Claudio Lucchese

3.3k total citations
122 papers, 1.8k citations indexed

About

Claudio Lucchese is a scholar working on Artificial Intelligence, Information Systems and Signal Processing. According to data from OpenAlex, Claudio Lucchese has authored 122 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 70 papers in Artificial Intelligence, 59 papers in Information Systems and 27 papers in Signal Processing. Recurrent topics in Claudio Lucchese's work include Data Mining Algorithms and Applications (26 papers), Topic Modeling (22 papers) and Data Management and Algorithms (22 papers). Claudio Lucchese is often cited by papers focused on Data Mining Algorithms and Applications (26 papers), Topic Modeling (22 papers) and Data Management and Algorithms (22 papers). Claudio Lucchese collaborates with scholars based in Italy, United States and Spain. Claudio Lucchese's co-authors include Raffaele Perego, Salvatore Orlando, Franco Maria Nardini, Fabrizio Silvestri, Francesco Bonchi, Gianmarco De Francisci Morales, Aristides Gionis, Gabriele Tolomei, Nicola Tonellotto and Diego Ceccarelli and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Access and IEEE Transactions on Knowledge and Data Engineering.

In The Last Decade

Claudio Lucchese

114 papers receiving 1.7k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Claudio Lucchese Italy 24 984 978 381 377 355 122 1.8k
Giovanni Romano Italy 19 1.1k 1.1× 1.2k 1.2× 521 1.4× 563 1.5× 391 1.1× 39 2.1k
Claudio Carpineto Italy 19 1.1k 1.1× 1.3k 1.3× 537 1.4× 565 1.5× 402 1.1× 43 2.1k
Nívio Ziviani Brazil 24 1.1k 1.1× 1.1k 1.1× 338 0.9× 163 0.4× 262 0.7× 115 2.0k
Edleno Silva de Moura Brazil 23 987 1.0× 1.0k 1.0× 337 0.9× 103 0.3× 275 0.8× 98 1.8k
Justin Zhan United States 19 794 0.8× 1.0k 1.1× 260 0.7× 311 0.8× 150 0.4× 73 1.6k
Salvatore Orlando Italy 26 1.1k 1.1× 945 1.0× 554 1.5× 382 1.0× 267 0.8× 151 2.1k
Atish Das Sarma United States 21 381 0.4× 621 0.6× 260 0.7× 262 0.7× 243 0.7× 43 1.4k
C. R. Ramakrishnan United States 22 548 0.6× 1.1k 1.1× 348 0.9× 227 0.6× 92 0.3× 86 1.7k
Omid Madani United States 16 633 0.6× 960 1.0× 200 0.5× 126 0.3× 260 0.7× 43 1.5k
Luca Becchetti Italy 18 597 0.6× 525 0.5× 157 0.4× 121 0.3× 165 0.5× 60 1.5k

Countries citing papers authored by Claudio Lucchese

Since Specialization
Citations

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

Fields of papers citing papers by Claudio Lucchese

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Claudio Lucchese

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

All Works

20 of 20 papers shown
1.
Lucchese, Claudio, et al.. (2025). Efficient Re-ranking with Cross-encoders via Early Exit. ISTI Open Portal. 2534–2544.
2.
Rizzo, Matteo, Matteo Marcuzzo, Alessandro Zangari, et al.. (2025). Machine learning models explanations as interpretations of evidence: a theoretical framework of explainability and its implications on high-stakes biomedical decision-making. BMC Medical Research Methodology. 25(S1). 282–282.
3.
Bruch, Sebastian, Claudio Lucchese, Maria Maistro, & Franco Maria Nardini. (2024). Special Section on Efficiency in Neural Information Retrieval. ACM Transactions on Information Systems. 42(5). 1–4.
4.
Lucchese, Claudio, et al.. (2024). A Learning-to-Rank Formulation of Clustering-Based Approximate Nearest Neighbor Search. arXiv (Cornell University). 2261–2265. 1 indexed citations
5.
Lucchese, Claudio, et al.. (2023). Early Exit Strategies for Learning-to-Rank Cascades. IEEE Access. 11. 126691–126704. 2 indexed citations
6.
Lucchese, Claudio, et al.. (2023). Can Embeddings Analysis Explain Large Language Model Ranking?. ARCA (Università Ca' Foscari Venezia). 4150–4154. 3 indexed citations
7.
Lucchese, Claudio, et al.. (2020). Query-level Early Exit for Additive Learning-to-Rank Ensembles. ISTI Open Portal. 3 indexed citations
8.
Calzavara, Stefano, et al.. (2020). Treant: training evasion-aware decision trees. IRIS Research product catalog (Sapienza University of Rome). 22 indexed citations
9.
Lucchese, Claudio, Franco Maria Nardini, Salvatore Orlando, et al.. (2018). Parallel Traversal of Large Ensembles of Decision Trees. IEEE Transactions on Parallel and Distributed Systems. 30(9). 2075–2089. 16 indexed citations
10.
Lucchese, Claudio, Franco Maria Nardini, Salvatore Orlando, et al.. (2018). Parallel Traversal of Large Ensembles of Decision Trees. Zenodo (CERN European Organization for Nuclear Research). 2 indexed citations
11.
Lucchese, Claudio, et al.. (2017). The Impact of Negative Samples on Learning to Rank.. ARCA (Università Ca' Foscari Venezia). 3 indexed citations
12.
Coletto, Mauro, Andrea Esuli, Claudio Lucchese, et al.. (2017). Perception of social phenomena through the multidimensional analysis of online social networks. ISTI Open Portal. 1. 14–32. 17 indexed citations
13.
Coletto, Mauro, Andrea Esuli, Claudio Lucchese, et al.. (2016). Sentiment-enhanced multidimensional analysis of online social networks: perception of the mediterranean refugees crisis. arXiv (Cornell University). 1270–1277. 10 indexed citations
14.
Lucchese, Claudio, et al.. (2015). QuickRank: a C++ Suite of Learning to Rank Algorithms. ARCA (Università Ca' Foscari Venezia). 1404. 8 indexed citations
15.
Cambazoğlu, B. Barla & Claudio Lucchese. (2011). Proceedings of the 9th workshop on Large-scale and distributed informational retrieval. 2 indexed citations
16.
Lucchese, Claudio, et al.. (2010). Scaling out All Pairs Similarity Search with MapReduce. International ACM SIGIR Conference on Research and Development in Information Retrieval. 630. 25–30. 10 indexed citations
17.
Bolettieri, Paolo, Fabrizio Falchi, Claudio Lucchese, et al.. (2009). Searching 100M Images by Content Similarity.. 88–99. 2 indexed citations
18.
Vlachos, Michail, Claudio Lucchese, Deepak Rajan, & Philip S. Yu. (2008). Ownership protection of shape datasets with geodesic distance preservation. ISTI Open Portal. 276–286. 3 indexed citations
19.
Batko, Michal, Fabrizio Falchi, Claudio Lucchese, et al.. (2008). Crawling, Indexing, and Similarity Searching Images on the Web. SEBD. 382–389. 2 indexed citations
20.
Lucchese, Claudio, Francesco Bonchi, Fosca Giannotti, et al.. (2006). On Interactive Pattern Mining from Relational Databases.. SEBD. 329–338. 1 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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