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Parameter optimisation for location extraction and prediction applications

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Thomason, Alasdair, Griffiths, Nathan and Sanchez Silva, Victor (2015) Parameter optimisation for location extraction and prediction applications. In: 13th IEEE International Conference on Pervasive Intelligence and Computing, Liverpool, UK, 26-28 Oct 2015. Published in: 2015 IEEE International Conference on Computer and Information Technology; Ubiquitous Computing and Communications; Dependable, Autonomic and Secure Computing; Pervasive Intelligence and Computing pp. 2173-2180. ISBN 9781509001545. doi:10.1109/CIT/IUCC/DASC/PICOM.2015.322

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Official URL: http://dx.doi.org/10.1109/CIT/IUCC/DASC/PICOM.2015...

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Abstract

The pervasive nature of location-aware hardware has provided an unprecedented foundation for understanding human behaviour. With a record of historic movement, in the form of geospatial trajectories, extracting locations meaningful to users is commonly performed as a basis for modelling a users’ interactions with their environment. Existing literature, however, has scarcely considered the applicability of extracted locations, typically focusing solely on the consequent knowledge acquisition process employed, due to the difficulty of evaluating the output of such unsupervised learning techniques. Towards the goal of ensuring the representativeness of extracted locations, and using location prediction as an example knowledge acquisition process, this work provides a method of automated parameter selection for both location extraction and prediction that ensures both the applicability of the locations extracted and the utility of the predictions performed. Specifically, we: (i) provide a metric for the evaluation of both extracted locations and predictions that characterises the goal of each of these tasks, (ii) frame the process of parameter selection as that of mathematical optimisation through the presented metric, and (iii) discuss characteristics of the metric while demonstrating its applicability over real-world data, location extraction algorithms and prediction techniques.

Item Type: Conference Item (Paper)
Subjects: Q Science > QA Mathematics > QA75 (Please use QA76 Electronic Computers. Computer Science)
Divisions: Faculty of Science, Engineering and Medicine > Science > Computer Science
Library of Congress Subject Headings (LCSH): Human behavior -- Data processing, Artificial Intelligence, Computer-aided design
Journal or Publication Title: 2015 IEEE International Conference on Computer and Information Technology; Ubiquitous Computing and Communications; Dependable, Autonomic and Secure Computing; Pervasive Intelligence and Computing
Publisher: IEEE
ISBN: 9781509001545
Official Date: 28 December 2015
Dates:
DateEvent
28 December 2015Published
2015Accepted
Page Range: pp. 2173-2180
DOI: 10.1109/CIT/IUCC/DASC/PICOM.2015.322
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Restricted or Subscription Access
Adapted As: Proceedings of the 2015 IEEE International Conference on Computer and Information Technology; Ubiquitous Computing and Communications; Dependable, Autonomic and Secure Computing; Pervasive Intelligence and Computing
Conference Paper Type: Paper
Title of Event: 13th IEEE International Conference on Pervasive Intelligence and Computing
Type of Event: Conference
Location of Event: Liverpool, UK
Date(s) of Event: 26-28 Oct 2015
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