H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 87 Citations 31,144 304 World Ranking 300 National Ranking 185

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Machine learning
  • Statistics

His main research concerns Artificial intelligence, Natural language processing, Parsing, Word and Inference. The Artificial intelligence study combines topics in areas such as Machine learning, Task and Set. His work carried out in the field of Natural language processing brings together such families of science as Annotation and FrameNet.

His studies in Parsing integrate themes in fields like Dependency, Representation and Graph. His Word study combines topics in areas such as WordNet, Space, Binary number and Embedding. His biological study spans a wide range of topics, including Commonsense reasoning and Translation.

His most cited work include:

  • From Tweets to Polls: Linking Text Sentiment to Public Opinion Time Series (1444 citations)
  • Part-of-Speech Tagging for Twitter: Annotation, Features, and Experiments (812 citations)
  • Improved Part-of-Speech Tagging for Online Conversational Text with Word Clusters (599 citations)

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

Noah A. Smith mostly deals with Artificial intelligence, Natural language processing, Machine learning, Parsing and Task. His Word, Language model, Dependency grammar, Inference and Natural language investigations are all subjects of Artificial intelligence research. Noah A. Smith regularly ties together related areas like Variety in his Language model studies.

As part of his studies on Natural language processing, he frequently links adjacent subjects like Context. His specific area of interest is Machine learning, where he studies Structured prediction. Noah A. Smith has included themes like Dependency, Probabilistic logic and Theoretical computer science in his Parsing study.

He most often published in these fields:

  • Artificial intelligence (67.20%)
  • Natural language processing (46.24%)
  • Machine learning (18.00%)

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

  • Artificial intelligence (67.20%)
  • Natural language processing (46.24%)
  • Language model (12.07%)

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

Artificial intelligence, Natural language processing, Language model, Machine learning and Task are his primary areas of study. His study on Artificial intelligence is mostly dedicated to connecting different topics, such as Code. His research in Natural language processing intersects with topics in Word and Vocabulary.

His Word research incorporates themes from Range and Coreference. The study incorporates disciplines such as Domain, Semantics, Transformer and Machine translation in addition to Language model. His studies in Machine learning integrate themes in fields like Test data, Variety and State.

Between 2018 and 2021, his most popular works were:

  • Linguistic Knowledge and Transferability of Contextual Representations (335 citations)
  • Don’t Stop Pretraining: Adapt Language Models to Domains and Tasks (225 citations)
  • Knowledge Enhanced Contextual Word Representations (185 citations)

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

  • Artificial intelligence
  • Machine learning
  • Statistics

Noah A. Smith focuses on Artificial intelligence, Machine learning, Language model, Natural language processing and Word. Noah A. Smith has researched Artificial intelligence in several fields, including Test data, Task and Set. His studies deal with areas such as Data mapping, Benchmark, State and Code as well as Machine learning.

His studies examine the connections between Language model and genetics, as well as such issues in Transformer, with regards to Recurrent neural network and Computer engineering. His Natural language processing study incorporates themes from Similarity and Coreference. His work carried out in the field of Word brings together such families of science as Polyglot, Semantic similarity, Range, Dependency grammar and Reinforcement learning.

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.

Top Publications

From Tweets to Polls: Linking Text Sentiment to Public Opinion Time Series

Brendan O'Connor;Ramnath Balasubramanyan;Bryan R. Routledge;Noah A. Smith.
international conference on weblogs and social media (2010)

2428 Citations

Part-of-Speech Tagging for Twitter: Annotation, Features, and Experiments

Kevin Gimpel;Nathan Schneider;Brendan O'Connor;Dipanjan Das.
meeting of the association for computational linguistics (2011)

1213 Citations

Improved Part-of-Speech Tagging for Online Conversational Text with Word Clusters

Olutobi Owoputi;Brendan O'Connor;Chris Dyer;Kevin Gimpel.
north american chapter of the association for computational linguistics (2013)

851 Citations

The Web as a parallel corpus

Philip Resnik;Noah A. Smith.
Computational Linguistics (2003)

795 Citations

A Latent Variable Model for Geographic Lexical Variation

Jacob Eisenstein;Brendan O'Connor;Noah A. Smith;Eric P. Xing.
empirical methods in natural language processing (2010)

751 Citations

A Simple, Fast, and Effective Reparameterization of IBM Model 2

Chris Dyer;Victor Chahuneau;Noah A. Smith.
north american chapter of the association for computational linguistics (2013)

679 Citations

Transition-Based Dependency Parsing with Stack Long Short-Term Memory

Chris Dyer;Miguel Ballesteros;Wang Ling;Austin Matthews.
arXiv: Computation and Language (2015)

649 Citations

Retrofitting Word Vectors to Semantic Lexicons

Manaal Faruqui;Jesse Dodge;Sujay Kumar Jauhar;Chris Dyer.
north american chapter of the association for computational linguistics (2015)

585 Citations

Better Hypothesis Testing for Statistical Machine Translation: Controlling for Optimizer Instability

Jonathan H. Clark;Chris Dyer;Alon Lavie;Noah A. Smith.
meeting of the association for computational linguistics (2011)

490 Citations

What is the Jeopardy Model? A Quasi-Synchronous Grammar for QA

Mengqiu Wang;Noah A. Smith;Teruko Mitamura.
empirical methods in natural language processing (2007)

438 Citations

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

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