<div class="csl-bib-body">
<div class="csl-entry">Huang, H., Cheng, Y., Dong, W., Gartner, G., Krisp, J. M., & Meng, L. (2024). Context modeling and processing in Location Based Services: research challenges and opportunities. <i>Journal of Location Based Services</i>. https://doi.org/10.1080/17489725.2024.2306349</div>
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dc.identifier.issn
1748-9725
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/204452
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dc.description.abstract
To ensure good usability, Location Based Services (LBS) should be context-aware, i.e. adapting the information and services according to the context of their user, such as his/her location, tasks, preferences, and the underlying geo-social environment. This article reviews the main challenges related to the context modelling and processing in LBS, and proposes a list of essential research opportunities that can be pursued to overcome the challenges. These research challenges and opportunities are classified into four groups: ‘modelling of the geo-social environment’, ‘modelling of the mobile user’, ‘context-aware adaptation’, and ‘ethical data modelling and processing’. Sufficiently addressing these issues will enable LBS to provide ‘5R’, i.e. the ‘right’ information, in the ‘right’ way, at the ‘right’ time, in the ‘right’ place, to the ‘right’ person.
en
dc.language.iso
en
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dc.publisher
Taylor & Francis
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dc.relation.ispartof
Journal of Location Based Services
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dc.subject
context modelling
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dc.subject
Location based services
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dc.subject
location privacy
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dc.subject
mobile data management
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dc.subject
research agenda
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dc.title
Context modeling and processing in Location Based Services: research challenges and opportunities