Mining urban lifestyles: Urban computing, human behavior and recommender systems

Xu, Sharon, Di Clemente, Riccardo and Gonzalez, Marta C. (2019) Mining urban lifestyles: Urban computing, human behavior and recommender systems. In: Big Data Recommender Systems: Application Paradigms. Institution of Engineering and Technology, pp. 71-81. ISBN 9781785619779

Abstract

human behavior. With the advancement of data storage and sensing technologies, electronic records now encompass a diverse spectrum of human activity, ranging from location data [1,2], phone [3,4], and email communication [5] to Twitter activity [6] and opensource contributions on Wikipedia and OpenStreetMap [7,8]. In particular, the study of the shopping and mobility patterns of individual consumers has the potential to give deeper insight into the lifestyles and infrastructure of the region. Credit card records (CCRs) provide detailed insight into purchase behavior and have been found to have inherent regularity in consumer shopping patterns [9]; call detail records (CDRs) present new opportunities to understand human mobility [10], analyze wealth [11], and model social network dynamics [12].

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Official URL:	https://doi.org/10.1049/PBPC035G_ch5
Item Type:	Book Section
Keywords:	Consumer behaviour,Data storage,Electronic records,Email communication,Human behavior,Human factors,Information networks,Marketing computing,Model social network dynamics,Openstreetmap,Recommender systems,Search engines,Sensing technologies,Ubiquitous com
Disciplines:	Network Science
Depositing User:	Riccardo Di Clemente
Date Deposited:	07 Nov 2023 17:40
Last Modified:	16 Jan 2024 10:37
URI:	https://nul.repository.guildhe.ac.uk/id/eprint/334

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