Antonio Irpino

793 total citations
22 papers, 329 citations indexed

About

Antonio Irpino is a scholar working on Artificial Intelligence, Signal Processing and Computational Theory and Mathematics. According to data from OpenAlex, Antonio Irpino has authored 22 papers receiving a total of 329 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Artificial Intelligence, 5 papers in Signal Processing and 4 papers in Computational Theory and Mathematics. Recurrent topics in Antonio Irpino's work include Neural Networks and Applications (8 papers), Advanced Clustering Algorithms Research (6 papers) and Data Management and Algorithms (4 papers). Antonio Irpino is often cited by papers focused on Neural Networks and Applications (8 papers), Advanced Clustering Algorithms Research (6 papers) and Data Management and Algorithms (4 papers). Antonio Irpino collaborates with scholars based in Italy, Brazil and Lithuania. Antonio Irpino's co-authors include Rosanna Verde, Francisco de A.T. de Carvalho, Annalisa Capuano, Barbara Rinaldi, Mario Rosario Guarracino, Francesco Rossi, Amelia Filippelli, Nicola Vanacore, Antonio Clavenna and Liberata Sportiello and has published in prestigious journals such as Expert Systems with Applications, Information Sciences and IEEE Transactions on Cybernetics.

In The Last Decade

Antonio Irpino

22 papers receiving 321 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Antonio Irpino Italy	11	148	48	47	45	41	22	329
Hideto Yokoi Japan	10	123 0.8×	18 0.4×	13 0.3×	65 1.4×	49 1.2×	44	343
Lars Asker Sweden	12	395 2.7×	13 0.3×	17 0.4×	54 1.2×	38 0.9×	35	547
Isak Karlsson Sweden	9	159 1.1×	11 0.2×	48 1.0×	134 3.0×	15 0.4×	17	271
Qing-Bin Gao China	15	77 0.5×	23 0.5×	3 0.1×	34 0.8×	82 2.0×	26	585
Shahram Ebadollahi United States	17	463 3.1×	18 0.4×	45 1.0×	88 2.0×	9 0.2×	44	810
André S. Fialho Portugal	10	220 1.5×	33 0.7×	37 0.8×	45 1.0×	7 0.2×	20	425
Federico Cismondi United States	9	203 1.4×	33 0.7×	32 0.7×	41 0.9×	7 0.2×	16	386
Arjen Hommersom Netherlands	12	199 1.3×	9 0.2×	31 0.7×	40 0.9×	32 0.8×	49	424
R. Marı́n Spain	15	327 2.2×	10 0.2×	30 0.6×	153 3.4×	58 1.4×	63	620

Countries citing papers authored by Antonio Irpino

Since Specialization

Citations

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

Fields of papers citing papers by Antonio Irpino

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Antonio Irpino

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

All Works

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20 of 20 papers shown

Falco, A. de & Antonio Irpino. (2024). A new approach for measuring and analysing residential segregation. Quality & Quantity. 58(5). 4569–4602. 2 indexed citations

Irpino, Antonio, et al.. (2023). Distribution free prediction for geographically weighted functional regression models. Spatial Statistics. 57. 100765–100765. 3 indexed citations

Carvalho, Francisco de A.T. de, et al.. (2022). Batch Self-Organizing Maps for Distributional Data with an Automatic Weighting of Variables and Components. Journal of Classification. 39(2). 343–375. 5 indexed citations

Carvalho, Francisco de A.T. de, et al.. (2020). Co-clustering algorithms for distributional data with automated variable weighting. Information Sciences. 549. 87–115. 7 indexed citations

Irpino, Antonio, et al.. (2019). Spatial prediction and spatial dependence monitoring on georeferenced data streams. Statistical Methods & Applications. 29(1). 101–128. 1 indexed citations

Carvalho, Francisco de A.T. de, Antonio Irpino, & Rosanna Verde. (2015). Fuzzy clustering of distribution-valued data using an adaptive L ₂ Wasserstein distance. 1–8. 3 indexed citations

Irpino, Antonio & Rosanna Verde. (2015). Linear regression for numeric symbolic variables: a least squares approach based on Wasserstein Distance. Advances in Data Analysis and Classification. 9(1). 81–106. 13 indexed citations

Verde, Rosanna, et al.. (2015). Dimension Reduction Techniques for Distributional Symbolic Data. IEEE Transactions on Cybernetics. 46(2). 344–355. 13 indexed citations

Irpino, Antonio & Rosanna Verde. (2014). Basic statistics for distributional symbolic variables: a new metric-based approach. Advances in Data Analysis and Classification. 9(2). 143–175. 28 indexed citations

10.

Irpino, Antonio, Rosanna Verde, & Francisco de A.T. de Carvalho. (2013). Dynamic clustering of histogram data based on adaptive squared Wasserstein distances. Expert Systems with Applications. 41(7). 3351–3366. 35 indexed citations

11.

Rafaniello, Concetta, Flavia Lombardo, Carmen Ferrajolo, et al.. (2013). Predictors of mortality in atypical antipsychotic-treated community-dwelling elderly patients with behavioural and psychological symptoms of dementia: a prospective population-based cohort study from Italy. European Journal of Clinical Pharmacology. 70(2). 187–195. 15 indexed citations

12.

Guarracino, Mario Rosario, et al.. (2013). Fuzzy regularized generalized eigenvalue classifier with a novel membership function. Information Sciences. 245. 53–62. 4 indexed citations

13.

Guarracino, Mario Rosario, et al.. (2012). Supervised classification of distributed data streams for smart grids. Energy Systems. 3(1). 95–108. 6 indexed citations

14.

Clavenna, Antonio, Maurizio Bonati, Paolo Siani, et al.. (2012). Active surveillance of adverse drug reactions in children in five Italian paediatric wards. Open Journal of Pediatrics. 2(2). 111–117. 10 indexed citations

15.

Guarracino, Mario Rosario, Antonio Irpino, & Rosanna Verde. (2010). Multiclass Generalized Eigenvalue Proximal Support Vector Machines. 2. 25–32. 10 indexed citations

16.

Capuano, Annalisa, et al.. (2009). Regional surveillance of emergency-department visits for outpatient adverse drug events. European Journal of Clinical Pharmacology. 65(7). 721–728. 46 indexed citations

17.

Verde, Rosanna & Antonio Irpino. (2009). NEW STATISTICS FOR NEW DATA: A PROPOSAL FORCOMPARING MULTIVALUED NUMERICAL DATA. 21(2). 185–206. 1 indexed citations

18.

Irpino, Antonio, et al.. (2007). Optimal histogram representation of large data sets: Fisher vs piecewise linear approximations. 1. 99–110. 18 indexed citations

19.

Irpino, Antonio, et al.. (2006). Clustering reduced interval data using Hausdorff distance. Computational Statistics. 21(2). 271–288. 6 indexed citations

20.

Irpino, Antonio. (2005). “Spaghetti” PCA analysis: An extension of principal components analysis to time dependent interval data. Pattern Recognition Letters. 27(5). 504–513. 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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