World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
97
Citations
51331
World Ranking
414
National Ranking
228

Research.com Recognitions

  • 2009 - Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) For significant contributions to many aspects of the theory and practice of machine learning.

Overview

William W. Cohen is affiliated with Google in the United States and has contributed extensively to research within the field of Computer Science, with a focus on Artificial Intelligence. Their work spans across subfields such as Computer Vision and Pattern Recognition, Statistical and Nonlinear Physics, Computer Science Applications, and Information Systems.

The main topics of research covered by Cohen include:

  • Topic Modeling
  • Natural Language Processing Techniques
  • Multimodal Machine Learning Applications
  • Explainable Artificial Intelligence (XAI)
  • Semantic Web and Ontologies
  • Domain Adaptation and Few-Shot Learning
  • Complex Network Analysis Techniques

Cohen has been published frequently in several venues, including:

  • arXiv (Cornell University)
  • Proceedings of the International AAAI Conference on Web and Social Media
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • Transactions of the Association for Computational Linguistics
  • Circulation

Recent published papers involving Cohen cover a range of topics and venues:

  • Link-PLSA-LDA: A New Unsupervised Model for Topics and Influence of Blogs, 2021, Proceedings of the International AAAI Conference on Web and Social Media
  • Program of Thoughts Prompting: Disentangling Computation from Reasoning for Numerical Reasoning Tasks, 2022, arXiv (Cornell University)
  • Transformer Memory as a Differentiable Search Index, 2022, arXiv (Cornell University)
  • Recovering Implicit Thread Structure in Newsgroup Style Conversations, 2021, Proceedings of the International AAAI Conference on Web and Social Media
  • Evaluating Explanations: How Much Do Explanations from the Teacher Aid Students?, 2022, Transactions of the Association for Computational Linguistics

Frequent co-authors of Cohen include:

  • Haitian Sun
  • Pat Verga
  • Wenhu Chen
  • Bhuwan Dhingra
  • Michiel de Jong

In 2009, Cohen was recognized as a Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) for significant contributions to theory and practice in the field of machine learning.

Best Publications

  • Fast effective rule induction

    William W. Cohen

  • Proceedings of the 25th international conference on Machine learning

    William Cohen;Andrew McCallum;Sam Roweis

  • A comparison of string distance metrics for name-matching tasks

    William W. Cohen;Pradeep Ravikumar;Stephen E. Fienberg

  • Recommendation as classification: using social and content-based information in recommendation

    Chumki Basu;Haym Hirsh;William Cohen

  • HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering

    Zhilin Yang;Peng Qi;Saizheng Zhang;Yoshua Bengio

  • Revisiting semi-supervised learning with graph embeddings

    Zhilin Yang;William W. Cohen;Ruslan Salakhutdinov

  • Context-sensitive learning methods for text categorization

    William W. Cohen;Yoram Singer

  • Never-ending learning

    T. Mitchell;W. Cohen;E. Hruschka;P. Talukdar

  • Never-ending learning

    T. Mitchell;W. Cohen;E. Hruschka;P. Talukdar

  • Learning to order things

    William W. Cohen;Robert E. Schapire;Yoram Singer

  • Semi-Markov Conditional Random Fields for Information Extraction

    Sunita Sarawagi;William W. Cohen

  • Learning Rules that Classify E-Mail

    William W. Cohen

  • Adaptive name matching in information integration

    M. Bilenko;R. Mooney;W. Cohen;P. Ravikumar

  • Relational retrieval using a combination of path-constrained random walks

    Ni Lao;William W. Cohen

  • Random Walk Inference and Learning in A Large Scale Knowledge Base

    Ni Lao;Tom Mitchell;William W. Cohen

  • Integration of heterogeneous databases without common domains using queries based on textual similarity

    William W. Cohen

  • Beyond Independent Relevance: Methods and Evaluation Metrics for Subtopic Retrieval

    Cheng Xiang Zhai;William W. Cohen;John Lafferty

  • A simple, fast, and effective rule learner

    William W. Cohen;Yoram Singer

  • PubMedQA: A Dataset for Biomedical Research Question Answering

    Qiao Jin;Bhuwan Dhingra;Zhengping Liu;William W. Cohen

  • Learning to match and cluster large high-dimensional data sets for data integration

    William W. Cohen;Jacob Richman

  • Ordered landmarks in planning

    Jörg Hoffmann;Julie Porteous;Laura Sebastia

Frequent Co-Authors

Kenneth R. Koedinger
Kenneth R. Koedinger Carnegie Mellon University
Ruslan Salakhutdinov
Ruslan Salakhutdinov Carnegie Mellon University
Lidong Bing
Lidong Bing Carnegie Mellon University
Haym Hirsh
Haym Hirsh Cornell University
William Yang Wang
William Yang Wang University of California, Santa Barbara
Robert F. Murphy
Robert F. Murphy Carnegie Mellon University
Yoram Singer
Yoram Singer Princeton University
Tom M. Mitchell
Tom M. Mitchell Carnegie Mellon University
Eric P. Xing
Eric P. Xing Mohamed bin Zayed University of Artificial Intelligence
Jamie Callan
Jamie Callan Carnegie Mellon University

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