Fattane Zarrinkalam
- Artificial Intelligence top 10%
- Information Systems top 5%
- Statistical and Nonlinear Physics top 5%
- Sociology and Political Science
- Communication
- Co-authors
- Mohsen KahaniEbrahim BagheriHossein FaniJelena JovanovićFeras Al‐ObeidatNegar ArabzadehWeichang DuGuangyuan Piao
- Topics
- Complex Network Analysis Techniques (13 papers)Recommender Systems and Techniques (11 papers)Topic Modeling (10 papers)
In The Last Decade
Fattane Zarrinkalam
31 papers receiving 286 citations
Peers
Comparison fields: 5 of 44
- Artificial Intelligence 166
- Information Systems 153
- Statistical and Nonlinear Physics 102
- Sociology and Political Science 71
- Communication 29
Countries citing papers authored by Fattane Zarrinkalam
This map shows the geographic impact of Fattane Zarrinkalam'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 Fattane Zarrinkalam with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fattane Zarrinkalam more than expected).
Fields of papers citing papers by Fattane Zarrinkalam
This network shows the impact of papers produced by Fattane Zarrinkalam. 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 Fattane Zarrinkalam. The network helps show where Fattane Zarrinkalam may publish in the future.
Co-authorship network of co-authors of Fattane Zarrinkalam
This figure shows the co-authorship network connecting the top 25 collaborators of Fattane Zarrinkalam. A scholar is included among the top collaborators of Fattane Zarrinkalam 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 Fattane Zarrinkalam. Fattane Zarrinkalam is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 4 | |
| 3 | 10 | |
| 4 | 7 | |
| 5 | 3 | |
| 6 | 2 | |
| 7 | 4 | |
| 8 | 4 | |
| 9 | 17 | |
| 10 | 1 | |
| 11 | 5 | |
| 12 | 14 | |
| 13 | 2 | |
| 14 | 78 | |
| 15 | 12 | |
| 16 | COLINA: a method for ranking SPARQL query results through content and link analysis | 0 |
| 17 | 4 | |
| 18 | 4 | |
| 19 | Using Semantic Relations to Improve Quality of a Citation Recommendation System | 2 |
| 20 | 22 |
About Fattane Zarrinkalam
Fattane Zarrinkalam is a scholar working on Information Systems, Statistical and Nonlinear Physics and Artificial Intelligence, having authored 33 papers that have together received 293 indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (13 papers), Recommender Systems and Techniques (11 papers) and Topic Modeling (10 papers). The work is most often cited by research in Statistical and Nonlinear Physics (102 citations), Information Systems (153 citations) and Artificial Intelligence (166 citations). Fattane Zarrinkalam has collaborated with scholars based in Canada, Iran and Italy. Frequent co-authors include Mohsen Kahani, Ebrahim Bagheri, Hossein Fani, Jelena Jovanović, Feras Al‐Obeidat, Negar Arabzadeh, Weichang Du, Guangyuan Piao, Ali A. Ghorbani and Yue Feng. Their work appears in journals such as Journal of Psychosomatic Research, Knowledge-Based Systems and Information Processing & Management.
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.