Massimo Guarascio
Impact in
- Environmental Engineering top 10%
- Soil Geostatistics and Mapping
- Management Information Systems top 10%
- Business Process Modeling and Analysis
Papers in
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- Anomaly Detection Techniques and Applications 8
- Imbalanced Data Classification Techniques 6
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- Spam and Phishing Detection 9
- Co-authors
- Luigi Pontieri (22 shared papers)Francesco Folino (19 shared papers)Gianluigi Folino (14 shared papers)Giuseppe Manco (12 shared papers)Geoffrey S. Watson (1 shared paper)Michel David (1 shared paper)Alfredo Cuzzocrea (7 shared papers)Mara Lombardi (9 shared papers)
In The Last Decade
Massimo Guarascio
59 papers receiving 534 citations
Peers
Comparison fields: 5 of 88
- Environmental Engineering 149
- Management Information Systems 61
- Signal Processing 65
- Artificial Intelligence 192
- Computer Networks and Communications 113
Countries citing papers authored by Massimo Guarascio
This map shows the geographic impact of Massimo Guarascio'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 Massimo Guarascio with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Massimo Guarascio more than expected).
Fields of papers citing papers by Massimo Guarascio
This network shows the impact of papers produced by Massimo Guarascio. 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 Massimo Guarascio. The network helps show where Massimo Guarascio may publish in the future.
Co-authors
The 25 scholars most cited alongside Massimo Guarascio, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 70 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 1976 | 139 | |
| 2 | 1977 | 61 | |
| 3 | 2021 | 51 | |
| 4 | 2022 | 23 | |
| 5 | 2007 | 22 | |
| 6 | 2020 | 18 | |
| 7 | A Deep Learning Approach for Detecting Security Attacks on Blockchain. | 2020 | 17 |
| 8 | 2018 | 17 | |
| 9 | 2013 | 16 | |
| 10 | 2023 | 15 | |
| 11 | 2011 | 12 | |
| 12 | 2016 | 12 | |
| 13 | 2016 | 12 | |
| 14 | 2019 | 9 | |
| 15 | 2009 | 9 | |
| 16 | 2023 | 8 | |
| 17 | 2015 | 8 | |
| 18 | 2024 | 7 | |
| 19 | Linee guida per la progettazione della sicurezza nelle gallerie stradali | 2006 | 7 |
| 20 | 2017 | 7 |
About Massimo Guarascio
Massimo Guarascio is a scholar working on Artificial Intelligence, Information Systems, Computer Networks and Communications, Management Information Systems and Signal Processing, having authored 70 papers that have together received 575 indexed citations. Recurring topics across this work include Business Process Modeling and Analysis (11 papers), Network Security and Intrusion Detection (11 papers), Advanced Malware Detection Techniques (10 papers), Spam and Phishing Detection (9 papers), Anomaly Detection Techniques and Applications (8 papers), Risk and Safety Analysis (6 papers), Misinformation and Its Impacts (6 papers) and Imbalanced Data Classification Techniques (6 papers). The work is most often cited by research in Environmental Engineering (149 citations), Management Information Systems (61 citations), Signal Processing (65 citations), Artificial Intelligence (192 citations) and Computer Networks and Communications (113 citations). Massimo Guarascio has collaborated with scholars based in Italy, Brazil and India. Frequent co-authors include Luigi Pontieri, Francesco Folino, Gianluigi Folino, Giuseppe Manco, Geoffrey S. Watson, Michel David, Alfredo Cuzzocrea, Mara Lombardi, Giulio Sciarra and Francesco Chiaravalloti. Their work appears in journals such as Journal of Intelligent Information Systems, Social Network Analysis and Mining, Future Generation Computer Systems, Applied Soft Computing and WIT transactions on the built environment.
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.