H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 75 Citations 30,573 155 World Ranking 605 National Ranking 370

Research.com Recognitions

Awards & Achievements

2018 - ACM Fellow For contributions in evaluation of information retrieval, question answering, and other language technologies

2009 - ACM Distinguished Member

Overview

What is she best known for?

The fields of study she is best known for:

  • Artificial intelligence
  • Information retrieval
  • Operating system

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.

Her most cited work include:

  • Query expansion using lexical-semantic relations (901 citations)
  • The TREC-8 Question Answering Track Report (698 citations)
  • Retrieval evaluation with incomplete information (604 citations)

What are the main themes of her work throughout her whole career to date?

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.

She most often published in these fields:

  • Information retrieval (77.05%)
  • Text Retrieval Conference (21.31%)
  • Track (17.49%)

What were the highlights of her more recent work (between 2012-2021)?

  • Information retrieval (77.05%)
  • Test (15.30%)
  • Track (17.49%)

In recent papers she was focusing on the following fields of study:

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.

Between 2012 and 2021, her most popular works were:

  • Overview of the TREC 2019 deep learning track. (79 citations)
  • Overview of the TREC 2014 Clinical Decision Support Track (70 citations)
  • Overview of the TREC 2015 Clinical Decision Support Track. (58 citations)

In her most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Information retrieval
  • Operating system

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.

Top Publications

Overview of TREC 2003.

Ellen M. Voorhees.
text retrieval conference (2003)

1988 Citations

Overview of TREC 2002

Ellen M. Voorhees.
text retrieval conference (2002)

1805 Citations

Query expansion using lexical-semantic relations

Ellen M. Voorhees.
international acm sigir conference on research and development in information retrieval (1994)

1363 Citations

Overview of the sixth text REtrieval conference (TREC-6)

Ellen M. Voorhees;Donna Harman.
text retrieval conference (2000)

1315 Citations

Overview of TREC 2001.

Ellen M. Voorhees.
text retrieval conference (2001)

1200 Citations

The TREC-8 Question Answering Track Report

Ellen M. Voorhees.
text retrieval conference (1999)

1054 Citations

Variations in relevance judgments and the measurement of retrieval effectiveness

Ellen M. Voorhees.
Information Processing and Management (2000)

864 Citations

Retrieval evaluation with incomplete information

Chris Buckley;Ellen M. Voorhees.
international acm sigir conference on research and development in information retrieval (2004)

837 Citations

Evaluating Evaluation Measure Stability

Chris Buckley;Ellen M. Voorhees.
international acm sigir conference on research and development in information retrieval (2000)

820 Citations

Using WordNet to disambiguate word senses for text retrieval

Ellen M. Voorhees.
international acm sigir conference on research and development in information retrieval (1993)

713 Citations

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking h-index is inferred from publications deemed to belong to the considered discipline.

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