George Karypis
Impact in
- Computational Mathematics top 0.1%
- Information Systems top 0.01%
- Recommender Systems and Techniques
- Data Mining Algorithms and Applications
Papers in
-
- Advanced Graph Neural Networks 40
- Algorithms and Data Compression 30
-
- Data Mining Algorithms and Applications 58
- Recommender Systems and Techniques 50
- Co-authors
- Vipin Kumar (56 shared papers)John Riedl (6 shared papers)Joseph A. Konstan (2 shared papers)Badrul Sarwar (2 shared papers)Vipin Kumar (11 shared papers)Eui-Hong Han (24 shared papers)Mukund Deshpande (9 shared papers)Ying Zhao (9 shared papers)
- Journals
- Journal of Chemical Information and Modeling (6 papers)IEEE Transactions on Knowledge and Data Engineering (6 papers)Journal of Parallel and Distributed Computing (5 papers)Parallel Computing (5 papers)Data Mining and Knowledge Discovery (4 papers)
- Partner nations
- United StatesChinaCanada
In The Last Decade
George Karypis
382 papers receiving 40.9k citations
George Karypis's Hit Papers
Peers
Comparison fields: 5 of 220
- Computational Mathematics 573
- Information Systems 18.5k
- Hardware and Architecture 4.1k
- Artificial Intelligence 16.3k
- Signal Processing 5.1k
Countries citing papers authored by George Karypis
This map shows the geographic impact of George Karypis'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 George Karypis with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites George Karypis more than expected).
Fields of papers citing papers by George Karypis
This network shows the impact of papers produced by George Karypis. 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 George Karypis. The network helps show where George Karypis may publish in the future.
Co-authors
The 25 scholars most cited alongside George Karypis, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 392 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Item-based collaborative filtering recommendation algorithms Hit paper breakdown → | 2001 | 6826 |
| 2 | A Fast and High Quality Multilevel Scheme for Partitioning Irregular Graphs Hit paper breakdown → | 1998 | 4057 |
| 3 | A Comparison of Document Clustering Techniques Hit paper breakdown → | 2000 | 1894 |
| 4 | Interferon-inducible gene expression signature in peripheral blood cells of patients with severe lupus Hit paper breakdown → | 2003 | 1777 |
| 5 | Item-based top-Nrecommendation algorithms Hit paper breakdown → | 2004 | 1712 |
| 6 | Chameleon: hierarchical clustering using dynamic modeling Hit paper breakdown → | 1999 | 1612 |
| 7 | Analysis of recommendation algorithms for e-commerce Hit paper breakdown → | 2000 | 1422 |
| 8 | Multilevelk-way Partitioning Scheme for Irregular Graphs Hit paper breakdown → | 1998 | 1284 |
| 9 | Introduction to parallel computing: design and analysis of algorithms Hit paper breakdown → | 1994 | 926 |
| 10 | METIS: A Software Package for Partitioning Unstructured Graphs, Partitioning Meshes, and Computing Fill-Reducing Orderings of Sparse Matrices Hit paper breakdown → | 1997 | 890 |
| 11 | Frequent subgraph discovery Hit paper breakdown → | 2002 | 804 |
| 12 | Multilevel hypergraph partitioning: applications in VLSI domain Hit paper breakdown → | 1999 | 582 |
| 13 | Multilevel hypergraph partitioning Hit paper breakdown → | 1997 | 576 |
| 14 | SLIM: Sparse Linear Methods for Top-N Recommender Systems Hit paper breakdown → | 2011 | 512 |
| 15 | FISM Hit paper breakdown → | 2013 | 507 |
| 16 | 2004 | 475 | |
| 17 | 2001 | 469 | |
| 18 | Criterion Functions for Document Clustering: Experiments and Analysis | 2001 | 465 |
| 19 | Hierarchical Clustering Algorithms for Document Datasets Hit paper breakdown → | 2005 | 456 |
| 20 | Evaluation of hierarchical clustering algorithms for document datasets Hit paper breakdown → | 2002 | 438 |
About George Karypis
George Karypis is a scholar working on Artificial Intelligence, Information Systems, Computer Networks and Communications, Computational Theory and Mathematics and Molecular Biology, having authored 392 papers that have together received 43.9k indexed citations. Recurring topics across this work include Data Mining Algorithms and Applications (58 papers), VLSI and FPGA Design Techniques (55 papers), Recommender Systems and Techniques (50 papers), Interconnection Networks and Systems (50 papers), Data Management and Algorithms (43 papers), Advanced Graph Neural Networks (40 papers), Parallel Computing and Optimization Techniques (35 papers) and Algorithms and Data Compression (30 papers). The work is most often cited by research in Computational Mathematics (573 citations), Information Systems (18.5k citations), Hardware and Architecture (4.1k citations), Artificial Intelligence (16.3k citations) and Signal Processing (5.1k citations). George Karypis has collaborated with scholars based in United States, China and Canada. Frequent co-authors include Vipin Kumar, John Riedl, Joseph A. Konstan, Badrul Sarwar, Vipin Kumar, Eui-Hong Han, Mukund Deshpande, Ying Zhao, M. Kuramochi and Xia Ning. Their work appears in journals such as Journal of Chemical Information and Modeling, IEEE Transactions on Knowledge and Data Engineering, Journal of Parallel and Distributed Computing, Parallel Computing and Data Mining and Knowledge Discovery.
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.