Leo Mark

1.2k citations
61 papers · 853 · h-index 13

Impact in

Papers in

Leo Mark

60 papers receiving 762 citations

Peers

Leo Mark
Comparison fields: 5 of 72
  • Signal Processing 394
  • Computer Networks and Communications 620
  • Artificial Intelligence 456
  • Information Systems 227
  • Information Systems and Management 57
Replace Dina Bitton with:
Dina Bitton United States
James P. Fry United States
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Upen S. Chakravarthy United States
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Citations per field
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Citations per year

Countries citing papers authored by Leo Mark

Since Specialization
Citations

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

Fields of papers citing papers by Leo Mark

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 61 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1990328
2 199164
3 200031
4 200230
5 200825
6 200225
7
Integration of Data, Schema and Meta-Schema in the Context of Self-Documenting Data Models.
198320
8 201120
9 199518
10 199516
11 199316
12 199416
13 199216
14 198512
15
A framework for vacuuming temporal databases
199012
16
What is the binary relationship approach
198311
17 198911
18 199511
19
Using caching, cache indexing and differential techniques to efficiently support transaction time
199010
20
Integrated semantics for information and communication systems
199710

About Leo Mark

Leo Mark is a scholar working on Computer Networks and Communications, Artificial Intelligence, Signal Processing, Information Systems and Information Systems and Management, having authored 61 papers that have together received 853 indexed citations. Recurring topics across this work include Advanced Database Systems and Queries (28 papers), Data Management and Algorithms (19 papers), Semantic Web and Ontologies (13 papers), Service-Oriented Architecture and Web Services (10 papers), Distributed systems and fault tolerance (9 papers), Scientific Computing and Data Management (6 papers), Business Process Modeling and Analysis (5 papers) and Anomaly Detection Techniques and Applications (5 papers). The work is most often cited by research in Signal Processing (394 citations), Computer Networks and Communications (620 citations), Artificial Intelligence (456 citations), Information Systems (227 citations) and Information Systems and Management (57 citations). Leo Mark has collaborated with scholars based in United States, Denmark and Spain. Frequent co-authors include Nick Roussopoulos, Witold Litwin, Christian S. Jensen, N. Roussopoulos, Edward Omiecinski, G. Harhalakis, Shamkant B. Navathe, Spencer Rugaber, Robert Meersman and Pedro R. Muro‐Medrano. Their work appears in journals such as IEEE Transactions on Knowledge and Data Engineering, Information Systems, Data & Knowledge Engineering, Software Practice and Experience and ACM Transactions on Database Systems.

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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