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Journals and Conferences
This paper describes our submission to the KDD Cup 2013 Track 1 Challenge: Author-Paper Indentification in the Microsoft Academic Search database. Our approach is based on Gradient Boosting Machine (GBM) of Friedman () and deep feature engineering. The method was second in the final standings with Mean Average Precision (MAP) of 0.98144, while the… (More)
This paper describes our team's (BS Man & Dmitry & Leustagos) approach to the KDD Cup 2013 track 2 challenge: Author Disambiguation in the Microsoft Academic Search database.