- MindNet: automated acquisition of semantic knowledge
- Summarization, focusing on summary generation and evaluation
- Making reading more effective
- Improving education through NLP
Lucy's research focuses on text understanding. She is deeply involved with developing MindNet, a method for automatically acquiring semantic information. All types of semantic information can be identified in and extracted from text. Dictionaries can provide the semantic information, for example, that a sheep is an animal; encyclopedias provide specific knowledge, for example, that Armstrong landed on the moon. Specialized data sets provide information on a given topic, for example, that Microsoft Research was founded in 1991. Common sense information can also be extracted from web-scale resources. Such information can be extracted in a variety of ways, from rule-based to completely unsupervised. Lucy's focus is to work with applications that demonstrate how the information in a knowledge resource such as MindNet can be used to improve human understanding and productivity.
Currently, Lucy is excited to be working on ways to make reading more effective. One avenue is to support a reader's mastery of the text by using Question Generation to create quizzes for arbitrary selections of text. With such quizzes, the reader can see for themselves which part(s) of the text they know and which they should re-read. The value of open-response questions to support learning is well-known. We are also working on enabling teachers to pose open-response questions by creating a workflow called Powergrading, where the teacher grades clusters of answers simultaneously, identifies answers that don't belong in the cluster, and provides rich feedback while gaining insight into how well the students are doing in class.
Lucy holds a Ph.D. in Computational Linguistics from Georgetown University, in Washington D.C. Lucy worked at IBM Bethesda on natural language processing from 1988 - 1990. In 1991, she was a Visiting Scientist at the Institute for Systems Science in Singapore. Lucy has worked at Microsoft Research since 1992. Lucy was Program Co-Chair for NAACL in 2009 and General Chair for NAACL in 2013. Since 2011, Lucy is also Affiliate Associate Faculty at University of Washington Department of Biomedical Health Informatics, part of a group who are using NLP technology to extract critical information from patient reports.
Click here for full list of publications
- Jackie C.K. Cheung, Hoifung Poon, and Lucy Vanderwende, Probabilistic Frame Induction, in Proceedings of NAACL-HLT 2013, Association for Computational Linguistics, 2013
- Lee Becker, Sumit Basu, and Lucy Vanderwende, Mind the Gap: Learning to Choose Gaps for Question Generation, in Proceedings of NAACL-HLT 2012, Association for Computational Linguistics, 2012
- Aria Haghighi and Lucy Vanderwende, Exploring Content Models for Multi-Document Summarization, in Proceedings of HLT-NAACL 2009, Association for Computational Linguistics, 2009
- Lucy Vanderwende, Answering and Questioning for Machine Reading, American Association for Artificial Intelligence , March 2007
- Ani Nenkova, Lucy Vanderwende, and Kathleen McKeown, A compositional context sensitive multi-document summarizer: exploring the factors that influence summarization, in Proceedings of SIGIR 2006, Association for Computing Machinery, Inc., 2006
- Lucy Vanderwende, Volunteers Created the Web, in Proceedings of the 2005 AAAI Spring Symposium, Knowledge Collection from Volunteer Contributors, American Association for Artificial Intelligence , March 2005
- William B. Dolan, Stephen D. Richardson, and Lucy Vanderwende, MindNet: acquiring and structuring semantic information from text, no. MSR-TR-98-23, May 1998
- Simonetta Montemagni and Lucy Vanderwende, Structural Patterns vs. String Patterns for Extracting Semantic Information from Dictionaries, in Proceedings of the Fourteenth International Conference on Computational Linguistics, Association for Computational Linguistics, 1992