Paula Severi

408 citations
23 papers · 141 · h-index 7

Impact in

Papers in

Paula Severi

20 papers receiving 107 citations

Peers

Paula Severi
Comparison fields: 5 of 28
  • Computational Theory and Mathematics 85
  • Artificial Intelligence 121
  • Software 8
  • Computer Networks and Communications 28
  • Theoretical Computer Science 1
Replace Aurélien Lemay with:
Aurélien Lemay France
Luca Roversi Italy
Claudio Sacerdoti Coen Italy
Sophie Tison France
Viorica Sofronie-Stokkermans Germany
Margherita Napoli Italy
Dominique Méry France
Luís Pinto Portugal
Rajeev Goré Australia
Peter Baumgartner Germany
Paula Severi relative to Aurélien Lemay France Aurélien Lemay's profile →
Citations per field
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Aurélien Lemay · 1×
Citations per year

Countries citing papers authored by Paula Severi

Since Specialization
Citations

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

Fields of papers citing papers by Paula Severi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 15 scholars most cited alongside Paula Severi, 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 Paula Severi Line = papers co-authored together Paula Severi links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 23 papers — load more, or switch the sort, to bring in the rest.

#Work
1 199636
2 199923
3
On normalisation
199512
4 201311
5 20197
6 19986
7 20036
8 20116
9 20126
10 20155
11 20114
12
Guiding Reification in OWL through Aggregation
20103
13 20153
14 20123
15 20003
16 20172
17
Complexity of the description logic ALCM
20161
18 20151
19 20191
20 20011

About Paula Severi

Paula Severi is a scholar working on Artificial Intelligence, Computational Theory and Mathematics, Computer Networks and Communications, Information Systems and Geometry and Topology, having authored 23 papers that have together received 141 indexed citations. Recurring topics across this work include Logic, programming, and type systems (16 papers), Logic, Reasoning, and Knowledge (10 papers), Formal Methods in Verification (8 papers), Semantic Web and Ontologies (7 papers), Advanced Database Systems and Queries (6 papers), Advanced Algebra and Logic (4 papers), Service-Oriented Architecture and Web Services (4 papers) and Computability, Logic, AI Algorithms (3 papers). The work is most often cited by research in Computational Theory and Mathematics (85 citations), Artificial Intelligence (121 citations), Software (8 citations), Computer Networks and Communications (28 citations) and Theoretical Computer Science (1 citation). Paula Severi has collaborated with scholars based in United Kingdom, Uruguay and Italy. Frequent co-authors include Femke van Raamsdonk, Mariangiola Dezani-Ciancaglini, Morten Heine Sørensen, Hongwei Xi, José Luiz Fiadeiro, Regina Motz, David Ekserdjian, Alexander Kurz, Emilio Tuosto and Luca Padovani. Their work appears in journals such as Journal of Web Semantics, Logical Methods in Computer Science, Information and Computation, ACM SIGPLAN Notices and Theoretical Computer Science.

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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