Affiliation:
1. School of Tourism and Urban-Rural Planning, ZheJiang Gongshang University, Hangzhou 310018, China
Abstract
With the rapid development of China’s economy, people pay attention to their own quality of life, and tourism has become the first choice for people from all walks of life to relax themselves. Tourism travel has mainly developed from the form of travel agency registration to the form of online registration based on the network platform business model. Considering the value cocreation and the diversity of tourism enterprise platform, this paper puts forward the business model research of intelligent recommendation of tourism enterprise platform from the perspective of value cocreation. Firstly, the commonly used recommendation algorithms are introduced, which are collaborative filtering recommendation algorithm, content filtering recommendation algorithm, and association rule recommendation algorithm. Secondly, it analyzes the number of tourists and economic benefits of the business platform of tourism enterprises from April 2020 to April 2021 and also analyzes the business models of five modules under the tourism platform on different platforms. Finally, three recommendation algorithms are used to compare the comprehensive performance of five modules in different business models. Finally, we find that the rate of accuracy and recall of business is above 88%, which can have good economic benefits and provide customers with high-quality recommendation service and good satisfaction.
Subject
Multidisciplinary,General Computer Science
Cited by
4 articles.
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