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Hongting Niu, Junming Liu, Yanjie Fu, Yanchi Liu, B. Lang (2016)
Exploiting Human Mobility Patterns for Gas Station Site Selection
Petko Georgiev, Anastasios Noulas, Cecilia Mascolo (2014)
Where businesses thrive: Predicting the impact of the olympic games on local retailers through location-based services dataProceedings of the International AAAI Conference on Web and Social Media. AAAI Press
Jovian Lin, R. Oentaryo, Ee-Peng Lim, Casey Vu, Adrian Vu, A. Kwee (2016)
Where is the Goldmine?: Finding Promising Business Locations through Facebook Data AnalyticsProceedings of the 27th ACM Conference on Hypertext and Social Media
Jing Yuan, Yu Zheng, Xing Xie (2012)
Discovering regions of different functions in a city using human mobility and POIs
Ying Shan, T. Ryan Hoens, Jian Jiao, Haijing Wang, Dong Yu, J. C. Mao (2016)
Deep crossing: Web-scale modeling without manually crafted combinatorial featuresProceedings of the 22nd ACM SIGKDD International Conference. ACM
Can Chen, Junming Liu, Qiao Li, Yijun Wang, Hui Xiong, Shanshan Wu (2017)
Warehouse site selection for online retailers in inter-connected warehouse networksProceedings of the International Conference on Data Mining. IEEE
Yanan Xu, Yanmin Zhu (2016)
When remote sensing data meet ubiquitous urban data: Fine-grained air quality inferenceProceedings of the 2016 IEEE International Conference on Big Data. IEEE, 2016
Miao Tian, Zhiwen Yu, Zhu Wang, Bin Guo (2015)
Combining social media and location-based services for shop type recommendationAdjunct Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2015 ACM International Symposium on Wearable Computers
S. Porta, V. Latora, Fahui Wang, Salvador Rueda, E. Strano, S. Scellato, Alessio Cardillo, E. Belli, Francisco Cardenas, Berta Cormenzana, L. Latora (2012)
Street Centrality and the Location of Economic Activities in BarcelonaUrban Studies, 49
Philippe Salembier, Sergi Liesegang, Carlos López-Martínez (2018)
Ship detection in SAR images based on Maxtree representation and graph signal processingIEEE Transactions on Geoscience and Remote Sensing, 57
Yu Zheng, Furui Liu, Hsun-Ping Hsieh (2013)
U-Air: when urban air quality inference meets big dataProceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
S. Ho, A. Talukder (2008)
Automated cyclone discovery and tracking using knowledge sharing in multiple heterogeneous satellite data
Lingzi Hong, Enrique Frias-Martinez, Vanessa Frias-Martinez (2016)
Topic models to infer socio-economic mapsProceedings of the 13th AAAI Conference on Artificial Intelligence. AAAI Press
Yanjie Fu, Guannan Liu, S. Papadimitriou, Hui Xiong, Yong Ge, Hengshu Zhu, Chen Zhu (2015)
Real Estate Ranking via Mixed Land-use Latent ModelsProceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
Yanan Xu, Yanyan Shen, Yanmin Zhu, Jiadi Yu (2018)
Fusing Satellite Data and Urban Data for Business Location Selection: A Neural Approach
Qi Wang, Yuan Yuan, Pingkun Yan, Xuelong Li (2013)
Saliency detection by multiple-instance learningIEEE Transactions on Cybernetics, 43
M. Sethi, Yupeng Yan, Anand Rangarajan, Ranga Vatsavai, S. Ranka (2015)
Scalable Machine Learning Approaches for Neighborhood Classification Using Very High Resolution Remote Sensing ImageryProceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
Meng Wang, Hui Li, Jiangtao Cui, Ke Deng, Sourav S. Bhowmick, Zhenhua Dong (2016)
Pinocchio: Probabilistic influence-based location selection over moving objectsIEEE Transactions on Knowledge and Data Engineering, 28
Yu Zhang, Stephen Wistar, Jia Li, Michael A Steinberg, James Z. Wang (2016)
Severe thunderstorm detection by visual learning using satellite imagesIEEE Transactions on Geoscience and Remote Sensing, 55
James S Bergstra, Rémi Bardenet, Yoshua Bengio, Balázs Kégl (2011)
Algorithms for hyper-parameter optimizationProceedings of the Advances in Neural Information Processing Systems. Neural Information Processing Systems Foundation
Yuhong Li, Yu Zheng, Shenggong Ji, Wenjun Wang, Leong U, Zhiguo Gong (2015)
Location selection for ambulance stations: a data-driven approachProceedings of the 23rd SIGSPATIAL International Conference on Advances in Geographic Information Systems
