References
- Alba-Fernández, M. V., Ariza-López, F. J., Jiménez-Gamero, M. D., & Rodríguez-Avi, J. (2016). On the similarity analysis of spatial patterns. Spatial Statistics, 18, 352–362. https://doi.org/10.1016/j.spasta.2016.07.004
- Alter, O., Brown, P. O., & Botstein, D. (2000). Singular value decomposition for genomewide expression data processing and modeling. Proceedings of the National Academy of Sciences of the United States of America, 97(18), 10101–10106. https://doi.org/10.1073/pnas.97.18.10101
- Andresen, M. A. (2009). Testing for similarity in area-based spatial patterns: A nonparametric Monte Carlo approach. Applied Geography, 29(3), 333–345. https://doi.org/10.1016/j.apgeog.2008.12.004
- Apparicio, P., Gelb, J., Dubé, A. S., Kingham, S., Gauvin, L., & Robitaille, É. (2017). The approaches to measuring the potential spatial access to urban health services revisited: Distance types and aggregation-error issues. International Journal of Health Geographics, 16(1), 32. https://doi.org/10.1186/s12942-017-0105-9
- Bailey, T. C., & Gatrell, A. C. (1995). Interactive Spatial Data Analysis. Longman Scientific. https://doi.org/10.1016/S0098-3004(96)80468-7
- Bu, J., Shen, X., Xu, B., Chen, C., He, X., & Cai, D. (2016). Improving collaborative recommendation via user-item subgroups. IEEE Transactions on Knowledge & Data Engineering, 28(9), 2363–2375. https://doi.org/10.1109/TKDE.2016.2566622
- Camacho, K., Portelli, R., Shortridge, A., & Takahashi, B. (2021). Sentiment mapping: Point pattern analysis of sentiment classified Twitter data[j]. Cartography and Geographic Information Science, 48(3), 241–257. https://doi.org/10.1080/15230406.2020.1869999
- Castelli, V., & Bergman, L. D. (2002). Image Databases: Search and Retrieval of Digital Imagery. John Wiley & Sons. https://doi.org/10.1002/0471224634
- Chen, Y., Wang, L., & Dong, M. (2010). Non-negative matrix factorization for semisupervised heterogeneous data coclustering. IEEE Transactions on Knowledge & Data Engineering, 22(10), 1459–1474. https://doi.org/10.1109/TKDE.2009.169
- Cova, T. J., & Goodchild, M. F. (2002). Extending geographical representation to include fields of spatial objects. International Journal of Geographical Information Systems, 16(6), 509–532. https://doi.org/10.1080/13658810210137040
- Dhillon, I. S., 2001. Co-Clustering documents and words using bipartite spectral graph partitioning. In: ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. ACM, 269–274. https://doi.org/10.1145/502512.502550
- Dong, W., Liao, H., Liu, B., Zhan, Z., Liu, H., Meng, L., & Liu, Y. (2020). Comparing pedestrians’ gaze behavior in desktop and in real environments[j]. Cartography and Geographic Information Science, 47(5), 432–451. https://doi.org/10.1080/15230406.2020.1762513
- Duda, R. O., Hart, P. E., & Stork, D. G. (2000). Pattern Classification. Wiley. https://doi.org/10.1007/978-3-319-57027-3_4
- Egenhofer, M. J. (1997). Query processing in spatial-query-by-sketch. Journal of Visual Languages & Computing, 8(4), 403–424. https://doi.org/10.1006/jvlc.1997.0054
- Fuentes-Santos, I., González-Manteiga, W., & Mateu, J. (2017). A nonparametric test for the comparison of first-order structures of spatial point processes. Spatial Statistics, 22, 240–260. https://doi.org/10.1016/j.spasta.2017.02.007
- Gatrell, A., Bailey, T., Diggle, P., & Rowlingson, B. (1996). Spatial point pattern analysis and its application in geographical epidemiology. Transactions of the Institute of British Geographers, 21(1), 256–274. https://doi.org/10.2307/622936
- Golub, G. H., & Van Loan, C. F. (1996). Matrix Computations. Johns Hopkins Univ Press. https://doi.org/10.1007/978-1-4612-5118-7_5
- Jiang, K., Zheng, Z., & Li, L. (2017). Topological structure matching measure between two graphs. Computer-Aided Civil & Infrastructure Engineering, 32(6), 515–524. https://doi.org/10.1111/mice.12270
- Joshi, D., Soh, L. K., Samal, A., & Zhang, J. (2014). A dissimilarity function for geospatial polygons. Knowledge & Information Systems, 41(1), 153–188. https://doi.org/10.1007/s10115-013-0666-2
- Kilic, B., & Gülgen, F. (2020). Investigating the quality of reverse geocoding services using text similarity techniques and logistic regression analysis[j]. Cartography and Geographic Information Science, 47(4), 336–349. https://doi.org/10.1080/15230406.2020.1746198
- Lee, D. D., & Seung, H. S. (1999). Learning the parts of objects by nonnegative matrix factorization. Nature, 401(6775), 788–791. https://doi.org/10.1038/44565
- Leslie, T. F., & Kronenfeld, B. J. (2011). The colocation quotient: A new measure of spatial association between categorical subsets of points. Geographical Analysis, 43(3), 306–326. https://doi.org/10.1111/j.1538-4632.2011.00821.x
- Li, Z. (2007). Algorithmic Foundation of Multi-Scale Spatial Representation. CRC. https://doi.org/10.1201/9781420008432
- Liu, G., Lin, Z., Yan, S., Sun, J., Yu, Y., & Ma, Y. (2013). Robust recovery of subspace structures by low-rank representation. IEEE Transactions on Pattern Analysis & Machine Intelligence, 35(1), 171–184. https://doi.org/10.1109/TPAMI.2012.88
