Please use this identifier to cite or link to this item: http://hdl.handle.net/10316/100515
Title: Identification and Classification of Routine Locations Using Anonymized Mobile Communication Data
Authors: Ferreira, Gonçalo 
Alves, Ana 
Veloso, Marco 
Bento, Carlos 
Keywords: call detail records; clustering algorithms; human mobility; meaningful places; mobile phone data; points of interest
Issue Date: 2022
Serial title, monograph or event: ISPRS International Journal of Geo-Information
Volume: 11
Issue: 4
Abstract: Digital location traces are a relevant source of insights into how citizens experience their cities. Previous works using call detail records (CDRs) tend to focus on modeling the spatial and temporal patterns of human mobility, not paying much attention to the semantics of places, thus failing to model and enhance the understanding of the motivations behind people’s mobility. In this paper, we applied a methodology for identifying individual users’ routine locations and propose an approach for attaching semantic meaning to these locations. Specifically, we used circular sectors that correspond to cellular antennas’ signal areas. In those areas, we found that all contained points of interest (POIs), extracted their most important attributes (opening hours, check-ins, category) and incorporated them into the classification. We conducted experiments with real-world data from Coimbra, Portugal, and the initial experimental results demonstrate the effectiveness of the proposed methodology to infer activities in the user’s routine areas.
URI: http://hdl.handle.net/10316/100515
ISSN: 2220-9964
DOI: 10.3390/ijgi11040228
Rights: openAccess
Appears in Collections:I&D CISUC - Artigos em Revistas Internacionais

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