from the database based on the real-time acquired user travel demand. The travel planning method can be applied to Figure 1 The travel planning system 100 shown can also be applied to the integrated data processing apparatus 102 described above, and the present application does not make any limitation.

[0033] The travel planning system 100 provided by the embodiments of the present application can receive and analyze the user demand information through the user interactive apparatus 101, the planning scheme database 103 stores various travel related data, and the data processing apparatus 102 uses the search engine and intelligent algorithm in it to search and intelligently calculate the data in the planning scheme database 103, and finally generates the optimal travel planning scheme and returns it to the user through the user interactive apparatus 101. The system can quickly respond based on real-time demand, and use intelligent algorithms to generate accurate and personalized optimal travel schemes combined with user preferences, significantly improving planning efficiency and user experience.

[0034] The travel planning method provided by the embodiments of the present application will be described below in conjunction with specific embodiments and the accompanying drawings of the specification: Figure 2 The flowchart of the travel planning method provided by the embodiments of the present application Figure 1 As shown in Figure 2 The travel planning method provided by the embodiments of the present application includes the following steps S201-S203: S201, obtain the travel demand information of the user.

[0035] The travel demand information of the user refers to a set of travel data generated and relied on by the user when planning or performing a travel activity, which can be used as a data basis for the user to plan a trip.

[0036] In some embodiments, the information related to the trip input by the user under the guidance of the dialogue of the intelligent assistant system is obtained; and the travel demand information of the user is determined based on the information related to the trip input by the user.

[0037] The intelligent assistant system is a software program driven by artificial intelligence technology, which can understand the demand of the user in natural language and actively perform dialogue operations to obtain the overall travel demand information of the user.

[0038] For example, the intelligent assistant system initiates a dialogue to guide the user to input the information related to the trip by asking, prompting, etc. For example, the user is asked, “Where are your departure and destination for this trip?” “Which mode of transportation do you plan to choose?” etc. The user inputs information related to the trip such as “the departure is Chengdu and the destination is Xi'an, and I want to take a plane” “I plan to play for 3 days and want to stay in an economy hotel” etc. Then the intelligent assistant system processes and analyzes the information input by the user to determine the travel demand information of the user, such as determining that the user is taking a 3-day high-speed rail trip from Chengdu to Xi'an and prefers an economy hotel.

[0039] For example, the intelligent assistant in the intelligent assistant system first asks, “Where do you want to travel?” The user answers, “Xi'an.” Then it asks, “From which city do you depart?” The user says, “Chengdu.” Then it asks, “What mode of transportation do you want to take?” The user answers, “plane.” Then it asks, “How many days do you plan to play?” The user says, “3 days.” Finally, it asks, “Do you have any requirements for accommodation?” The user answers, “economy hotel.” After integrating the information related to the trip, the intelligent assistant system determines that the user's travel demand is to take a high-speed rail from Chengdu to Xi'an for a 3-day trip and to stay in an economy hotel.

[0040] In some embodiments, the travel demand information of the user includes at least one of the following: the departure and destination, the user's travel plan, the transportation transfer mode, the purchase of travel tickets, the hotel and scenic spot arrangement.

[0041] The departure and destination refer to the starting point and the final destination of the user's trip.

[0042] In one possible implementation, the information can be directly inputted or directly located by the user in the dialogue with the intelligent assistant system. After the departure and destination are determined, the path can be further calculated, the available transportation modes can be queried, and the subsequent travel planning scheme can be constructed, thereby providing a key basis for the user's travel ticket selection.

[0043] The user travel planning refers to the preliminary user travel planning information of the user on the travel time, days, budget, and core activities.

[0044] In one possible implementation, the user travel planning information is obtained through multiple dialogues between the intelligent assistant and the user, and the information is used to filter the matching train, hotel, and activity, thereby providing an overall framework and preference constraint for generating all subsequent arrangements, and ensuring that the final scheme meets the user's expectations in terms of time, cost, and experience.

[0045] The transportation transfer mode refers to the main transportation tool and its connection mode adopted by the user when moving between different locations.

[0046] In one possible implementation, the user completes the setting by selecting or directly stating the preference in the options (such as airplane, high-speed rail, self-driving, etc.) provided by the intelligent assistant. The selection directly determines the core logic of the travel planning, because different transportation modes correspond to different schedules, costs, and experiences, and are the key to organically connecting scattered locations into a feasible route.

