CN116796072A - Travel and entertainment service platform for travel destination - Google Patents
Travel and entertainment service platform for travel destination Download PDFInfo
- Publication number
- CN116796072A CN116796072A CN202310788236.5A CN202310788236A CN116796072A CN 116796072 A CN116796072 A CN 116796072A CN 202310788236 A CN202310788236 A CN 202310788236A CN 116796072 A CN116796072 A CN 116796072A
- Authority
- CN
- China
- Prior art keywords
- travel
- information
- user
- recommendation
- entertainment
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 235000013305 food Nutrition 0.000 claims abstract description 47
- 230000004308 accommodation Effects 0.000 claims abstract description 44
- 230000037213 diet Effects 0.000 claims description 27
- 235000005911 diet Nutrition 0.000 claims description 27
- 238000005065 mining Methods 0.000 claims description 17
- 238000000034 method Methods 0.000 claims description 11
- 238000012163 sequencing technique Methods 0.000 claims description 11
- 238000012216 screening Methods 0.000 claims description 4
- 230000000694 effects Effects 0.000 abstract description 4
- 238000012795 verification Methods 0.000 description 9
- 230000006870 function Effects 0.000 description 6
- 238000012544 monitoring process Methods 0.000 description 6
- 238000004364 calculation method Methods 0.000 description 5
- 230000008569 process Effects 0.000 description 3
- 230000009286 beneficial effect Effects 0.000 description 2
- 238000007405 data analysis Methods 0.000 description 2
- 238000010801 machine learning Methods 0.000 description 2
- 238000004458 analytical method Methods 0.000 description 1
- 238000012550 audit Methods 0.000 description 1
- 238000013475 authorization Methods 0.000 description 1
- 238000009412 basement excavation Methods 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 238000013135 deep learning Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000009977 dual effect Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000011156 evaluation Methods 0.000 description 1
- 230000004438 eyesight Effects 0.000 description 1
- 239000000446 fuel Substances 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 230000010354 integration Effects 0.000 description 1
- 238000011835 investigation Methods 0.000 description 1
- 210000001503 joint Anatomy 0.000 description 1
- 230000007246 mechanism Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012856 packing Methods 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 238000012552 review Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 238000012559 user support system Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/95—Retrieval from the web
- G06F16/953—Querying, e.g. by the use of web search engines
- G06F16/9535—Search customisation based on user profiles and personalisation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/95—Retrieval from the web
- G06F16/953—Querying, e.g. by the use of web search engines
- G06F16/9537—Spatial or temporal dependent retrieval, e.g. spatiotemporal queries
Landscapes
- Engineering & Computer Science (AREA)
- Databases & Information Systems (AREA)
- Theoretical Computer Science (AREA)
- Data Mining & Analysis (AREA)
- Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The application discloses a travel and shopping service platform for a travel destination, and relates to the technical field of travel, wherein the platform comprises a food recommendation module, an accommodation recommendation module, a travel recommendation module, a shopping recommendation module and an entertainment recommendation module, and customized eating, living, traveling, purchasing and entertainment recommendation services are provided for a user through the food recommendation module, the accommodation recommendation module, the travel recommendation module, the shopping recommendation module and the entertainment recommendation module, so that the most suitable scenic spots, restaurants, hotels, traffic modes, shopping places and entertainment activities can be recommended for the user. The platform can provide personalized and intelligent travel experience for tourists and help the tourists to plan the journey, explore the destination and enjoy various services in the travel better.
Description
Technical Field
The application relates to the technical field of travel, in particular to a travel and entertainment service platform for traveling at a travel destination.
Background
With the continuous improvement of the living standard of people, the demands of travel consumption and the like of people are greatly improved. At present, the travelling industry in China has the pain points of difficult operation, messy market, high cost, poor service and the like. Most tourist platform products are relatively one-sided in coverage and relatively scattered in distribution, lack of organic planning integration in space and function, and are inconsistent in development of six elements of 'eating, holding, traveling, purchasing and entertaining', so that a tourist industry chain is not formed, and the current situation of 'weak, scattered, messy and slow' of the tourist industry is caused.
