2018 - ACM Fellow For contributions in evaluation of information retrieval, question answering, and other language technologies
2009 - ACM Distinguished Member
Information retrieval, Question answering, Relevance, Text Retrieval Conference and Set are her primary areas of study. Her study in Information retrieval is interdisciplinary in nature, drawing from both Test and World Wide Web. Her Test research is multidisciplinary, incorporating perspectives in Philosophy of information and Information needs.
As part of her studies on Question answering, Ellen M. Voorhees frequently links adjacent subjects like Track. Her studies examine the connections between Text Retrieval Conference and genetics, as well as such issues in Text retrieval, with regards to Human–computer information retrieval. Her Search engine study integrates concerns from other disciplines, such as Stability and Data mining, Measure.
Ellen M. Voorhees focuses on Information retrieval, Text Retrieval Conference, Track, Test and Relevance. Her Information retrieval research is multidisciplinary, incorporating elements of NIST and World Wide Web. Her study on Text Retrieval Conference is mostly dedicated to connecting different topics, such as Text retrieval.
She combines subjects such as Data science, Overfitting and Information needs with her study of Test. Her research in Document retrieval intersects with topics in Human–computer information retrieval and Natural language processing. Ellen M. Voorhees has researched Search engine in several fields, including Query expansion and Data mining.
Ellen M. Voorhees mostly deals with Information retrieval, Test, Track, Data science and Text Retrieval Conference. Relevance is the focus of her Information retrieval research. Her Relevance study combines topics from a wide range of disciplines, such as Natural language understanding, Natural language and Knowledge-based systems.
In her study, Selection bias and Data set is strongly linked to Overfitting, which falls under the umbrella field of Test. In her study, which falls under the umbrella issue of Data science, State is strongly linked to Clinical decision support system. Her Text Retrieval Conference research includes themes of NIST, Search analytics and TRECVID.
Her primary areas of study are Information retrieval, Track, Clinical decision support system, Test and Medical record. Her work often combines Information retrieval and Baseline studies. Her Track research integrates issues from Social media, Microblogging and Automatic summarization.
Her work is dedicated to discovering how Clinical decision support system, Data science are connected with Decision support system and other disciplines. Her Test research incorporates elements of Modality and Relevance. The various areas that Ellen M. Voorhees examines in her World Wide Web study include Text Retrieval Conference, Service and Section.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Overview of TREC 2003.
Ellen M. Voorhees.
text retrieval conference (2003)
Overview of TREC 2002
Ellen M. Voorhees.
text retrieval conference (2002)
Query expansion using lexical-semantic relations
Ellen M. Voorhees.
international acm sigir conference on research and development in information retrieval (1994)
Overview of the sixth text REtrieval conference (TREC-6)
Ellen M. Voorhees;Donna Harman.
text retrieval conference (2000)
Overview of TREC 2001.
Ellen M. Voorhees.
text retrieval conference (2001)
The TREC-8 Question Answering Track Report
Ellen M. Voorhees.
text retrieval conference (1999)
Variations in relevance judgments and the measurement of retrieval effectiveness
Ellen M. Voorhees.
Information Processing and Management (2000)
Retrieval evaluation with incomplete information
Chris Buckley;Ellen M. Voorhees.
international acm sigir conference on research and development in information retrieval (2004)
Evaluating Evaluation Measure Stability
Chris Buckley;Ellen M. Voorhees.
international acm sigir conference on research and development in information retrieval (2000)
Using WordNet to disambiguate word senses for text retrieval
Ellen M. Voorhees.
international acm sigir conference on research and development in information retrieval (1993)
If you think any of the details on this page are incorrect, let us know.
We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:
National Institute of Standards and Technology
National Institute of Standards and Technology
Oregon Health & Science University
United States National Library of Medicine
University of Waterloo
Microsoft (United States)
Cornell University
University of Amsterdam
Microsoft (United States)
Cornell University
University of Science and Technology of China
Carnegie Mellon University
University of Maryland, College Park
University of Sussex
University of Barcelona
Institut de Recherche pour le Développement
Stanford University
Near East University
Arecibo Observatory
Mario Negri Institute for Pharmacological Research
United States Department of Agriculture
McGill University
University of Waterloo
University of Arkansas for Medical Sciences
King's College London
California Institute of Technology