[0047] The travel ticket purchase condition refers to the state and information of various transportation tickets ordered by the user.

[0048] In one possible implementation, the user can actively provide the transportation information such as flight number and train number that has been booked or ticketed in the dialogue with the intelligent assistant. The information is used as a fixed time node in the travel, the planning is rolled back (such as arranging transportation to the airport) and the arrangement is extended forward (such as planning the connection and activity at the destination), thereby ensuring that the dynamically generated travel scheme can seamlessly connect with the determined ticket information and avoid time conflicts.

[0049] The hotel and attraction arrangement includes the user's plan for the accommodation location and the tour project at the destination.

[0050] In one possible implementation, the user can actively provide the preferred accommodation area, the booked hotel name, or the planned attractions and activities in the dialogue with the intelligent assistant. Based on this information, the daily travel route and stay duration are arranged, and the surrounding catering and entertainment options are recommended, thereby filling the basic travel framework into a rich, specific, and executable personalized travel planning scheme.

[0051] In a possible implementation, when the user has a travel plan and interacts with the intelligent assistant system, relevant information reflecting the user's travel appeal is collected, which covers at least one aspect of the starting point and final destination of the user's trip, the approximate travel time arrangement and travel direction, the preferred conversion form of different traffic modes, whether the tickets for the trip have been purchased, and the preliminary intention of the hotel and the planned tourist attractions, etc. For example, the user tells the intelligent assistant "I want to go to Shanghai next week, and I may take the high-speed rail and then transfer to the subway. I haven't bought the ticket yet, and I want to stay at a hotel near the Bund". At this time, the information collected includes the departure city (the current city), the destination (Shanghai), the travel time (next week), the traffic transfer mode (high-speed rail to subway), the ticket status (not purchased), and the hotel arrangement (near the Bund).

[0052] In a possible implementation, the intelligent assistant system takes a mobile travel application software as a carrier, relies on the development framework of the volcano big model to build a technical foundation, and uses an intelligent communication mode in the interaction with the user. The intelligent assistant system can intelligently guide the user's travel intention and further enrich the user's travel idea, and finally accurately acquire the user's travel demand. The volcano big model is a large artificial intelligence model that can deeply understand and intelligently analyze the input information (such as questions, keywords, documents, pictures, etc.), and then generate accurate, fluent, easy-to-understand, and context-related natural language explanations and answers.

[0053] For example, the user logs in to the dialogue interface of the intelligent assistant system through the mobile travel application software of a certain airline, and inputs the corresponding travel demand information in the form of dialogue, including the destination and the user's travel plan. For example, if the user has input "three-day tour in Shanghai from December 24 to 26", the intelligent assistant system will automatically identify whether the user has started automatic positioning, acquire the information of the current departure city, and analyze the destination (Shanghai) and the user's travel plan (three-day travel plan from December 24 to 26) from the user's input information. At the same time, after initially confirming the user's travel information, the intelligent assistant system feeds back and asks "whether a three-day travel guide from Guangzhou to Shanghai on December 24-26 is needed", so as to determine the main direction of the user's travel itinerary.

[0054] The embodiments of the present application help the intelligent assistant system to communicate with the user intelligently, acquire the user's travel related data in this process, and further enrich the user's travel idea through multi-directional guidance, so as to accurately capture the user's travel demand information and provide a key data basis for generating a user travel planning scheme subsequently.

[0055] S202, based on the user's travel demand information, performing keyword search and matching on the data in the database to obtain at least one travel planning scheme that meets the travel demand.

[0056] wherein the database comprises data matching the user travel demand information.

[0057] In some embodiments, the travel demand information is classified to obtain at least one type of travel demand information; for each type of travel demand information in the at least one type of travel demand information, keyword search and matching are performed on the data in the database based on each type of travel demand information to obtain at least one travel planning information satisfying each type of travel demand; wherein the database comprises a database matching the type of each type of travel demand information in the at least one type of travel demand information; based on the at least one travel planning information satisfying each type of travel demand, a set of travel planning information satisfying the at least one type of travel demand is obtained; and the travel planning information in the set of travel planning information is combined to obtain at least one travel planning scheme.

