基于公共大数据的居住物业风险预警模型研究——以沈阳市为例  

Research on Risk Early Warning Model of Real Estate Industry Based on Big Data—Taking Shenyang as an Example

作　　者：樊莹莹 李征宇[1] 孙平[1] 

机构地区：[1]沈阳建筑大学,信息与控制工程学院,辽宁 沈阳

出　　处：《数据挖掘》2022年第4期297-309,共13页Hans Journal of Data Mining

摘　　要：大数据时代的来临,房地产行业在资金、人员、规模方面的投入都受到了数据的影响。大数据可以提供实时数据分析、预测分析和基准报告。沈阳是东北地区最大的中心城市,对我国经济有着重要影响。建立风险预警模型,可以将风险系数降到最低,提升企业的核心竞争力。本文以沈阳市房产局、沈阳市统计局以及各大房地产企业官网中抓取的HTML字符串为数据来源进行处理,通过可视化的手段希望能够启迪企业领导、相关人员的工作,为企业的经济发展提供有价值的建议。依托于大数据背景下的房地产行业竞争情报风险预警体系能够对竞争情报预警过程进行实时跟踪,提高房地产行业的风险预警能力,使房地产行业免受不必要的损失,保证房地产企业的稳步发展。With the advent of the era of big data, the investment in the real estate industry in terms of capital, personnel and scale has been affected by data. Big data can provide real-time data analysis, predictive analysis, and benchmark reporting. Shenyang is the largest central city in Northeast China and has an important impact on my country’s economy. Establishing a risk early warning model can minimize the risk factor and enhance the core competitiveness of an enterprise. This article uses the HTML strings captured from the Shenyang Real Estate Bureau, Shenyang Statistics Bureau and the official websites of major real estate companies as the data source for processing. Through visual means, it is hoped that it can inspire the work of enterprise leaders and related personnel, and contribute to the economic development of enterprises. Provide valuable advice. Relying on the real estate industry competitive intelligence risk early warning system under the background of big data, it can track the competitive intelligence early warning process in real time, improve the risk early warning ability of the real estate industry, protect the real estate industry from unnecessary losses, and ensure the steady development of real estate enterprises.

关 键 词：房地产行业 风险预警体系 风险系数 房地产企业 居住物业 风险预警模型 竞争情报 大数据 

分 类 号：TP311.13[自动化与计算机技术—计算机软件与理论]