Disclosure of Invention
Aiming at the defects in the prior art, the application provides a travel and entertainment service platform for traveling at a travel destination, which aims to solve the problems of covering the surface of a piece and having single function of the existing travel platform.
The technical scheme of the application is as follows: a travel and entertainment service platform for a travel destination comprising:
the food recommendation module is used for mining food information in the travel route, calculating the similarity between the food information and the historical diet information and recommending food to a user according to the similarity;
the accommodation recommendation module is used for mining accommodation information in the travel route, calculating the similarity of the accommodation information and the historical accommodation information, and recommending accommodation places to users after sorting the accommodation places from high to low according to the similarity;
the travel recommendation module is used for mining traffic information in the travel route and recommending travel services to the user according to the traffic information;
the tourist recommendation module is used for excavating scenic spot information in a tourist route, determining a first recommendation value of each tourist attraction according to travel service selected by a user, determining a second recommendation value of each tourist attraction according to real-time heat of each tourist attraction, calculating a comprehensive recommendation value of the tourist attraction, and recommending the tourist attraction to the user after sequencing according to the small arrival of the comprehensive recommendation value;
the shopping recommendation module is used for mining commodity information in the travel route, determining a commodity recommendation model according to travel service selected by a user, calculating recommendation values of all commodities according to the determined commodity recommendation model, and recommending the commodities to the user after sorting the commodities from large to small according to the recommendation values;
and the entertainment recommending module is used for excavating entertainment information in the travel route, determining the distance between the accommodation position of the user and the entertainment place, sequencing the entertainment place according to the distance from small to small, marking the corresponding predicted people flow and the optimal people flow, and recommending the entertainment place to the user.
Preferably, the historical diet information comprises first historical diet information and second historical diet information, wherein the first historical diet information is diet information before the current journey, and the second diet information is diet information before the current period of time in the current journey.
Preferably, the food recommendation module is specifically configured to: calculating first similarity of the food information and first historical food information, screening out target food information according to the first similarity, calculating second similarity of the target food information and second historical food information, and recommending the target food to a user after sequencing the target food according to the second similarity from high to low.
Preferably, the travel recommendation module is specifically configured to: mining scenic spot information in a tourist route, determining a tourist recommendation model according to travel service selected by a user, calculating first recommendation values of all tourist spots according to the determined tourist recommendation model, inputting real-time heat of the tourist spots and real-time heat of the tourist spots within a preset range into a heat prediction model to obtain predicted heat, determining second recommendation values of the tourist spots according to the preset heat, determining comprehensive recommendation values of the tourist spots according to the first recommendation values and the second recommendation values, and recommending the tourist spots to the user after the comprehensive recommendation values are ordered from small arrival.
Preferably, the travel service comprises one or more of a taxi self-driving service, a package quality trip service system and a bus follow-up trip service system.
Preferably, the method for calculating the predicted traffic flow comprises: and acquiring the real-time traffic of the entertainment place and the real-time traffic of the same type of entertainment place within the preset distance range, and inputting a plurality of real-time traffic into a traffic prediction model to obtain predicted traffic.
Preferably, the system also comprises a toilet recommending module, which is used for mining toilet information in the travel route, determining the distance between the user and the toilet, sequencing the toilets according to the distance from small to large, marking the corresponding predicted occupancy rate, and recommending the toilets to the user.
Preferably, the method of calculating the predicted occupancy comprises: acquiring real-time occupancy rate, search information and navigation information of a toilet, determining prediction time according to the distance, and calculating the prediction occupancy rate according to the prediction time, the real-time occupancy rate, the search information and the navigation information.
Preferably, the intelligent navigation system further comprises an intelligent navigation module for navigating the user in real time.
Preferably, the navigation module is compatible with a plurality of navigation systems, including a Beidou navigation system, a GPS navigation system, a Galileo navigation system and a Gelnas navigation system.
