Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
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).
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.
Koudas, Nick, et al.. (2013). Some Research Opportunities on Twitter Advertising.. IEEE Data(base) Engineering Bulletin. 36. 77–82.6 indexed citations
3.
Zhang, Qing, Nick Koudas, Divesh Srivastava, & Ting Yu. (2007). Aggregate Query Answering on Anonymized Tables. NCSU Libraries Repository (North Carolina State University Libraries). 116–125.225 indexed citations
4.
Bansal, Nilesh & Nick Koudas. (2007). BlogScope: a system for online analysis of high volume text streams. Very Large Data Bases. 1410–1413.55 indexed citations
5.
Vossen, Gottfried, Miltiadis D. Lytras, & Nick Koudas. (2007). Revisiting the (Machine) Semantic Web: The Missing Layers for the Human Semantic Web. Data & Knowledge Engineering. 19.2 indexed citations
6.
Bansal, Nilesh & Nick Koudas. (2007). Searching the Blogosphere..24 indexed citations
7.
Bansal, Nilesh, Fei Chiang, Nick Koudas, & Frank Wm. Tompa. (2007). Seeking stable clusters in the blogosphere. Very Large Data Bases. 806–817.44 indexed citations
8.
Koudas, Nick, Chen Li, Anthony K. H. Tung, & Rares Vernica. (2006). Relaxing join and selection queries. Very Large Data Bases. 199–210.64 indexed citations
9.
Dai, Bing Tian, Nick Koudas, Beng Chin Ooi, Divesh Srivastava, & Suresh Venkatasubramanian. (2006). Column heterogeneity as a measure of data quality. Singapore Management University Institutional Knowledge (InK) (Singapore Management University). 1–1.8 indexed citations
Cho, SungRan, Nick Koudas, & Divesh Srivastava. (2005). MIX: a meta-data indexing system for XML. Very Large Data Bases. 1326–1329.1 indexed citations
12.
Koudas, Nick & Divesh Srivastava. (2005). Approximate joins: concepts and techniques. Very Large Data Bases. 1363–1363.21 indexed citations
13.
Gunopulos, Dimitrios & Nick Koudas. (2001). DIMACS Summer School Tutorial on New Frontiers in Data Mining.. International Conference on Management of Data. 30. 94–96.1 indexed citations
14.
Gravano, Luis, Panagiotis G. Ipeirotis, H. V. Jagadish, et al.. (2001). Approximate String Joins in a Database (Almost) for Free. Very Large Data Bases. 491–500.351 indexed citations
15.
Gravano, Luis, Panagiotis G. Ipeirotis, H. V. Jagadish, et al.. (2001). Using q-grams in a DBMS for Approximate String Processing.. IEEE Data(base) Engineering Bulletin. 24. 28–34.71 indexed citations
16.
Naughton, Jeffrey F., et al.. (2000). Proceedings of the 2000 ACM SIGMOD international conference on Management of data. International Conference on Management of Data.34 indexed citations
17.
Indyk, Piotr, Nick Koudas, & S. Muthukrishnan. (2000). Identifying Representative Trends in Massive Time Series Data Sets Using Sketches. Very Large Data Bases. 363–372.135 indexed citations
18.
Jagadish, H. V., Nick Koudas, & S. Muthukrishnan. (1999). Mining Deviants in a Time Series Database. Very Large Data Bases. 102–113.71 indexed citations
19.
Jagadish, H. V., Nick Koudas, S. Muthukrishnan, et al.. (1998). Optimal Histograms with Quality Guarantees. Very Large Data Bases. 275–286.255 indexed citations
20.
Sevcik, Kenneth C. & Nick Koudas. (1996). Filter Trees for Managing Spatial Data over a Range of Size Granularities. Very Large Data Bases. 16–27.30 indexed citations
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.