Natural Language Engineering

725 papers and 12.8k indexed citations i.

About

The 725 papers published in Natural Language Engineering in the last decades have received a total of 12.8k indexed citations. Papers published in Natural Language Engineering usually cover Artificial Intelligence (669 papers), Information Systems (78 papers) and Computer Vision and Pattern Recognition (53 papers) specifically the topics of Natural Language Processing Techniques (518 papers), Topic Modeling (461 papers) and Speech and dialogue systems (156 papers). The most active scholars publishing in Natural Language Engineering are Robert Dale, Kenneth Church, Adam Lally, David Ferrucci, John S. Justeson, Ehud Reiter, Steven Abney, Dekang Lin, Mark Sanderson and Ellen M. Voorhees.

In The Last Decade

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.

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).

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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2025