D-Index & Metrics Best Publications

D-Index & Metrics 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.

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 41 Citations 7,529 182 World Ranking 5503 National Ranking 2690

Research.com Recognitions

Awards & Achievements

1977 - Fellow of the American Association for the Advancement of Science (AAAS)

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Linguistics
  • Natural language processing

His scientific interests lie mostly in Data science, Text mining, Biomedical text mining, Information extraction and MEDLINE. K. Bretonnel Cohen regularly links together related areas like Dimension in his Data science studies. The concepts of his Text mining study are interwoven with issues in Knowledge base and Protein–protein interaction.

His Biomedical text mining study combines topics in areas such as Pragmatics, Part of speech, World Wide Web and Ambiguity. His World Wide Web research is multidisciplinary, incorporating perspectives in Biocurator, Workflow and Identification. His Information extraction study which covers Ontology that intersects with Text processing.

His most cited work include:

  • Amazon mechanical turk: Gold mine or coal mine? (637 citations)
  • Overview of BioCreative II gene normalization. (281 citations)
  • A shared task involving multi-label classification of clinical free text (279 citations)

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

K. Bretonnel Cohen mainly investigates Artificial intelligence, Natural language processing, Data science, Information retrieval and Text mining. In his work, Component is strongly intertwined with Domain, which is a subfield of Natural language processing. He combines subjects such as Field, Use case, World Wide Web and Workflow with his study of Data science.

His work carried out in the field of Information retrieval brings together such families of science as Annotation and Entrez Gene. His work on Biomedical text mining as part of general Text mining research is frequently linked to MEDLINE and Manual curation, thereby connecting diverse disciplines of science. His studies deal with areas such as Semantics and Information extraction as well as Biomedical text mining.

He most often published in these fields:

  • Artificial intelligence (48.67%)
  • Natural language processing (46.02%)
  • Data science (30.97%)

What were the highlights of his more recent work (between 2015-2020)?

  • Artificial intelligence (48.67%)
  • Natural language processing (46.02%)
  • Annotation (12.39%)

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

His primary scientific interests are in Artificial intelligence, Natural language processing, Annotation, Information retrieval and Data science. His Natural language processing research is multidisciplinary, incorporating elements of Ontology and Contrast. His research investigates the link between Annotation and topics such as Domain that cross with problems in Treebank.

Within one scientific family, K. Bretonnel Cohen focuses on topics pertaining to Semantics under Information retrieval, and may sometimes address concerns connected to Referent, Information extraction, Noun phrase and Coreference. His study in Data science is interdisciplinary in nature, drawing from both Agile software development, Web service, Personalization, Text mining and Use case. His research integrates issues of Natural language and Biomedical text mining in his study of Ontology.

Between 2015 and 2020, his most popular works were:

  • Coreference annotation and resolution in the Colorado Richly Annotated Full Text (CRAFT) corpus of biomedical journal articles (22 citations)
  • The Colorado Richly Annotated Full Text (CRAFT) Corpus: Multi-Model Annotation in the Biomedical Domain (16 citations)
  • The Colorado Richly Annotated Full Text (CRAFT) Corpus: Multi-Model Annotation in the Biomedical Domain (16 citations)

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

Amazon mechanical turk: Gold mine or coal mine?

Karën Fort;Gilles Adda;K. Bretonnel Cohen.
Computational Linguistics (2011)

702 Citations

A shared task involving multi-label classification of clinical free text

John P. Pestian;Chris Brew;Pawel Matykiewicz;DJ Hovermale.
meeting of the association for computational linguistics (2007)

430 Citations

Frontiers of biomedical text mining: current progress

Pierre Zweigenbaum;Dina Demner-Fushman;Hong Yu;Kevin Bretonnel Cohen.
Briefings in Bioinformatics (2007)

394 Citations

Biomedical language processing: what's beyond PubMed?

Lawrence Hunter;K. Bretonnel Cohen.
Molecular Cell (2006)

392 Citations

Overview of BioCreative II gene normalization.

Alexander A. Morgan;Zhiyong Lu;Xinglong Wang;Aaron M. Cohen.
Genome Biology (2008)

387 Citations

Getting started in text mining.

K Bretonnel Cohen;Lawrence E Hunter.
PLOS Computational Biology (2008)

311 Citations

Manual curation is not sufficient for annotation of genomic databases

William A. Baumgartner;K. Bretonnel Cohen;Lynne M. Fox;George Acquaah-Mensah.
intelligent systems in molecular biology (2007)

296 Citations

Concept annotation in the CRAFT corpus

Michael Bada;Miriam Eckert;Donald Evans;Kristin Garcia.
BMC Bioinformatics (2012)

234 Citations

OpenDMAP: an open source, ontology-driven concept analysis engine, with applications to capturing knowledge regarding protein transport, protein interactions and cell-type-specific gene expression.

Lawrence Hunter;Zhiyong Lu;James Firby;William A Baumgartner.
BMC Bioinformatics (2008)

197 Citations

Sentiment Analysis of Suicide Notes: A Shared Task.

John P. Pestian;Pawel Matykiewicz;Michelle Linn-Gust;Brett R South.
Biomedical Informatics Insights (2012)

190 Citations

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