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The Development of a Hypothesis-driven Framework for Commercial Geo-position Data Visual Analytics Open Access


Other title
Geo Analytics
Information Visualization
Visual Analytics
Type of item
Degree grantor
University of Alberta
Author or creator
Li, Xingkai
Supervisor and department
Randy Goebel, Department of Computing Science
Examining committee member and department
Randy Goebel, Department of Computing Science
Eleni Stroulia, Department of Computing Science
Walter Bischof, Department of Computing Science
Department of Computing Science

Date accepted
Graduation date
Master of Science
Degree level
Modern geo-position system (GPS) enabled smart phones are generating an increasing volume of information about their users, including geo-located search, movement, and transaction data. While this kind of data is increasingly rich and offers many grand opportunities to identify patterns and predict behaviour of groups and individuals, it is not immediately obvious how to develop a framework for extracting plausible inferences from these data. In our case, we have access to a large volume of real user data from the Poynt smart phone application, and we have developed a generic and layered system architecture to incrementally find aggregate items of interest within that data. This includes time and space correlations, e.g., are people searching for dinner and a movie; distributions of usage patterns and platforms, e.g., geographic distribution of Android, Apple, and BlackBerry users; and clustering to identify relatively complex search and movement patterns we call “consumer trajectories.” Our pursuit of these kinds of patterns has helped guide our development of conceptual tools and visualization tools in aid of investigating the geo-located data, and finding both interesting and useful patterns in that data, in a hypothesis-driven process. Included in our system architecture is the ability to consider the difference between exploratory and explanatory searches on data patterns, as well as the deployment of multiple visualization methods that can provide alternatives to help expose patterns. Here we provide examples of formulating hypotheses on geo-located behaviour, and how visual analytics can help formulate hypotheses, and confirm or deny the value of such hypotheses as they emerge.
Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. Where the thesis is converted to, or otherwise made available in digital form, the University of Alberta will advise potential users of the thesis of these terms. The author reserves all other publication and other rights in association with the copyright in the thesis and, except as herein before provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.
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