[0058] In the embodiments of the present application, first, the travel demand information is classified to obtain at least one type of travel demand information; for each type of travel demand information, keyword search and matching are performed in the corresponding type of database to obtain travel planning information related to the type of travel demand information, thereby forming a set of travel planning information corresponding to each type of travel demand information, each set containing at least one travel planning information; subsequently, the travel planning information in each set of travel planning information is combined to generate at least one travel planning scheme.

[0059] Exemplarily, Figure 3 The flowchart of a travel planning method provided by the embodiments of the present application Figure 2 . First, a comprehensive travel demand information is input, which is classified into at least one explicit category (such as category A travel demand information, category B travel demand information, etc., such as transportation, accommodation, etc.); parallel search and set generation are performed, each classified demand is sent to the corresponding special category database for keyword search and matching (such as searching special database A, searching special database B), each category search will produce an independent "set of travel planning information for a certain type of travel demand" (such as "set of travel planning information for category A, set of travel planning information for category B, etc.), each such set contains at least one alternative scheme satisfying the type of demand (for example, the transportation set has {high-speed train G01, flight CA123}); from each set, at least one option is selected for combination, at least one option is selected from the "set of travel planning information for category A" and at least one option is selected from the "set of travel planning information for category B", and the options from different sets are combined to form a complete travel planning scheme; finally, different travel planning schemes are output (such as travel planning scheme A, travel planning scheme B, etc.).

[0060] For example, the user's travel demand information (such as "three-day tour in Beijing, visit the Forbidden City, the Great Wall, and stay in a four-star hotel in Wangfujing") is first classified to obtain at least one type of demand such as scenic spots, accommodation, and transportation. Subsequently, the system performs keyword matching in the corresponding database for each type of demand to obtain a corresponding set of travel planning information (for example, the scenic spot set includes the Forbidden City, the Great Wall of Badaling, etc.; the accommodation set includes several four-star hotels near Wangfujing). Finally, at least one complete and feasible travel planning scheme is automatically generated by cross-classifying the information in different sets (such as "Forbidden City + Badaling Great Wall + A Hotel + subway and special bus"), thereby providing the user with diversified customized options.

[0061] In one possible implementation, the user's travel mode and travel time can be combined to match the opening hours, features, and other data of scenic spots in the database to optimize the travel planning scheme. For example, after arriving in Shanghai on December 24, the user can go shopping on Nanjing East Road and enjoy the night view of the Bund in the evening. On December 25, due to Christmas, there are relatively rich activities in Disneyland, and the user can choose to spend a day there.

[0062] The embodiments of the present application can accurately obtain travel planning information related to each type of demand by first classifying the travel demand information and then performing keyword search and matching in the database of the corresponding type of demand, effectively avoiding demand adaptation deviation caused by general matching, improving the matching degree of travel planning information and various types of travel demand, and ensuring that each type of demand can be responded to specifically. At the same time, the information in different sets of travel planning information is combined to generate a travel planning scheme, simplifying the generation process of the travel planning scheme and improving the planning efficiency, which comprehensively covers various complex travel scenarios, making the travel planning scheme more complete, thereby effectively meeting the user's needs and improving user satisfaction.

[0063] S203, ranking at least one travel planning scheme to obtain an optimal travel planning scheme.

[0064] In some embodiments, ranking at least one travel planning scheme to obtain an optimal travel planning scheme includes: using an intelligent algorithm model to comprehensively score and rank at least one travel planning scheme according to multi-objective optimization parameters; wherein the multi-objective optimization parameters include: distance between scenic spots, user travel time, scenic spot opening hours, and transportation convenience; and determining the travel planning scheme with the highest score from the ranking result as the optimal travel planning scheme.

[0065] The intelligent algorithm model can be a decision model based on a weighted scoring method or a genetic algorithm.

[0066] The weighted scoring method is a multi-criteria decision-making method based on linear weighted sum. First, different evaluation indices (e.g., attraction distance, travel time, etc.) are quantified or normalized to eliminate the dimension effect; second, a weight coefficient is assigned to each index according to its importance, and the sum of all weights is 1; finally, the score of each scheme on each index is multiplied by the corresponding weight and summed up to obtain the comprehensive score of the scheme. The final decision of this method is based on the scheme with the highest comprehensive score.

