基于Hadoop实现大数据可视化分析的Web系统源码+项目说明+sql数据库.zip

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Hadoop

大数据可视化分析

67 浏览量 2023-12-28 14:21:58 上传评论 3 收藏 41.44MB ZIP 举报

【资源说明】基于Hadoop实现大数据可视化分析的Web系统源码+项目说明+sql数据库.zip 1.本项目利用Hadoop处理高校无线定位大数据,有效地将位置信息应用于学生时空行为模式挖掘，建立基于精准位置信息的行为数据挖掘计算模型。 2.基于Hadoop计算平台，并实现对大数据进行可视化分析的Web系统,采用ssm+mysql技术。 3.利用一些合适的算法实现校园热点区域提取、学生异常轨迹探测、人流迁徙分析及学生时空行为相似性分析推测等功能。 4.基于学校地图API和echarts插件可视化展现。校园热点区域提取采用基本的K-means算法，然后在校园地图上使用热力图形式呈现学生异常轨迹探测采用地理接口，筛选出不在建筑物范围内的定点。人流迁徙分析从wifi定点数据中根据用户特性、时间特性、建筑特性，归纳出有效完整轨迹，之后采用分段轨迹聚类算法，分析校内人员轨迹迁徙状况。在地图上使用echarts插件里的迁徙图在校园地图上动态呈现校园人群迁徙分布。学生时空行为相似性分析推测等功能采用基本的Word2Vec的Skip-Gram模型用于计算人员的基于时空行为的相似人群，根据人员的脱敏信息，进行分析与预测。使用该算法的主要工作就是基于WiFi定位数据构建自己的“语料库”。为什么可以采用Word2Vec的Skip-Gram模型的原因：解决用户时空行为相似问题一种行为的所有用户（学号） -> 分词处理后一段语言文字每个用户（学号）-> 每个关键词用户之间的亲密程度 -> 关键词相近概率可视化web端项目特点： 1.实现了在自己指定的地图范围上使用echerts插件，实现热力图，迁徙图。 2.基于wifi定位数据，使用了K-means算法、Word2Vec算法、轨迹分段聚类算法。 3.基于真实数据的课题实践。 4.Hadoop分布式计算的应用。【备注】 1.项目代码均经过功能验证ok，确保稳定可靠运行。欢迎下载使用体验！ 2.主要针对各个计算机相关专业，包括计算机科学、信息安全、数据科学与大数据技术、人工智能、通信、物联网等领域的在校学生、专业教师、企业员工。 3.项目具有丰富的拓展空间，不仅可作为入门进阶，也可直接作为毕设、课程设计、大作业、初期项目立项演示等用途。 4.当然也鼓励大家基于此进行二次开发。在使用过程中，如有问题或建议，请及时沟通。 5.期待你能在项目中找到乐趣和灵感，也欢迎你的分享和反馈！

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基于Hadoop实现大数据可视化分析的Web系统源码+项目说明+sql数据库.zip （1236个子文件）

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