Andrea Capotorti

501 total citations
34 papers, 295 citations indexed

About

Andrea Capotorti is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Management Science and Operations Research. According to data from OpenAlex, Andrea Capotorti has authored 34 papers receiving a total of 295 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Artificial Intelligence, 11 papers in Computational Theory and Mathematics and 7 papers in Management Science and Operations Research. Recurrent topics in Andrea Capotorti's work include Bayesian Modeling and Causal Inference (17 papers), Logic, Reasoning, and Knowledge (13 papers) and Rough Sets and Fuzzy Logic (6 papers). Andrea Capotorti is often cited by papers focused on Bayesian Modeling and Causal Inference (17 papers), Logic, Reasoning, and Knowledge (13 papers) and Rough Sets and Fuzzy Logic (6 papers). Andrea Capotorti collaborates with scholars based in Italy, Netherlands and United States. Andrea Capotorti's co-authors include Barbara Vantaggi, Marco Baioletti, Gianna Figà‐Talamanca, Giulianella Coletti, Alessandro Brozzi, Laura Galli, Andrea Formisano, Raffaella Branciari, Linda C. van der Gaag and Rossana Roila and has published in prestigious journals such as Fuzzy Sets and Systems, Food Control and Computational Statistics & Data Analysis.

In The Last Decade

Andrea Capotorti

29 papers receiving 271 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Andrea Capotorti Italy	11	171	66	64	34	32	34	295
Jim Q. Smith United Kingdom	11	122 0.7×	19 0.3×	64 1.0×	25 0.7×	12 0.4×	36	263
Inchi Hu Hong Kong	11	69 0.4×	30 0.5×	81 1.3×	15 0.4×	51 1.6×	43	390
Thomas Whalen United States	9	178 1.0×	89 1.3×	155 2.4×	8 0.2×	3 0.1×	53	297
José Villén‐Altamirano Spain	9	21 0.1×	32 0.5×	147 2.3×	11 0.3×	14 0.4×	17	283
Anureet Saxena United States	7	19 0.1×	113 1.7×	83 1.3×	11 0.3×	32 1.0×	13	256
A. A. Yushkevich United States	11	86 0.5×	49 0.7×	86 1.3×	70 2.1×	73 2.3×	22	302
Mridul Kumar Gupta India	12	80 0.5×	20 0.3×	30 0.5×	15 0.4×	33 1.0×	25	375
Pedro Miranda Spain	11	92 0.5×	85 1.3×	246 3.8×	44 1.3×	2 0.1×	35	331
Balázs Szörényi Hungary	9	148 0.9×	50 0.8×	73 1.1×	5 0.1×	4 0.1×	24	200
Isaac M. Sonin United States	8	31 0.2×	27 0.4×	114 1.8×	12 0.4×	18 0.6×	21	228

Countries citing papers authored by Andrea Capotorti

Since Specialization

Citations

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

Fields of papers citing papers by Andrea Capotorti

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Andrea Capotorti

This figure shows the co-authorship network connecting the top 25 collaborators of Andrea Capotorti. A scholar is included among the top collaborators of Andrea Capotorti 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 Andrea Capotorti. Andrea Capotorti 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

Baioletti, Marco & Andrea Capotorti. (2023). A further step for efficient corrections of inconsistent probabilistic data sets. International Journal of Approximate Reasoning. 159. 108942–108942. 1 indexed citations

Cirocchi, Roberto, Giulia Poli, Paolo Bruzzone, et al.. (2021). Analysis of the Different Lymphatic Drainage Patterns during Sentinel Lymph Node Biopsy for Skin Melanoma. Journal of Clinical Medicine. 10(23). 5544–5544. 5 indexed citations

Capotorti, Andrea & Gianna Figà‐Talamanca. (2019). SMART-or and SMART-and fuzzy average operators: A generalized proposal. Fuzzy Sets and Systems. 395. 1–20. 5 indexed citations

Gaag, Linda C. van der & Andrea Capotorti. (2018). Naive Bayesian classifiers with extreme probability features. Utrecht University Repository (Utrecht University). 72. 499–510. 3 indexed citations

Baioletti, Marco & Andrea Capotorti. (2018). A L1 based probabilistic merging algorithm and its application to statistical matching. Applied Intelligence. 49(1). 112–124. 6 indexed citations

Branciari, Raffaella, Michele Balzano, Deborah Pacetti, et al.. (2016). Dietary CLA supplementation of pigs confers higher oxidative stability to Ciauscolo and Fabriano salami produced from their meat with no negative impact on the physico‐chemical, microbiological and sensorial characteristics. European Journal of Lipid Science and Technology. 118(10). 1475–1485. 10 indexed citations

Capotorti, Andrea, Giulianella Coletti, & Barbara Vantaggi. (2014). Standard and nonstandard representability of positive uncertainty orderings. Kybernetika. 189–215. 14 indexed citations

Capotorti, Andrea, et al.. (2010). Correction of incoherent conditional probability assessments. International Journal of Approximate Reasoning. 51(6). 718–727. 16 indexed citations

Capotorti, Andrea, et al.. (2009). On the use of a new discrepancy measure to correct incoherent assessments and to aggregate conflicting opinions based on imprecise conditional probabilities. 71–78. 3 indexed citations

10.

Capotorti, Andrea, et al.. (2007). Qualitative Uncertainty Orderings Revised. Electronic Notes in Theoretical Computer Science. 169. 43–59.

11.

Capotorti, Andrea, Giulianella Coletti, & Barbara Vantaggi. (2007). Preferences Representable by a Lower Expectation: Some Characterizations. Theory and Decision. 64(2-3). 119–146. 4 indexed citations

12.

Capotorti, Andrea. (2005). Configurations of Locally Strong Coherence in the Presence of Conditional Exchangeability (the case of cardinality k <= 3).. 98–106.

13.

Baioletti, Marco, et al.. (2002). Simplification Rules for the Coherent Probability Assessment Problem. Annals of Mathematics and Artificial Intelligence. 35(1-4). 11–28. 14 indexed citations

14.

Capotorti, Andrea & Barbara Vantaggi. (2002). Locally Strong Coherence in Inference Processes. Annals of Mathematics and Artificial Intelligence. 35(1-4). 125–149. 31 indexed citations

15.

Capotorti, Andrea & Barbara Vantaggi. (2001). A simplified algorithm for inference by lower conditional probabilities.. 68–76. 1 indexed citations

16.

Capotorti, Andrea & Barbara Vantaggi. (2000). Axiomatic characterization of partial ordinal relations. International Journal of Approximate Reasoning. 24(2-3). 207–219. 3 indexed citations

17.

Capotorti, Andrea, et al.. (1999). Local coherence of conditional probability assessments: definition and application. 3 indexed citations

18.

Capotorti, Andrea, Giulianella Coletti, & Barbara Vantaggi. (1998). NON ADDITIVE ORDINAL RELATIONS REPRESENTABLE BY LOWER OR UPPER PROBABILITIES. Kybernetika. 34(1). 79–90. 8 indexed citations

19.

Baioletti, Marco & Andrea Capotorti. (1996). A Comparison Between Classical Logic and Three Valued logic for Conditional Events. 1217–1221. 4 indexed citations

20.

Capotorti, Andrea & Barbara Vantaggi. (1996). The Consistency Problem in Belief and Probability Assessments. 2. 751–762. 4 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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