J. Friedman (2001)
Greedy function approximation: A gradient boosting machine.Annals of Statistics, 29
Yanjie Fu, Hui Xiong (2015)
Modeling of geographic dependencies for real estate ranking on site selectionProceedings of the IEEE International Conference on Data Mining Workshop. IEEE
Zhe Cao, Tao Qin, Tie-Yan Liu, Ming-Feng Tsai, Hang Li (2007)
Learning to rank: from pairwise approach to listwise approach
Jiaxuan You, Xiaocheng Li, Melvin Low, David Lobell, Stefano Ermon (2017)
Deep Gaussian process for crop yield prediction based on remote sensing dataProceedings of the 31st AAAI Conference on Artificial Intelligence. AAAI Press
Salman H. Khan, Xuming He, Fatih Porikli, Mohammed Bennamoun (2017)
Forest change detection in incomplete satellite images with deep neural networksIEEE Transactions on Geoscience and Remote Sensing, 55
Michael Xie, Neal Jean, Marshall Burke, David Lobell, Stefano Ermon (2016)
Transfer learning from deep features for remote sensing and poverty mappingProceedings of the 13th AAAI Conference on Artificial Intelligence. AAAI Press
Bahaeddin Eravci, Neslihan Bulut, Cagri Etemoglu, Hakan Ferhatosmanoğlu (2016)
Location recommendations for new businesses using check-in dataProceedings of the IEEE International Conference on Data Mining Workshop. IEEE
Qi Wang, Shaoteng Liu, Jocelyn Chanussot, Xuelong Li (2019)
Scene classification with recurrent attention of VHR remote sensing imagesIEEE Transactions on Geoscience and Remote Sensing, 57
Yanjie Fu, Hui Xiong, Yong Ge, Zijun Yao, Yu Zheng, Zhi-Hua Zhou (2014)
Exploiting geographic dependencies for real estate appraisal: a mutual perspective of ranking and clusteringProceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining
Scott Workman, Menghua Zhai, David J. Crandall, Nathan Jacobs (2017)
A unified model for near and remote sensingProceedings of the International Conference on Computer Vision. IEEE
S. Porta, E. Strano, V. Iacoviello, R. Messora, V. Latora, Alessio Cardillo, Fahui Wang, S. Scellato (2009)
Street Centrality and Densities of Retail and Services in Bologna, ItalyEnvironment and Planning B: Planning and Design, 36
Mengwen Xu, Tianyi Wang, Zhengwei Wu, Jingbo Zhou, Jian Li, Haishan Wu (2016)
Store location selection via mining search query logs of Baidu mapsCoRR arXiv:1606.03662. http://arxiv.org/abs/1606.03662.
Mai Quyen Pham, Pascal Lacroix, Marie Pierre Doin (2018)
Sparsity optimization method for slow-moving landslides detection in satellite image time-seriesIEEE Transactions on Geoscience and Remote Sensing, 57
C. Burges, Tal Shaked, Erin Renshaw, Ari Lazier, Matt Deeds, Nicole Hamilton, Gregory Hullender (2005)
Learning to rank using gradient descentProceedings of the 22nd international conference on Machine learning
Shailesh M. Pandey, Tushar Agarwal, Narayanan C. Krishnan (2018)
Multi-task deep learning for predicting poverty from satellite imagesProceedings of the 13th AAAI Conference on Innovative Applications of Artificial Intelligence. AAAI Press
Ming Zhong, Qian Zeng, Yuanyuan Zhu, Jianxin Li, T. Qian (2018)
Sample Location Selection for Efficient Distance-Aware Influence Maximization in Geo-Social Networks
M. Pinkovskiy, Xavier Sala-i-Martin (2016)
Lights, Camera … Income! Illuminating the National Accounts-Household Surveys DebateQuarterly Journal of Economics, 131
Zhiwen Yu, Miao Tian, Zhu Wang, Bin Guo, Tao Mei (2016)
Shop-Type Recommendation Leveraging the Data from Social Media and Location-Based ServicesACM Transactions on Knowledge Discovery from Data (TKDD), 11
Yanjie Fu, Yong Ge, Yu Zheng, Zijun Yao, Yanchi Liu, Hui Xiong, Jing Yuan (2014)
Sparse real estate ranking with online user reviews and offline moving behaviorsProceedings of the International Conference on Data Mining. IEEE
D. Sculley (2010)
Combined regression and rankingProceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
Sebastian Baumbach, Frank Wittich, Florian Sachs, Sheraz Ahmed, Andreas Dengel (2016)
A novel approach for data-driven automatic site recommendation and selectionCoRR arXiv:1608.01212. http://arxiv.org/abs/1608.01212.
