Negar Arabzadeh
- Information Systems top 5%
- Information Retrieval and Search Behavior 16
- Web Data Mining and Analysis 5
- Expert finding and Q&A systems 3
- Artificial Intelligence top 10%
- Topic Modeling 22
- Natural Language Processing Techniques 6
- Domain Adaptation and Few-Shot Learning 6
- Machine Learning and Algorithms 3
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- Advanced Image and Video Retrieval Techniques 7
- Co-authors
- Ebrahim BagheriCharles L. A. ClarkeMohammad AliannejadiMorteza ZihayatAlexandra VtyurinaJelena JovanovićXinyi YanMaarten de Rijke
- Journals
- Machine Learning (2 papers)Information Processing & Management (1 paper)Journal of Biomedical Informatics (1 paper)
- Partner nations
- CanadaNetherlandsIran
In The Last Decade
Negar Arabzadeh
32 papers receiving 184 citations
Peers
Comparison fields: 5 of 26
- Information Systems 111
- Artificial Intelligence 123
- Signal Processing 27
- Health Informatics 2
- Computer Vision and Pattern Recognition 25
Countries citing papers authored by Negar Arabzadeh
This map shows the geographic impact of Negar Arabzadeh'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 Negar Arabzadeh with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Negar Arabzadeh more than expected).
Fields of papers citing papers by Negar Arabzadeh
This network shows the impact of papers produced by Negar Arabzadeh. 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 Negar Arabzadeh. The network helps show where Negar Arabzadeh may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Negar Arabzadeh, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 1 | |
| 2 | 2025 | 2 | |
| 3 | 2025 | 0 | |
| 4 | 2025 | 1 | |
| 5 | 2025 | 2 | |
| 6 | 2025 | 1 | |
| 7 | 2024 | 10 | |
| 8 | 2024 | 4 | |
| 9 | 2024 | 5 | |
| 10 | 2024 | 2 | |
| 11 | 2024 | 1 | |
| 12 | 2023 | 3 | |
| 13 | 2023 | 5 | |
| 14 | 2023 | 1 | |
| 15 | 2023 | 10 | |
| 16 | 2022 | 1 | |
| 17 | 2022 | 25 | |
| 18 | 2021 | 19 | |
| 19 | 2019 | 6 | |
| 20 | 2018 | 5 |
About Negar Arabzadeh
Negar Arabzadeh is a scholar working on Information Systems, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 37 papers that have together received 186 indexed citations. Recurring topics across this work include Topic Modeling (22 papers), Information Retrieval and Search Behavior (16 papers), Advanced Image and Video Retrieval Techniques (7 papers), Natural Language Processing Techniques (6 papers), Domain Adaptation and Few-Shot Learning (6 papers), Web Data Mining and Analysis (5 papers), Expert finding and Q&A systems (3 papers) and Machine Learning and Algorithms (3 papers). The work is most often cited by research in Information Systems (111 citations), Artificial Intelligence (123 citations) and Signal Processing (27 citations). Negar Arabzadeh has collaborated with scholars based in Canada, Netherlands and Iran. Frequent co-authors include Ebrahim Bagheri, Charles L. A. Clarke, Mohammad Aliannejadi, Morteza Zihayat, Alexandra Vtyurina, Jelena Jovanović, Xinyi Yan, Maarten de Rijke, Fattane Zarrinkalam and Bhaskar Mitra. Their work appears in journals such as Machine Learning, Information Processing & Management and Journal of Biomedical Informatics.
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.