Francesca Bugiotti

753 citations
20 papers · 248 · h-index 8

Impact in

Papers in

Francesca Bugiotti

18 papers receiving 231 citations

Peers

Francesca Bugiotti
Comparison fields: 5 of 55
  • Computer Networks and Communications 145
  • Information Systems 104
  • Signal Processing 47
  • Management Science and Operations Research 45
  • Information Systems and Management 21
Replace Xiaomeng Yi with:
Xiaomeng Yi China
D. S. Lavrova Russia
Agnese Pinto Italy
Myriam Leggieri Germany
Md Zakirul Alam Bhuiyan United States
Elham Azhir Iran
Karamjit Kaur India
Filippo Tangorra Italy
Rohitash Kumar Banyal India
Francesca Bugiotti relative to Xiaomeng Yi China Xiaomeng Yi's profile →
Citations per field
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Citations per year

Countries citing papers authored by Francesca Bugiotti

Since Specialization
Citations

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

Fields of papers citing papers by Francesca Bugiotti

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 23 scholars most cited alongside Francesca Bugiotti, 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 Francesca Bugiotti Line = papers co-authored together Francesca Bugiotti links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 201665
2 201364
3
Invisible Glue: Scalable Self-Tunning Multi-Stores.
201521
4 202317
5 202314
6 202412
7 202211
8 202410
9 20187
10 20117
11
A Comparison of Data Models and APIs of NoSQL Datastores
20135
12 20124
13 20213
14 20133
15 20231
16 20221
17 20221
18 20171
19 20231
20
A platform for model-independent solutions to model management problems.
20080

About Francesca Bugiotti

Francesca Bugiotti is a scholar working on Computer Networks and Communications, Information Systems, Artificial Intelligence, Management Information Systems and Information Systems and Management, having authored 20 papers that have together received 248 indexed citations. Recurring topics across this work include Advanced Database Systems and Queries (9 papers), Semantic Web and Ontologies (5 papers), Cloud Computing and Resource Management (4 papers), Distributed systems and fault tolerance (3 papers), Data Mining Algorithms and Applications (2 papers), Big Data and Business Intelligence (2 papers), Advanced Data Storage Technologies (2 papers) and Graph Theory and Algorithms (2 papers). The work is most often cited by research in Computer Networks and Communications (145 citations), Information Systems (104 citations), Signal Processing (47 citations), Management Science and Operations Research (45 citations) and Information Systems and Management (21 citations). Francesca Bugiotti has collaborated with scholars based in France, Italy and Spain. Frequent co-authors include Paolo Atzeni, Luca Rossi, Luca Cabibbo, Riccardo Torlone, Tatiana Morosuk, Antoine Harfouche, Alin Deutsch, Ioana Manolescu, Frédéric Magoulès and Luigi Bellomarini. Their work appears in journals such as Information Systems, Computer Standards & Interfaces, Data Science and Engineering, Journal of Global Information Management and Data & Knowledge Engineering.

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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