Balázs Rácz
- Statistical and Nonlinear Physics top 1%
- Artificial Intelligence top 5%
- Information Systems top 5%
- Computer Networks and Communications top 10%
- Computer Vision and Pattern Recognition top 5%
- Co-authors
- Dániel FogarasAndrás LukácsAlbert-Ĺaszló BarabásiAlexei VázquezKároly CsalogányTamás SarlósZoltán DezsőEivind Almaas
- Topics
- Complex Network Analysis Techniques (5 papers)Web Data Mining and Analysis (3 papers)Data Mining Algorithms and Applications (3 papers)
- Journals
- Physical Review LettersIEEE Transactions on Knowledge and Data EngineeringTheoretical Computer Science
- Partner nations
- HungaryUnited StatesItaly
In The Last Decade
Balázs Rácz
11 papers receiving 785 citations
Peers
Comparison fields: 5 of 73
- Statistical and Nonlinear Physics 529
- Artificial Intelligence 290
- Information Systems 200
- Computer Networks and Communications 162
- Computer Vision and Pattern Recognition 150
Countries citing papers authored by Balázs Rácz
This map shows the geographic impact of Balázs Rácz'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 Balázs Rácz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Balázs Rácz more than expected).
Fields of papers citing papers by Balázs Rácz
This network shows the impact of papers produced by Balázs Rácz. 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 Balázs Rácz. The network helps show where Balázs Rácz may publish in the future.
Co-authorship network of co-authors of Balázs Rácz
This figure shows the co-authorship network connecting the top 25 collaborators of Balázs Rácz. A scholar is included among the top collaborators of Balázs Rácz 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 Balázs Rácz. Balázs Rácz is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 233 | |
| 3 | 7 | |
| 4 | PageRank és azon túl: Hiperhivatkozások szerepe a keresésben | 1 |
| 5 | 178 | |
| 6 | 36 | |
| 7 | The Dynamics of Information Access in the Online Media | 1 |
| 8 | 11 | |
| 9 | 131 | |
| 10 | 186 | |
| 11 | 15 | |
| 12 | nonordfp: an FP-growth variation without rebuilding the FP-tree | 39 |
About Balázs Rácz
Balázs Rácz is a scholar working on Statistical and Nonlinear Physics, Information Systems and Computational Theory and Mathematics, having authored 12 papers that have together received 840 indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (5 papers), Web Data Mining and Analysis (3 papers) and Data Mining Algorithms and Applications (3 papers). The work is most often cited by research in Statistical and Nonlinear Physics (529 citations), Transportation (76 citations) and Signal Processing (111 citations). Balázs Rácz has collaborated with scholars based in Hungary, United States and Italy. Frequent co-authors include Dániel Fogaras, András Lukács, Albert-Ĺaszló Barabási, Alexei Vázquez, Károly Csalogány, Tamás Sarlós, Zoltán Dezső, Eivind Almaas, Lars Schmidt-Thieme and Ferenc Bodon. Their work appears in journals such as Physical Review Letters, IEEE Transactions on Knowledge and Data Engineering and Theoretical Computer Science.
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.