The beneficial effects of the application are as follows: the business travel and shopping entertainment service platform for the travel destination provided by the application provides customized business, living, traveling, purchasing and entertainment recommendation services for users according to the historical travel data and the real-time travel data of the users by utilizing a big data analysis and machine learning algorithm, and can recommend most suitable scenic spots, restaurants, hotels, traffic modes, shopping places and entertainment activities for the users. The platform can provide individualized and intelligent travel experience for tourists and help the tourists to plan the journey, explore the destination and enjoy various services in the travel better.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below. Like elements or portions are generally identified by like reference numerals throughout the several figures. In the drawings, elements or portions thereof are not necessarily drawn to scale.
Fig. 1 is a schematic structural view of a travel and shopping service platform for travel destination according to an embodiment of the present application;
fig. 2 is a schematic structural view of a travel and purchase entertainment service platform for a travel destination according to another embodiment of the present application.
Detailed Description
Embodiments of the technical scheme of the present application will be described in detail below with reference to the accompanying drawings. The following examples are only for more clearly illustrating the technical aspects of the present application, and thus are merely examples, and are not intended to limit the scope of the present application.
It is noted that unless otherwise indicated, technical or scientific terms used herein should be given the ordinary meaning as understood by one of ordinary skill in the art to which this application belongs.
As shown in fig. 1, a travel and entertainment service platform for a travel destination, comprising:
the food recommendation module is used for mining food information in the travel route, calculating the similarity between the food information and the historical diet information and recommending food to a user according to the similarity;
in the embodiment of the application, the historical diet information comprises first historical diet information and second historical diet information, wherein the first historical diet information is diet information before the current travel, and the second diet information is diet information before the current time period in the current travel.
In the embodiment of the application, the food recommendation module is specifically used for: calculating first similarity of the food information and first historical food information, screening out target food information according to the first similarity, calculating second similarity of the target food information and second historical food information, and recommending the target food to a user after sequencing the target food according to the second similarity from high to low.
The initial food set is screened through the diet data of the user before the current trip so as to be selected by the user, and the initial food set is optimized through the historical diet data of the user during the current trip so as to meet the requirements of the user.
According to the food recommendation module provided by the embodiment of the application, through the use of the similarity calculation method of the historical diet information, and the food is recommended to the user according to the sequence from high similarity to low similarity, personalized food recommendation service is provided, the time and energy of the user are saved, the food recommendation accuracy is improved, the requirements of the user on food selection are better met, and the travel experience of the user is improved.
The accommodation recommendation module is used for mining accommodation information in the travel route, calculating the similarity of the accommodation information and the historical accommodation information, and recommending accommodation places to users after sorting the accommodation places from high to low according to the similarity;
specifically, before the user starts traveling, historical accommodation information of the user, including accommodation sites, accommodation types, accommodation evaluations, and the like, is recorded, and these historical information are used for similarity comparison with accommodation information in travel routes, and relevant accommodation information, including accommodation sites, accommodation prices, accommodation facilities, and the like, is acquired according to the travel route selected by the user, and is to be a recommended object. Then, similarity calculation is performed on the accommodation information obtained in the previous step and the historical accommodation information of the user, and various similarity calculation methods, such as cosine similarity or Jaccard similarity, can be adopted. After calculation, the accommodation information is ranked from high to low according to the similarity, accommodation places with higher similarity are recommended to users according to the ranking result, and screening can be performed according to the user demands and preferences, such as price, facilities and other factors.
According to the accommodation recommendation module provided by the embodiment of the application, through using the similarity calculation method of the historical accommodation information, and recommending delicious foods to the user according to the sequence from high similarity to low similarity, personalized accommodation recommendation service is provided, the time and energy of the user are saved, the accuracy of accommodation recommendation is improved, the requirement of the user on accommodation selection is better met, and the travel experience of the user is improved.
The travel recommendation module is used for mining traffic information in the travel route and recommending travel services to the user according to the traffic information;
in the embodiment of the application, the travel service comprises one or more of a taxi self-driving service system, a package quality tour service system and a bus follow tour service system.
