Gus Hahn-Powell

460 citations
18 papers · 220 · h-index 7

Impact in

Papers in

    • Natural Language Processing Techniques 7
    • Topic Modeling 6
    • Semantic Web and Ontologies 5
    • Speech Recognition and Synthesis 2
    • Biomedical Text Mining and Ontologies 5
    • Bioinformatics and Genomic Networks 2

Gus Hahn-Powell

17 papers receiving 208 citations

Peers

Gus Hahn-Powell
Comparison fields: 5 of 57
  • Artificial Intelligence 117
  • Literature and Literary Theory 34
  • Language and Linguistics 18
  • Information Systems and Management 9
  • Experimental and Cognitive Psychology 15
Replace Martin Reynaert with:
Martin Reynaert Netherlands
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Citations per year

Countries citing papers authored by Gus Hahn-Powell

Since Specialization
Citations

This map shows the geographic impact of Gus Hahn-Powell's research. 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 Gus Hahn-Powell with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gus Hahn-Powell more than expected).

Fields of papers citing papers by Gus Hahn-Powell

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Gus Hahn-Powell. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Gus Hahn-Powell. The network helps show where Gus Hahn-Powell may publish in the future.

Co-authors

The 23 scholars most cited alongside Gus Hahn-Powell, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Gus Hahn-Powell Line = papers co-authored together Gus Hahn-Powell links everyone, so they are left out of the graph.

All Works

18 of 18 papers shown
#Work
1 201546
2 201946
3 201837
4 201529
5 201621
6 20148
7
Odinson: A Fast Rule-based Information Extraction Framework
20207
8 20206
9 20234
10 20174
11 20183
12 20142
13
An investigation of coreference phenomena in the biomedical domain
20162
14
Country-level Arabic Dialect Identification using RNNs with and without Linguistic Features
20212
15 20181
16 20221
17 20181
18 20250

About Gus Hahn-Powell

Gus Hahn-Powell is a scholar working on Artificial Intelligence, Molecular Biology, Language and Linguistics, Management Science and Operations Research and Education, having authored 18 papers that have together received 220 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (7 papers), Topic Modeling (6 papers), Semantic Web and Ontologies (5 papers), Biomedical Text Mining and Ontologies (5 papers), Bioinformatics and Genomic Networks (2 papers), Speech Recognition and Synthesis (2 papers), Data Quality and Management (2 papers) and Writing and Handwriting Education (1 paper). The work is most often cited by research in Artificial Intelligence (117 citations), Literature and Literary Theory (34 citations), Language and Linguistics (18 citations), Information Systems and Management (9 citations) and Experimental and Cognitive Psychology (15 citations). Gus Hahn-Powell has collaborated with scholars based in United States. Frequent co-authors include Mihai Surdeanu, Marco A. Valenzuela-Escárcega, Robert Poole, Peter E. Clark, Daniel Fried, Peter Jansen, Diana Archangeli, Emek Demir, Özgün Babur and Clayton T. Morrison. Their work appears in journals such as The Journal of the Acoustical Society of America, Journal of English for Academic Purposes, Transactions of the Association for Computational Linguistics, Language learning & technology and Language Resources and Evaluation.

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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