SM-PageRank Algorithm-Based User Interest Model for Mobile Smart Tourism Platform

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.