H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science D-index 94 Citations 45,785 239 World Ranking 204 National Ranking 124

Research.com Recognitions

Awards & Achievements

2020 - Fellow of the American Academy of Arts and Sciences

2019 - Fellow of the American Association for the Advancement of Science (AAAS)

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Natural language processing
  • Law

His primary areas of study are Artificial intelligence, Natural language processing, Parsing, Word and Machine learning. His work carried out in the field of Artificial intelligence brings together such families of science as Coherence and Pattern recognition. Natural language processing is represented through his Sentence, Phrase, Natural language, WordNet and Noun research.

His study in Parsing is interdisciplinary in nature, drawing from both Probabilistic logic, Rule-based machine translation and Pruning. Many of his research projects under Word are closely connected to Path with Path, tying the diverse disciplines of science together. The concepts of his Machine learning study are interwoven with issues in Semantic similarity and Automatic summarization.

His most cited work include:

  • Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition (2624 citations)
  • Speech and Language Processing (1997 citations)
  • Distant supervision for relation extraction without labeled data (1996 citations)

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

Dan Jurafsky mainly focuses on Artificial intelligence, Natural language processing, Speech recognition, Parsing and Machine learning. Language model, Machine translation, Word, Natural language and Phrase are among the areas of Artificial intelligence where the researcher is concentrating his efforts. Much of his study explores Language model relationship to Artificial neural network.

The study incorporates disciplines such as Conversation and Grammar in addition to Natural language processing. Dan Jurafsky focuses mostly in the field of Speech recognition, narrowing it down to topics relating to Dependency grammar and, in certain cases, Grammar induction. Dan Jurafsky is studying Reinforcement learning, which is a component of Machine learning.

He most often published in these fields:

  • Artificial intelligence (59.76%)
  • Natural language processing (47.34%)
  • Speech recognition (19.53%)

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

  • Artificial intelligence (59.76%)
  • Natural language processing (47.34%)
  • Framing (3.55%)

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

His primary scientific interests are in Artificial intelligence, Natural language processing, Framing, Language model and Machine learning. Dan Jurafsky undertakes multidisciplinary studies into Artificial intelligence and GLUE in his work. His work on Sentence as part of general Natural language processing research is often related to Structure, thus linking different fields of science.

His biological study deals with issues like Social media, which deal with fields such as Implicature, Frame, Inference, Categorization and Presupposition. Dan Jurafsky interconnects Training set, Vocabulary, Transfer of learning, Syntax and Natural language in the investigation of issues within Language model. His Machine learning research is multidisciplinary, incorporating elements of Null hypothesis, Point, Set and Benchmark.

Between 2018 and 2021, his most popular works were:

  • The Diversity-Innovation Paradox in Science (95 citations)
  • Generalization through Memorization: Nearest Neighbor Language Models (49 citations)
  • Social Bias Frames: Reasoning about Social and Power Implications of Language (40 citations)

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

  • Artificial intelligence
  • Law
  • Machine learning

Artificial intelligence, Social media, Language model, Natural language processing and Framing are his primary areas of study. In his study, which falls under the umbrella issue of Artificial intelligence, Automatic summarization and Training set is strongly linked to Machine learning. His studies in Social media integrate themes in fields like Cognitive psychology, Implicature, Statement, Inference and Categorization.

His Language model research includes themes of Textual entailment, Coherence, Feature learning, Reading comprehension and Generalization. Dan Jurafsky mostly deals with Sentence in his studies of Natural language processing. His Framing study combines topics in areas such as Framing, Terrorism, Data science and Polarization.

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

Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition

Daniel Jurafsky;James H. Martin.
(2000)

4271 Citations

Speech and Language Processing

Dan Jurafsky;James H. Martin.
(2000)

3006 Citations

Automatic labeling of semantic roles

Daniel Gildea;Daniel Jurafsky.
Computational Linguistics (2002)

2225 Citations

Cheap and Fast -- But is it Good? Evaluating Non-Expert Annotations for Natural Language Tasks

Rion Snow;Brendan O'Connor;Daniel Jurafsky;Andrew Ng.
empirical methods in natural language processing (2008)

2181 Citations

Distant supervision for relation extraction without labeled data

Mike Mintz;Steven Bills;Rion Snow;Daniel Jurafsky.
international joint conference on natural language processing (2009)

2148 Citations

Dialogue act modeling for automatic tagging and recognition of conversational speech

Andreas Stolcke;Noah Coccaro;Rebecca Bates;Paul Taylor.
Computational Linguistics (2000)

1174 Citations

Learning Syntactic Patterns for Automatic Hypernym Discovery

Rion Snow;Daniel Jurafsky;Andrew Y. Ng.
neural information processing systems (2004)

881 Citations

Probabilistic Relations between Words: Evidence from Reduction in Lexical Production

Daniel Jurafsky;Alan Bell;Michelle Gregory;William D. Raymond.
(2008)

756 Citations

Deep Reinforcement Learning for Dialogue Generation

Jiwei Li;Will Monroe;Alan Ritter;Dan Jurafsky.
empirical methods in natural language processing (2016)

754 Citations

A Probabilistic Model of Lexical and Syntactic Access and Disambiguation

Daniel Jurafsky;Daniel Jurafsky.
Cognitive Science (1996)

667 Citations

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