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Computer Science

D-Index
43
Citations
13166
World Ranking
7778
National Ranking
3362

Ted Pedersen publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Ted Pedersen sits on this spectrum.

32–41 publications: 7 scientists 42–51 publications: 22 scientists 52–61 publications: 82 scientists 62–71 publications: 134 scientists 72–81 publications: 249 scientists 82–91 publications: 324 scientists 92–101 publications: 421 scientists 102–111 publications: 420 scientists 112–121 publications: 497 scientists 122–131 publications: 544 scientists 132–141 publications: 555 scientists 142–151 publications: 609 scientists 152–161 publications: 559 scientists 162–171 publications: 534 scientists 172–181 publications: 556 scientists 182–191 publications: 583 scientists 192–201 publications: 519 scientists 202–211 publications: 508 scientists 212–221 publications: 490 scientists 222–231 publications: 437 scientists 232–241 publications: 423 scientists 242–251 publications: 408 scientists 252–261 publications: 377 scientists 262–271 publications: 301 scientists 272–281 publications: 335 scientists 282–291 publications: 320 scientists 292–301 publications: 293 scientists 302–311 publications: 250 scientists 312–321 publications: 238 scientists 322–331 publications: 206 scientists 332–341 publications: 209 scientists 342–351 publications: 208 scientists 352–361 publications: 162 scientists 362–371 publications: 176 scientists 372–381 publications: 127 scientists 382–391 publications: 158 scientists 392–401 publications: 128 scientists 402–411 publications: 104 scientists 412–421 publications: 94 scientists 422–431 publications: 99 scientists 432–441 publications: 83 scientists 442–451 publications: 108 scientists 452–461 publications: 73 scientists 462–471 publications: 77 scientists 472–481 publications: 69 scientists 482–491 publications: 84 scientists 492–501 publications: 62 scientists 502–511 publications: 54 scientists 512–521 publications: 57 scientists 522–531 publications: 51 scientists 532–541 publications: 51 scientists 542–551 publications: 32 scientists 552–561 publications: 38 scientists 562–571 publications: 28 scientists 572–581 publications: 43 scientists 582–591 publications: 33 scientists 592–601 publications: 41 scientists 602–611 publications: 32 scientists 612–621 publications: 28 scientists 622–631 publications: 25 scientists 632–641 publications: 27 scientists 642–651 publications: 17 scientists 652–661 publications: 20 scientists 662–671 publications: 17 scientists 672–681 publications: 15 scientists 682–691 publications: 14 scientists 692–701 publications: 21 scientists 702–711 publications: 13 scientists 712–721 publications: 12 scientists 722–731 publications: 19 scientists 732–741 publications: 14 scientists 742–751 publications: 12 scientists 752–761 publications: 10 scientists 762–771 publications: 10 scientists 772–781 publications: 11 scientists 782–791 publications: 10 scientists 792–801 publications: 11 scientists 802–811 publications: 8 scientists 812–821 publications: 8 scientists 822–831 publications: 7 scientists 832–841 publications: 11 scientists 842–851 publications: 10 scientists 852–861 publications: 5 scientists 862–871 publications: 9 scientists 872–881 publications: 4 scientists 882–891 publications: 6 scientists 892–901 publications: 3 scientists 902–911 publications: 6 scientists 912–921 publications: 3 scientists 922–931 publications: 2 scientists 932–941 publications: 2 scientists 942–951 publications: 2 scientists 952–961 publications: 3 scientists 962–971 publications: 3 scientists 972–981 publications: 3 scientists 982–990 publications: 5 scientists 991+ publications: 100 scientists
32 publications 991+

This scientist: 139 publications — 22nd percentile

22% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

Ted Pedersen D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Ted Pedersen sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 983 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 968 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 763 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 518 scientists 54–55 D-Index: 500 scientists 56–57 D-Index: 458 scientists 58–59 D-Index: 400 scientists 60–61 D-Index: 337 scientists 62–63 D-Index: 308 scientists 64–65 D-Index: 292 scientists 66–67 D-Index: 249 scientists 68–69 D-Index: 213 scientists 70–71 D-Index: 192 scientists 72–73 D-Index: 189 scientists 74–75 D-Index: 165 scientists 76–77 D-Index: 139 scientists 78–79 D-Index: 119 scientists 80–81 D-Index: 121 scientists 82–83 D-Index: 113 scientists 84–85 D-Index: 88 scientists 86–87 D-Index: 87 scientists 88–89 D-Index: 75 scientists 90–91 D-Index: 69 scientists 92–93 D-Index: 57 scientists 94–95 D-Index: 46 scientists 96–97 D-Index: 38 scientists 98–99 D-Index: 34 scientists 100–101 D-Index: 36 scientists 102–103 D-Index: 27 scientists 104–105 D-Index: 37 scientists 106–107 D-Index: 18 scientists 108–109 D-Index: 31 scientists 110–111 D-Index: 19 scientists 112–113 D-Index: 16 scientists 114–115 D-Index: 12 scientists 116–117 D-Index: 20 scientists 118–119 D-Index: 15 scientists 120–121 D-Index: 5 scientists 122–123 D-Index: 20 scientists 124–125 D-Index: 8 scientists 126–127 D-Index: 5 scientists 128–129 D-Index: 7 scientists 130 D-Index: 3 scientists 131+ D-Index: 98 scientists
30 D-Index 131+

This scientist: 43 D-Index — 46th percentile

46% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

Overview

Ted Pedersen is a researcher affiliated with the University of Minnesota in the United States. Their primary field of study is Computer Science, with a focus on Artificial Intelligence. The scientist's work spans multiple interdisciplinary areas, including Molecular Biology, Social Psychology, and Experimental and Cognitive Psychology.

