基于海量网站日志数据的房地产需求指数研究

网络日志数据作为亿万消费者的意图数据库,为研究消费者需求波动提供了有效的量化指标,研究以北京市二手房为例,首先构建网站浏览日志数据与房地产成交量的关联模型,根据用户购房意图对网站进行分类,以不同类型房产网站的浏览次数(PV)、用户数(UV)等数据衡量购房者的关注及需求波动,构建房产成交量的先行、一致和滞后指数并对其关系进行检验,构建的房产指数是对现有指标体系的补充,为房地产开发商、普通购房者、政府相关管理部门提供决策指导和参考依据.

Real Estate Demanding Index Research Based on Massive Web Log Data

Web log data,as an intention database of hundreds millions of consumers,provide a quantitative measurement for the consumers' demand fluctuation.This study collected the web log data of 300 real estate related website,extracted PV and UV as the measurable indicator of buyer's attention and demanding,research on the correlation and lead-lag relationship weblog data and real estate transactions,finally build leading index,coincident index and lagging index to monitor the demanding of the real estate market.This study is a supplement to the existing index system,to provide guidance and reference for the real estate developers,ordinary property buyers and the relevant government departments.