[0067] The genetic algorithm is a heuristic optimization algorithm that simulates the "natural selection" and "genetic mechanism" in the biological world. The potential solution to the problem to be solved (e.g., a travel planning scheme) is encoded as a "chromosome", and a "population" containing multiple chromosomes is initialized; then, the evolution process is simulated through iterative "selection", "crossover" (hybridization), and "mutation" operators, where the fitness function (defined according to the optimization objective, such as the comprehensive score) is used to evaluate the individual and guide the selection of "survival of the fittest"; in each generation, individuals with high fitness are more likely to pass their genes (scheme fragments) to the next generation, new solutions are generated through crossover, and diversity is introduced through mutation, gradually driving the entire population to evolve towards better solutions.

[0068] In one possible implementation, the related parameters of traffic convenience further include the number of public transportation transfers, walking distance, and real-time traffic indicators; the user travel time parameter matches the expected departure / arrival time period input by the user; the attraction opening time parameter is used to constrain the attraction visiting activity within the opening time window; through an intelligent algorithm model, each parameter is first normalized to eliminate the dimension effect, then the weighted total score is calculated according to the weight coefficients configured by the user preference or the system default configuration, and finally all travel planning schemes are ranked in descending order of the total score.

[0069] Exemplarily, for a 5-day 4-night parent-child long-distance travel plan from Guangdong to Shanghai, according to step S202, the "Jiangnan Ancient Town Style Line" (Guangzhou → Nannong Ancient Town → Shanghai urban area → Disneyland) and the "Shanghai-Suzhou Culture Experience Line" (Guangzhou → Shanghai urban area → Suzhou Humble Administrator's Garden → Shanghai Disneyland) preliminary schemes can be generated. Then, by using an intelligent algorithm model, the user's demand for parent-child long-distance travel "less travel, slow rhythm, and stable experience" is combined to assign different weights to multi-objective optimization parameters and sort them: the distance between scenic spots and the weight of traffic time is set to 35% (emphasizing the evaluation of cross-city commuting efficiency, "Ancient Town Line" from Guangzhou to Shanghai by high-speed rail to Nannong takes only 1.5 hours, and after returning to Shanghai Hongqiao, the subway directly reaches the accommodation, and the total traffic time is controlled within 3 hours, which is significantly better than the travel cost of nearly 2.5 hours of "Shanghai-Suzhou Line" from Shanghai to Suzhou), the user travel time weight is set to 30% (focusing on matching the physical rhythm of children, "Ancient Town Line" has 4-5 hours of core tour per day, with 2 hours of lunch break and free activity time to avoid excessive fatigue of children, while "Shanghai-Suzhou Line" compresses the rest time due to cross-city round trip, and the travel rhythm is tight), the scenic spot opening time weight is set to 20% (guaranteeing the feasibility of the trip, "Ancient Town Line" has a small lotus garden in Nannong open at 8:00 and Shanghai Disneyland open at 8:30, which completely covers the time planning, and avoids the risk of delay due to limited flow of Humble Administrator's Garden in the peak season), and the traffic convenience weight is set to 15% (focusing on the adaptation of supporting facilities for children, "Ancient Town Line" selects accommodations located at subway stations or within scenic areas, and provides free shuttle services for Disneyland accommodations, which greatly reduces the transfer pressure). Through intelligent algorithm, the performance of each scheme under different weight parameters is calculated by weighting, and finally "Jiangnan Ancient Town Style Line" is determined as the optimal travel planning scheme because it has significant advantages in high-weight traffic connection and travel rhythm dimensions, and the comprehensive weighted result is higher than that of "Shanghai-Suzhou Culture Experience Line".

[0070] In some embodiments, the optimal travel planning scheme is fed back to the user, and the user's evaluation of the optimal travel planning scheme is obtained; in the case that the user approves the optimal travel planning scheme, the user is sent traffic ticket information corresponding to the optimal travel planning scheme; in the case that the user does not approve the optimal travel planning scheme, the user's travel demand information is re-obtained, and the travel planning scheme is re-determined.

