摘要
针对民俗文化旅游资源信息量大,单机平台存在推荐效果差的缺陷,提出了基于Hadoop平台的民俗文化旅游资源推荐系统,首先采集民俗文化旅游资源信息,信息经预处理后导入Hadoop平台的分布式文件系统中,并采用查询时间和旅游资源一致度的信息权重建立协同过滤推荐算法,然后采用MapReduce编程模型并行实现民俗文化旅游资源推荐算法,从而获得民俗文化旅游资源推荐结果,最后进行了民俗文化旅游资源推荐仿真实验,结果表明,本文系统的民俗文化旅游资源推荐精度高,而且提升了民俗文化旅游资源推荐效率,具有重要的实际应用价值。
In view of the large amount of information of folk culture tourism resources and the poor recommendation effect of single platform,a recommendation system of folk culture tourism resources based on Hadoop platform is proposed.Firstly,the information of folk culture tourism resources is collected,and after preprocessing,it is imported into the distributed file system of Hadoop platform,and the information right of query time and tourism resource consistency is used to reconstruct The collaborative filtering recommendation algorithm is established,and then the MapReduce programming model is used to realize the recommendation algorithm of folk culture tourism resources in parallel,so as to obtain the recommendation results of folk culture tourism resources.Finally,the simulation experiment of folk culture tourism resources recommendation is carried out,the results show that the recommendation accuracy of folk culture tourism resources in this system is high,and the recommendation efficiency of folk culture tourism resources is improved It has important practical value.
作者
宫园园
艾宏志
Gong Yuanyuan;Ai Hongzhi(Yulin University,Yulin Shaanxi 719000,China)
出处
《科技通报》
2021年第2期62-66,共5页
Bulletin of Science and Technology
关键词
云计算技术
民俗文化
旅游资源
推荐系统
并行处理
cloud computing technology
folk culture
tourism resources
recommendation system
parallel processing
