Abstract
Smart tourism, also known as smart tourism, actively captures tourism activities, tourists, tourism economy, tourism resources, and other information through mobile Internet and mobile terminal Internet of things devices and emerging technologies such as cloud computing and Internet of things. In order to release the intelligent tourism information in time, let the masses know the information in time, and adjust the work and tourism plan in time, this paper proposes SM-PageRank algorithm and secondary ranking based on user interest model, in order to study the accuracy of tourism information retrieval. The methods used in this paper include the principle of three weighted information fusion algorithms, LBS technology, and the design of intelligent tourism system. The function of information fusion algorithm is to find the global optimal solution for travel routing. LBS technology collects real-time tourism information through some entity sensors. Through information retrieval experiment and fusion technology solution experiment, the results show that the SM-PageRank algorithm and the secondary sorting based on user interest model proposed in this paper improve the average accuracy by 20.1% compared with the traditional algorithm and 2.6% compared with Google search. The Internet of things fusion algorithm gives a line planning set with standard deviation of 0.4 for the set of travel days with standard deviation of 1.92.
Highlights
Tourism has become one of the leisure activities of most people
The amount of tourism information stored on the Internet is becoming more and more complex, and users pay more and more attention to the relevance of tourism information provided by the search platform
With the increase in the number of web pages, manual classification cannot keep up with the pace of the times, search engines have evolved to text retrieval, and SM-PageRank sorting algorithm came into being
Summary
Tourism has become one of the leisure activities of most people. Users usually retrieve tourism information on the search platform when planning their trip. Providing users with the most relevant and reliable information source as search results and allowing them to really enjoy smart tourism is one of the urgent problems to be solved by the search platform. With the increase in the number of web pages, manual classification cannot keep up with the pace of the times, search engines have evolved to text retrieval, and SM-PageRank sorting algorithm came into being. This algorithm has a very good effect on ranking web pages, so it is often used to solve the problem of intelligent tourism systems. This article applies the Internet of things technology to tourism route planning, so that the average travel time of each scenic spot can be well controlled and has high stability
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