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August 8, 2007
Betsy George, a CSE doctoral student studying spatial databases and data mining, wants to improve Web services relating to travel. So far, her work on the issue has yielded two best paper awards.
This month, George’s paper on the subject, entitled "TAG: A Framework for the Discovery of Spatio-Temporal Patterns in Sensor Data," won a best paper award from the First International Workshop on Knowledge Discovery from Sensor Data. The award includes a certificate and $500. But this is not her first win. Earlier this year, George also received another best paper recognition and was invited to submit an expansion of her paper, “Time-Aggregated Graphs for Modeling Spatio-Temporal Networks” for publication in the academic publication, Journal on Semantics and Data.
George said that Web services like MapQuest and Google Maps can be helpful in finding fast ways to get from point A to point B, but travel routes can vary greatly in commute time depending on the time of day – especially during rush hour. “MapQuest doesn’t consider start time options,” she said. “These services are capable of finding the shortest routes, but are unable to predict the start time that would result in the least travel time.”
George is seeking solutions for this issue as part of her doctoral thesis, working with CSE Professor Shashi Shekhar. Her goal: to study the best start time for commuters using graphs and account for time or “temporal” changes. To do this, George proposed the ‘Time-Aggregated Graph Model’ inspired by the evacuation planning project in the Spatial Databases group. This model takes into account temporal variations of travel times. George is confident of its potential due to increasing availability of real-time traffic data.
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