[0071] Exemplarily, for the Guangzhou-Shanghai 5-day 4-night family travel scenario, when the system determines the "Jiangnan Ancient Town Style Line" (Guangzhou → Nanxun Ancient Town → Shanghai urban area → Disneyland) as the optimal solution, the intelligent assistant system pushes the travel planning solution to the user in the form of a picture and text combination, which shows the detailed content, including daily itinerary (such as Day 1 Guangzhou to Shanghai Hongqiao, Day 2 Nanxun Ancient Town tour), scenic spot reservation guide (such as Nanxun Ancient Town ticket reservation QR code), and traffic connection suggestion (such as Shanghai Hongqiao to Nanxun Ancient Town high-speed rail schedule recommendation), etc., and asks the user in the dialogue box whether the user is satisfied with the travel planning solution. After obtaining the reply, the system will rearrange, search for the itinerary, or end the travel planning. If the user approves, the system will immediately jump to the ticket reservation result page to show the high-cost-effective ticket information (such as Guangzhou-Shanghai round-trip economy class tickets, Shanghai urban area to Disneyland subway transfer route and ticket purchase link) that has been screened out, supporting the user to directly click to book; if the user feedback is not approved (such as replacing Nanxun Ancient Town with Suzhou Gardens), the user will be guided to select new destination preferences, travel rhythm requirements, etc. After collecting the information, the algorithm model is called again, and the multi-objective optimization parameter weight is adjusted according to the new requirements (such as increasing the "scenic spot preference matching degree" weight), to generate a new travel plan for the user to choose, ensuring that the plan meets the actual needs of the user.

[0072] The embodiments of the present application improve the accuracy of the solution by comprehensively optimizing multiple target parameters through an intelligent algorithm model, adapt to the individual preferences of the user through an iterative optimization mechanism to improve the acceptance of the solution, and help the user save time and cost by linking the air ticket reservation after determining the solution, thereby effectively improving the user service satisfaction.

[0073] Exemplarily, a flowchart of the travel planning method provided by the present application based on an intelligent assistant system is shown, Figure 4 a flowchart of the travel planning method provided by the embodiments of the present application Figure 3 . First, the user inputs the travel demand information, which includes simple travel planning and travel ticket strategy. At this time, the intelligent assistant system can identify the user's travel purpose. Based on the travel demand information, the user's travel purpose is output, which is obtained through the guided inquiry and further question guidance of the intelligent assistant system. Based on the user's travel purpose, the intelligent assistant system analyzes the travel demand information and matches the corresponding travel planning. Finally, the travel planning solution with both pictures and texts and the air ticket purchase link of the traffic travel are output.

[0074] Based on steps S201-S203, the application first communicates with the user through an intelligent assistant, obtains travel data, guides rich travel ideas, accurately captures demand to lay the foundation for the scheme, and then classifies the demand, matches travel information corresponding to the database keywords to avoid adaptation deviation, combines to generate a scheme to simplify the process and cover scenarios, then uses an intelligent algorithm model to optimize the scheme with multiple parameters such as scenic spot distance and travel time, combines feedback iteration to adapt to individualization, and finally connects with air ticketing to save time. In short, the accuracy of the travel planning scheme is improved, and the user's satisfaction with the travel planning service is also improved.

[0075] The application also provides another travel planning system, as shown in Figure 5 Figure 5 A travel planning system provided by an embodiment of the application has a structure as shown in Figure 2 The system includes an information import module 501, an information interaction module 502, an information collection module 503, an information integration module 504, and an information export module 505.

[0076] In some embodiments, the information import module 501 is connected to the user end, which includes an information input end, an information receiving end, an information screening and analysis end, and a key information extraction end. The information import module 501 is used to obtain and process the user's travel demand information, obtain the user's travel key information, and complete the import of the information.

[0077] In a possible implementation, the user inputs simple or complex travel demand information of the user at the information input end, the information receiving end receives the travel demand information, then the information screening and analysis end intelligently analyzes and screens the travel demand information, extracts the key travel demand information, and feeds back the information to the information input end, determines and further guides the user to provide more accurate and detailed travel demand information, interacts with the information interaction module 502, and then completes the import of the travel demand information.

[0078] In some embodiments, the information interaction module 502 is connected to the information import module 501, connected to the information collection module 503, and connected to the information integration module 504, and is used for the transfer and arrangement of the user's travel key information.

