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Multi-Document & Topic-Specific Summarization
This project’s goal is to build an algorithm that is able to understand and summarize content and sentiment from multiple sources based on a given topic or opinion. This algorithm would then be adapted into TrafficSoda’s existing infrastructure allowing them to maintain and grow a competitive advantage in our marketplace. It would also save the company a significant amount of time by making research and online content consumption much more streamlined.
Faculty Supervisor:
Drs. Glenn Heppler & Paul Fieguth
Student:
Timothy John Lahey
Partner:
TrafficSoda
Discipline:
Engineering
Sector:
Information and communications technologies
University:
University of Waterloo
Program:
Accelerate
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