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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.
Web log data, as a database of intentions of hundreds of millions of consumers, provides an effective quantitative index for studying consumer demand fluctuations. Taking Beijing’s second-hand housing as an example, this paper first builds an association model of website browsing log data and real estate transaction volumes. The purpose of purchase is to classify the website, measure the buyers’ attention and demand fluctuation with the number of visits (PV) and the number of users (UV) of different types of real estate websites, construct and prioritize the real estate transaction volume To test and build the real estate index is the complement of the existing indicator system for real estate developers, ordinary home buyers, government-related management decision-making guidance and reference.