H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 37 Citations 9,833 136 World Ranking 5422 National Ranking 8

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Natural language processing
  • Programming language

His primary areas of investigation include Natural language processing, Artificial intelligence, Czech, Parsing and Dependency. His Natural language processing study combines topics from a wide range of disciplines, such as Scheme, Speech recognition and Categorization. Jan Hajič combines Artificial intelligence and Code in his studies.

Within one scientific family, Jan Hajič focuses on topics pertaining to Word under Czech, and may sometimes address concerns connected to State, Artificial neural network and Named-entity recognition. His work on Dependency grammar, Top-down parsing and Semantic dependency as part of general Parsing study is frequently linked to Semantic computing, bridging the gap between disciplines. Jan Hajič combines topics linked to Annotation with his work on Dependency.

His most cited work include:

  • Non-Projective Dependency Parsing using Spanning Tree Algorithms (806 citations)
  • Universal Dependencies v1: A Multilingual Treebank Collection (602 citations)
  • The Prague Dependency Treebank (290 citations)

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

His primary scientific interests are in Artificial intelligence, Natural language processing, Czech, Treebank and Annotation. Artificial intelligence is often connected to Speech recognition in his work. His study explores the link between Natural language processing and topics such as Dependency that cross with problems in Scheme.

His Czech research also works with subjects such as

  • Translation most often made with reference to German,
  • Word together with Named-entity recognition. His Treebank study incorporates themes from Syntax and Spoken language. His Annotation research incorporates elements of Semantics, Layer, Information retrieval and Coreference.

He most often published in these fields:

  • Artificial intelligence (67.40%)
  • Natural language processing (64.76%)
  • Czech (40.09%)

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

  • Artificial intelligence (67.40%)
  • Natural language processing (64.76%)
  • Treebank (29.07%)

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

His primary areas of study are Artificial intelligence, Natural language processing, Treebank, Dependency and Annotation. His work carried out in the field of Artificial intelligence brings together such families of science as Named-entity recognition and Valency. His Natural language processing research is multidisciplinary, incorporating elements of Czech and Scheme.

Jan Hajič works mostly in the field of Treebank, limiting it down to topics relating to Lexicon and, in certain cases, Synonym, as a part of the same area of interest. His Annotation study combines topics in areas such as Computational linguistics, Semantics, Coreference and Syntax. While the research belongs to areas of Parsing, Jan Hajič spends his time largely on the problem of Natural language, intersecting his research to questions surrounding Categorization.

Between 2017 and 2021, his most popular works were:

  • CoNLL 2018 Shared Task : Multilingual Parsing from Raw Text to Universal Dependencies (177 citations)
  • Neural Architectures for Nested NER through Linearization (66 citations)
  • Universal Dependencies v2: An Evergrowing Multilingual Treebank Collection (56 citations)

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

  • Artificial intelligence
  • Natural language processing
  • Programming language

Jan Hajič focuses on Artificial intelligence, Natural language processing, Dependency, Universal dependencies and Parsing. In general Artificial intelligence study, his work on Annotation and Artificial neural network often relates to the realm of Modal and Matching, thereby connecting several areas of interest. He has included themes like Scheme, Web search query, Word and Czech in his Natural language processing study.

As a part of the same scientific family, Jan Hajič mostly works in the field of Scheme, focusing on Natural language and, on occasion, Computational linguistics. Universal dependencies is a subfield of Treebank that Jan Hajič investigates. He combines subjects such as Sentence, Directed graph and Serialization with his study of Parsing.

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

Non-Projective Dependency Parsing using Spanning Tree Algorithms

Ryan McDonald;Fernando Pereira;Kiril Ribarov;Jan Hajic.
empirical methods in natural language processing (2005)

1050 Citations

Universal Dependencies v1: A Multilingual Treebank Collection

Joakim Nivre;Marie-Catherine de Marneffe;Filip Ginter;Yoav Goldberg.
language resources and evaluation (2016)

819 Citations

Prague Dependency Treebank 2.0 (PDT 2.0)

Jan Hajič;Jarmila Panevová;Eva Hajičová;Petr Sgall.
(2006)

510 Citations

The Prague Dependency Treebank

Alena Böhmová;Jan Hajič;Eva Hajičová;Barbora Hladká.
(2003)

435 Citations

Prague Dependency Treebank

Jan Hajič;Eva Hajičová;Marie Mikulová;Jiří Mírovský.
(2017)

407 Citations

CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies

Daniel Zeman;Martin Popel;Milan Straka;Jan Hajic.
conference on computational natural language learning (2017)

368 Citations

CoNLL 2018 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies

Daniel Zeman;Jan Hajič;Martin Popel;Martin Potthast.
Proceedings of the CoNLL 2018 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies (2018)

362 Citations

UDPipe: Trainable Pipeline for Processing CoNLL-U Files Performing Tokenization, Morphological Analysis, POS Tagging and Parsing

Milan Straka;Jan Hajic;Jana Straková.
language resources and evaluation (2016)

339 Citations

A Statistical Parser for Czech

Michael Collins;Jan Hajic;Lance Ramshaw;Christoph Tillmann.
meeting of the association for computational linguistics (1999)

316 Citations

Universal Dependencies 2.1

Joakim Nivre;Željko Agić;Lars Ahrenberg;Lene Antonsen.
(2017)

246 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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