Using PageRank for Fraud Detection in Healthcare Data – Ofer Mendelevitch @ Hortonworks
Anomaly detection in healthcare data is an enabling technology for the detection of overpayment and fraud. In this talk, we demonstrate how to use PageRank with Hadoop and SociaLite (a distributed query language for large-scale graph analysis) to identify anomalies in healthcare payment information. We demonstrate a variant of PageRank applied to graph data generated from the Medicare-B dataset for anomaly detection, and show real anomalies discovered in the dataset.
Ofer Mendelevitch is Director of data sciences @ Hortonworks, where he is responsible for professional services involving data science with Hadoop. He is coming to Israel from the US for a short period of time.
Prior to joining Hortonworks, Ofer served as Entrepreneur in Residence at XSeed Capital where he developed an investment strategy around big data. Before XSeed,
Ofer served as VP of Engineering at Nor1, and before that he was Director of engineering at Yahoo! where he led multiple engineering and data science teams responsible for R&D of large scale computational advertising projects including CTR prediction (with Hadoop), a new front-end ad-serving system and sales tools.