- Li, L. X., Wu, L., Zhang, H. S., & Wu, F. X. (2014). A fast algorithm for nonnegative matrix factorization and its convergence. IEEE Transactions on Neural Networks & Learning Systems, 25(10), 1855. https://doi.org/10.1109/TNNLS.2013.2296627
- Luo, X., Zhou, M. C., Leung, H., Xia, Y., Zhu, Q., You, Z., & Li, S. (2016). An incremental-and-static-combined scheme for matrix-factorization-based collaborative filtering. IEEE Transactions on Automation Science & Engineering, 13(1), 333–343. https://doi.org/10.1109/TASE.2014.2348555
- Lu, Y., Yuan, C., Zhu, W., & Li, X. (2018). Structurally incoherent low-rank nonnegative matrix factorization for image classification. IEEE Transactions on Image Processing, 27(11), 5248–5260. https://doi.org/10.1109/TIP.2018.2855433
- Mahoney, M. W., & Drineas, P. (2009). Cur matrix decompositions for improved data analysis. Proceedings of the National Academy of Sciences of the United States of America, 106(3), 697. https://doi.org/10.1073/pnas.0803205106
- Markovsky, I. (2008). Structured low-rank approximation and its applications. Automatica, 44(4), 891–909. https://doi.org/10.1016/j.automatica.2007.09.011
- Mateu, J., Schoenberg, F. P., Diez, D. M., González, J. A., & Lu, W. (2015). On measures of dissimilarity between point patterns: Classification based on prototypes and multidimensional scaling. Biometrical Journal, 57(2), 340–358. https://doi.org/10.1002/bimj.201300150
- Nakaya, T., & Yano, K. (2010). Visualising crime clusters in a space‐time cube: An exploratory data‐analysis approach using space‐time kernel density estimation and scan statistics. Transactions in GIS, 14(3), 223–239. https://doi.org/10.1111/j.1467-9671.2010.01194.x
- Pang, J., Huang, J., Yang, X., Wang, Z., Yu, H., & Huang, Q., Yin, B. (2017). Discovering fine-grained spatial pattern from taxi trips: Where point process meets matrix decomposition and factorization. IEEE Transactions on Intelligent Transportation Systems, 99, 1–12. https://doi.org/10.1109/TITS.2017.2771262
- Pavlidis, T. (1982). Algorithms for graphics and image processing. Computer Science Press. https://doi.org/10.1109/PROC.1983.12734
- Ranacher, P., & Tzavella, K. (2014). How to compare movement? A review of physical movement similarity measures in geographic information science and beyond [J]. Cartography and Geographic Information Science, 41(3), 286–307. https://doi.org/10.1080/15230406.2014.890071
- Ripley, B. D. (1976). The second-order analysis of stationary point processes. Journal of Applied Probability, 13(2), 255–266. https://doi.org/10.2307/3212829
- Ripley, B. (1981). Spatial Statistics. Wiley. https://doi.org/10.2307/3151630
- Shekhar, S., & Chawla, S. (2003). Spatial databases: A tour. Prentice Hall. https://doi.org/10.1016/B0-12-369398-5/00337-6
- Tobler, W. R. (1970). A computer movie simulating urban growth in the Detroit region. Economic Geography, 46(sup1), 234–240. https://doi.org/10.2307/143141
- Tu, X., Chen, Z., Wang, B., & Xu, C. (2020). Mining regional patterns of land use with adaptive adjacent criteria[j]. Cartography and Geographic Information Science, 47(5), 418–431. https://doi.org/10.1080/15230406.2020.1761452
- Wei, C. P., Chen, C. F., & Wang, Y. C. (2014). Robust face recognition with structurally incoherent low-rank matrix decomposition. IEEE Transactions on Image Processing, 23(8), 3294–3307. https://doi.org/10.1109/TIP.2014.2329451
- Yang, L., Jing, L., & Ng, M. K. (2015). Robust and non-negative collective matrix factorization for text-to-image transfer learning. IEEE Transactions on Image Processing, 24(12), 4701–4714. https://doi.org/10.1109/TIP.2015.2465157
- Yan, H., & Weibel, R. (2008). An algorithm for point cluster generalization based on the Voronoi diagram. Computers & Geosciences, 34(8), 939–954. https://doi.org/10.1016/j.cageo.2007.07.008
- Yu, W. (2018). Quality assessment in point feature generalization with pattern preserved. Transactions in GIS, 22(3), 872–888. https://doi.org/10.1111/tgis.12339
- Zhang, Y., Du, B., Zhang, L., & Wang, S. (2016). A low-rank and sparse matrix decomposition-based mahalanobis distance method for hyperspectral anomaly detection. IEEE Transactions on Geoscience & Remote Sensing, 54(3), 1376–1389. https://doi.org/10.1109/TGRS.2015.2479299
- Zhang, Y., Yu, W., & Zhu, D. (2022). Terrain feature-aware deep learning network for digital elevation model superresolution. ISPRS Journal of Photogrammetry and Remote Sensing, 189, 143–162. https://doi.org/10.1016/j.isprsjprs.2022.04.028
- Zhao, R., Ai, T. H., Yu, W. H., He, Y. K., & Shen, Y. L. (2020). Recognition of building group patterns using graph convolutional network. Cartography and Geographic Information Science, 47(5), 400–417. https://doi.org/10.1080/15230406.2020.1757512
- Zheng, Y., Liu, Y., Yuan, J., & Xie, X., 2011. Urban computing with taxicabs. In: International Conference on Ubiquitous Computing. ACM, 89–98. https://doi.org/10.1145/2030112.2030126