H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science D-index 32 Citations 4,608 248 World Ranking 7416 National Ranking 370

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Programming language
  • Natural language processing

Josef van Genabith mainly investigates Artificial intelligence, Natural language processing, Parsing, Speech recognition and Machine translation. His Artificial intelligence research incorporates themes from Machine learning and Arabic. His Natural language processing research incorporates elements of Dependency and Grammar.

The study incorporates disciplines such as Syntax, Variety and Phrase in addition to Speech recognition. His study in Machine translation is interdisciplinary in nature, drawing from both Domain and Translation. His research investigates the connection between Treebank and topics such as Structure that intersect with issues in Unification and Annotation.

His most cited work include:

  • Discourse representation theory (211 citations)
  • Learning Morphology with Morfette (113 citations)
  • Long-Distance Dependency Resolution in Automatically Acquired Wide-Coverage PCFG-Based LFG Approximations (110 citations)

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

Josef van Genabith focuses on Artificial intelligence, Natural language processing, Machine translation, Parsing and Speech recognition. His studies in Artificial intelligence integrate themes in fields like Machine learning and Task. His studies deal with areas such as Annotation and Grammar as well as Natural language processing.

His Machine translation research is multidisciplinary, incorporating perspectives in Translation and Phrase. His Speech recognition research is multidisciplinary, incorporating elements of Sentence, Context and Test set. His Treebank study combines topics from a wide range of disciplines, such as Probabilistic logic, Arabic, German and Link grammar.

He most often published in these fields:

  • Artificial intelligence (73.08%)
  • Natural language processing (65.03%)
  • Machine translation (34.62%)

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

  • Machine translation (34.62%)
  • Artificial intelligence (73.08%)
  • Transformer (5.94%)

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

His primary scientific interests are in Machine translation, Artificial intelligence, Transformer, Natural language processing and Translation. Josef van Genabith has researched Machine translation in several fields, including Machine learning, Contrast, Task and Human–computer interaction. His research in Artificial intelligence is mostly concerned with Computational linguistics.

He interconnects Algorithm, Residual, Phrase and Pronoun in the investigation of issues within Transformer. Josef van Genabith is interested in Hindi, which is a branch of Natural language processing. The various areas that Josef van Genabith examines in his Translation study include Curriculum, Representation, Index and Readability.

Between 2018 and 2021, his most popular works were:

  • Self-Supervised Neural Machine Translation (12 citations)
  • Lipschitz Constrained Parameter Initialization for Deep Transformers (8 citations)
  • Why Deep Transformers are Difficult to Converge? From Computation Order to Lipschitz Restricted Parameter Initialization (7 citations)

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

  • Artificial intelligence
  • Programming language
  • Machine learning

His main research concerns Machine translation, Artificial intelligence, Algorithm, Transformer and Natural language processing. Josef van Genabith combines subjects such as Speech recognition and Task with his study of Machine translation. His Task study integrates concerns from other disciplines, such as Computational linguistics and Contrast.

His research links Machine learning with Artificial intelligence. His research integrates issues of Initialization and Normalization in his study of Algorithm. Josef van Genabith studies BLEU, a branch of Natural language processing.

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

Discourse representation theory

Hans Kamp;Josef Van Genabith;Uwe Reyle.
IBM Germany Scientific Symposium Series (2011)

334 Citations

#hardtoparse: POS tagging and parsing the twitterverse

Jennifer Foster;Özlem Çetinoǧlu;Joachim Wagner;Joseph Le Roux.
national conference on artificial intelligence (2011)

160 Citations

Learning Morphology with Morfette

Grzegorz Chrupala;Georgiana Dinu;Josef van Genabith.
language resources and evaluation (2008)

155 Citations

Long-Distance Dependency Resolution in Automatically Acquired Wide-Coverage PCFG-Based LFG Approximations

Aoife Cahill;Michael Burke;Ruth O'Donovan;Josef Van Genabith.
meeting of the association for computational linguistics (2004)

130 Citations

QuestionBank: Creating a Corpus of Parse-Annotated Questions

John Judge;Aoife Cahill;Josef van Genabith.
meeting of the association for computational linguistics (2006)

112 Citations

Bridging SMT and TM with Translation Recommendation

Yifan He;Yanjun Ma;Josef van Genabith;Andy Way.
meeting of the association for computational linguistics (2010)

98 Citations

From News to Comment: Resources and Benchmarks for Parsing the Language of Web 2.0

Jennifer Foster;Ozlem Cetinoglu;Joachim Wagner;Joseph Le Roux.
international joint conference on natural language processing (2011)

95 Citations

Automatic Extraction of Arabic Multiword Expressions

Mohammed Attia;Antonio Toral;Lamia Tounsi;Pavel Pecina.
international conference on computational linguistics (2010)

92 Citations

Statistical Post-Editing for a Statistical MT System

Hanna Bechara;Yanjun Ma;Josef van Genabith.
Proceedings of Machine Translation Summit XIII: Papers (2011)

83 Citations

Exploring the Use of Text Classification in the Legal Domain

Octavia-Maria Sulea;Marcos Zampieri;Shervin Malmasi;Mihaela Vela.
arXiv: Computation and Language (2017)

73 Citations

If you think any of the details on this page are incorrect, let us know.

Contact us

Best Scientists Citing Josef van Genabith

Andy Way

Andy Way

Dublin City University

Publications: 53

Lucia Specia

Lucia Specia

Imperial College London

Publications: 45

Qun Liu

Qun Liu

Huawei Technologies (China)

Publications: 38

Marco Turchi

Marco Turchi

Fondazione Bruno Kessler

Publications: 27

Nizar Habash

Nizar Habash

New York University Abu Dhabi

Publications: 22

Barbara Plank

Barbara Plank

IT University of Copenhagen

Publications: 22

Philipp Koehn

Philipp Koehn

Johns Hopkins University

Publications: 21

Marcos Zampieri

Marcos Zampieri

Rochester Institute of Technology

Publications: 21

Anders Søgaard

Anders Søgaard

University of Copenhagen

Publications: 20

Marcello Federico

Marcello Federico

Amazon (United States)

Publications: 15

Rico Sennrich

Rico Sennrich

University of Zurich

Publications: 13

Barry Haddow

Barry Haddow

University of Edinburgh

Publications: 13

Slav Petrov

Slav Petrov

Google (United States)

Publications: 13

Holger Schwenk

Holger Schwenk

Facebook (United States)

Publications: 13

Joakim Nivre

Joakim Nivre

Uppsala University

Publications: 13

Timothy Baldwin

Timothy Baldwin

University of Melbourne

Publications: 13

Something went wrong. Please try again later.