Kris Ganjam
Impact in
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- Data Quality and Management
- Signal Processing top 5%
- Data Management and Algorithms
Papers in
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- Data Quality and Management 14
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- Web Data Mining and Analysis 7
- Co-authors
- Surajit Chaudhuri (10 shared papers)Rajeev Motwani (2 shared papers)Venkatesh Ganti (2 shared papers)Kaushik Chakrabarti (5 shared papers)Mohamed Yakout (1 shared paper)Yeye He (8 shared papers)Vivek Narasayya (5 shared papers)Xu Chu (2 shared papers)
- Journals
- Proceedings of the VLDB Endowment (2 papers)IEEE Data(base) Engineering Bulletin (3 papers)
- Partner nations
- United StatesUnited KingdomCanada
In The Last Decade
Kris Ganjam
16 papers receiving 642 citations
Peers
Comparison fields: 5 of 45
- Management Science and Operations Research 466
- Signal Processing 213
- Information Systems 347
- Artificial Intelligence 376
- Computer Networks and Communications 248
Countries citing papers authored by Kris Ganjam
This map shows the geographic impact of Kris Ganjam'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 Kris Ganjam with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kris Ganjam more than expected).
Fields of papers citing papers by Kris Ganjam
This network shows the impact of papers produced by Kris Ganjam. 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 Kris Ganjam. The network helps show where Kris Ganjam may publish in the future.
Co-authors
The 24 scholars most cited alongside Kris Ganjam, 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 | 2003 | 320 | |
| 2 | 2012 | 150 | |
| 3 | 2018 | 36 | |
| 4 | 2015 | 25 | |
| 5 | 2015 | 24 | |
| 6 | 2005 | 24 | |
| 7 | 2003 | 23 | |
| 8 | 2015 | 22 | |
| 9 | Data services leveraging Bing's data assets. | 2016 | 18 |
| 10 | 2018 | 13 | |
| 11 | 2008 | 11 | |
| 12 | 2017 | 7 | |
| 13 | Towards a Domain Independent Platform for Data Cleaning. | 2011 | 6 |
| 14 | 2017 | 5 | |
| 15 | Experiences with using Data Cleaning Technology for Bing Services. | 2012 | 1 |
| 16 | Expansion of Tail Concept Using Web Tables | 2014 | 1 |
About Kris Ganjam
Kris Ganjam is a scholar working on Management Science and Operations Research, Information Systems, Computer Networks and Communications, Artificial Intelligence and Signal Processing, having authored 16 papers that have together received 686 indexed citations. Recurring topics across this work include Data Quality and Management (14 papers), Web Data Mining and Analysis (7 papers), Advanced Database Systems and Queries (7 papers), Data Management and Algorithms (6 papers), Semantic Web and Ontologies (3 papers), Privacy-Preserving Technologies in Data (2 papers), Topic Modeling (2 papers) and Advanced Text Analysis Techniques (1 paper). The work is most often cited by research in Management Science and Operations Research (466 citations), Signal Processing (213 citations), Information Systems (347 citations), Artificial Intelligence (376 citations) and Computer Networks and Communications (248 citations). Kris Ganjam has collaborated with scholars based in United States, United Kingdom and Canada. Frequent co-authors include Surajit Chaudhuri, Rajeev Motwani, Venkatesh Ganti, Kaushik Chakrabarti, Mohamed Yakout, Yeye He, Vivek Narasayya, Xu Chu, Yudian Zheng and Xu Chu. Their work appears in journals such as Proceedings of the VLDB Endowment and IEEE Data(base) Engineering Bulletin.
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.