D-Index & Metrics Best Publications

D-Index & Metrics

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Computer Science D-index 35 Citations 5,025 161 World Ranking 5953 National Ranking 90

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Programming language
  • Natural language processing

His primary areas of investigation include Artificial intelligence, Natural language processing, Parsing, Task and Head-driven phrase structure grammar. His Artificial intelligence research is multidisciplinary, relying on both Machine learning and Pattern recognition. Yusuke Miyao combines subjects such as Generative grammar, Support vector machine and Task with his study of Natural language processing.

Yusuke Miyao has researched Parsing in several fields, including Sentence, Probabilistic logic and Rule-based machine translation. His research in Task intersects with topics in Paraphrase, Logical consequence, Inference and Contradiction. Yusuke Miyao focuses mostly in the field of Bottom-up parsing, narrowing it down to topics relating to Ambiguity and, in certain cases, Domain and Information extraction.

His most cited work include:

  • Probabilistic CFG with Latent Annotations (253 citations)
  • Event extraction from biomedical papers using a full parser. (218 citations)
  • Feature forest models for probabilistic hpsg parsing (183 citations)

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

Yusuke Miyao mostly deals with Artificial intelligence, Natural language processing, Parsing, Head-driven phrase structure grammar and Treebank. His research on Artificial intelligence often connects related areas such as Task. The Task study combines topics in areas such as Question answering and Inference.

His studies in Natural language processing integrate themes in fields like Annotation, Programming language and Grammar. His Parsing research also works with subjects such as

  • Probabilistic logic which is related to area like Statistical model,
  • Information retrieval together with Relation. His research integrates issues of Vietnamese and Text segmentation in his study of Treebank.

He most often published in these fields:

  • Artificial intelligence (85.71%)
  • Natural language processing (81.43%)
  • Parsing (41.43%)

What were the highlights of his more recent work (between 2015-2021)?

  • Artificial intelligence (85.71%)
  • Natural language processing (81.43%)
  • Treebank (16.67%)

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

Yusuke Miyao mainly focuses on Artificial intelligence, Natural language processing, Treebank, Parsing and Task. His work is dedicated to discovering how Artificial intelligence, Machine learning are connected with Baseline and other disciplines. His work carried out in the field of Natural language processing brings together such families of science as Annotation, Textual entailment and Relation.

His Treebank research is multidisciplinary, incorporating perspectives in Syntactic structure, Scheme and Vietnamese. His Parsing research is multidisciplinary, incorporating elements of Example-based machine translation, Machine translation software usability, Word order and Graph. His Task research incorporates elements of Context and Closed captioning.

Between 2015 and 2021, his most popular works were:

  • Classifying Temporal Relations by Bidirectional LSTM over Dependency Paths (47 citations)
  • Using Left-corner Parsing to Encode Universal Structural Constraints in Grammar Induction (34 citations)
  • TwiMed: Twitter and PubMed Comparable Corpus of Drugs, Diseases, Symptoms, and Their Relations. (33 citations)

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

  • Artificial intelligence
  • Programming language
  • Natural language processing

Yusuke Miyao focuses on Artificial intelligence, Natural language processing, Econometrics, Textual entailment and Primary market. His studies deal with areas such as Machine learning and Task as well as Artificial intelligence. His study on Treebank is often connected to On demand as part of broader study in Natural language processing.

His Textual entailment study combines topics from a wide range of disciplines, such as Lexical knowledge, Automated theorem proving and Relation. His Primary market study combines topics in areas such as Stock market bubble and Restricted stock. Many of his research projects under Programming language are closely connected to ENCODE with ENCODE, tying the diverse disciplines of science together.

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

Event extraction from biomedical papers using a full parser.

Akane Yakushiji;Yuka Tateisi;Yusuke Miyao;Jun-ichi Tsujii.
pacific symposium on biocomputing (2000)

321 Citations

Probabilistic CFG with Latent Annotations

Takuya Matsuzaki;Yusuke Miyao;Jun'ichi Tsujii.
meeting of the association for computational linguistics (2005)

309 Citations

Feature forest models for probabilistic hpsg parsing

Yusuke Miyao;Jun'ichi Tsujii.
Computational Linguistics (2008)

265 Citations

Universal Dependencies 1.2

Joakim Nivre;Željko Agić;Maria Jesus Aranzabe;Masayuki Asahara.
(2015)

193 Citations

Protein–protein interaction extraction by leveraging multiple kernels and parsers

Makoto Miwa;Rune Sætre;Yusuke Miyao;Jun’ichi Tsujii;Jun’ichi Tsujii.
International Journal of Medical Informatics (2009)

189 Citations

SemEval 2015 Task 18: Broad-Coverage Semantic Dependency Parsing

Stephan Oepen;Marco Kuhlmann;Yusuke Miyao;Daniel Zeman.
north american chapter of the association for computational linguistics (2014)

188 Citations

Evaluating contributions of natural language parsers to protein–protein interaction extraction

Yusuke Miyao;Kenji Sagae;Rune Sætre;Takuya Matsuzaki.
Bioinformatics (2009)

188 Citations

Corpus-Oriented grammar development for acquiring a head-driven phrase structure grammar from the penn treebank

Yusuke Miyao;Takashi Ninomiya;Jun’ichi Tsujii.
international joint conference on natural language processing (2004)

177 Citations

Probabilistic Disambiguation Models for Wide-Coverage HPSG Parsing

Yusuke Miyao;Jun'ichi Tsujii.
meeting of the association for computational linguistics (2005)

158 Citations

Task-oriented Evaluation of Syntactic Parsers and Their Representations

Yusuke Miyao;Rune Saetre;Kenji Sagae;Takuya Matsuzaki.
meeting of the association for computational linguistics (2008)

123 Citations

Best Scientists Citing Yusuke Miyao

Jun'ichi Tsujii

Jun'ichi Tsujii

National Institute of Advanced Industrial Science and Technology

Publications: 104

Sophia Ananiadou

Sophia Ananiadou

University of Manchester

Publications: 101

Yoshimasa Tsuruoka

Yoshimasa Tsuruoka

University of Tokyo

Publications: 40

Makoto Miwa

Makoto Miwa

Toyota Technological Institute

Publications: 36

Yue Zhang

Yue Zhang

Westlake University

Publications: 31

Daniel Klein

Daniel Klein

University of California, Berkeley

Publications: 28

Sampo Pyysalo

Sampo Pyysalo

University of Turku

Publications: 27

Ting Liu

Ting Liu

Harbin Institute of Technology

Publications: 24

Josef van Genabith

Josef van Genabith

German Research Centre for Artificial Intelligence

Publications: 23

Stephan Oepen

Stephan Oepen

University of Oslo

Publications: 23

Xiaojun Wan

Xiaojun Wan

Peking University

Publications: 22

Joakim Nivre

Joakim Nivre

Uppsala University

Publications: 19

Noah A. Smith

Noah A. Smith

University of Washington

Publications: 19

Tomoko Ohta

Tomoko Ohta

University of Tokyo

Publications: 18

Cathy H. Wu

Cathy H. Wu

University of Delaware

Publications: 18

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking d-index is inferred from publications deemed to belong to the considered discipline.

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