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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