2023 - Research.com Computer Science in Czech Republic Leader Award
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 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
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.
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.
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Universal Dependencies v1: A Multilingual Treebank Collection
Joakim Nivre;Marie-Catherine de Marneffe;Filip Ginter;Yoav Goldberg.
language resources and evaluation (2016)
Non-Projective Dependency Parsing using Spanning Tree Algorithms
Ryan McDonald;Fernando Pereira;Kiril Ribarov;Jan Hajic.
empirical methods in natural language processing (2005)
CoNLL 2018 Shared Task : Multilingual Parsing from Raw Text to Universal Dependencies
Daniel Zeman;Jan Hajič;Martin Popel;Martin Potthast.
conference on computational natural language learning (2018)
Prague Dependency Treebank 2.0 (PDT 2.0)
Jan Hajič;Jarmila Panevová;Eva Hajičová;Petr Sgall.
The Prague Dependency Treebank
Alena Böhmová;Jan Hajič;Eva Hajičová;Barbora Hladká.
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)
Prague Dependency Treebank
Jan Hajič;Eva Hajičová;Marie Mikulová;Jiří Mírovský.
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)
A Statistical Parser for Czech
Michael Collins;Jan Hajic;Lance Ramshaw;Christoph Tillmann.
meeting of the association for computational linguistics (1999)
Universal Dependencies 2.1
Joakim Nivre;Željko Agić;Lars Ahrenberg;Lene Antonsen.
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