A. Segev

1.0k citations
29 papers · 535 · h-index 12

Impact in

Papers in

    • Advanced Database Systems and Queries 18
    • Advanced Data Storage Technologies 6
    • Distributed systems and fault tolerance 6
    • Constraint Satisfaction and Optimization 4
    • Distributed and Parallel Computing Systems 2
    • Data Management and Algorithms 13

A. Segev

24 papers receiving 470 citations

Peers

A. Segev
Comparison fields: 5 of 50
  • Signal Processing 291
  • Computer Networks and Communications 393
  • Artificial Intelligence 173
  • Information Systems 111
  • Information Systems and Management 31
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Citations per field
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Citations per year

Countries citing papers authored by A. Segev

Since Specialization
Citations

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

Fields of papers citing papers by A. Segev

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside A. Segev, 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 A. Segev Line = papers co-authored together A. Segev links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 29 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1992107
2 198963
3
Event-join optimization in temporal relational databases
198950
4 200247
5 199343
6 200335
7 200232
8 200230
9 200329
10
Leveraging Electronic Commerce for Competitive Advantage: A Business Value Framework
199626
11 199316
12 200216
13 20026
14 19886
15 20026
16
Selectivity estimation in temporal databases
19903
17 20013
18 20023
19
The TSQL2 Language Specification
19943
20 20023

About A. Segev

A. Segev is a scholar working on Computer Networks and Communications, Signal Processing, Artificial Intelligence, Information Systems and Strategy and Management, having authored 29 papers that have together received 535 indexed citations. Recurring topics across this work include Advanced Database Systems and Queries (18 papers), Data Management and Algorithms (13 papers), Advanced Data Storage Technologies (6 papers), Distributed systems and fault tolerance (6 papers), Semantic Web and Ontologies (5 papers), Constraint Satisfaction and Optimization (4 papers), Data Mining Algorithms and Applications (3 papers) and Distributed and Parallel Computing Systems (2 papers). The work is most often cited by research in Signal Processing (291 citations), Computer Networks and Communications (393 citations), Artificial Intelligence (173 citations), Information Systems (111 citations) and Information Systems and Management (31 citations). A. Segev has collaborated with scholars based in United States, France and Canada. Frequent co-authors include Andrew J. Park, Christian S. Jensen, Richard T. Snodgrass, Shashi K. Gadia, Jin Baek Kim, Michael Stonebraker, Doron Rotem, Yves Pigneur, Abhirup Chatterjee and Jun Zhao. Their work appears in journals such as IEEE Transactions on Knowledge and Data Engineering, IEEE Transactions on Software Engineering, ACM SIGMOD Record, Journal of Organizational Computing and Electronic Commerce and Zenodo (CERN European Organization for Nuclear Research).

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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