[1] FU Chun, TU Xiaoqiang, HUANG An. Identification and characterization of production-living-ecological space in a central urban area based on POI data:a case study for Wuhan, China[J]. Sustainability, 2021, 13(14):7691. [2] 宋辞, 裴韬. 北京市多尺度中心特征识别与群聚模式发现[J]. 地球信息科学学报, 2019, 21(3):384-397. SONG Ci, PEI Tao. Exploring polycentric characteristic and residential cluster patterns of urban city from big data[J]. Journal of Geo-Information Science, 2019, 21(3):384-397. [3] 禹文豪, 艾廷华, 刘鹏程, 等. 设施POI分布热点分析的网络核密度估计方法[J]. 测绘学报, 2015, 44(12):1378-1383, 1400.DOI:10.11947/j.AGCS.2015.20140538. YU Wenhao, AI Tinghua, LIU Pengcheng, et al. Network kernel density estimation for the analysis of facility POI hotspots[J]. Acta Geodaetica et Cartographica Sinica, 2015, 44(12):1378-1383, 1400.DOI:10.11947/j.AGCS.2015.20140538. [4] 蔡建南, 刘启亮, 徐枫, 等. 多层次空间同位模式自适应挖掘方法[J]. 测绘学报, 2016, 45(4):475-485.DOI:10.11947/j.AGCS.2016.20150337. CAI Jiannan, LIU Qiliang, XU Feng, et al. An adaptive method for mining hierarchical spatial co-location patterns[J]. Acta Geodaetica et Cartographica Sinica, 2016, 45(4):475-485.DOI:10.11947/j.AGCS.2016.20150337. [5] 赵卫锋, 李清泉, 李必军. 利用城市POI数据提取分层地标[J]. 遥感学报, 2011, 15(5):973-988. ZHAO Weifeng, LI Qingquan, LI Bijun. Extracting hierarchical landmarks from urban POI data[J]. Journal of Remote Sensing, 2011, 15(5):973-988. [6] HOU Gang, CHEN Lizhu. Regional commercial center identification based on POI big data in China[J]. Arabian Journal of Geosciences, 2021, 14(14):1360. [7] 杨小明. 电子地图兴趣点分类自动标注算法研究[J]. 网络安全技术与应用, 2015(3):13-15. YANG Xiaoming. Research on automatic labeling algorithm of electronic map points of interest classification[J]. Network Security Technology & Application, 2015(3):13-15. [8] KRUMM J, ROUHANA D. Placer:semantic place labels from diary data[C]//Proceedings of 2013 ACM International Joint Conference on Pervasive and Ubiquitous Computing. Zurich, Switzerland:ACM Press, 2013:163-172. [9] KRUMM J, ROUHANA D, CHANG Mingwei. Placer:semantic place labels beyond the visit[C]//Proceedings of 2015 IEEE International Conference on Pervasive Computing and Communications (PerCom).St. Louis, MO, USA:IEEE, 2015:11-19. [10] HE Tieke, YIN Hongzhi, CHEN Zhenyu, et al. A spatial-temporal topic model for the semantic annotation of POIs in LBSNs[J]. ACM Transactions on Intelligent Systems and Technology, 2017, 8(1):1-24. [11] HEGDE V, PARREIRA J X, HAUSWIRTH M. Semantic tagging of places based on user interest profiles from online social networks[C]//Proceedings of the 35th European conference on Advances in Information Retrieval. New York,NY,USA:ACM Press,2013:218-229. [12] YE M, SHOU D, LEE W C, et al. On the semantic annotation of places in location-based social networks[C]//Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Hong Kong, China:ACM Press,2011. [13] SHI Shaochong, CHEN Peng, ZENG Zhaolong, et al. STL-FNN:an intelligent prediction model of daily theft level[C]//Proceedings of the 9th International Conference on Computer Engineering and Networks. Singapore:Springer Singapore, 2020:703-711. [14] TOMEK I.Two modifications of CNN[J]. IEEE Transactions on Systems, Man, and Cybernetics, 1976, SMC-6(11):769-772. [15] CHAWLA N V, BOWYER K W, HALL L O, et al. SMOTE:synthetic minority over-sampling technique[J]. Journal of Artificial Intelligence Research, 2002, 16:321-357. [16] THAI-NGHE N, GANTNER Z, SCHMIDT-THIEME L. Cost-sensitive learning methods for imbalanced data[C]//Proceedings of 2010 International Joint Conference on Neural Networks (IJCNN).Barcelona, Spain:IEEE, 2010:1-8. [17] BREIMAN L. Bagging predictors[J]. Machine Learning, 1996, 24(2):123-140. [18] SCHAPIRE R E. The strength of weak learnability[C]//Proceedings of the Second Annual Workshop on Computational Learning Theory. Amsterdam Netherlands:Elsevier, 1989,5(2):197-227. [19] BREIMAN L. Random forests[J]. Machine Learning, 2001, 45(1):5-32. [20] PORTA S, STRANO E, IACOVIELLO V, et al. Street centrality and densities of retail and services in bologna, Italy[J]. Environment and Planning B:Planning and Design, 2009, 36(3):450-465. [21] OKABE A, SATOH T, SUGIHARA K. A kernel density estimation method for networks, its computational method and a GIS-based tool[J]. International Journal of Geographical Information Science, 2009, 23(1):7-32. [22] KASHIAN A, RAJABIFARD A, RICHTER K F, et al. Automatic analysis of positional plausibility for points of interest in OpenStreetMap using coexistence patterns[J]. International Journal of Geographical Information Science, 2019, 33(7):1420-1443. [23] 梁杰, 陈嘉豪, 张雪芹, 等. 基于独热编码和卷积神经网络的异常检测[J]. 清华大学学报(自然科学版), 2019, 59(7):523-529. LIANG Jie, CHEN Jiahao, ZHANG Xueqin, et al. One-hot encoding and convolutional neural network based anomaly detection[J]. Journal of Tsinghua University (Science and Technology), 2019, 59(7):523-529. [24] FRIEDMAN J, HASTIE T, TIBSHIRANI R. Additive logistic regression:a statistical view of boosting (With discussion and a rejoinder by the authors)[J]. The Annals of Statistics, 2000, 28(2):1-6. [25] MYLES A J, FEUDALE R N, LIU Yang, et al. An introduction to decision tree modeling[J]. Journal of Chemometrics, 2004, 18(6):275-285. [26] VISHWANATHAN S V M, NARASIMHA MURTY M. SSVM:a simple SVM algorithm[C]//Proceedings of the 2002 International Joint Conference on Neural Networks.Honolulu, HI, USA:IEEE, 2002:2393-2398. [27] 王圣音, 刘瑜, 陈泽东, 等. 大众点评数据下的城市场所范围感知方法[J]. 测绘学报, 2018, 47(8):1105-1113.DOI:10.11947/j.AGCS.2018.20180110. WANG Shengyin, LIU Yu, CHEN Zedong, et al. Representing multiple urban places' footprints from dianping.com data[J]. Acta Geodaetica et Cartographica Sinica, 2018, 47(8):1105-1113.DOI:10.11947/j.AGCS.2018.20180110. [28] 朱婷婷, 涂伟, 乐阳, 等. 利用地理标签数据感知城市活力[J]. 测绘学报, 2020, 49(3):365-374.DOI:10.11947/j.AGCS.2020.20190051. ZHU Tingting, TU Wei, YUE Yang, et al. Sensing urban vibrancy using geo-tagged data[J]. Acta Geodaetica et Cartographica Sinica, 2020, 49(3):365-374. DOI:10.11947/j.AGCS.2020.20190051. |