World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
31
Citations
4092
World Ranking
13671
National Ranking
495

Overview

Claudio Lucchese is affiliated with Ca Foscari University of Venice in Italy. Their research predominantly lies within the field of Computer Science, with a focus on several subfields including Artificial Intelligence, Signal Processing, Safety Research, Management Science and Operations Research, and Information Systems.

The scientist's work spans multiple topics, notably Adversarial Robustness in Machine Learning, Explainable Artificial Intelligence (XAI), Advanced Malware Detection Techniques, Machine Learning and Data Classification, Ethics and Social Impacts of AI, Anomaly Detection Techniques and Applications, and Security and Verification in Computing.

Claudio Lucchese has contributed to numerous publications across various venues. Some of the frequent publication outlets include:

  • arXiv (Cornell University)
  • Proceedings of the 37th ACM/SIGAPP Symposium on Applied Computing
  • Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval
  • ACM Transactions on Information Systems
  • IRIS Research product catalog (Sapienza University of Rome)

Recent papers authored or co-authored by Claudio Lucchese are:

  • "Treant: training evasion-aware decision trees", 2020, Data Mining and Knowledge Discovery
  • "Treant: training evasion-aware decision trees", 2020, IRIS Research product catalog (Sapienza University of Rome)
  • "Efficient and Effective Tree-based and Neural Learning to Rank", 2023, Foundations and Trends® in Information Retrieval
  • "ReNeuIR: Reaching Efficiency in Neural Information Retrieval", 2022, Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval
  • "Beyond robustness: Resilience verification of tree-based classifiers", 2022, Computers & Security

Collaboration appears to be an important aspect of Lucchese's research activities, with frequent co-authors including Salvatore Orlando, Franco Maria Nardini, Stefano Calzavara, Federico Marcuzzi, and Raffaele Perego.

Best Publications

  • Fast and memory efficient mining of frequent closed itemsets

    C. Lucchese;S. Orlando;R. Perego

  • CoPhIR: a Test Collection for Content-Based Image Retrieval

    Paolo Bolettieri;Andrea Esuli;Fabrizio Falchi;Claudio Lucchese

  • From chatter to headlines: harnessing the real-time web for personalized news recommendation

    Gianmarco De Francisci Morales;Aristides Gionis;Claudio Lucchese

  • Identifying task-based sessions in search engine query logs

    Claudio Lucchese;Salvatore Orlando;Raffaele Perego;Fabrizio Silvestri

  • Building a web-scale image similarity search system

    Michal Batko;Fabrizio Falchi;Claudio Lucchese;David Novak

  • Document Similarity Self-Join with MapReduce

    Ranieri Baraglia;Gianmarco De Francisci Morales;Claudio Lucchese

  • On closed constrained frequent pattern mining

    F. Bonchi;C. Lucchese

  • Learning relatedness measures for entity linking

    Diego Ceccarelli;Claudio Lucchese;Salvatore Orlando;Raffaele Perego

  • Direct local pattern sampling by efficient two-step random procedures

    Mario Boley;Claudio Lucchese;Daniel Paurat;Thomas Gärtner

  • Pushing tougher constraints in frequent pattern mining

    Francesco Bonchi;Claudio Lucchese

  • Extending the state-of-the-art of constraint-based pattern discovery

    Francesco Bonchi;Claudio Lucchese

  • kDCI: a Multi-Strategy Algorithm for Mining Frequent Sets.

    Salvatore Orlando;Claudio Lucchese;Paolo Palmerini;Raffaele Perego

  • Fast Ranking with Additive Ensembles of Oblivious and Non-Oblivious Regression Trees

    Domenico Dato;Claudio Lucchese;Franco Maria Nardini;Salvatore Orlando

  • Dexter: an open source framework for entity linking

    Diego Ceccarelli;Claudio Lucchese;Salvatore Orlando;Raffaele Perego

  • QuickScorer: A Fast Algorithm to Rank Documents with Additive Ensembles of Regression Trees

    Claudio Lucchese;Franco Maria Nardini;Salvatore Orlando;Raffaele Perego

  • Discovering tasks from search engine query logs

    Claudio Lucchese;Salvatore Orlando;Raffaele Perego;Fabrizio Silvestri

  • DCI_Closed: A Fast and Memory Efficient Algorithm to Mine Frequent Closed Itemsets

    Claudio Lucchese;Salvatore Orlando;R. Perego

  • Quality versus efficiency in document scoring with learning-to-rank models

    Gabriele Capannini;Claudio Lucchese;Franco Maria Nardini;Salvatore Orlando

  • Mining Top-K Patterns from Binary Datasets in presence of Noise

    Claudio Lucchese;Salvatore Orlando;Raffaele Perego

  • A Unifying Framework for Mining Approximate Top-k Binary Patterns

    Claudio Lucchese;Salvatore Orlando;Raffaele Perego

  • DCI Closed: A Fast and Memory Efficient Algorithm to Mine Frequent Closed Itemsets.

    Claudio Lucchese;Salvatore Orlando;Raffaele Perego

Frequent Co-Authors

Raffaele Perego
Raffaele Perego Institute of Information Science and Technologies
Salvatore Orlando
Salvatore Orlando Ca Foscari University of Venice
Fabrizio Silvestri
Fabrizio Silvestri Sapienza University of Rome
Francesco Bonchi
Francesco Bonchi Institute for Scientific Interchange
Michail Vlachos
Michail Vlachos University of Lausanne
Fosca Giannotti
Fosca Giannotti Scuola Normale Superiore di Pisa
Andrea Esuli
Andrea Esuli Institute of Information Science and Technologies
Philip S. Yu
Philip S. Yu University of Illinois at Chicago
Aristides Gionis
Aristides Gionis Royal Institute of Technology
Domenico Talia
Domenico Talia University of Calabria

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