Specifically, the user selects a travel route, the travel route comprises a plurality of cities and county regions, the travel recommendation module obtains traffic information such as self-driving, vehicle packing, group following and the like among all the positions through excavation according to the travel route selected by the user, obtains travel service information such as self-driving vehicles, group following companies and the like meeting the user requirements through interface butt joint with a third-party travel service platform, and recommends the travel service information to the user.
Specifically, the renting self-driving service system comprises:
a registration module for registering the user: the user needs to register an account in the system, provide personal information such as name, phone number, email, etc., and upload a photograph or scanned item of the driver's license.
Wherein the registration module further comprises: and the driving license verification module is used for verifying the driving license submitted by the user, comparing the driving license information submitted by the user with a related database, and determining the authenticity of the driving license through an image recognition technology. A security pre-examination module: after the user's driving license passes the verification, the system may review the user's travel records, such as traffic violation records, accident records, and the like. If the records of the user all meet the taxi requirements, the system allows the user to continue to subscribe to the taxi.
Furthermore, when the user uploads the driving license photograph, the system should encrypt the data by using a security protocol (such as SSL) to ensure the security of the data in the transmission process. At the same time, the system should implement technical measures to prevent the photograph of the driving license from being tampered, such as adding watermarks, digital signatures, etc., to ensure the integrity and authenticity of the photograph. The system can use efficient image recognition and processing techniques, such as computer vision, deep learning, etc., to recognize information on the driver's license photograph, which can automatically read text and related information in the photograph and compare with the driver's license database. Of course, to increase the accuracy and reliability of verification, the system may employ a dual verification mechanism. For example, in addition to image recognition, the user may be required to input specific information on the driver's license (e.g., driver's license number, name, etc.) for verification. In the process of image recognition and verification, the system should ensure that the driver's license photograph and related information of the user are used only for verification purposes and are deleted or anonymized in time after verification is completed.
Through the measures, the renting self-driving service system can ensure safe image identification and verification of the driving license photo uploaded by the user, and ensure the privacy and information safety of the user. Meanwhile, the user can also protect the information security by knowing the security policy and compliance measures of the system and the knowledge and authorization of uploading photos.
And the car renting module enables a user to select a date, a duration and a type of the car to be rented through the WeChat applet.
Wherein, the taxi module includes:
the reservation module is used for selecting and reserving vehicles, and a user can browse an available vehicle list through the system and select a proper vehicle according to own requirements. The user can view detailed information of the vehicle, such as a brand, model, mileage, fuel type, etc., and know related information of rental fees, insurance fees, etc. The user may select a lease period and make a reservation. After the user selects a vehicle, the user needs to confirm the order of renting the vehicle and pay corresponding rentals or deposit, and the payment mode can comprise credit card, payment bank or WeChat payment and the like.
The pick-up and return module requires the user to select the time and place of pick-up in the system before rental begins. After the user finishes paying, the control authority of the corresponding vehicle can be obtained, and functions of unlocking, locking, opening air conditioner and the like of the vehicle can be performed through function keys in the system. When the car is used, the car door is automatically unlocked, the system is started without a key, after the car is used up, the car is returned by one key through a small program (car renting service system) of a mobile phone, and the whole car renting self-driving process is finished without manual assistance.
The vehicle monitoring module is used for monitoring the vehicle during the vehicle renting process, so that the safety of the vehicle renting and the vehicle renting user can be ensured. The method specifically comprises the following steps: GPS tracking module: the vehicle is equipped with a GPS tracking device that can track the position of the vehicle in real time, which can help to ensure the safety of the vehicle and provide position information when needed. Vehicle identification and monitoring system: the video monitoring system installed on the rented vehicle can record video of the vehicle during driving to provide monitoring of the vehicle usage, which can be used for post audit, dispute resolution, and investigation of safety issues. And the electronic fence module is used for detecting whether the user driving area is in the set area.
