Colloquium - Finding Patterns with a Rotten Core: Data Mining for Crime Series with Cores

Location: 
118 MLH
Speaker: 
Tong Wang
Management Sciences | Tippie College of Business | The University of Iowa
https://tippie.uiowa.edu/people/tong-wang

Tong Wang - PortraitOne of the most challenging problems facing crime analysts is that of identifying crime series, which are sets of crimes committed by the same individual or group. Detecting crime series can be an important step in predictive policing, as knowledge of a pattern can be of paramount importance toward finding the offenders or stopping the pattern. Currently, crime analysts detect crime series manually; our goal is to assist them by providing automated tools for discovering crime series from within a database of crimes. Our approach relies on a key hypothesis that each crime series possesses at least one core of crimes that are very similar to each other, which can be used to characterize the modus operandi (M.O.) of the criminal. Based on this assumption, as long as we find all of the cores in the database, we have found a piece of each crime series. We propose a subspace clustering method, where the subspace is the M.O. of the series. The method has three steps: We first construct a similarity graph to link crimes that are generally similar, second we find cores of crime using an integer linear programming approach, and third we construct the rest of the crime series by merging cores to form the full crime series. To judge whether a set of crimes is indeed a core, we consider both pattern-general similarity, which can be learned from past crime series, and pattern-specific similarity, which is specific to the M.O. of the series and cannot be learned. Our method can be used for general pattern detection beyond crime series detection, as cores exist for patterns in many domains.

Bio:

Tong Wang is an Assistant Professor of Management Sciences at the Tippie College of Business and a member of Iowa Informatics Initiative. She received her Ph.D. in Computer Science from the Massachusetts Institute of Technology in 2016. Her general research interests are in machine learning, data mining, and their application in computational criminology, healthcare, marketing, etc. Her research on crime data mining is the second place winner in "Doing Good with Good OR” at INFORMS 2015, and her algorithm has been implemented by the New York Police Department. Her work on crime data mining has been reported in multiple media including Wikipedia and wired.com. Dr. Wang has served as program committee or reviewer for several conferences and journals, including NIPS, IJCAI, Management Sciences Journal, Decision Sciences Journal, Information System Research Journal, etc.