湖北农业科学 ›› 2021, Vol. 60 ›› Issue (9): 123-126.doi: 10.14088/j.cnki.issn0439-8114.2021.09.025

• 信息工程 • 上一篇    下一篇

基于数据挖掘的个性化旅游推荐系统研究与实现

欧丹   

  1. 四川信息职业技术学院消费者行为研究中心,四川 广元 628000
  • 收稿日期:2021-02-07 发布日期:2021-05-14
  • 作者简介:欧 丹(1986-),女,四川广元人,讲师,主要从事旅游管理工作,(电话)13618120778(电子信箱)shijie221@163.com。

Research and implementation of personalized travel recommendation system based on data mining

OU Dan   

  1. Consumer Behavior Research Center of Sichuan Vocational College of Information Technology, Guangyuan 628000, Sichuan,China
  • Received:2021-02-07 Published:2021-05-14

摘要: 为应对大数据时代大量多媒体照片、视频等为个性化旅游推荐带来的挑战,提出了基于数据挖掘的上下文感知个性化旅游推荐系统,该结构能根据用户给定的地理标记照片集合,定位和总结旅游地点,并建立每个用户的旅游历史,以获得其旅游偏好,从而进行上下文感知的个性化查询,推荐最适合其兴趣的旅游地点。通过仿真分析,将该方法与传统数据挖掘Apriori、Eclat、决策树及逻辑回归等算法进行了对比,仿真结果验证了该方法的优越性能,且最终平均推荐准确率能达到80%左右。

关键词: 数据挖掘, 个性化推荐, 智慧旅游, 上下文感知

Abstract: In order to deal with the challenge of personalized tourism recommendation brought by a large number of multimedia photos and videos in the era of big data, this paper proposes a context aware personalized tourism recommendation system based on data mining. The structure can locate and summarize the tourism location according to the given geographical tag photo set of users, and establish the tourism history of each user to obtain their tourism preferences, so as to promote the tourism. The personalized query based on context aware is used to recommend the most suitable tourist destination. Through simulation analysis, the proposed method was compared with traditional data mining algorithms such as Apriori, Eclat, decision tree and logistic regression. The simulation results verify the superior performance of the proposed method, and the final average recommendation accuracy can reach about 80%.

Key words: data mining, personalized recommendation, smart tourism, context awareness

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