Natural Language Engineering

18.7k citations
719 papers · · active since 1950

Impact in

    • Natural Language Processing Techniques
    • Topic Modeling
    • Speech and dialogue systems
    • Semantic Web and Ontologies
    • Advanced Text Analysis Techniques
    • Text Readability and Simplification
    • Sentiment Analysis and Opinion Mining

Papers in

    • Natural Language Processing Techniques 513
    • Topic Modeling 450
    • Speech and dialogue systems 157
    • Advanced Text Analysis Techniques 69
    • Text Readability and Simplification 68
    • Semantic Web and Ontologies 61
    • Text and Document Classification Technologies 37
    • Authorship Attribution and Profiling 35

Natural Language Engineering

660 papers receiving 16.0k citations

Peers

Natural Language Engineering
Comparison fields: 5 of 182
  • Artificial Intelligence 15.6k
  • Health Informatics 192
  • Information Systems 2.9k
  • Language and Linguistics 898
  • Computer Science Applications 355
Replace Transactions of the Association for Computational Linguistics with:
Transactions of the Association for Computational Linguistics United States
Cognitive Systems Research United States
Connection Science China
Semantic Web Germany
The Knowledge Engineering Review United Kingdom
Minds and Machines United States
Journal of Web Semantics Germany
Artificial Life United States
Autonomous Agents and Multi-Agent Systems United States
IEEE Computational Intelligence Magazine China
Natural Language Engineering relative to Transactions of the Association for Computational Linguistics United States Transactions of the Association for Computational Linguistics's profile →
Citations per field
00.5×1.5×1.8×
Transactions of the Association for Computational Linguistics · 1×
Citations per year

Countries where authors publish in Natural Language Engineering

Since Specialization
Citations

This map shows the geographic impact of research published in Natural Language Engineering. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by papers published in Natural Language Engineering with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Natural Language Engineering more than expected).

Fields of papers published in Natural Language Engineering

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers published in Natural Language Engineering. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers published in Natural Language Engineering.

About Natural Language Engineering

The 719 papers published in Natural Language Engineering in the last decades have received a total of 18.7k indexed citations . Papers published in Natural Language Engineering usually cover Artificial Intelligence (663 papers), Language and Linguistics (36 papers), Information Systems (73 papers), Health Informatics (4 papers) and Computer Vision and Pattern Recognition (49 papers) specifically the topics of Natural Language Processing Techniques (513 papers), Topic Modeling (450 papers), Speech and dialogue systems (157 papers), Advanced Text Analysis Techniques (69 papers), Text Readability and Simplification (68 papers), Semantic Web and Ontologies (61 papers), Text and Document Classification Technologies (37 papers) and Authorship Attribution and Profiling (35 papers). The most active scholars publishing in Natural Language Engineering are Robert Dale, Kenneth Church, Steven Abney, Adam Lally, David Ferrucci, Dekang Lin, John S. Justeson, Dan Flickinger, Ehud Reiter and Martha Palmer.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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