David Menestrina

1.3k citations
11 papers · 767 · h-index 9

Impact in

Papers in

David Menestrina

10 papers receiving 696 citations

Peers

David Menestrina
Comparison fields: 5 of 40
  • Management Science and Operations Research 538
  • Information Systems 389
  • Computer Networks and Communications 323
  • Artificial Intelligence 411
  • Signal Processing 116
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Kris Ganjam United States
Ekaterini Ioannou Germany
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Héléna Galhardas Portugal
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Citations per field
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Citations per year

Countries citing papers authored by David Menestrina

Since Specialization
Citations

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

Fields of papers citing papers by David Menestrina

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 17 scholars most cited alongside David Menestrina, 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 David Menestrina Line = papers co-authored together David Menestrina links everyone, so they are left out of the graph.

All Works

11 of 11 papers shown
#Work
1 2008266
2 2013157
3 2009152
4 201263
5 201045
6 200726
7
Generic Entity Resolution with Data Confidences
200523
8
Generic Entity Resolution in the SERF Project
200620
9
P-Swoosh: Parallel Algorithm for Generic Entity Resolution
200612
10
Evaluating Entity Resolution Results (Extended version)
20093
11
Bufoosh: Buffering Algorithms for Generic Entity Resolution
20060

About David Menestrina

David Menestrina is a scholar working on Management Science and Operations Research, Information Systems, Computer Networks and Communications, Artificial Intelligence and Signal Processing, having authored 11 papers that have together received 767 indexed citations. Recurring topics across this work include Data Quality and Management (10 papers), Advanced Database Systems and Queries (5 papers), Privacy-Preserving Technologies in Data (4 papers), Web Data Mining and Analysis (3 papers), Cloud Computing and Resource Management (2 papers), Data Management and Algorithms (2 papers), Data Mining Algorithms and Applications (2 papers) and Dental Radiography and Imaging (1 paper). The work is most often cited by research in Management Science and Operations Research (538 citations), Information Systems (389 citations), Computer Networks and Communications (323 citations), Artificial Intelligence (411 citations) and Signal Processing (116 citations). David Menestrina has collaborated with scholars based in United States and Greece. Frequent co-authors include Héctor García-Molina, Steven Euijong Whang, Omar Benjelloun, Jennifer Widom, Qi Su, Georgia Koutrika, Martin Theobald, Foto Afrati, Anish Das Sarma and Aditya Parameswaran. Their work appears in journals such as Proceedings of the VLDB Endowment, The VLDB Journal, DSpace - NTUA (National Technical University of Athens) 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.

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