Their research covers a range of topics in natural language processing and computational linguistics. These topics include:

  • Hate Speech and Cyberbullying Detection
  • Topic Modeling
  • Natural Language Processing Techniques
  • Sentiment Analysis and Opinion Mining
  • Text Readability and Simplification
  • Biomedical Text Mining and Ontologies
  • Humor Studies and Applications

Ted Pedersen's publication record includes several papers in various academic venues. The majority of their work has appeared in arXiv (Cornell University), with a smaller number of publications in other venues such as the Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022).

Notable recent papers authored by Ted Pedersen include:

  • Duluth at SemEval-2019 Task 6: Lexical Approaches to Identify and Categorize Offensive Tweets, 2020, arXiv (Cornell University)
  • Duluth at SemEval-2020 Task 7: Using Surprise as a Key to Unlock Humorous Headlines, 2020, arXiv (Cornell University)

The scientist has collaborated with several coauthors including Jennifer D'Souza, Sören Auer, Rupak Kumar Das, Shuning Jin, and Yue Yin. These collaborative efforts have contributed to a variety of topics and publications in the field.

Best Publications

  • WordNet::Similarity: measuring the relatedness of concepts

    Ted Pedersen;Siddharth Patwardhan;Jason Michelizzi

  • An Adapted Lesk Algorithm for Word Sense Disambiguation Using WordNet

    Satanjeev Banerjee;Ted Pedersen

  • Extended gloss overlaps as a measure of semantic relatedness

    Satanjeev Banerjee;Ted Pedersen

  • Measures of semantic similarity and relatedness in the biomedical domain

    Ted Pedersen;Serguei V. S. Pakhomov;Siddharth Patwardhan;Christopher G. Chute

  • Using measures of semantic relatedness for word sense disambiguation

    Siddharth Patwardhan;Satanjeev Banerjee;Ted Pedersen

  • Using WordNet Based Context Vectors to Estimate the Semantic Relatedness of Concepts

    Siddharth Patwardhan;Ted Pedersen

  • The design, implementation, and use of the Ngram statistics package

    Satanjeev Banerjee;Ted Pedersen

  • An evaluation exercise for word alignment

    Rada Mihalcea;Ted Pedersen

  • Maximizing Semantic Relatedness to Perform Word Sense Disambiguation

    Ted Pedersen;Satanjeev Banerjee;Siddharth Patwardhan

  • Word Sense Discrimination by Clustering Contexts in Vector and Similarity Spaces

    Amruta Purandare;Ted Pedersen

  • A simple approach to building ensembles of Naive Bayesian classifiers for word sense disambiguation

    Ted Pedersen

  • Semantic Similarity and Relatedness between Clinical Terms: An Experimental Study

    Serguei Pakhomov;Bridget McInnes;Terrence Adam;Ying Liu

  • Distinguishing Word Senses in Untagged Text

    Ted Pedersen;Rebecca F. Bruce

  • SenseRelate targetword: a generalized framework for word sense disambiguation

    Siddharth Patwardhan;Satanjeev Banerjee;Ted Pedersen

  • A decision tree of bigrams is an accurate predictor of word sense

    Ted Pedersen

  • UMLS-Interface and UMLS-Similarity : open source software for measuring paths and semantic similarity.

    Bridget T. McInnes;Ted Pedersen;Serguei V.S. Pakhomov

  • Name discrimination by clustering similar contexts

    Ted Pedersen;Amruta Purandare;Anagha Kulkarni

  • Fishing for Exactness

    Ted Pedersen

  • Abbreviation and acronym disambiguation in clinical discourse.

    Serguei Pakhomov;Ted Pedersen;Christopher G. Chute

  • Offspring from Reproduction Problems: What Replication Failure Teaches Us

    Antske Fokkens;Marieke van Erp;Marten Postma;Ted Pedersen

  • Gloss overlaps as a measure of semantic relatedness

    Satanjeev Banerjee;Ted Pedersen

Frequent Co-Authors

Serguei V. S. Pakhomov
Serguei V. S. Pakhomov University of Minnesota
Thamar Solorio
Thamar Solorio Mohamed bin Zayed University of Artificial Intelligence
Christopher G. Chute
Christopher G. Chute Johns Hopkins University
Janyce Wiebe
Janyce Wiebe University of Pittsburgh
Steven Bethard
Steven Bethard University of Arizona
Rada Mihalcea
Rada Mihalcea University of Michigan–Ann Arbor
Jill Burstein
Jill Burstein Princeton University
Saif M. Mohammad
Saif M. Mohammad National Research Council Canada
Christof Monz
Christof Monz University of Amsterdam
Martha Palmer
Martha Palmer University of Colorado Boulder

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