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Research and Modeling of Commercial Location Selection Based on Geographic Big Data and Mobile Signaling Data—A Case Study of the Central Urban Area of Beijing
16 references·0 citing·52 second hop
Research and Modeling of Commercial Location Selection Based on Geographic Big Data and Mobile Signaling Data—A Case Study of the Central Urban Area of Beijing (2024)Research and Modeling of Commercial Locat…A BiLSTM-CNN model for predicting users’ next locations based on geotagged social media (2020)A BiLSTM-CNN model for predic…Reconstruction of human movement trajectories from large-scale low-frequency mobile phone data (2019)Reconstruction of human movem…Strategic adjustment of land use policy under the economic transformation (2018)Strategic adjustment of land …Site Selection of Retail Shops Based on Spatial Accessibility and Hybrid BP Neural Network (2018)Site Selection of Retail Shop…DeepMove (2018)DeepMovePredicting mobile users’ behaviors and locations using dynamic Bayesian networks (2016)Predicting mobile users’ beha…Discovering interpretable geo-social communities for user behavior prediction (2016)Discovering interpretable geo…Demand driven store site selection via multiple spatial-temporal data (2016)Demand driven store site sele…Hotel location evaluation: A combination of machine learning tools and web GIS (2015)Hotel location evaluation: A …Exploring multiple evidence to infer users’ location in Twitter (2015)Exploring multiple evidence t…Literature Review on Selection Criteria of Store Location Based on Performance Measures (2013)Literature Review on Selectio…Geo-spotting (2013)Geo-spotting@Phillies Tweeting from Philly? Predicting Twitter User Locations with Spatial Word Usage (2012)@Phillies Tweeting from Phill…A combined fuzzy MCDM approach for selecting shopping center site: An example from Istanbul, Turkey (2009)A combined fuzzy MCDM approac…Multi-criteria Decision Making Methods: A Comparative Study (2000)Multi-criteria Decision Makin…Determinants of Store-Level Price Elasticity (1995)Determinants of Store-Level P…Placing flickr photos on a map (2009)You are where you tweet (2010)"I'm eating a sandwich in Glasgow" (2011)Hierarchical Discriminative Classification for Text-Based Geolocation (2014)Choosing the Right Home Location Definition Method for the Given Dataset (2015)On the Accuracy of Hyper-local Geotagging of Social Media Content (2015)Stability in Competition (1929)Defining and Estimating a Trading Area (1964)Stability in Competition (1990)Configurational path to customer satisfaction and stickiness for a restaurant chain using fuzzy set qualitative comparative analysis (2016)Portuguese food retailers – Exploring three classic theories of retail location (2016)Consumer Behavior in Clothing Industry and Its Relationship with Open Innovation Dynamics during the COVID-19 Pandemic (2021)Measuring the efficiency of decision making units (1978)The Tourist-Historic City (2000)Agglomeration effects and performance: a test of the Texas lodging industry (2001)Does hotel location tell a true story? 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References

  • 2000Multi-criteria Decision Making Methods: A Comparative Study2,407 cited
  • 2018DeepMove714 cited
  • 2018Strategic adjustment of land use policy under the economic transformation610 cited
  • 1995Determinants of Store-Level Price Elasticity547 cited
  • 2013Geo-spotting208 cited
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  • 2012@Phillies Tweeting from Philly? Predicting Twitter User Locations with Spatial Word Usage135 cited
  • 2016Discovering interpretable geo-social communities for user behavior prediction123 cited
  • 2015Hotel location evaluation: A combination of machine learning tools and web GIS108 cited
  • 2013Literature Review on Selection Criteria of Store Location Based on Performance Measures91 cited
  • 2019Reconstruction of human movement trajectories from large-scale low-frequency mobile phone data90 cited
  • 2018Site Selection of Retail Shops Based on Spatial Accessibility and Hybrid BP Neural Network59 cited
  • 2020A BiLSTM-CNN model for predicting users’ next locations based on geotagged social media53 cited
  • 2016Demand driven store site selection via multiple spatial-temporal data42 cited
  • 2015Exploring multiple evidence to infer users’ location in Twitter

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26 cited
  • 2016Predicting mobile users’ behaviors and locations using dynamic Bayesian networks14 cited
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