Cases of fraud at self-checkout stations in grocery stores is a growing problem and one way to combat that issue is to let some of the brightest minds in the world try to solve it in an international competition.
That is what a team of Iowa State University graduate students did after they beat nearly 150 teams from 114 universities in 28 countries, when they brought home the top prize from the 20th annual Data Mining Cup in Berlin earlier this month.
Data mining is essentially “finding and quantifying useful non-random patterns in large data sets,” said Stephen Vardeman, University Professor of statistics and industrial engineering.
Teams had six weeks to come up with a mathematical model to detect cases of fraud at self-checkout stations in grocery stores without putting innocent customers through unnecessary inspections.
“I was really confident in our model because it captured the relationship between input and outcome,” said Iowa State’s first place team leader and statistics Ph.D. candidate Qihao Zhang. “Sometimes people will try to use a complicated model, but the outcome may not be that stable. We developed a really simple model — which is not easy to find — to achieve our winning performance.”
In addition to Iowa State’s first place win, a second Iowa State team placed eighth in the competition.
Prudsys AG, an European data mining company, sponsored the intelligent-data analysis competition for universities.
A jury scored all of the submitted solutions, and invited the top 10 teams to Berlin to present their solution methods at last week’s Prudsys retail intelligence summit, which examined how retailers can use artificial intelligence to be successful. Each team gave a 10-minute presentation.
The first place Iowa State team received a prize of 2,000 euros (about $2,244) and a plaque. Switzerland’s University of Geneva took second place, and Washington, D.C.’s George Washington University placed third.
Iowa State’s first place team members and their departments are Xingche Guo (statistics), Gang Han (statistics), Haoyan Hu (statistics), Qinglong Tian (statistics), Shaodong Wang (industrial and manufacturing systems engineering), Yueying Wang (statistics), Haihan Yu (statistics), Lijin Zhang (statistics), Qihao Zhang (statistics), Zerui Zhang (bioinformatics and computational biology), Wenting Zhao (statistics) and Yifan Zhu (statistics).