Sabrina Senatore

1.5k citations
92 papers · 1.1k indexed · h-index 18
Topics
Semantic Web and Ontologies (28 papers)Data Management and Algorithms (22 papers)Advanced Text Analysis Techniques (12 papers)
Partner nations
ItalyCanadaPoland

In The Last Decade

Sabrina Senatore

90 papers receiving 1.0k citations

Peers

Sabrina Senatore
Comparison fields: 5 of 106
  • Artificial Intelligence 613
  • Information Systems 334
  • Computer Vision and Pattern Recognition 197
  • Signal Processing 169
  • Computational Theory and Mathematics 168
Replace Ramasamy Uthurusamy with:
Ramasamy Uthurusamy United States
Yun Sing Koh New Zealand
Jee-Hyong Lee South Korea
Matt J. Kusner United States
Juan F. Huete Spain
Zied Elouedi Tunisia
Mohammad Karim Sohrabi Iran
Ye Chen China
Christopher J. Matheus United States
Éric Gaussier France
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Citations per field
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Citations per year

Countries citing papers authored by Sabrina Senatore

Since Specialization
Citations

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

Fields of papers citing papers by Sabrina Senatore

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sabrina Senatore

This figure shows the co-authorship network connecting the top 25 collaborators of Sabrina Senatore. A scholar is included among the top collaborators of Sabrina Senatore 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 Sabrina Senatore. Sabrina Senatore is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 1
2 8
3 5
4 4
5 18
6 1
7
Enabling a Semantic Sensor Knowledge Approach for Quality Control Support in Cleanrooms
1
8 1
9 29
10
Hand-Draw Sketching for Image Retrieval through Fuzzy Clustering Techniques.
1
11 46
12
Local Semantic Context Analysis for Automatic Ontology Matching
7
13 3
14 3
15 52
16 40
17
Proactive Utilization of Proximity-Oriented Information Inside an Agent-based Framework.
1
18 29
19 1
20 12

About Sabrina Senatore

Sabrina Senatore is a scholar working on Signal Processing, Artificial Intelligence and Information Systems, having authored 92 papers that have together received 1.1k indexed citations. Recurring topics across this work include Semantic Web and Ontologies (28 papers), Data Management and Algorithms (22 papers) and Advanced Text Analysis Techniques (12 papers). The work is most often cited by research in Artificial Intelligence (613 citations), Signal Processing (169 citations) and Information Systems (334 citations). Sabrina Senatore has collaborated with scholars based in Italy, Canada and Poland. Frequent co-authors include Vincenzo Loia, Giuseppe Fenza, Carmen De Maio, Witold Pedrycz, Ferdinando Di Martino, María I. Sessa, Ugo Erra, Mario Vento, Giuseppe Caggianese and Alessia Saggese. Their work appears in journals such as IEEE Access, Information Sciences and IEEE Transactions on Fuzzy 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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