Sramana Mitra: You are saying that the number and complexity of input variables are going to go up, creating greater accuracy. Saed Syad: Yes. If you have more variables, you have a chance to better understand the problem. But at the same time, traditional modeling can not support this type of change because of the
Sramana Mitra: So your system sits in between the advertiser and the different publisher venues into which you are placing those ads? Saed Syad: The publisher is on the other side. We are on the side of advertisers.
Sramana Mitra: One common experience I find myself having often is that I go to a website that I use to keep track of theaters, for example. Then I buy tickets to a particular show. But there is some sort of a re-targeting algorithm that has picked up that I was interested in this show
Saed Syad: The second thing is that there are many issues related to those types of techniques, which is independence between variables. To come up with a solution to solve this issue, they found a remedy for it by creating enneagrams, just to find the correlation between different keywords. If I have a data set
Saed Syad: With big data, even without having any predictive modeling, we can answer some of those questions by looking into the database. What we call targeting or retargeting is some sort of a database query that makes it faster than you do it in memory. Just having the amount of data we have it
Dr. Saed Sayad is the chief data scientist at AdTheorent, a platform that provides real-time analytics for advertisers. Saed is an adjunct professor at the University of Toronto and has more than 20 years of experience in data mining and statistics. In this interview he gives us detailed and technical information about the process of