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As part of the 2018 HPCC Systems Summit Community Day event:
Up first, Farah Alshanik, Clemson University briefly discusses her poster, Equivalence Terms of Text Search Bundle.
Following, Lili Xu and Gus Reyna present their breakout session in the Machine Learning track.
There is a challenge of incorporating public records data into business processes given disparate descriptions across states for similar events, and then finding a standard that gives one consistent meaning for use. This session tells the story of how the HPCC Systems Machine Learning addressed the problem of mapping thousands of disparate public record data descriptions to a corresponding set of standard codes and the future direction for this approach.
Lili Xu is a PhD candidate from DICE lab directed by Dr. Apon in the school of computing of Clemson University. It’s her third time interning in HPCC Systems team working on machine learning applications. Her research area is machine learning, natural language processing and high performance computing. She can speak only three language but she can program more than three languages.
Gus Reyna is a Director with LexisNexis Risk Solutions where he leads the engineering team for the Motor Vehicle Report (MVR) data products. He has been working at LexisNexis for 9 years building data solutions on the HPCC Systems platform.