Sahar Ghannay

592 total citations
19 papers, 102 citations indexed

About

Sahar Ghannay is a scholar working on Artificial Intelligence, Molecular Biology and Signal Processing. According to data from OpenAlex, Sahar Ghannay has authored 19 papers receiving a total of 102 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Artificial Intelligence, 4 papers in Molecular Biology and 3 papers in Signal Processing. Recurrent topics in Sahar Ghannay's work include Natural Language Processing Techniques (9 papers), Topic Modeling (6 papers) and Speech and dialogue systems (5 papers). Sahar Ghannay is often cited by papers focused on Natural Language Processing Techniques (9 papers), Topic Modeling (6 papers) and Speech and dialogue systems (5 papers). Sahar Ghannay collaborates with scholars based in France. Sahar Ghannay's co-authors include Nathalie Camelin, Yannick Estève, Guillaume Postic, Fariza Tahi, Antoine Laurent, Sophie Rosset, Emmanuel Morin, Hervé Bredin, Paul Deléglise and Christophe Servan and has published in prestigious journals such as Bioinformatics, Briefings in Bioinformatics and Speech Communication.

In The Last Decade

Sahar Ghannay

16 papers receiving 93 citations

Peers

Sahar Ghannay
Comparison fields: 5 of 19
  • Artificial Intelligence 69
  • Molecular Biology 29
  • Signal Processing 22
  • Materials Chemistry 4
  • Sociology and Political Science 3
Replace Julien Tourille with:
Julien Tourille France
Chuanbiao Song China
Gowthami Somepalli United States
Guillaume Wisniewski France
Saravanan Radhakrishnan India
Wolfgang Seeker Germany
Prajjwal Bhargava United States
Wael Farhan Jordan
Suyang Dai China
Wael Salloum United States
Julien Tourille France View profile →
Citations per field, relative to Sahar Ghannay
Sahar Ghannay · 1×
Citations per year, relative to Sahar Ghannay
Sahar Ghannay · 1×

Countries citing papers authored by Sahar Ghannay

Since Specialization
Citations

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

Fields of papers citing papers by Sahar Ghannay

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sahar Ghannay

This figure shows the co-authorship network connecting the top 25 collaborators of Sahar Ghannay. A scholar is included among the top collaborators of Sahar Ghannay 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 Sahar Ghannay. Sahar Ghannay is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

19 of 19 papers shown
# Work Indexed citations
1 10
2 7
3 0
4 0
5 11
6 2
7 1
8 3
9 1
10 1
11 11
12 3
13 1
14 1
15 3
16
Experiments from LIMSI at the French Named Entity Recognition Coarse-grained task
1
17 1
18 37
19 8

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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