D-Index & Metrics Best Publications
Regina Barzilay

Regina Barzilay

D-Index & Metrics

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Computer Science D-index 73 Citations 21,480 204 World Ranking 682 National Ranking 414

Research.com Recognitions

Awards & Achievements

2018 - Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) For significant contributions to Natural Language Processing.

2017 - Fellow of the MacArthur Foundation

Overview

What is she best known for?

The fields of study she is best known for:

  • Artificial intelligence
  • Machine learning
  • Natural language processing

Artificial intelligence, Natural language processing, Automatic summarization, Information retrieval and Task are her primary areas of study. The concepts of her Artificial intelligence study are interwoven with issues in Machine learning, Baseline and Set. She has included themes like Context and Word in her Natural language processing study.

Her research integrates issues of Document retrieval, Data mining and Cluster analysis in her study of Automatic summarization. Her work carried out in the field of Information retrieval brings together such families of science as Transcription and Segmentation. Her research in Task intersects with topics in Speech recognition, Arabic, Semitic languages and Hebrew.

Her most cited work include:

  • Using lexical chains for text summarization (843 citations)
  • Modeling local coherence: An entity-based approach (499 citations)
  • Modeling local coherence: An entity-based approach (499 citations)

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

Her scientific interests lie mostly in Artificial intelligence, Natural language processing, Machine learning, Task and Theoretical computer science. Her Artificial intelligence research focuses on Set and how it connects with Data mining. The study incorporates disciplines such as Structure, Speech recognition and Information retrieval in addition to Natural language processing.

Her Machine learning study combines topics in areas such as Representation and Inference. The various areas that Regina Barzilay examines in her Task study include Question answering, Contrast, Baseline and Reinforcement learning. Her Theoretical computer science study integrates concerns from other disciplines, such as Graph and Molecular graph.

She most often published in these fields:

  • Artificial intelligence (65.85%)
  • Natural language processing (36.62%)
  • Machine learning (20.77%)

What were the highlights of her more recent work (between 2018-2021)?

  • Artificial intelligence (65.85%)
  • Machine learning (20.77%)
  • Natural language processing (36.62%)

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

Regina Barzilay mostly deals with Artificial intelligence, Machine learning, Natural language processing, Theoretical computer science and Generative grammar. Regina Barzilay regularly ties together related areas like Context in her Artificial intelligence studies. Regina Barzilay focuses mostly in the field of Context, narrowing it down to topics relating to Information needs and, in certain cases, Task.

Her Machine learning study incorporates themes from Variation and Representation. Her Natural language processing research is multidisciplinary, relying on both Similarity, Word and Decipherment. She has researched Theoretical computer science in several fields, including Correctness, Graph and Drug discovery.

Between 2018 and 2021, her most popular works were:

  • A Deep Learning Approach to Antibiotic Discovery (253 citations)
  • A graph-convolutional neural network model for the prediction of chemical reactivity. (159 citations)
  • Analyzing Learned Molecular Representations for Property Prediction. (138 citations)

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

  • Artificial intelligence
  • Machine learning
  • Programming language

Regina Barzilay mainly investigates Artificial intelligence, Theoretical computer science, Natural language processing, Graph and Language model. Her Artificial intelligence research integrates issues from Machine learning and Workflow. Her study in Theoretical computer science is interdisciplinary in nature, drawing from both Generative grammar, Transformer and Drug discovery.

Her Natural language processing research incorporates themes from Word, Task and Shot. Her studies deal with areas such as Intervention, Randomized controlled trial, Clinical trial and Documentation as well as Task. The Language model study combines topics in areas such as Stylometry and Fake news.

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.

Best Publications

Using lexical chains for text summarization

Regina Barzilay;Michael Elhadad.
Intelligent Scalable Text Summarization (1997)

1347 Citations

Modeling local coherence: An entity-based approach

Regina Barzilay;Regina Barzilay;Mirella Lapata.
Computational Linguistics (2008)

688 Citations

Extracting Paraphrases from a Parallel Corpus

Regina Barzilay;Kathleen R. McKeown.
meeting of the association for computational linguistics (2001)

627 Citations

Learning to paraphrase: an unsupervised approach using multiple-sequence alignment

Regina Barzilay;Lillian Lee.
north american chapter of the association for computational linguistics (2003)

584 Citations

Information Fusion in the Context of Multi-Document Summarization

Regina Barzilay;Kathleen R. McKeown;Michael Elhadad.
meeting of the association for computational linguistics (1999)

525 Citations

Inferring strategies for sentence ordering in multidocument news summarization

Regina Barzilay;Noemie Elhadad;Kathleen R. McKeown.
Journal of Artificial Intelligence Research (2002)

436 Citations

Multiple Aspect Ranking Using the Good Grief Algorithm

Benjamin Snyder;Regina Barzilay.
north american chapter of the association for computational linguistics (2007)

393 Citations

Tracking and summarizing news on a daily basis with Columbia's Newsblaster

Kathleen R. McKeown;Regina Barzilay;David Evans;Vasileios Hatzivassiloglou.
international conference on human language technology research (2002)

365 Citations

Style Transfer from Non-Parallel Text by Cross-Alignment

Tianxiao Shen;Tao Lei;Regina Barzilay;Tommi S. Jaakkola.
neural information processing systems (2017)

345 Citations

Catching the Drift: Probabilistic Content Models, with Applications to Generation and Summarization

Regina Barzilay;Lillian Lee.
north american chapter of the association for computational linguistics (2004)

341 Citations

Best Scientists Citing Regina Barzilay

Kathleen R. McKeown

Kathleen R. McKeown

Columbia University

Publications: 58

Mirella Lapata

Mirella Lapata

University of Edinburgh

Publications: 51

Dan Roth

Dan Roth

University of Pennsylvania

Publications: 42

Ani Nenkova

Ani Nenkova

Adobe Systems (United States)

Publications: 41

Dragomir R. Radev

Dragomir R. Radev

Yale University

Publications: 40

Eduard Hovy

Eduard Hovy

Carnegie Mellon University

Publications: 37

Ting Liu

Ting Liu

Harbin Institute of Technology

Publications: 33

Noah A. Smith

Noah A. Smith

University of Washington

Publications: 32

Ido Dagan

Ido Dagan

Bar-Ilan University

Publications: 30

Daniel Klein

Daniel Klein

University of California, Berkeley

Publications: 30

Chris Callison-Burch

Chris Callison-Burch

University of Pennsylvania

Publications: 29

Luke Zettlemoyer

Luke Zettlemoyer

University of Washington

Publications: 28

Graham Neubig

Graham Neubig

Carnegie Mellon University

Publications: 28

Horacio Saggion

Horacio Saggion

Pompeu Fabra University

Publications: 27

Hannaneh Hajishirzi

Hannaneh Hajishirzi

University of Washington

Publications: 26

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

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