摘要
线上营销平台房源数据离散分布,帮助消费者正确搜集房源信息、预测房价、制定购房决策对于提高购房效率具有重要作用。以房地产线上营销平台的结构化房产信息为研究对象,首先采用网络爬虫技术Scrapy框架采集并处理小区信息、房源信息等数据,选取其中具有代表性的特征,基于最小二乘法建立并优化多元线性回归模型,进行房产价格预测;然后开发一个基于Vue框架的Web端房产信息分析与展示系统,后端采用SpringBoot框架连接关系型数据库MySQL存储数据。最终实现了房源信息检索、比较及数据可视化功能,为购房者提供了房源价格展示、分析以及购房辅助决策服务。
The discrete distribution of housing data on online marketing platforms plays an important role in helping consumers correctly col⁃lect housing information,predict housing prices,and make purchasing decisions to improve purchasing efficiency.Taking the structured real estate information of the real estate online marketing platform as the research object,firstly,the web crawler technology Scrapy framework is used to collect and process data such as community information and housing source information,select the representative characteristics,es⁃tablish and optimize the multiple linear regression model based on the least square method,and predict the real estate price;Then we devel⁃oped a web end real estate information analysis and display system based on Vue framework.The back-end uses the SpringBoot framework to connect the relational database MySQL to store data.Finally,we realized the functions of house source information retrieval,comparison and data visualization,providing buyers with house source price display,analysis and purchase auxiliary decision-making services.
作者
毛晨希
董可扬
宋瑾钰
MAO Chenxi;DONG Keyang;SONG Jinyu(Qixin School,Zhejiang Sci-Tech University;School of Computer Science and Technology,Zhejiang Sci-Tech University,Hangzhou 310018,China)
出处
《软件导刊》
2023年第7期104-111,共8页
Software Guide
基金
浙江理工大学高等教育科学研究课题项目(GJYB2105)。
