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Dmytro Karamshuk, Anastasios Noulas, Salvatore Scellato, Vincenzo Nicosia, Cecilia Mascolo
2013 Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD '13  
The problem of identifying the optimal location for a new retail store has been the focus of past research, especially in the field of land economy, due to its importance in the success of a business.  ...  With the growth of location-based social networks, fine grained data describing user mobility and popularity of places has recently become attainable.  ...  OPTIMAL RETAIL STORE PLACEMENT IN LOCATION-BASED SERVICES In this section we formalize the problem of optimal retail store placement in the context of location-based social networks.  ... 
doi:10.1145/2487575.2487616 dblp:conf/kdd/KaramshukNSNM13 fatcat:klszyb4sb5fnrbh4w7ytd5f5zy

Estimating Potential Customers Anywhere and Anytime Based on Location-Based Social Networks [chapter]

Hsun-Ping Hsieh, Cheng-Te Li, Shou-De Lin
2015 Lecture Notes in Computer Science  
Acquiring the knowledge about the volume of customers for places and time of interest has several benefits such as determining the locations of new retail stores and planning advertising strategies.  ...  geographical, mobility, and features on location-based social networks.  ...  Related Work Investigating Location Popularity. The most relevant study is Geo-Spotting [8] , which is to identify the popular locations for optimal retail store placement.  ... 
doi:10.1007/978-3-319-23525-7_35 fatcat:g2uxz5sm5bhnnfq3tl6yrg7lvu

Coupling Implicit and Explicit Knowledge for Customer Volume Prediction

Jingyuan Wang, Yating Lin, Junjie Wu, Zhong Wang, Zhang Xiong
Customer volume prediction, which predicts the volume from a customer source to a service place, is a very important technique for location selection, market investigation, and other related applications  ...  GR-NMF shows particularly evident advantages to all baselines in location selection with the cold-start challenge.  ...  For instance, Geo-spotting (Karamshuk et al. 2013 ) adopts nine geographic features including density, neighbors entropy, competitiveness, etc., for mining online LBS data for optimal retail store placement  ... 
doi:10.1609/aaai.v31i1.10727 fatcat:bepnbjrpljetthsiv2deovqrte

Mobile Crowd Sensing and Computing

Bin Guo, Zhu Wang, Zhiwen Yu, Yu Wang, Neil Y. Yen, Runhe Huang, Xingshe Zhou
2015 ACM Computing Surveys  
MCSC extends the vision of participatory sensing by leveraging both participatory sensory data from mobile devices (offline) and user-contributed data from mobile social networking services (online).  ...  This article characterizes the unique features and novel application areas of MCSC and proposes a reference framework for building human-in-the-loop MCSC systems.  ...  ACKNOWLEDGMENTS The authors would like to thank all the colleagues for their discussion and suggestions.  ... 
doi:10.1145/2794400 fatcat:lol35ouj75eplapvdod5kyy2me

Predicting popularity of EV charging infrastructure from GIS data [article]

Milan Straka, Pasquale De Falco, Gabriella Ferruzzi, Daniela Proto, Gijs van der Poel, Shahab Khormali, Ľuboš Buzna
2019 arXiv   pre-print
The availability of charging infrastructure is essential for large-scale adoption of electric vehicles (EV).  ...  The best fit was identified for the size of the unique group of visitors (popularity) attracted by the charging infrastructure. Consecutively, charging infrastructure is ranked by popularity.  ...  Acknowledgements This work was supported by the research grants: VEGA 1/0089/19 Data analysis methods and decisions support tools for service systems supporting electric vehicles, VEGA 1/342/18 Optimal  ... 
arXiv:1910.02498v1 fatcat:v7rtmqwu2rbm3pnxmvlfhcdmzu