[0079] In a possible implementation, the information interaction module 502 can quickly complete the analysis, extraction, and transmission of the user's travel key information, and can also arrange the data related to travel in the external database, realize the extraction and transmission of effective information.

[0080] ​In some embodiments, the information collection module 503 is connected with the information interaction module 502, which includes a data platform system, searches and matches the travel demand information in different platforms, and collects information related to travel. The information includes social media information, city attraction information, transportation hub information, location distance calculation information, and other travel-related information.

[0081] In a possible implementation, the key information obtained is transmitted to the data platform system through the information interaction module 502, the data platform system automatically classifies and manages the information related to travel, issues instructions to the information collection module 503, simultaneously searches and matches different types of travel demand information in different information platforms, matches the corresponding information related to travel, imports the information into the corresponding travel planning information, and then feeds back to the information data platform system for unified transmission to the information interaction module 502.

[0082] In some embodiments, the information integration module 504 is connected with the information interaction module 502, which is used for integrating and sorting the travel demand information. The information integration module 504 includes matching of demand conditions, logical analysis of information sorting, optimal travel matching, and other condition analysis and matching affecting user experience.

[0083] In a possible implementation, the information interaction module 502 integrates the travel planning information fed back from the information collection module 503, filters the travel elements meeting the user requirements through matching of demand conditions, determines the reasonable order of attractions and activities through logical analysis of information sorting, recommends efficient and personalized travel routes through optimal travel matching, and comprehensively considers other condition analysis and matching affecting user experience to obtain an optimal travel planning scheme, thereby further improving the overall quality and satisfaction of travel planning.

[0084] For example, the information interaction module 502 combines the time, location, purpose, and other related conditions of the user's travel demand, arranges and combines different travel planning information, further realizes matching of pictures and texts, uses the logic of play time to link different travel attractions and play orders, thereby deriving the corresponding travel planning scheme, and then outputs the optimal travel planning scheme based on the intelligent algorithm model.

[0085] In some embodiments, the information output module 505 is connected with the information integration module 504, which is used for outputting the travel planning scheme. The information output module 505 includes a travel play strategy output end, a travel traffic service purchase link end, and other travel planning output ends.

[0086] For example, after receiving the optimal travel plan output by the information integration module 504 after integrating and sorting the travel planning information, the information export module 505 will feed the plan back to the user through the travel guide output terminal, further inquire whether the user needs to supplement the transportation service plan, gradually guide and improve the user's travel needs, and supplement and feed back transportation services that meet the user's travel needs through the travel transportation service purchase link terminal via ticketing links. At the same time, it will provide more relevant travel suggestions through other travel planning output terminals, thereby realizing a one-stop travel service mode, that is, without switching other applications or services, travel planning and ticketing can be realized.

[0087] In some embodiments, the system also includes a satisfaction analysis of the planning scheme. When the user approves the itinerary planning scheme, the system process ends. If the user does not approve the itinerary planning scheme, the system returns to the information interaction module 502 to determine the optimal planning scheme based on further supplemented user demand information.

[0088] For example, a specific embodiment of a travel planning system is given, such as... Figure 6 As shown, Figure 6 A schematic diagram of the structure of a travel planning system provided in this application embodiment. Figure 3 The user's travel needs information is input into a smart travel assistant. This information includes departure and destination points, travel planning, transportation modes, ticket purchase options, hotel and attraction arrangements, etc. The information interaction module exchanges and shares information with the data platform system. Based on the travel needs information, it performs keyword searches and matching on different information to generate corresponding itinerary planning information, which is then fed back to the information interaction module. For example, the data platform system can export travel transportation connections through the location's transportation hub information system, arrange itineraries for attractions through the collection of information on destination attractions and travel guides, and recommend restaurants and accommodations through information on accommodation and dining. Finally, it exports a travel planning scheme with both text and images, as well as links to purchase travel tickets.

