H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science D-index 32 Citations 3,643 97 World Ranking 7530 National Ranking 20

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Linguistics
  • Programming language

His scientific interests lie mostly in Artificial intelligence, Natural language processing, Parsing, Grammar and Treebank. His Artificial intelligence study frequently draws connections to adjacent fields such as Set. Stephan Oepen has included themes like Discriminative model and Ranking in his Natural language processing study.

His Parsing study combines topics from a wide range of disciplines, such as Affix grammar, Extended Affix Grammar, SemEval and Adaptive grammar. Stephan Oepen combines subjects such as Open text, British National Corpus and Ambiguity with his study of Grammar. His biological study spans a wide range of topics, including Programming language, Grammar systems theory and Minimal recursion semantics.

His most cited work include:

  • The grammar matrix: an open-source starter-kit for the rapid development of cross-linguistically consistent broad-coverage precision grammars (170 citations)
  • SemEval 2015 Task 18: Broad-Coverage Semantic Dependency Parsing (164 citations)
  • LinGO Redwoods: A Rich and Dynamic Treebank for HPSG (135 citations)

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

Stephan Oepen mainly focuses on Artificial intelligence, Natural language processing, Parsing, Grammar and Head-driven phrase structure grammar. Artificial intelligence and Set are commonly linked in his work. Stephan Oepen combines subjects such as Dependency and Annotation with his study of Natural language processing.

His Parsing study integrates concerns from other disciplines, such as Software, Theoretical computer science, Selection and Graph. His studies examine the connections between Grammar and genetics, as well as such issues in Programming language, with regards to Synchronous context-free grammar. The study incorporates disciplines such as Computational linguistics and Realization in addition to Head-driven phrase structure grammar.

He most often published in these fields:

  • Artificial intelligence (73.55%)
  • Natural language processing (71.07%)
  • Parsing (45.45%)

What were the highlights of his more recent work (between 2014-2021)?

  • Natural language processing (71.07%)
  • Artificial intelligence (73.55%)
  • Parsing (45.45%)

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

His primary areas of investigation include Natural language processing, Artificial intelligence, Parsing, Linguistics and Graph. His Natural language processing research is multidisciplinary, incorporating perspectives in Annotation, Grammar, Classifier and Meaning. Much of his study explores Artificial intelligence relationship to Dependency graph.

His Parsing study combines topics from a wide range of disciplines, such as Ranking, Sentence, Dependency, Semantics and Natural language. His Representation and Semantic analysis study in the realm of Linguistics connects with subjects such as Standardization and Multitude. His work deals with themes such as Constructed language, Terminology, Linguistic Data Consortium and Comparability, which intersect with Graph.

Between 2014 and 2021, his most popular works were:

  • Word vectors, reuse, and replicability: Towards a community repository of large-text resources (77 citations)
  • Towards a catalogue of linguistic graph banks (33 citations)
  • Layers of Interpretation: On Grammar and Compositionality (31 citations)

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

  • Artificial intelligence
  • Linguistics
  • Programming language

Stephan Oepen spends much of his time researching Natural language processing, Artificial intelligence, Parsing, Sentence and Linguistics. His Natural language processing study frequently involves adjacent topics like Terminology. Stephan Oepen combines topics linked to Dependency with his work on Parsing.

The concepts of his Sentence study are interwoven with issues in Principle of compositionality, Meaning, Directed graph, Graph and Semantic property. His work on Grammar and Interpretation as part of general Linguistics research is frequently linked to Concreteness, bridging the gap between disciplines. His Grammar research is multidisciplinary, relying on both Annotation, Frame and Granularity.

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

The grammar matrix: an open-source starter-kit for the rapid development of cross-linguistically consistent broad-coverage precision grammars

Emily M. Bender;Dan Flickinger;Stephan Oepen.
international conference on computational linguistics (2002)

344 Citations

LinGO Redwoods: A Rich and Dynamic Treebank for HPSG

Stephan Oepen;Dan Flickinger;Kristina Toutanova;Christopher D. Manning.
Research on Language and Computation (2004)

206 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

The LinGO Redwoods treebank motivation and preliminary applications

Stephan Oepen;Kristina Toutanova;Stuart Shieber;Christopher Manning.
international conference on computational linguistics (2002)

162 Citations

TSNLP: Test Suites for Natural Language Processing

Sabine Lehmann;Stephan Oepen;Sylvie Regnier-Prost;Klaus Netter.
international conference on computational linguistics (1996)

133 Citations

Word vectors, reuse, and replicability: Towards a community repository of large-text resources

Murhaf Fares;Andrey Kutuzov;Stephan Oepen;Erik Velldal.
Proceedings of the 21st Nordic Conference on Computational Linguistics, NoDaLiDa, 22-24 May 2017, Gothenburg, Sweden (2017)

130 Citations

Discriminant-Based MRS Banking

Stephan Oepen;Jan Tore Lønning.
language resources and evaluation (2006)

122 Citations

High efficiency realization for a wide-coverage unification grammar

John Carroll;Stephan Oepen.
international joint conference on natural language processing (2005)

113 Citations

Towards systematic grammar profiling.Test suite technology 10 years after

Stephan Oepen;Dan Flickinger.
Computer Speech & Language (1998)

100 Citations

Stochastic HPSG Parse Disambiguation using the Redwoods Corpus

Kristina Toutanova;Christopher D. Manning;Dan Flickinger;Stephan Oepen.
Research on Language and Computation (2005)

96 Citations

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