Uploaded June 2015 | Updated September 2026, 1 hour ago
This talk was given by undergraduate Andrew Ghobrial during the 8th Annual Computer Science Undergraduate Research Symposium in 2014. Andrew‘s research was supervised by Dr. Prasun Dewan and doctoral student Jacob Bartel.
"Groups from E-mail Messages"
Wouldn’t it be useful to have your e-mail client automatically generate relevant groups based on your past e-mail exchanges? This study aims to solve this problem by applying group generation techniques used in different contexts to e-mail. This study looked at data collected over twenty students and tested various techniques to determine which method generates groups that are most likely to be used in the future. The study applies Kelli Bacon’s group generation algorithm by generating different variations of graphs that represent the user’s past e-mail history. We conclude that Jacob Bartel’s bursty model and Google’s Interactions Rank formula produce groups that are most relevant to the user.
Andrew Ghobrial is a junior from Fayetteville, North Carolina majoring in computer science with minors in Arabic and entrepreneurship. He is interested in applying original computer science research to create viable technology start-ups. This fall, he will be studying at University College London.
This talk was given by undergraduate Andrew Ghobrial during the 8th Annual Computer Science Undergraduate Research Symposium in 2014. Andrew‘s research was supervised by Dr. Prasun Dewan and doctoral student Jacob Bartel.
"Groups from E-mail Messages"
Wouldn’t it be useful to have your e-mail client automatically generate relevant groups based on your past e-mail exchanges? This study aims to solve this problem by applying group generation techniques used in different contexts to e-mail. This study looked at data collected over twenty students and tested various techniques to determine which method generates groups that are most likely to be used in the future. The study applies Kelli Bacon’s group generation algorithm by generating different variations of graphs that represent the user’s past e-mail history. We conclude that Jacob Bartel’s bursty model and Google’s Interactions Rank formula produce groups that are most relevant to the user.
Andrew Ghobrial is a junior from Fayetteville, North Carolina majoring in computer science with minors in Arabic and entrepreneurship. He is interested in applying original computer science research to create viable technology start-ups. This fall, he will be studying at University College London.
