Ganesh Krishnan
Impact in
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- Data Quality and Management
- Artificial Intelligence top 5%
- Topic Modeling
- Privacy-Preserving Technologies in Data
- Semantic Web and Ontologies
- Advanced Graph Neural Networks
Papers in
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- Data Quality and Management 7
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- Web Data Mining and Analysis 5
- Co-authors
- AnHai Doan (6 shared papers)Esteban Arcaute (3 shared papers)Youngchoon Park (3 shared papers)Theodoros Rekatsinas (1 shared paper)Sidharth Mudgal (1 shared paper)Han Li (1 shared paper)Sanjib Das (4 shared papers)Haojun Zhang (4 shared papers)
- Journals
- Proceedings of the VLDB Endowment (2 papers)ACM SIGMOD Record (1 paper)BMC Medical Informatics and Decision Making (1 paper)Journal of Forensic Sciences (1 paper)Soft Matter (1 paper)
- Partner nations
- United States
In The Last Decade
Ganesh Krishnan
11 papers receiving 613 citations
Ganesh Krishnan's Hit Papers
Peers
Comparison fields: 5 of 62
- Management Science and Operations Research 474
- Artificial Intelligence 466
- Urology 52
- Information Systems 170
- Information Systems and Management 34
Countries citing papers authored by Ganesh Krishnan
This map shows the geographic impact of Ganesh Krishnan'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 Ganesh Krishnan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ganesh Krishnan more than expected).
Fields of papers citing papers by Ganesh Krishnan
This network shows the impact of papers produced by Ganesh Krishnan. 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 Ganesh Krishnan. The network helps show where Ganesh Krishnan may publish in the future.
Co-authors
The 25 scholars most cited alongside Ganesh Krishnan, 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 | Deep Learning for Entity Matching Hit paper breakdown → | 2018 | 290 |
| 2 | 2016 | 154 | |
| 3 | 2017 | 64 | |
| 4 | 2017 | 63 | |
| 5 | 2016 | 46 | |
| 6 | 2015 | 17 | |
| 7 | 2013 | 12 | |
| 8 | 2018 | 9 | |
| 9 | 2012 | 6 | |
| 10 | 2018 | 4 | |
| 11 | 2018 | 1 |
About Ganesh Krishnan
Ganesh Krishnan is a scholar working on Management Science and Operations Research, Information Systems, Computer Networks and Communications, Artificial Intelligence and Organic Chemistry, having authored 11 papers that have together received 666 indexed citations. Recurring topics across this work include Data Quality and Management (7 papers), Web Data Mining and Analysis (5 papers), Advanced Database Systems and Queries (3 papers), Topic Modeling (2 papers), Forensic Anthropology and Bioarchaeology Studies (1 paper), Organic Electronics and Photovoltaics (1 paper), Forensic and Genetic Research (1 paper) and Fullerene Chemistry and Applications (1 paper). The work is most often cited by research in Management Science and Operations Research (474 citations), Artificial Intelligence (466 citations), Urology (52 citations), Information Systems (170 citations) and Information Systems and Management (34 citations). Ganesh Krishnan has collaborated with scholars based in United States. Frequent co-authors include AnHai Doan, Esteban Arcaute, Youngchoon Park, Theodoros Rekatsinas, Sidharth Mudgal, Han Li, Sanjib Das, Haojun Zhang, Pradap Konda and Shishir Prasad. Their work appears in journals such as Proceedings of the VLDB Endowment, ACM SIGMOD Record, BMC Medical Informatics and Decision Making, Journal of Forensic Sciences and Soft Matter.
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.