[0089] Based on the above embodiment, the application first communicates with the user through the intelligent assistant system, obtains the user travel related data in the process, and further enriches the user's travel imagination through multi-directional guidance, so as to accurately capture the user's travel demand information, lay the key data foundation for subsequent generation of user travel planning scheme; then, by classifying the travel demand information first, and then searching and matching the keywords in the corresponding category database for each type of demand, the travel planning information related to this type of demand is accurately obtained, the demand adaptation deviation caused by general matching is effectively avoided, the matching degree of travel planning information and various travel demands is improved to ensure that each type of demand is responded specifically, and the information in the information set of different categories of travel planning information is combined to generate a travel planning scheme, which simplifies the scheme generation process, improves the planning efficiency, and comprehensively covers diversified complex travel scenarios, so that the travel planning scheme is more comprehensive; then, through the intelligent algorithm model, the multi-objective optimization parameters such as the distance between scenic spots, the user travel time, the scenic spot opening time and the traffic convenience are comprehensively considered, the one-dimensional planning is avoided, the accuracy of the optimal travel planning scheme is improved, and the scheme feedback, the reacquisition of the user travel demand information and the iterative optimization of the travel planning scheme can adapt to the personalized travel preferences of the user to effectively improve the acceptance of the user to the scheme, and finally the scheme is determined and directly connected with the aviation ticket information push to help the user save time cost. In summary, the application does not need the user to manually switch between multiple isolated application platforms to develop a travel planning scheme, can provide a coherent one-stop travel itinerary planning service, simplify the planning process and improve the planning efficiency.

[0090] In summary, the travel planning device provided by the application comprises at least one of the corresponding hardware structure and software module for executing each function. Those skilled in the art should easily realize that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be realized in the form of hardware or a combination of hardware and computer software. Whether a certain function is executed by hardware or computer software driven hardware depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present disclosure.

[0091] In some embodiments, the application also provides a travel planning device, which can include one or more functional modules for implementing the travel planning method of the above method embodiments.

[0092] For example, Figure 7 A composition schematic diagram of a travel planning device provided by the embodiment of the application. As Figure 7As shown, the apparatus includes an acquisition module 701, a matching module 702, and a sorting module 703. The acquisition module 701 is configured to acquire travel demand information of a user. The matching module 702 is configured to perform keyword search and matching on data in a database based on the travel demand information of the user, to obtain at least one travel planning scheme that meets the travel demand. The database includes data that matches the travel demand information of the user. The sorting module 703 is configured to sort the at least one travel planning scheme, to obtain an optimal travel planning scheme.

[0093] In some embodiments, the matching module 702 is specifically configured to classify the travel demand information, to obtain at least one type of travel demand information. For each type of travel demand information in the at least one type of travel demand information, the matching module 702 is configured to perform keyword search and matching on data in a database based on each type of travel demand information, to obtain at least one travel planning information that meets each type of travel demand. The database includes a database that matches the type of each type of travel demand information in the at least one type of travel demand information. Based on the at least one travel planning information that meets each type of travel demand, a set of travel planning information that meets the at least one type of travel demand is obtained. The set of travel planning information is combined to obtain the at least one travel planning scheme.

[0094] In some embodiments, the sorting module 703 is specifically configured to use an intelligent algorithm model to comprehensively score and sort the at least one travel planning scheme according to multi-objective optimization parameters. The multi-objective optimization parameters include: distance between scenic spots, user travel time, scenic spot opening time, and traffic convenience. The travel planning scheme with the highest score is determined from the sorting result as the optimal travel planning scheme.

[0095] In some embodiments, the apparatus further includes an evaluation module 704. The evaluation module 704 is configured to feed back the optimal travel planning scheme to the user, and acquire the user's evaluation of the optimal travel planning scheme. In the case that the user approves the optimal travel planning scheme, the evaluation module 704 is configured to send traffic ticket information corresponding to the optimal travel planning scheme to the user. In the case that the user does not approve the optimal travel planning scheme, the evaluation module 704 is configured to re-acquire the travel demand information of the user, and re-determine the travel planning scheme.

[0096] In some embodiments, the acquisition module 701 is configured to acquire information related to travel input by the user under the guidance of a dialogue of an intelligent assistant system. Based on the information related to travel input by the user, the acquisition module 701 is configured to determine the travel demand information of the user.

[0097] In some embodiments, the travel demand information of the user includes at least one of the following: a departure location and a destination, a user travel plan, a traffic transfer mode, a travel ticket purchase situation, and hotel and scenic spot arrangements.

