面向智慧商圈的多源数据采集与综合评价系统
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摘要
针对智慧商圈建设过程中各类数据需求,设计一个多源数据采集与综合评价系统。利用Pyspider框架采集数据,基于二分思想和多边形规则对采集的数据进行商圈边界探测、商圈内点判定,通过构建一套兴趣点与商圈的映射规则,解决不同数据源对商圈定义不同的问题。利用融合后的数据,从60多个维度进行商圈结构分析和对标分析。实验结果表明,该系统能为各类分析模型提供数据支持,从而为各类商业行为提供决策支撑。
Focusing on the data requirement of intelligent business district's construction,this paper designs a multisource data acquisition and comprehensive evaluation system. The system uses the Pyspider framework to collect data.Based on the idea of dichotomy and the rules of polygon,the business district boundary detection and the inner district point determination are conducted and used to set up the mapping rule between Point of Interest( POI) and business district. In this way,the different definition of business district from different data sources can be solved. Furthermore,60 features are extracted from the integrated data to analyze the structure and comparison of business districts. Experimental results showthe system can provide data support for various types of analysis models which can provide some decision support for business behaviors.
Focusing on the data requirement of intelligent business district's construction,this paper designs a multisource data acquisition and comprehensive evaluation system. The system uses the Pyspider framework to collect data.Based on the idea of dichotomy and the rules of polygon,the business district boundary detection and the inner district point determination are conducted and used to set up the mapping rule between Point of Interest( POI) and business district. In this way,the different definition of business district from different data sources can be solved. Furthermore,60 features are extracted from the integrated data to analyze the structure and comparison of business districts. Experimental results showthe system can provide data support for various types of analysis models which can provide some decision support for business behaviors.
引文
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[2]张珣.商业GIS设计及其商业地理分析---以北京市为例[D].北京:中国科学院研究生院,2014.
[3]李依.基于GIS的零售业选址问题分析[J].商业时代,2016(7):22-23.
[4]金敏.基于等级加权Voronoi图模型的商圈划分研究[D].杭州:浙江大学,2016.
[5]鲁成,汪泓,柳琳.零售商圈辐射范围比较模型构建与上海商圈实证[J].经济地理,2015,35(11):133-137.
[6]姚丽贞,乐阳.基于主成分Logistic模型的商圈吸引力因子分析[J].地球信息科学学报,2016,18(11):1494-1499.
[7]陈以增,于齐.基于SERVQUAL模型的商圈服务质量模糊综合评价[J].上海大学学报(自然科学版),2014,20(3):296-303.
[8]李长东,孙爱庐,贾莹,等.城市中心商圈空间品质评价意义及指标体系研究[J].西部人居环境学刊,2014,29(4):98-106.
[9]MENG X F,CI X.Big data management:concepts,techniques and challenges[J].Journal of Computer Research and Development,2013,50(1):146-169.
[10]王元卓,靳小龙,程学旗.网络大数据:现状与展望[J].计算机学报,2013,36(6):1125-1138.
[11]HOU D Y,WU H,CHEN J,et al.A focused crawler for borderlands situation information w ith geographical properties of place names[J].Sustainahility,2014,6(10):6529-6552.
[12]PICCININI H,CASANOVA M,LEME L P,et al.Publishing deep web geographic data[J].Geoinformatica,2014,18(4):769-792.
[13]夏火松,李保国.基于Python的动态网页评价爬虫算法[J].软件工程,2016,19(2):43-46.
[14]杨俊峰,黎建辉,杨风雷,等.深层网站Ajax页面数据采集研究综述[J].计算机应用研究,2013,30(6):1606-1610,1616.
[15]刘彤,张阳,孙琦,等.基于Hadoop的可视化Deep Web采集平台设计[J].计算机工程与科学,2016,38(2):217-223.