H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science D-index 140 Citations 171,999 386 World Ranking 18 National Ranking 12

Research.com Recognitions

Awards & Achievements

2013 - ACM Fellow For contributions to natural language processing research and education.

2010 - Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) For significant contributions to statistical natural language processing, including in statistical parsing and grammar induction, and education through leading textbooks.

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Programming language
  • Linguistics

Artificial intelligence, Natural language processing, Parsing, Machine learning and Word are his primary areas of study. Christopher D. Manning regularly links together related areas like Pattern recognition in his Artificial intelligence studies. His Natural language processing research is multidisciplinary, incorporating elements of Speech recognition and Task.

His Parsing research is multidisciplinary, incorporating perspectives in Dependency, Grammar and Syntactic structure. His Machine learning study combines topics in areas such as Data mining, Relationship extraction, Consistency, Question answering and Resource. His Word research includes elements of Context, Variety, Representation and Support vector machine.

His most cited work include:

  • Glove: Global Vectors for Word Representation (17101 citations)
  • Introduction to Information Retrieval (11187 citations)
  • Foundations of Statistical Natural Language Processing (7614 citations)

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

His main research concerns Artificial intelligence, Natural language processing, Parsing, Machine learning and Task. His research is interdisciplinary, bridging the disciplines of Pattern recognition and Artificial intelligence. His Natural language processing study incorporates themes from Dependency, Speech recognition and Word.

His Parsing research integrates issues from Theoretical computer science and Grammar. The various areas that he examines in his Machine translation study include Translation and Phrase. As part of his studies on Sentence, he often connects relevant subjects like Artificial neural network.

He most often published in these fields:

  • Artificial intelligence (75.16%)
  • Natural language processing (56.99%)
  • Parsing (21.09%)

What were the highlights of his more recent work (between 2017-2021)?

  • Artificial intelligence (75.16%)
  • Natural language processing (56.99%)
  • Syntax (8.35%)

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

Christopher D. Manning mostly deals with Artificial intelligence, Natural language processing, Syntax, Language model and Sentence. His study in Artificial intelligence is interdisciplinary in nature, drawing from both Machine learning and Task. Christopher D. Manning frequently studies issues relating to Coreference and Natural language processing.

In his research, Fluency is intimately related to Predicate, which falls under the overarching field of Syntax. His Language model study integrates concerns from other disciplines, such as Artificial neural network, Context and Transformer. His work on Semantic dependency as part of general Parsing study is frequently connected to Poverty, therefore bridging the gap between diverse disciplines of science and establishing a new relationship between them.

Between 2017 and 2021, his most popular works were:

  • What Does BERT Look at? An Analysis of BERT’s Attention (455 citations)
  • HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering (424 citations)
  • CoQA: A Conversational Question Answering Challenge (385 citations)

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

  • Artificial intelligence
  • Programming language
  • Linguistics

Christopher D. Manning mainly investigates Artificial intelligence, Natural language processing, Question answering, Language model and Syntax. His Artificial intelligence research includes themes of Machine learning and Graph. His Natural language processing research incorporates themes from Scratch and Coreference.

The study incorporates disciplines such as Natural language understanding, Encoder and Discriminative model in addition to Language model. His research integrates issues of Parse tree, Word, Word representation and Space in his study of Syntax. His work deals with themes such as Test and Context, which intersect with Information retrieval.

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

Introduction to Information Retrieval

Christopher D. Manning;Prabhakar Raghavan;Hinrich Schütze.
(2005)

19238 Citations

Glove: Global Vectors for Word Representation

Jeffrey Pennington;Richard Socher;Christopher Manning.
empirical methods in natural language processing (2014)

16468 Citations

Foundations of Statistical Natural Language Processing

Christopher D. Manning;Hinrich Schütze.
(1999)

14790 Citations

The Stanford CoreNLP Natural Language Processing Toolkit

Christopher Manning;Mihai Surdeanu;John Bauer;Jenny Finkel.
meeting of the association for computational linguistics (2014)

5544 Citations

Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank

Richard Socher;Alex Perelygin;Jean Wu;Jason Chuang.
empirical methods in natural language processing (2013)

4364 Citations

Feature-rich part-of-speech tagging with a cyclic dependency network

Kristina Toutanova;Dan Klein;Christopher D. Manning;Yoram Singer.
north american chapter of the association for computational linguistics (2003)

3721 Citations

Accurate Unlexicalized Parsing

Dan Klein;Christopher D. Manning.
meeting of the association for computational linguistics (2003)

3664 Citations

Incorporating Non-local Information into Information Extraction Systems by Gibbs Sampling

Jenny Rose Finkel;Trond Grenager;Christopher Manning.
meeting of the association for computational linguistics (2005)

3409 Citations

Generating Typed Dependency Parses from Phrase Structure Parses

Marie-Catherine de Marneffe;Bill MacCartney;Christopher D. Manning.
language resources and evaluation (2006)

2800 Citations

Effective Approaches to Attention-based Neural Machine Translation

Minh-Thang Luong;Hieu Pham;Christopher D. Manning.
arXiv: Computation and Language (2015)

2375 Citations

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Best Scientists Citing Christopher D. Manning

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Google (United States)

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Max Planck Institute for Informatics

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University of Illinois at Urbana-Champaign

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University of Paderborn

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Jianfeng Gao

Jianfeng Gao

Microsoft (United States)

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Hai Zhao

Hai Zhao

Shanghai Jiao Tong University

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University of Melbourne

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