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Gordon V. Cormack

Gordon V. Cormack

D-Index & Metrics

Computer Science

D-Index
49
Citations
10698
World Ranking
5844
National Ranking
225

Overview

Gordon V. Cormack is affiliated with the University of Waterloo in Canada. Their research spans across fields of computer science and medicine, with a specific focus on subfields such as artificial intelligence, general health professions, health, infectious diseases, and public health, environmental and occupational health.

Their work covers a variety of main topics including geriatric care and nursing homes, topic modeling, machine learning and algorithms, COVID-19 and healthcare impacts, frailty in older adults, intergenerational family dynamics and caregiving, as well as health disparities and outcomes.

Notable recent papers by Gordon V. Cormack include:

  • Preventing the transmission of COVID-19 and other coronaviruses in older adults aged 60 years and above living in long-term care: a rapid review (2020), Systematic Reviews
  • Comparative-effectiveness research of COVID-19 treatment: a rapid scoping review (2022), BMJ Open
  • Recent innovations in long-term care coverage and financing: a rapid scoping review (2024), BMJ Open
  • Continuous Active Learning Using Pretrained Transformers (2022), arXiv (Cornell University)
  • Does the LLMperor Have New Clothes? Some Thoughts on the Use of LLMs in eDiscovery (2024), SSRN Electronic Journal

Frequent coauthors in their publications include:

  • Maura R. Grossman
  • Ba' Pham
  • Sharon E. Straus
  • Andrea C. Tricco
  • Patricia Rios

Publication venues where their work commonly appears include:

  • arXiv (Cornell University)
  • BMJ Open
  • Systematic Reviews
  • SSRN Electronic Journal
  • PLoS ONE

Best Publications

  • Novelty and diversity in information retrieval evaluation

    Charles L.A. Clarke;Maheedhar Kolla;Gordon V. Cormack;Olga Vechtomova

  • Information Retrieval: Implementing and Evaluating Search Engines

    Stefan Büttcher;Charles Clarke;Gordon V. Cormack

  • Reciprocal rank fusion outperforms condorcet and individual rank learning methods

    Gordon V. Cormack;Charles L A Clarke;Stefan Buettcher

  • Efficient and effective spam filtering and re-ranking for large web datasets

    Gordon V. Cormack;Mark D. Smucker;Charles L. Clarke

  • Email Spam Filtering: A Systematic Review

    Gordon V. Cormack

  • Data compression using dynamic Markov modelling

    G. V. Cormack;R. N. S. Horspool

  • Spam Filtering Using Statistical Data Compression Models

    Andrej Bratko;Bogdan Filipič;Gordon V. Cormack;Thomas R. Lynam

  • Exploiting redundancy in question answering

    Charles L. A. Clarke;Gordon V. Cormack;Thomas R. Lynam

  • TREC 2005 Spam Track Overview

    Gordon V. Cormack;Thomas R. Lynam

  • Efficient construction of large test collections

    Gordon V. Cormack;Christopher R. Palmer;Charles L. A. Clarke

  • Relevance ranking for one to three term queries

    Charles L. A. Clarke;Gordon V. Cormack;Elizabeth A. Tudhope

  • An Algebra for Structured Text Search and a Framework for its Implementation

    Charles L. A. Clarke;Gordon V. Cormack;Forbes J. Burkowski

  • Technology-Assisted Review in E-Discovery Can Be More Effective and More Efficient Than Exhaustive Manual Review

    Maura R. Grossman;Gordon V. Cormack

  • Spam and the ongoing battle for the inbox

    Joshua Goodman;Gordon V. Cormack;David Heckerman

  • Data compression on a database system

    Gordon V. Cormack

  • Spam filtering for short messages

    Gordon V. Cormack;José María Gómez Hidalgo;Enrique Puertas Sánz

  • Evaluation of machine-learning protocols for technology-assisted review in electronic discovery

    Gordon V. Cormack;Maura R. Grossman

  • Online supervised spam filter evaluation

    Gordon V. Cormack;Thomas R. Lynam

  • Question Answering by Passage Selection (MultiText Experiments for TREC-9).

    Charles L. A. Clarke;Gordon V. Cormack;D. I. E. Kisman;Thomas R. Lynam

  • Statistical precision of information retrieval evaluation

    Gordon V. Cormack;Thomas R. Lynam

  • TREC 2007 Spam Track Overview

    Gordon V. Cormack

Frequent Co-Authors

Charles L. A. Clarke
Charles L. A. Clarke University of Waterloo
Jimmy Lin
Jimmy Lin University of Waterloo
Krisztian Balog
Krisztian Balog University of Stavanger
Ian Soboroff
Ian Soboroff National Institute of Standards and Technology
Nick Craswell
Nick Craswell Microsoft (United States)
Martin Potthast
Martin Potthast Leipzig University
Jayashree Kalpathy-Cramer
Jayashree Kalpathy-Cramer Harvard University
David Hawking
David Hawking Microsoft (United States)
Douglas W. Oard
Douglas W. Oard University of Maryland, College Park
Sharon E. Straus
Sharon E. Straus University of Toronto

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