Penelope Sibun

744 total citations
8 papers, 494 citations indexed

About

Penelope Sibun is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Information Systems. According to data from OpenAlex, Penelope Sibun has authored 8 papers receiving a total of 494 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Artificial Intelligence, 2 papers in Computer Vision and Pattern Recognition and 1 paper in Information Systems. Recurrent topics in Penelope Sibun's work include Natural Language Processing Techniques (6 papers), Topic Modeling (5 papers) and Speech and dialogue systems (4 papers). Penelope Sibun is often cited by papers focused on Natural Language Processing Techniques (6 papers), Topic Modeling (5 papers) and Speech and dialogue systems (4 papers). Penelope Sibun collaborates with scholars based in United States. Penelope Sibun's co-authors include Julian Kupiec, Jan Pedersen, Doug Cutting and Andreas Spitz and has published in prestigious journals such as Computational Intelligence and Scholarworks (University of Massachusetts Amherst).

In The Last Decade

Penelope Sibun

6 papers receiving 387 citations

Peers

Penelope Sibun
Comparison fields: 5 of 44
  • Artificial Intelligence 444
  • Computer Vision and Pattern Recognition 65
  • Information Systems 54
  • Molecular Biology 46
  • Language and Linguistics 28
Replace Jorn Veenstra with:
Jorn Veenstra Netherlands
Jakub Zavrel Netherlands
Mark Ferguson United Kingdom
Philippe Langlais Canada
Iñaki Alegria Spain
Abdessamad Echihabi United States
Ulrich Germann United Kingdom
Rabih Zbib United States
Hany Hassan United States
Patrick Schone United States
Jorn Veenstra Netherlands View profile →
Citations per field, relative to Penelope Sibun
Penelope Sibun · 1×
Citations per year, relative to Penelope Sibun
Penelope Sibun · 1×

Countries citing papers authored by Penelope Sibun

Since Specialization
Citations

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

Fields of papers citing papers by Penelope Sibun

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Penelope Sibun. 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 Penelope Sibun. The network helps show where Penelope Sibun may publish in the future.

Co-authorship network of co-authors of Penelope Sibun

This figure shows the co-authorship network connecting the top 25 collaborators of Penelope Sibun. A scholar is included among the top collaborators of Penelope Sibun based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Penelope Sibun. Penelope Sibun is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

8 of 8 papers shown
# Work Indexed citations
1 3
2 30
3
Domain Structure, Rhetorical Structure, and Text Structure
0
4 419
5 27
6
Locally organized text generation
9
7 6
8
Ap: A System to Direct and Control Natural Language Generation
0

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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