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Computer Science

D-Index
35
Citations
5115
World Ranking
11720
National Ranking
4800

Research.com Recognitions

  • 2020 - ACM Distinguished Member

Overview

Kevyn Collins-Thompson is affiliated with the University of Michigan-Ann Arbor in the United States. Their research focuses primarily on areas within Computer Science, with a specific emphasis on Artificial Intelligence.

The main topics covered in their work include:

  • Topic Modeling
  • Natural Language Processing Techniques
  • Text Readability and Simplification

Kevyn Collins-Thompson's recent scholarly publications include:

  • Toward more effective and equitable learning: Identifying barriers and solutions for the future of online education. (2022), Technology Mind and Behavior
  • An Attention-Based Model for Predicting Contextual Informativeness and Curriculum Learning Applications. (2022), arXiv (Cornell University)

Their frequent co-authors are:

  • Kathryn S. McCarthy
  • Scott A. Crossley
  • Kayla Meyers
  • Ulrich Boser
  • Laura K. Allen

Kevyn Collins-Thompson has published in venues such as:

  • Technology Mind and Behavior
  • arXiv (Cornell University)

In 2020, Kevyn Collins-Thompson received the designation of ACM Distinguished Member.

Best Publications

  • Pairwise ranking aggregation in a crowdsourced setting

    Xi Chen;Paul N. Bennett;Kevyn Collins-Thompson;Eric Horvitz

  • A Language Modeling Approach to Predicting Reading Difficulty.

    Kevyn Collins-Thompson;James P. Callan

  • Computational assessment of text readability: A survey of current and future research

    Kevyn Collins-Thompson

  • Combining Lexical and Grammatical Features to Improve Readability Measures for First and Second Language Texts

    Michael Heilman;Kevyn Collins-Thompson;Jamie Callan;Maxine Eskenazi

  • Predicting reading difficulty with statistical language models

    Kevyn Collins-Thompson;Jamie Callan

  • Query expansion using random walk models

    Kevyn Collins-Thompson;Jamie Callan

  • Personalizing web search results by reading level

    Kevyn Collins-Thompson;Paul N. Bennett;Ryen W. White;Sebastian de la Chica

  • Towards searching as a learning process

    Soo Young Rieh;Kevyn Collins-Thompson;Preben Hansen;Hye-Jung Lee

  • An Analysis of Statistical Models and Features for Reading Difficulty Prediction

    Michael Heilman;Kevyn Collins-Thompson;Maxine Eskenazi

  • Reducing the risk of query expansion via robust constrained optimization

    Kevyn Collins-Thompson

  • TREC 2014 Web Track Overview

    Kevyn Collins-Thompson;Craig Macdonald;Paul N. Bennett;Fernando Diaz

  • Probabilistic models for personalizing web search

    David Sontag;Kevyn Collins-Thompson;Paul N. Bennett;Ryen W. White

  • Estimation and use of uncertainty in pseudo-relevance feedback

    Kevyn Collins-Thompson;Jamie Callan

  • The JAVELIN Question-Answering System at TREC 2002

    Eric Nyberg;Teruko Mitamura;Jaime G. Carbonell;James P. Callan

  • Characterizing web content, user interests, and search behavior by reading level and topic

    Jin Young Kim;Kevyn Collins-Thompson;Paul N. Bennett;Susan T. Dumais

  • Lexical Quality in the Brain: ERP Evidence for Robust Word Learning From Context

    Gwen A. Frishkoff;Charles A. Perfetti;Kevyn Collins-Thompson

  • Classroom success of an intelligent tutoring system for lexical practice and reading comprehension.

    Michael Heilman;Kevyn Collins-Thompson;Jamie Callan;Maxine Eskénazi

  • Toward whole-session relevance: exploring intrinsic diversity in web search

    Karthik Raman;Paul N. Bennett;Kevyn Collins-Thompson

  • Assessing Learning Outcomes in Web Search: A Comparison of Tasks and Query Strategies

    Kevyn Collins-Thompson;Soo Young Rieh;Carl C. Haynes;Rohail Syed

  • Slow Search: Information Retrieval without Time Constraints

    Jaime Teevan;Kevyn Collins-Thompson;Ryen W. White;Susan T. Dumais

  • TREC 2013 Web Track Overview

    Kevyn Collins-Thompson;Paul Bennett;Fernando Diaz;Charles L Clarke

Frequent Co-Authors

Paul N. Bennett
Paul N. Bennett Microsoft (United States)
Jamie Callan
Jamie Callan Carnegie Mellon University
Ryen W. White
Ryen W. White Microsoft (United States)
Susan T. Dumais
Susan T. Dumais Microsoft (United States)
Maxine Eskenazi
Maxine Eskenazi Carnegie Mellon University
Jaime Teevan
Jaime Teevan Microsoft (United States)
Scott A. Crossley
Scott A. Crossley Vanderbilt University
Charles A. Perfetti
Charles A. Perfetti University of Pittsburgh
Ellen M. Voorhees
Ellen M. Voorhees National Institute of Standards and Technology

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