Martin Ester, Hans-Peter Kriegel, Jörg Sander, Xiaowei Xu (1996)
A density-based algorithm for discovering clusters in large spatial databases with noiseProceedings of the 2nd International Conference on Knowledge Discovery and Data
Nitish Srivastava, Geoffrey E Hinton, Alex Krizhevsky, Ilya Sutskever, Ruslan Salakhutdinov (2014)
Dropout: A simple way to prevent neural networks from overfittingJournal of Machine Learning Research, 15
Marti A. Hearst, Susan T. Dumais, Edgar Osuna, John Platt, Bernhard Scholkopf (1998)
Support vector machinesIEEE Intelligent Systems and their Applications, 13
Xiaokui Xiao, Bin Yao, Feifei Li (2011)
Optimal location queries in road network databasesProceedings of the 2011 IEEE 27th International Conference on Data Engineering. IEEE, 2011
Dmytro Karamshuk, A. Noulas, S. Scellato, V. Nicosia, C. Mascolo (2013)
Geo-spotting: mining online location-based services for optimal retail store placementProceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
Yanchun Qu, Jun Zhang (2013)
Trade area analysis using user generated mobile location dataProceedings of the 22nd international conference on World Wide Web
D. Comaniciu, P. Meer (2002)
Mean Shift: A Robust Approach Toward Feature Space AnalysisIEEE Trans. Pattern Anal. Mach. Intell., 24
Yiqing Guo, Xiuping Jia, David Paull (2018)
Effective sequential classifier training for SVM-based multitemporal remote sensing image classificationIEEE Transactions on Image Processing, 27
Minhao Cheng, Ian Davidson, Cho-Jui Hsieh (2018)
Extreme learning to rank via low rank assumptionProceedings of the International Conference on Machine Learning. PMLR
M. Kendall (1938)
A NEW MEASURE OF RANK CORRELATIONBiometrika, 30
Neal Jean, M. Burke, Sang Xie, W. Davis, D. Lobell, Stefano Ermon (2016)
Combining satellite imagery and machine learning to predict povertyScience, 353
Liujuan Cao, Rongrong Ji, Cheng Wang, Jonathan Li (2016)
Towards domain adaptive vehicle detection in satellite image by supervised super-resolution transferProceedings of the AAAI on Artificial Intelligence. AAAI Press
John Duchi, Elad Hazan, Y. Singer (2011)
Adaptive Subgradient Methods for Online Learning and Stochastic OptimizationJ. Mach. Learn. Res., 12
Liang-Xiao Sun, Xiao-Yong Zhuge, Yuan Wang (2018)
A contour-based algorithm for automated detection of overshooting tops using satellite infrared imageryIEEE Transactions on Geoscience and Remote Sensing, 57
Business location selection is crucial to the success of businesses. Traditional approaches like manual survey investigate multiple factors, such as foot traffic, neighborhood structure, and available workforce, which are typically hard to measure. In this article, we propose to explore both satellite data (e.g., satellite images and nighttime light data) and urban data for business location selection tasks of various businesses. We extract discriminative features from the two kinds of data and perform empirical analysis to evaluate the correlation between extracted features and the business popularity of locations. A novel neural network approach named R2Net is proposed to learn deep interactions among features and predict the business popularity of locations. The proposed approach is trained with a regression-and-ranking combined loss function to preserve accurate popularity estimation and the ranking order of locations simultaneously. To support the location selection for multiple businesses, we propose an approach named AR2Net with three attention modules, which enable the approach to focus on different latent features according to business types. Comprehensive experiments on a real-world dataset demonstrate that the satellite features are effective and our models outperform the state-of-the-art methods in terms of four metrics.
ACM Transactions on Knowledge Discovery from Data (TKDD) – Association for Computing Machinery
Published: Feb 10, 2020
Keywords: Satellite data
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