Saeedeh Shekarpour
- Artificial Intelligence top 5%
- Information Systems top 5%
- Management Science and Operations Research top 10%
- Molecular Biology
- Computer Networks and Communications
- Co-authors
- Sören AuerAxel-Cyrille Ngonga NgomoAmit ShethEdgard MarxS.D. KatebiJens LehmannKuldeep SinghManas Gaur
- Topics
- Semantic Web and Ontologies (16 papers)Topic Modeling (11 papers)Natural Language Processing Techniques (7 papers)
- Partner nations
- GermanyUnited StatesIran
In The Last Decade
Saeedeh Shekarpour
27 papers receiving 368 citations
Peers
Comparison fields: 5 of 50
- Artificial Intelligence 334
- Information Systems 111
- Management Science and Operations Research 68
- Molecular Biology 53
- Computer Networks and Communications 48
Countries citing papers authored by Saeedeh Shekarpour
This map shows the geographic impact of Saeedeh Shekarpour'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 Saeedeh Shekarpour with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Saeedeh Shekarpour more than expected).
Fields of papers citing papers by Saeedeh Shekarpour
This network shows the impact of papers produced by Saeedeh Shekarpour. 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 Saeedeh Shekarpour. The network helps show where Saeedeh Shekarpour may publish in the future.
Co-authorship network of co-authors of Saeedeh Shekarpour
This figure shows the co-authorship network connecting the top 25 collaborators of Saeedeh Shekarpour. A scholar is included among the top collaborators of Saeedeh Shekarpour 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 Saeedeh Shekarpour. Saeedeh Shekarpour is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 15 | |
| 2 | 3 | |
| 3 | Context-aware Entity Linking with Attentive Neural Networks on Wikidata Knowledge Graph | 1 |
| 4 | 32 | |
| 5 | 21 | |
| 6 | 5 | |
| 7 | Publishing a Quality Context-aware Annotated Corpus and Lexicon for Harassment Research. | 1 |
| 8 | Personalized Health Knowledge Graph. | 22 |
| 9 | 3 | |
| 10 | 9 | |
| 11 | 1 | |
| 12 | 61 | |
| 13 | 19 | |
| 14 | 6 | |
| 15 | 16 | |
| 16 | 1 | |
| 17 | 7 | |
| 18 | 27 | |
| 19 | Query Segmentation and Resource Disambiguation Leveraging Background Knowledge. | 4 |
| 20 | 0 |
About Saeedeh Shekarpour
Saeedeh Shekarpour is a scholar working on Artificial Intelligence, Management Science and Operations Research and Signal Processing, having authored 29 papers that have together received 402 indexed citations. Recurring topics across this work include Semantic Web and Ontologies (16 papers), Topic Modeling (11 papers) and Natural Language Processing Techniques (7 papers). The work is most often cited by research in Artificial Intelligence (334 citations), Management Science and Operations Research (68 citations) and Information Systems (111 citations). Saeedeh Shekarpour has collaborated with scholars based in Germany, United States and Iran. Frequent co-authors include Sören Auer, Axel-Cyrille Ngonga Ngomo, Amit Sheth, Edgard Marx, S.D. Katebi, Jens Lehmann, Kuldeep Singh, Manas Gaur, Amélie Gyrard and María-Esther Vidal. Their work appears in journals such as IEEE Intelligent Systems, Journal of Web Semantics and Semantic Web.
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.