Ellen Riloff facts for kids

Ellen Riloff is a smart American computer scientist. She is a professor at the University of Utah. She studies how computers can understand and use human language. This field is called natural language processing. She also works on computational linguistics, which is about how language works in computers.

Her research helps computers understand text better. For example, she works on information extraction. This means teaching computers to find specific facts in a lot of text. She also works on sentiment analysis. This helps computers figure out if a text is positive, negative, or neutral. She also teaches computers to learn from texts they haven't seen before.

Education

Ellen Riloff went to Carnegie Mellon University. There, she earned her first degree in applied mathematics and computer science. After that, she went to the University of Massachusetts Amherst. She earned both her master's degree and her Ph.D. in Computer Science there. Her Ph.D. research was guided by Wendy Lehnert.

Career

Today, Ellen Riloff is a Professor of Computer Science. She teaches at the School of Computing at the University of Utah. She has helped organize big conferences for computer scientists. For example, she was the main leader for the EMNLP 2018 conference. She also helped lead the NAACL HLT 2012 conference.

She has also served on important boards. These boards help guide the field of computational linguistics. In 2018, she was given a special honor. She was named a Fellow of the Association for Computational Linguistics (ACL). This means she is recognized for her important work.

Research

Professor Riloff's main research areas are about understanding text. She works on information extraction. This is about getting specific facts from text. She also studies sentiment and how text shows feelings. This is called affective text analysis. She looks at how people use social media. She also works on coreference resolution. This helps computers understand when different words refer to the same thing.

One of her most famous works is about "bootstrapping." This is a way for computers to learn from a lot of text. She and Rosie Jones won a special award for this work in 2017. It was called the AAAI Classic Paper Award. She also received an honorable mention for her work on information extraction in 2012. Her research helps computers become smarter at understanding what we write and say.

Awards and recognition

• ACL Fellow. This award recognized her important work in information extraction. It also honored her studies on how text shows feelings. This award was given by the Association for Computational Linguistics (ACL) in 2018.
• AAAI Classic Paper Award. She received this award in 2017. It was for her paper on "Learning Dictionaries for Information Extraction by Multi-Level Bootstrapping." This paper showed a new way for computers to learn.
• AMIA 2017 Distinguished Paper Award Finalist. Her paper was a finalist for this award in 2017. It was about using unlabeled texts to help classify medical information.
• AAAI Classic Paper Honorable Mention. She received this honor in 2012. It was for her paper on "Automatically Constructing a Dictionary for Information Extraction Tasks." This work helped computers build their own knowledge.