Team with INESC TEC researchers wins the 2017 ICDM best paper award
The Carnegie Mellon University (CMU) Database Group and the University of Porto won the 2017 IEEE International Conference on Data Mining (ICDM) Best Paper award for the paper “TensorCast: Forecasting with Context using Coupled Tensors”, a novel method that forecasts time-evolving networks like Twitter, for example. The conference will be held between on November 18-21 in New Orleans, US.
10th November 2017
“TensorCast is able to forecast multiple co-evolving sequences, such as users buying products or user retweets. It takes into account side information (like demographics) and it scales up to millions of data points by carefully focusing on the few most active ones,” explain the co-authors Miguel Ramos de Araújo, Carnegie Mellon Portugal Program Computer Science Ph. D. Alumnus, researcher at the Centre for Research in Advanced Computing Systems (CRACS) of INESC TEC, and Data Analyst at Feedzai; Pedro Manuel Pinto Ribeiro, Araújo’s Ph. D. co-adviser, Faculty Member at the Department of Computer Science of the Faculty of Sciences of the University of Porto, and researcher at the Centre for Research in Advanced Computing Systems (CRACS) of INESC TEC; and Christos Faloutsos, Araújo’s Ph. D. co-advisor and Faculty Member at CMU.
The ICDM is the world’s premier research conference in data mining and according to the team “despite all the data sources our systems have available, forecasts combining all this information are simultaneously very relevant and very difficult to create”. The paper acceptance rate in this conference was only 9.25% (72 papers accepted from the 778 submitted).
The collaboration was enabled by the CMU Portugal Program, as both the Ph. D. funding and the travel support were instrumental to connect the two sides of the ocean.
Back in 2014, Miguel Araújo had already won a Best Student Paper Runner-Up Award at the Pacific Asia Knowledge Discovery and Data Mining 2014 (PAKDD) for the paper he co-authored with his advisors titled “Com2: Fast Automatic Discovery of Temporal (’Comet’) Communities”.
The researchers mentioned in this news piece are associated with INESC TEC, CMU, Feedzai and UP-FCUP.