Of course, in some embodiments, an information module may also be included for displaying information of a parking lot, a charging station, a local activity, and the like.
Of course, in some embodiments, the customer service and emergency notification module may also: a rental car company can maintain emergency contact with the rental car user when needed to provide assistance and solve the problem in a timely manner. Meanwhile, the user can report the problem or request support to the taxi company through the customer service channel.
In conclusion, the monitoring measures of the car renting system can provide safety guarantee for vehicles and users, reduce risks and disputes and provide better user support and service. In addition, the renting car self-driving system allows tourists to freely arrange the journey according to own timetable and journey plan, the tourists can freely select the destination to which the tourists want to go, the stay time and the route, the tourists are not limited by public transportation means, the renting car self-driving system has convenience and convenience, play efficiency is provided, and the tourists are helped to plan and enjoy the journey better.
According to the travel recommendation module provided by the embodiment of the application, the user is helped to find the most convenient traffic route and traffic means according to the user requirement and the travel route, the travel time and energy of the user are saved, the user can select the traffic mode which is most suitable for the user from the recommended travel service, and the convenience and efficiency of travel are improved.
The tourist recommendation module is used for excavating scenic spot information in a tourist route, determining a first recommendation value of each tourist attraction according to travel service selected by a user, determining a second recommendation value of each tourist attraction according to real-time heat of each tourist attraction, calculating a comprehensive recommendation value of the tourist attraction, and recommending the tourist attraction to the user after sequencing according to the small arrival of the comprehensive recommendation value;
in the embodiment of the application, the travel recommendation module is specifically used for: mining scenic spot information in a tourist route, determining a tourist recommendation model according to travel service selected by a user, calculating first recommendation values of all tourist spots according to the determined tourist recommendation model, inputting real-time heat of the tourist spots and real-time heat of the tourist spots within a preset range into a heat prediction model to obtain predicted heat, determining second recommendation values of the tourist spots according to the preset heat, determining comprehensive recommendation values of the tourist spots according to the first recommendation values and the second recommendation values, and recommending the tourist spots to the user after the comprehensive recommendation values are ordered from small arrival.
Specifically, each scenic spot information in the travel route is acquired through data acquisition and analysis, including scenic spot names, positions, introduction, scores and the like, corresponding travel recommendation models are determined according to travel services selected by users, the models can be trained and optimized according to factors such as travel purposes, preferences and histories of the users, then a first recommendation value of each scenic spot is calculated according to the determined travel recommendation models, the recommendation value can be comprehensively calculated based on factors such as matching degree of the scenic spot and the travel services of the users, historical interests of the users and the like, real-time heat of the scenic spot and the real-time heat of other scenic spots within a preset range are input into a heat prediction model, future heat of the scenic spot is predicted, accordingly, a second recommendation value of the scenic spot is determined according to the future heat, and the comprehensive recommendation value of each scenic spot is calculated by combining the first recommendation value and the second recommendation value of the scenic spot.
According to the travel recommendation module, accurate, personalized and popular travel spot recommendation is provided through personalized recommendation and real-time heat prediction, and user travel experience and planning accuracy are improved.
And the shopping recommendation module is used for mining commodity information in the travel route, determining a commodity recommendation model according to travel service selected by the user, calculating recommendation values of all commodities according to the determined commodity recommendation model, and recommending the commodities to the user after sorting the commodities from large to small according to the recommendation values.
Because the selected travel services are different, tourist attractions possibly passed by the user are also different, the corresponding commodity types involved by the user are also different, further the commodity recommendation models corresponding to the commodities are also different, and the differences of the commodity recommendation models are that the weights of the influence factors in the commodity recommendation models are different, wherein the influence factors comprise price, quality, client-oriented type and the like.
And the entertainment recommending module is used for excavating entertainment information in the travel route, determining the distance between the accommodation position of the user and the entertainment place, sequencing the entertainment place according to the distance from small to small, marking the corresponding predicted people flow and the optimal people flow, and recommending the entertainment place to the user.