[0098] In an example embodiment, the electronic device can be the travel planning system or the travel planning apparatus. Figure 8 An example structure of an electronic device provided by the embodiments of the present application is shown in FIG. 8. Figure 8 As shown in FIG. 8, the electronic device includes a processor 801 and a memory 802. The memory 802 stores instructions executable by the processor 801. The processor 801 is configured to execute the instructions, so that the electronic device implements the method described in the foregoing method embodiments.

[0099] In an example embodiment, the embodiments of the present application also provide a computer readable storage medium having computer program instructions stored therein. When the computer program instructions are executed by a computer, the computer implements the method described in the foregoing embodiments. The computer can be an electronic device or a network device or a manager. The computer readable storage medium can be a non-transitory computer readable storage medium, for example, a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, and an optical data storage device, etc.

[0100] In an example embodiment, the embodiments of the present application also provide a computer program product, which includes a computer program. When the computer program runs on an electronic device, the electronic device executes the travel planning method described above.

[0101] In the description of the embodiments of the present application, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0102] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art can easily think of changes or replacements within the technical scope disclosed by the present application, which should be covered by the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A travel planning method, characterized in that, The method includes: Obtain users' travel needs information; Based on the user's travel demand information, keyword search and matching are performed on the data in the database to obtain at least one travel planning scheme that meets the travel demand; the database includes data that matches the user's travel demand information; The at least one travel planning scheme is sorted to obtain the optimal travel planning scheme.

2. The method according to claim 1, characterized in that, The step of performing keyword search and matching on data in the database based on the user's travel demand information to obtain at least one travel planning scheme that meets the travel demand includes: The travel demand information is classified to obtain at least one category of travel demand information; For each type of travel demand information in the at least one type of travel demand information, based on each type of travel demand information, keyword search and matching are performed on the data in the database to obtain at least one type of travel planning information that satisfies each type of travel demand; wherein, the database includes a database that matches the type of each type of travel demand information in the at least one type of travel demand information. Based on at least one type of travel planning information that satisfies each type of travel demand, a set of travel planning information that satisfies at least one type of travel demand is obtained. The travel planning information in the travel planning information set is combined to obtain the at least one travel planning scheme.

3. The method according to claim 1, characterized in that, The step of ranking the at least one travel planning scheme to obtain the optimal travel planning scheme includes: An intelligent algorithm model is used to comprehensively score and rank the at least one travel planning scheme based on multi-objective optimization parameters; wherein, the multi-objective optimization parameters include: distance between attractions, user travel time, attraction opening hours, and transportation convenience. The travel plan with the highest score from the ranking results is selected as the optimal travel plan.

4. The method according to claim 1, characterized in that, The method further includes: The optimal travel plan is fed back to the user, and the user's evaluation of the optimal travel plan is obtained. If the user approves the optimal travel plan, the system will send the user the corresponding transportation ticketing information. If the user does not agree with the optimal travel plan, the user's travel needs information is retrieved again, and a new travel plan is determined.

5. The method according to claim 1, characterized in that, The acquisition of users' travel demand information includes: Obtain travel-related information entered by the user under the guidance of the intelligent assistant system; Based on the travel-related information input by the user, the user's travel needs information is determined.

6. The method according to claim 1, characterized in that, The user's travel needs information includes at least one of the following: departure point and destination, user's travel plan, transportation mode, ticket purchase status, hotel and attraction arrangements.

7. A travel planning device, characterized in that, The device includes an acquisition module, a matching module, and a sorting module: The acquisition module is used to acquire users' travel demand information; The matching module is used to perform keyword search and matching on data in the database based on the user's travel demand information to obtain at least one travel planning scheme that meets the travel demand; the database includes data that matches the user's travel demand information; The sorting module is used to sort the at least one travel planning scheme to obtain the optimal travel planning scheme.

8. An electronic device, characterized in that, The electronic device includes: a processor and a memory; The memory stores instructions that the processor can execute; When the processor is configured to execute the instructions, it causes the controller to implement the method as described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes: computer software instructions; When computer software instructions are executed in an electronic device, the electronic device causes the electronic device to perform the method as described in any one of claims 1 to 6.

10. A computer program product, characterized in that, The computer program product includes a computer program that, when run on an electronic device, causes the electronic device to perform the travel planning method as described in any one of claims 1 to 6.

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