Abstract
Smart tourism can provide high-quality and convenient services for different tourists, and tourism itinerary planning system can simplify tourists’ tourism preparation. In order to improve the limitation of the recommendation dimension of traditional travel planning system, this paper designs a mixed user interest model on the premise of traditional user interest modeling and combines various attributes of scenic spots to form personalized recommendation of scenic spots. Then, it uses heuristic travel planning cost-effective method to construct the corresponding travel planning system for travel planning. In terms of the accuracy rate of travel planning recommendation, the accuracy rate of multidimensional hybrid travel recommendation algorithm is 0.984, and the missing rate is 0. When the travel cost and travel time are the same and the number of scenic spots is 20–30, the memory occupation of MH algorithm is only 1/2 of that of TM algorithm. The results show that the multidimensional hybrid travel recommendation algorithm can improve the personalized travel planning of users and the travel time efficiency ratio. The results of this study have a certain reference value in improving user satisfaction with the travel planning system and reducing user interaction.
Highlights
Smart tourism is to actively perceive the information of tourism resources, tourism economy, tourism activities, and tourists by using new technologies such as cloud computing and the Internet of things, through the Internet/mobile Internet and with the help of portable terminal Internet access equipment. rough timely release, people can understand this information and arrange and adjust work and tourism plans in a timely manner, so as to achieve the effect of intelligent perception and convenient utilization of all kinds of tourism information. e construction and development of smart tourism will eventually be reflected in three levels: tourism management, tourism service, and tourism marketing
Database interest measurement of multidimensional features solves the problems of data sparsity and recommendation efficiency. is calculation method can adapt to both extremely sparse data sets and large data sets and improve the adaptability and scalability of the recommended model. is paper selects user based collaborative filtering recommendation algorithm (UB-CF), geographic location modeling recommendation algorithm (GEO-INFO), friend relationship based recommendation algorithm (SNS-INFO), and multidimensional hybrid travel itinerary recommendation algorithm (MH) as the experimental objects to compare the accuracy and missing rate of the four travel itinerary planning algorithms
To sum up, compared with the accuracy of SNS-INFO recommendation algorithm, the accuracy of multidimensional hybrid travel itinerary recommendation algorithm is improved by 0.706, and the missing rate is reduced by 0.73, which indicates that the travel itinerary planning completed by multidimensional hybrid travel itinerary recommendation algorithm can accurately meet the needs of users for travel itinerary planning and formulate personalized travel strategies in line with users, which is conducive to improving the quality of travel customer satisfaction
Summary
Smart tourism is to actively perceive the information of tourism resources, tourism economy, tourism activities, and tourists by using new technologies such as cloud computing and the Internet of things, through the Internet/mobile Internet and with the help of portable terminal Internet access equipment. rough timely release, people can understand this information and arrange and adjust work and tourism plans in a timely manner, so as to achieve the effect of intelligent perception and convenient utilization of all kinds of tourism information. e construction and development of smart tourism will eventually be reflected in three levels: tourism management, tourism service, and tourism marketing. Smart tourism is to actively perceive the information of tourism resources, tourism economy, tourism activities, and tourists by using new technologies such as cloud computing and the Internet of things, through the Internet/mobile Internet and with the help of portable terminal Internet access equipment. E construction and development of smart tourism will eventually be reflected in three levels: tourism management, tourism service, and tourism marketing It is based on the integrated communication and information technology, centered on the interactive experience of tourists, guaranteed by the integrated industry information management, and characterized by encouraging industrial innovation and promoting the upgrading of industrial structure. Smart tourism is to actively perceive tourism related information by using new technologies, such as mobile cloud computing and the Internet, and portable terminal Internet devices. In the organization and purpose of tourism destination, there are some deficiencies in the way of land planning [3, 4]. erefore, to explore a more effective and comprehensive travel recommendation algorithm is of great significance for improving users’ satisfaction with the travel recommendation system, reducing user interaction, enhancing the scientific and effective travel planning, and meeting the personalized needs of users
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