In the embodiment of the application, the method for calculating the predicted people flow comprises the following steps: and acquiring the real-time traffic of the entertainment place and the real-time traffic of the same type of entertainment place within the preset distance range, and inputting a plurality of real-time traffic into a traffic prediction model to obtain predicted traffic.
Specifically, the entertainment place is generally selected to be closer to the accommodation place, so that the entertainment place can be conveniently returned to the accommodation place for rest after entertainment or can be selected to be within the range of 2km, 5km and 10km from the accommodation place, and the specific distance is not limited in the embodiment of the application.
It should be noted that, when people in one entertainment place flow too much, the user will choose to go to other entertainment places, so that the people flow in the entertainment place is related to the people flow of the user, but also the people flow in the entertainment places of the same type around the user.
Further, some users like to go to places with more people, some users like to go to places with less people, some places have more people and have sense of atmosphere and some places have less people and have sense of range, so that the optimal people flow is related to the user preference flow and the entertainment standard flow, and the predicted people flow can be determined to be the optimal people flow when the predicted people flow meets the user preference flow and the entertainment standard flow.
In summary, the business travel and purchase entertainment service platform for the travel destination provided by the application provides customized business, living, traveling, purchasing and entertainment recommendation services for users according to the historical travel data and the real-time travel data of the users by utilizing the big data analysis and machine learning algorithm, and can recommend most suitable scenic spots, restaurants, hotels, transportation modes, shopping places and entertainment activities for the users. The platform can provide individualized and intelligent travel experience for tourists and help the tourists to plan the journey, explore the destination and enjoy various services in the travel better.
Example 2
As shown in fig. 2, on the basis of the above embodiment, the system further includes a toilet recommendation module, configured to mine toilet information in the travel route, determine a distance between the user and the toilet, sort the toilets according to the distance from small to large, and mark a corresponding predicted occupancy rate for recommendation to the user.
In the embodiment of the application, the method for calculating the predicted occupancy comprises the following steps: acquiring real-time occupancy rate, search information and navigation information of a toilet, determining prediction time according to the distance, and calculating the prediction occupancy rate according to the prediction time, the real-time occupancy rate, the search information and the navigation information.
Specifically, the predicted occupancy=real-time occupancy (search information weight navigation information weight)/prediction time. The real-time occupancy rate represents the real-time occupancy rate of the current toilet, and can be obtained through real-time data, the search information weight comprises a first search information weight and a second search information weight, the first search information weight represents the search requirement and the priority of a user and can be adjusted according to the importance degree of the user requirement, the second search information weight represents the user search quantity weight in the preset range of the user at the current moment, the navigation information weight represents the priority of the navigation route of the user reaching the toilet, the adjustment can be carried out by considering factors such as traffic conditions and road conditions, and the prediction time represents the time required by the user reaching the toilet according to the distance estimation.
The embodiment of the application comprehensively considers the real-time occupancy rate of the toilets, the user requirements and the navigation information, balances the predicted occupancy rates of different toilets through predicting the time consumption, and can sort and recommend the toilets to the user according to the order from small to large according to the size of the predicted occupancy rate.
In the embodiment of the application, the intelligent navigation module is also included for the real-time navigation of the user, and the navigation module is compatible with various navigation systems including a Beidou navigation system, a GPS navigation system, a Galileo navigation system and a Geronaisi navigation system.
It should be noted that, the intelligent navigation module is configured with an intelligent map system, and can mark scenic spots, hotels, food stores and the like reached by the user through different coincidence marks, and the marked information includes positions, times and the like.
The intelligent navigation module in the embodiment of the application provides accurate navigation positioning and global coverage navigation services by being compatible with various navigation systems, increases the stability and reliability of navigation, is beneficial to users to efficiently and safely reach destinations, and improves the convenience and comfort of travel.
In summary, the embodiment of the application provides a travel and shopping entertainment service platform for travel destinations, and also provides functions of toilet recommendation, positioning navigation and the like, has high coverage rate and various functions, and can meet modern travel requirements.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present application, and not for limiting the same; although the application has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some or all of the technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit of the application, and are intended to be included within the scope of the appended claims and description.
