| 数据挖掘视角下二手房市场与调控政策研究 |
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| 引用本文： | 赵凯,杨云帆,宋卓远,陈镱尹,杨秀璋,罗子江.数据挖掘视角下二手房市场与调控政策研究[J].情报探索,2020(4):87-93. |
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| 作者姓名： | 赵凯 杨云帆 宋卓远 陈镱尹 杨秀璋 罗子江 |
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| 作者单位： | 贵州财经大学信息学院 贵州贵阳 550025;贵州财经大学信息学院 贵州贵阳 550025;贵州财经大学信息学院 贵州贵阳 550025;贵州财经大学信息学院 贵州贵阳 550025;贵州财经大学信息学院 贵州贵阳 550025;贵州财经大学信息学院 贵州贵阳 550025 |
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| 基金项目： | 贵州省教育厅青年科技人才成长项目“实体和属性对齐方法的研究与实现”(项目编号:黔教合KY字﹝2016﹞172);贵州省研究生教育创新计划“贵州省二手房价格特征及购房决策模型研究”(项目编号:黔教合YJSCXJH﹝2019﹞066)成果。 |
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| 摘 要： | 目的/意义]旨在为促进国内二手房市场健康持续发展提供参考。方法/过程]以我国一二三线城市共20370条二手房交易数据为样本,利用数据挖掘方法将政策与市场相结合进行研究,采用Python2.7进行词云和K-means聚类分析,利用SPSS Clementine进行关联分析。结果/结论]宏观政策下我国二手房交易市场总体健康,自住需求大,但旅游城市房价居高。提出加强旅游城市的土地监管与房价调控;构建房屋核心价值评价指标;二手房购房相关税采用累进税率等对策建议。
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| 关 键 词： | 二手房 数据挖掘 K-means聚类 关联分析 |
Research on the Regulation and Control Policy of Second-hand Housing Based on Data Mining |
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| Zhao Kai,Yang Yunfan,Song Zhuoyuan,Chen Yiyin,Yang Xiuzhang,Luo Zijiang.Research on the Regulation and Control Policy of Second-hand Housing Based on Data Mining[J].Information Research,2020(4):87-93. |
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| Authors: | Zhao Kai Yang Yunfan Song Zhuoyuan Chen Yiyin Yang Xiuzhang Luo Zijiang |
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| Institution: | (School of Information Guizhou University of Finance and Economics,Guiyang Guizhou 550025) |
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| Abstract: | Purpose/significance]The paper is to provide references for the promotion of the domestic second-hand housing market healthy and sustainable development.Method/process]The paper takes 20370 second-hand housing transaction data in China’s first second and third-tier cities as samples uses data mining to research on policy and market uses Python2.7 to have word cloud and k-means clustering analysis and uses SPSS Clementine for correlation analysis.Result/conclusion]The results show that China’s second-hand housing market under the macroscopic policy is overall healthy the living demand is big but the tourist city house prices high.Based on these the paper puts forwards some suggestions including:strengthening land supervision and housing price control in tourist cities;constructing the index of house core value;using progressive tax rate for the second-hand house purchase. |
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| Keywords: | second-hand housing data mining K-means clustering association analysis |
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