Armando Segatori

565 total citations
13 papers, 410 citations indexed

About

Armando Segatori is a scholar working on Information Systems, Artificial Intelligence and Signal Processing. According to data from OpenAlex, Armando Segatori has authored 13 papers receiving a total of 410 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Information Systems, 7 papers in Artificial Intelligence and 4 papers in Signal Processing. Recurrent topics in Armando Segatori's work include Data Mining Algorithms and Applications (8 papers), Data Management and Algorithms (4 papers) and Fuzzy Logic and Control Systems (4 papers). Armando Segatori is often cited by papers focused on Data Mining Algorithms and Applications (8 papers), Data Management and Algorithms (4 papers) and Fuzzy Logic and Control Systems (4 papers). Armando Segatori collaborates with scholars based in Italy, Canada and United Kingdom. Armando Segatori's co-authors include Francesco Marcelloni, Alessio Bechini, Pietro Ducange, Witold Pedrycz, Michela Antonelli, Eleonora D’Andrea, Simone Brienza, Beatrice Lazzerini, Domenico De Guglielmo and Giuseppe Anastasi and has published in prestigious journals such as Expert Systems with Applications, Information Sciences and IEEE Transactions on Fuzzy Systems.

In The Last Decade

Armando Segatori

13 papers receiving 394 citations

Peers

Armando Segatori

CTM

CNC

MSOR

Alejandro Rosete Suárez Cuba

Francisco Herrera Triguero Spain

Yurong Cheng China

Xiaoyu Sean Lu China

Gregorio Dı́az Spain

Piotr Jędrzejowicz Poland

Heloisa A. Camargo Brazil

Marek Kisiel‐Dorohinicki Poland

N. R. Achuthan Australia

Dingyu Yang China

Alejandro Rosete Suárez Cuba

Armando Segatori

189 ×0.7

150 ×1.0

119 ×1.6

CTM

26 ×0.6

CNC

62 ×1.6

MSOR

Citations per year, relative to Armando Segatori Armando Segatori (= 1×) peers Alejandro Rosete Suárez

Countries citing papers authored by Armando Segatori

Since Specialization

Citations

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

Fields of papers citing papers by Armando Segatori

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Armando Segatori

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

All Works

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13 of 13 papers shown

Segatori, Armando, Francesco Marcelloni, & Witold Pedrycz. (2017). On Distributed Fuzzy Decision Trees for Big Data. IEEE Transactions on Fuzzy Systems. 26(1). 174–192. 102 indexed citations

Segatori, Armando, Alessio Bechini, Pietro Ducange, & Francesco Marcelloni. (2017). A Distributed Fuzzy Associative Classifier for Big Data. IEEE Transactions on Cybernetics. 48(9). 2656–2669. 35 indexed citations

Marcelloni, Francesco, et al.. (2017). A distributed approach to multi-objective evolutionary generation of fuzzy rule-based classifiers from big data. Information Sciences. 415-416. 319–340. 28 indexed citations

Bechini, Alessio, et al.. (2016). Spreading fuzzy random forests with MapReduce. CINECA IRIS Institutial research information system (University of Pisa). 33. 2641–2646. 4 indexed citations

Marcelloni, Francesco, et al.. (2016). A Multi-objective evolutionary fuzzy system for big data. CINECA IRIS Institutial research information system (University of Pisa). 25. 1562–1569. 4 indexed citations

Bechini, Alessio, Francesco Marcelloni, & Armando Segatori. (2015). A MapReduce solution for associative classification of big data. Information Sciences. 332. 33–55. 81 indexed citations

Antonelli, Michela, Pietro Ducange, Francesco Marcelloni, & Armando Segatori. (2015). On the influence of feature selection in fuzzy rule-based regression model generation. Information Sciences. 329. 649–669. 32 indexed citations

Ducange, Pietro, Francesco Marcelloni, & Armando Segatori. (2015). A MapReduce-based fuzzy associative classifier for big data. CINECA IRIS Institutial research information system (University of Pisa). 17 indexed citations

Marcelloni, Francesco, et al.. (2015). A new approach to fuzzy random forest generation. CINECA IRIS Institutial research information system (University of Pisa). 1–8. 10 indexed citations

10.

Antonelli, Michela, Pietro Ducange, Francesco Marcelloni, & Armando Segatori. (2014). A novel associative classification model based on a fuzzy frequent pattern mining algorithm. Expert Systems with Applications. 42(4). 2086–2097. 32 indexed citations

11.

Anastasi, Giuseppe, Michela Antonelli, Alessio Bechini, et al.. (2013). Urban and social sensing for sustainable mobility in smart cities. CINECA IRIS Institutial research information system (University of Pisa). 1–4. 53 indexed citations

12.

Antonelli, Michela, Pietro Ducange, Francesco Marcelloni, & Armando Segatori. (2013). Evolutionary fuzzy classifiers for imbalanced datasets: An experimental comparison. CINECA IRIS Institutial research information system (University of Pisa). 6. 13–18. 2 indexed citations

13.

Bechini, Alessio, Francesco Marcelloni, & Armando Segatori. (2013). A mobile application leveraging QR-codes to support efficient urban parking. CINECA IRIS Institutial research information system (University of Pisa). 1–3. 10 indexed citations

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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