Claims (10)
1. A travel and entertainment service platform for a travel destination comprising:
the food recommendation module is used for mining food information in the travel route, calculating the similarity between the food information and the historical diet information and recommending food to a user according to the similarity;
the accommodation recommendation module is used for mining accommodation information in the travel route, calculating the similarity of the accommodation information and the historical accommodation information, and recommending accommodation places to users after sorting the accommodation places from high to low according to the similarity;
the travel recommendation module is used for mining traffic information in the travel route and recommending travel services to the user according to the traffic information;
the tourist recommendation module is used for excavating scenic spot information in a tourist route, determining a first recommendation value of each tourist attraction according to travel service selected by a user, determining a second recommendation value of each tourist attraction according to real-time heat of each tourist attraction, calculating a comprehensive recommendation value of the tourist attraction, and recommending the tourist attraction to the user after sequencing according to the small arrival of the comprehensive recommendation value;
the shopping recommendation module is used for mining commodity information in the travel route, determining a commodity recommendation model according to travel service selected by a user, calculating recommendation values of all commodities according to the determined commodity recommendation model, and recommending the commodities to the user after sorting the commodities from large to small according to the recommendation values;
and the entertainment recommending module is used for excavating entertainment information in the travel route, determining the distance between the accommodation position of the user and the entertainment place, sequencing the entertainment place according to the distance from small to small, marking the corresponding predicted people flow and the optimal people flow, and recommending the entertainment place to the user.
2. The amusement ride service platform for a travel destination of a travel of claim 1 wherein said historical diet information comprises a first historical diet information and a second historical diet information, wherein said first historical diet information is the diet information prior to the present travel and said second diet information is the diet information prior to the present time period during the present travel.
3. A travel and entertainment service platform for a travel destination as set forth in claim 2 wherein said food recommendation module is specifically configured to: calculating first similarity of the food information and first historical food information, screening out target food information according to the first similarity, calculating second similarity of the target food information and second historical food information, and recommending the target food to a user after sequencing the target food according to the second similarity from high to low.
4. A travel and entertainment service platform for a travel destination as set forth in claim 1 wherein said travel recommendation module is specifically configured to: mining scenic spot information in a tourist route, determining a tourist recommendation model according to travel service selected by a user, calculating first recommendation values of all tourist spots according to the determined tourist recommendation model, inputting real-time heat of the tourist spots and real-time heat of the tourist spots within a preset range into a heat prediction model to obtain predicted heat, determining second recommendation values of the tourist spots according to the preset heat, determining comprehensive recommendation values of the tourist spots according to the first recommendation values and the second recommendation values, and recommending the tourist spots to the user after the comprehensive recommendation values are ordered from small arrival.
5. A travel and entertainment service platform for a travel destination as recited in claim 1, wherein the travel service includes one or more of a rental car self-driving service, a package quality tour service system, and a bus follow tour service system.
6. A travel and purchase entertainment service platform for a travel destination according to claim 1, wherein said optimal human traffic is related to user preference traffic and casino standard traffic; the method for calculating the predicted people flow comprises the following steps: and acquiring the real-time traffic of the entertainment place and the real-time traffic of the same type of entertainment place within the preset distance range, and inputting a plurality of real-time traffic into a traffic prediction model to obtain predicted traffic.
7. The amusement ride service platform for traveling at a travel destination of claim 1 further comprising a toilet recommendation module for mining toilet information in the travel route, determining a distance between the user and the toilet, sequencing the toilets from small to large according to the distance, and marking a corresponding predicted occupancy for recommendation to the user.
8. A travel and purchase entertainment service platform for a travel destination as recited in claim 7, wherein the method of calculating the predicted occupancy comprises: acquiring real-time occupancy rate, search information and navigation information of a toilet, determining prediction time according to the distance, and calculating the prediction occupancy rate according to the prediction time, the real-time occupancy rate, the search information and the navigation information.
