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Imputing relevant information from multi-day GPS tracers for retail planning and management using data fusion and context-sensitive learning
Authors:Anastasia Moiseeva  Harry Timmermans
Institution:1. Department of Virology, Parasitology and Immunology, Faculty of Veterinary Medicine, Ghent University, Salisburylaan 133, 9820 Merelbeke, Belgium;2. Merial SAS, 28 Avenue Tony Garnier, Lyon 69007, France;3. National Reference Centre of Rabies, Viral Diseases, Scientific Institute of Public Health (WIV-ISP), Engelandstraat 642, B-1180 Brussels, Belgium;4. Department of Comparative Physiology and Biometrics, Faculty of Veterinary Medicine, Ghent University, Salisburylaan 133, 9820 Merelbeke, Belgium;5. Department of Biosystems, Faculty of Bioscience Engineering, Kasteelpark Arenberg 30, 3001 Heverlee, Belgium;1. Health Promotion & Policy Research Unit, University of Otago, Wellington, New Zealand;2. Department of Geography, Environment & Spatial Sciences, Michigan State University, East Lansing, MI, USA;3. National Institute for Health Innovation, University of Auckland, Auckland, New Zealand;1. ETSAB,Universitat Politècnica de Catalunya-BarcelonaTech, Avda. Diagonal 649, Barcelona 08028, Spain;2. Arquitectura La Salle Barcelona, Universitat Ramon LLull, C/.Quatre Camins Camins 2, Barcelona 08022, Spain;1. Laboratorio Nacional de Fusión (LNF), Centro de Investigaciones Tecnológicas, Medioambientales y Tecnológicas (CIEMAT), Av/Complutense 40, 28040 Madrid, Spain;2. Istituto di Fisica del Plasma “Piero Caldirola”, Consiglio Nazionale delle Ricerche, via Cozzi 53, 20125 Milano, Italy
Abstract:It is well known that the right location of shopping centres is of paramount importance. Unless stores succeed in attracting their own clientele, they rely to a large extent on the impulse behaviour of shoppers. To evaluate alternative locations, models of pedestrian behaviour may be useful. Modern technologies such as GPS and RFID offer new possibilities providing data on routes and stops, which are required as input for such models. An automatic interpretation of GPS tracers with respect to the activities being conducted could enhance the applicability of such technologies to retail management applications. This paper reviews this rapidly growing literature, and shows how automatic data imputation can be established by using Bayesian belief networks and how GPS traces can be fused with land use data of retail location.
Keywords:
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