Flip Korn

4.9k citations
64 papers · 2.7k indexed · h-index 26

Impact in

Papers in

Flip Korn

60 papers receiving 2.5k citations

Peers

Flip Korn
Comparison fields: 5 of 92
  • Signal Processing 1.5k
  • Computer Networks and Communications 1.2k
  • Artificial Intelligence 1.3k
  • Management Science and Operations Research 397
  • Geography, Planning and Development 158
Replace Nilesh Dalvi with:
Nilesh Dalvi United States
Marios Hadjieleftheriou United States
Dmitri V. Kalashnikov United States
Yannis Kotidis Greece
Viswanath Poosala United States
Sunil Prabhakar United States
Kyuseok Shim South Korea
Jan Chomicki United States
Martin Kersten Netherlands
Chee-Yong Chan Singapore
Flip Korn relative to Nilesh Dalvi United States Nilesh Dalvi's profile →
Citations per field
00.5×1.5×
Nilesh Dalvi · 1×
Citations per year

Countries citing papers authored by Flip Korn

Since Specialization
Citations

This map shows the geographic impact of Flip Korn'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 Flip Korn with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Flip Korn more than expected).

Fields of papers citing papers by Flip Korn

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Flip Korn. 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 Flip Korn. The network helps show where Flip Korn may publish in the future.

Co-authors

The 25 scholars most cited alongside Flip Korn, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Flip Korn Line = papers co-authored together Flip Korn links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20240
2 20220
3 20223
4 20187
5 20182
6
Managing Google’s data lake: an overview of the Goods system
201633
7 2016107
8 201521
9 20154
10 201513
11 20141
12 20121
13
Efficient and Effective Analysis of Data Quality using Pattern Tableaux.
201115
14 200834
15 2008120
16 200833
17 20035
18 200322
19 200257
20 200118

About Flip Korn

Flip Korn is a scholar working on Signal Processing, Computer Networks and Communications, Artificial Intelligence, Management Science and Operations Research and Information Systems, having authored 64 papers that have together received 2.7k indexed citations. Recurring topics across this work include Data Management and Algorithms (31 papers), Advanced Database Systems and Queries (28 papers), Data Mining Algorithms and Applications (12 papers), Data Quality and Management (12 papers), Algorithms and Data Compression (9 papers), Data Stream Mining Techniques (9 papers), Semantic Web and Ontologies (8 papers) and Time Series Analysis and Forecasting (5 papers). The work is most often cited by research in Signal Processing (1.5k citations), Computer Networks and Communications (1.2k citations), Artificial Intelligence (1.3k citations), Management Science and Operations Research (397 citations) and Geography, Planning and Development (158 citations). Flip Korn has collaborated with scholars based in United States, Canada and Singapore. Frequent co-authors include S. Muthukrishnan, Divesh Srivastava, Christos Faloutsos, H. V. Jagadish, Johannes Gehrke, Graham Cormode, Lukasz Golab, Bernd-Uwe Pagel, Zhiyuan Chen and Howard Karloff. Their work appears in journals such as Proceedings of the VLDB Endowment, ACM SIGMOD Record, IEEE Transactions on Knowledge and Data Engineering, Data & Knowledge Engineering and Journal of Computer and System Sciences.

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.

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