Journal of Geo-information Science, Volume. 22, Issue 6, 1370(2020)

Extracting Mixed Topic Patterns within Downtown Beijing at the Block Level

Jingjing LIU1...1,2,2, Yusi LIU1,1,2,2, Disheng YI1,1,2,2, Jing YANG1,1,2,2, and Jing ZHANG1,1,22,* |Show fewer author(s)
Author Affiliations
  • 1. 首都师范大学 三维信息获取与应用教育部重点实验室,北京 100048
  • 1MOE Key Lab of 3D Information Acquisition and Application, Capital Normal University, Beijing 100048, China
  • 2. 首都师范大学资源环境与旅游学院,北京 100048
  • 2College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, China
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    Figures & Tables(18)
    Schematic diagram of block within the fourth ringroad of Beijing
    Schematic diagram of LDA topic model construction。。。
    Line graph of two methods to determine topic number in LDA model
    GVF in different classification numbers
    Block distribution within the fourth ringroad of Beijing by natural break method
    The proportion of three types of blocks in the structure of ring and administrative district within the fourth ringroad of Beijing
    The distribution of hierarchical clustering results and the histogram of mean value of various subjects in high mixed block
    The distribution of hierarchical clustering results and the histogram of mean value of various subjects in middle mixed block
    The distribution of hierarchical clustering results and the histogram of mean value of various subjects in low mixed block
    • Table 1. Introduction of POI Attributes within the fourth ringroad of Beijing in 2016

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      Table 1. Introduction of POI Attributes within the fourth ringroad of Beijing in 2016

      序号属性字段名称数据类型作用描述
      1OBJECTIDInteger唯一识别码
      2名称StringPOI点名称
      3xDouble经度
      4yDouble纬度
      5TypeStringPOI类型
    • Table 2. Categories of POIs within the fourth ringroad of Beijing in 2016

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      Table 2. Categories of POIs within the fourth ringroad of Beijing in 2016

      类别名称类别名称
      1茶座甜品13科研机构
      2KTV14培训机构
      3展览馆15体育场馆
      4公司企业16图书馆
      5大学17餐厅
      6风景名胜18文化宫
      7购物中心19基础教育
      8集市20银行
      9商铺21游乐园
      10酒吧22住宅区
      11酒店23医院
      12剧院
    • Table 3. Weight results of the first six POIs in typical blocks

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      Table 3. Weight results of the first six POIs in typical blocks

      街区1街区216街区345街区360
      POI类型权重POI类型权重POI类型权重POI类型权重
      游乐园10.33风景名胜7.45商铺13.99商铺17.8
      商铺6.82游乐园1.44餐厅7.49住宅区9.30
      公司企业6.62公司企业0.69酒吧5.83餐厅9.28
      餐厅3.41茶座甜品0.36住宅区5.57公司企业6.18
      风景名胜3.37基础教育0.20茶座甜品5.35酒店1.99
      茶座甜品3.30商铺0.17购物中心2.20茶座甜品1.48
    • Table 4. Top 5 POIs of some topics in LDA modeling results

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      Table 4. Top 5 POIs of some topics in LDA modeling results

      主题1主题2主题4主题7主题12主题14
      茶座甜品风景名胜酒吧图书馆购物中心科研机构
      餐厅餐厅餐厅住宅区商铺商铺
      商铺酒店茶座甜品餐厅餐厅茶座甜品
      培训机构剧院住宅区商铺茶座甜品餐厅
      公司企业公司企业商铺银行酒吧基础教育
      主题 15主题 16主题 17主题 19主题 20主题 21
      酒店游乐园公司企业住宅区体育场馆大学
      餐厅茶座甜品餐厅商铺餐厅餐厅
      商铺公司企业培训机构餐厅商铺商铺
      体育场馆商铺基础教育公司企业培训机构茶座甜品
      文化宫购物中心文化宫酒店公司企业公司企业
    • Table 5. Significance of multivariate linear regression equation for three kinds of mixed block

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      Table 5. Significance of multivariate linear regression equation for three kinds of mixed block

      回归模型FSig.
      高混合街区16.7060.000
      中等混合街区11.3990.000
      低混合街区9.4670.000
    • Table 6. Results of multiple linear regression for block mixing degree and 22 topics

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      Table 6. Results of multiple linear regression for block mixing degree and 22 topics

      变量非标准化系数标准误差标准系数tSig.
      高混和街区(R2=0.497)(常量)17.7630.54932.3360.000
      主题19-17.4632.849-0.464-6.1310.000
      主题20-6.7543.210-0.151-2.1040.037
      主题128.4402.6650.2143.1680.002
      主题49.3352.6830.2413.4790.001
      主题1-22.5744.687-0.433-4.8160.000
      主题21-7.6352.113-0.304-3.6140.000
      主题18-5.5852.114-0.188-2.6410.009
      主题137.6113.1180.1602.4400.016
      中等混合街区(R2=0.361)(常量)12.1320.40330.0690.000
      主题19-8.3291.575-0.366-5.2890.000
      主题20-4.7611.914-0.181-2.4880.014
      主题17-5.1421.869-0.186-2.7500.007
      主题106.5502.2900.1962.8610.005
      主题225.2752.3310.1602.2630.025
      主题134.5252.2650.1411.9980.047
      低混合街区(R2=0.425)(常量)4.5080.26517.0160.000
      主题520.4174.9150.3964.1540.000
      主题15.6281.8570.2883.0310.004
      主题311.4694.5560.2432.5170.014
      主题612.5334.6400.2602.7010.009
      主题2-2.4601.014-0.236-2.4260.018
    • Table 7. Mixed pattern of high mixed blocks

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      Table 7. Mixed pattern of high mixed blocks

      模式类型主题混合模式
      模式1(高1类)购物中心主题+住宅(商铺)主题+茶座餐厅主题+其他
      模式2(高2类)医院主题+茶座餐厅主题+其他
      模式3(高3类)住宅(商铺)主题+茶座餐厅主题+其他
      模式4(高4类)大学主题+茶座餐厅主题+住宅(商铺)主题+其他
      模式5(高5类)酒吧主题+茶座餐厅主题+其他
    • Table 8. Mixed pattern of medium mixed blocks

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      Table 8. Mixed pattern of medium mixed blocks

      模式类型主题混合模式
      模式1(中1类)公司企业主题+住宅(商铺)主题+银行主题+其他
      模式2(中2类)公司企业主题+住宅(商铺)主题+其他
      模式3(中3类)住宅(商铺)主题+公司企业主题+体育场馆主题+其他
      模式4(中4类)公司企业主题+体育场馆主题+其他
      模式5(中5类)休闲娱乐主题+公司企业主题+住宅(商铺)主题+其他
    • Table 9. Mixed pattern of low mixed blocks

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      Table 9. Mixed pattern of low mixed blocks

      模式类型主题混合模式
      模式1(低1类)住宅(集市)主题+展览馆主题+其他
      模式2(低2类)茶座餐厅主题+其他
      模式3(低3类)风景名胜主题+其他
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    Jingjing LIU, Yusi LIU, Disheng YI, Jing YANG, Jing ZHANG. Extracting Mixed Topic Patterns within Downtown Beijing at the Block Level[J]. Journal of Geo-information Science, 2020, 22(6): 1370

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    Paper Information

    Received: Oct. 11, 2019

    Accepted: --

    Published Online: Nov. 12, 2020

    The Author Email: ZHANG Jing (zhangjing5946@sina.com)

    DOI:10.12082/dqxxkx.2020.190594

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