Nick Koudas

183 papers receiving 7.3k citations

Hit Papers

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Peers

Nick Koudas
Comparison fields: 5 of 118
  • Signal Processing 4.2k
  • Computer Networks and Communications 4.2k
  • Artificial Intelligence 4.2k
  • Information Systems 2.2k
  • Management Science and Operations Research 1.2k
Replace Haixun Wang with:
Haixun Wang United States
Divyakant Agrawal United States
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M. TAMER ÖZSU Canada
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Citations per year

Countries citing papers authored by Nick Koudas

Since Specialization
Citations

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

Fields of papers citing papers by Nick Koudas

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nick Koudas

This figure shows the co-authorship network connecting the top 25 collaborators of Nick Koudas. A scholar is included among the top collaborators of Nick Koudas 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 Nick Koudas. Nick Koudas is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 5
2
Some Research Opportunities on Twitter Advertising.
6
3 225
4
BlogScope: a system for online analysis of high volume text streams
55
5
Revisiting the (Machine) Semantic Web: The Missing Layers for the Human Semantic Web
2
6
Searching the Blogosphere.
24
7
Seeking stable clusters in the blogosphere
44
8 64
9
Column heterogeneity as a measure of data quality
8
10 24
11
MIX: a meta-data indexing system for XML
1
12
Approximate joins: concepts and techniques
21
13
DIMACS Summer School Tutorial on New Frontiers in Data Mining.
1
14
Approximate String Joins in a Database (Almost) for Free
351
15
Using q-grams in a DBMS for Approximate String Processing.
71
16
Proceedings of the 2000 ACM SIGMOD international conference on Management of data
34
17
Identifying Representative Trends in Massive Time Series Data Sets Using Sketches
135
18
Mining Deviants in a Time Series Database
71
19
Optimal Histograms with Quality Guarantees
255
20
Filter Trees for Managing Spatial Data over a Range of Size Granularities
30

About Nick Koudas

Nick Koudas is a scholar working on Signal Processing, Computer Networks and Communications and Artificial Intelligence, having authored 187 papers that have together received 7.8k indexed citations. Recurring topics across this work include Data Management and Algorithms (104 papers), Advanced Database Systems and Queries (82 papers) and Data Quality and Management (33 papers). The work is most often cited by research in Signal Processing (4.2k citations), Computer Networks and Communications (4.2k citations) and Artificial Intelligence (4.2k citations). Nick Koudas has collaborated with scholars based in Canada, United States and Singapore. Frequent co-authors include Divesh Srivastava, Michael Mathioudakis, Nicolas Bruno, Sudipto Guha, S. Muthukrishnan, Dimitrios Gunopulos, H. V. Jagadish, Chaitanya Mishra, Gautam Das and Luis Gravano. Their work appears in journals such as IEEE Transactions on Knowledge and Data Engineering, Computer Networks and Proceedings of the VLDB Endowment.

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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