9. A travel and purchase entertainment service platform for a travel destination as recited in claim 8, further comprising an intelligent navigation module for navigating a user in real time.
10. A travel and purchase entertainment service platform for a travel destination according to claim 9, wherein said navigation module is compatible with a variety of navigation systems including a beidou navigation system, a GPS navigation system, a galileo navigation system and a gulrnus navigation system.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310788236.5A CN116796072A (en) | 2023-06-29 | 2023-06-29 | Travel and entertainment service platform for travel destination |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310788236.5A CN116796072A (en) | 2023-06-29 | 2023-06-29 | Travel and entertainment service platform for travel destination |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN116796072A true CN116796072A (en) | 2023-09-22 |
Family
ID=88047912
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310788236.5A Pending CN116796072A (en) | 2023-06-29 | 2023-06-29 | Travel and entertainment service platform for travel destination |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116796072A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117557413A (en) * | 2024-01-12 | 2024-02-13 | 华御祥茶科学研究院(深圳)有限公司 | Man-machine interaction method and system for cultural tourism integrated service cloud platform |
| CN117557413B (en) * | 2024-01-12 | 2024-06-04 | 华御祥茶科学研究院(深圳)有限公司 | Man-machine interaction method and system for cultural tourism integrated service cloud platform |
-
2023
- 2023-06-29 CN CN202310788236.5A patent/CN116796072A/en active Pending
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117557413A (en) * | 2024-01-12 | 2024-02-13 | 华御祥茶科学研究院(深圳)有限公司 | Man-machine interaction method and system for cultural tourism integrated service cloud platform |
| CN117557413B (en) * | 2024-01-12 | 2024-06-04 | 华御祥茶科学研究院(深圳)有限公司 | Man-machine interaction method and system for cultural tourism integrated service cloud platform |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US20220084407A1 (en) | Connected user communication and interface system with shuttle tracking application | |
| US20210223051A1 (en) | Systems and methods for vehicle ridesharing | |
| US20220366326A1 (en) | Systems and Methods of Multimodal Transportation Management | |
| US9972201B2 (en) | Method and system for legal parking | |
| US10275948B2 (en) | Method and system for refilling a parking meter | |
| US10395535B2 (en) | Method and system for legal parking | |
| JP6539092B2 (en) | Recommendation information management server and computer program | |
| US20020186144A1 (en) | System and method for automating a vehicle rental process | |
| JP7010194B2 (en) | Vehicle dispatch system, server and information processing method | |
| US20190266897A1 (en) | Drone usage in connected user and connected fleet communication and interface systems | |
| JP7173695B2 (en) | Information providing device, information providing system, information providing method, information providing program | |
| JP7201394B2 (en) | Information providing device, information providing system, information providing method, information providing program | |
| JP7096138B2 (en) | Information processing equipment, information processing method, information processing program | |
| US20220113146A1 (en) | Method and system for planning a journey | |
| US20080021756A1 (en) | Integrated supply chain business model and website for free auto rental | |
| US20200132494A1 (en) | Data generating apparatus, data generating system, data generation method, and non-transitory recording medium | |
| WO2009087489A1 (en) | Networking system | |
| CN116796072A (en) | Travel and entertainment service platform for travel destination | |
| Link et al. | Combining GPS tracking and surveys for a mode choice model: Processing data from a quasi-natural experiment in Germany | |
| Weinberger et al. | Parking-cruising caused congestion | |
| CA2445580A1 (en) | System and method for automating a vehicle rental process | |
| JP7311345B2 (en) | Database generation method, database generation device, database generation program, data analysis method, data analysis device and data analysis program | |
| Pašalić et al. | Information Systems and Technologies for Green Public Transportation | |
| Hoblík | Comparisons of Accessibility to Public Transit Stations by Ridesourcing and Its Competitors | |
| Evbogbai | Usage Trend Analysis and Forecasting for Ride Sharing: A case of Bildeleringen: An empirical approach using the car-specific data |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |