The University of Massachusetts Amherst
University of Massachusetts Amherst

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Amanda Stent (Bloomberg): "NLP for Natural Documents"

Machine Learning and Friends Lunch
Thursday, March 5, 2020 - 11:45am to 1:00pm
Computer Science Building, Room 150/151


Abstract: Today's finance industry is continuously searching for alpha, through more advanced modeling and through alternative sources of data. Many alternative sources of data are not raw numerical data but natural documents - human-readable documents containing tables, graphics and text. In this talk, I will present an overview of how we use NLP at Bloomberg to extract information from natural documents, and highlight some research challenges. I also present a case study of how such information can be combined with market data for better predictive modeling.


Amanda Stent is a NLP architect in the data science group in the office of the CTO at Bloomberg LP. Previously, she was a director of research and principal research scientist at Yahoo Labs, a principal member of technical staff at AT&T Labs - Research, and an associate professor in the Computer Science Department at Stony Brook University. Her research interests center on natural language processing and its applications. She holds a PhD in computer science from the University of Rochester. She is co-editor of the book Natural Language Generation in Interactive Systems (Cambridge University Press), has co-authored over 100 papers on natural language processing and is co-inventor on over 25 patents and patent applications.