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

  • Author / Creator
    Li, Xingkai
  • 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.

  • Subjects / Keywords
  • Graduation date
  • Type of Item
  • Degree
    Master of Science
  • DOI
  • License
    This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.
  • Language
  • Institution
    University of Alberta
  • Degree level
  • Department
    • Department of Computing Science
  • Supervisor / co-supervisor and their department(s)
    • Randy Goebel, Department of Computing Science
  • Examining committee members and their departments
    • Eleni Stroulia, Department of Computing Science
    • Randy Goebel, Department of Computing Science
    • Walter Bischof, Department of Computing Science