World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
34
Citations
6212
World Ranking
12032
National Ranking
409

Overview

Paolo Cremonesi is affiliated with the Polytechnic University of Milan in Italy. Their research primarily spans multiple domains within computer science, with a strong emphasis on artificial intelligence and information systems.

The scientist has contributed notably to various subfields, including:

  • Artificial Intelligence
  • Information Systems
  • Computer Vision and Pattern Recognition
  • Management Science and Operations Research
  • Computational Theory and Mathematics

The main topics of Cremonesi's work reflect interests across several advanced technological areas:

  • Recommender Systems and Techniques
  • Quantum Computing Algorithms and Architecture
  • Advanced Bandit Algorithms Research
  • Topic Modeling
  • Quantum Information and Cryptography
  • Scientific Computing and Data Management
  • Image Retrieval and Classification Techniques

Recent publications by Paolo Cremonesi showcase a diverse set of research outputs in various prestigious venues.

  • "Recommender Systems Leveraging Multimedia Content," 2020, ACM Computing Surveys
  • "Evaluating the job shop scheduling problem on a D-wave quantum annealer," 2022, Scientific Reports
  • "CGPTuner," 2021, Proceedings of the VLDB Endowment
  • "Towards Feature Selection for Ranking and Classification Exploiting Quantum Annealers," 2022, Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval
  • "A Survey on Recent Approaches to Question Difficulty Estimation from Text," 2022, ACM Computing Surveys

Frequent co-authors who have collaborated with Cremonesi include:

  • Maurizio Ferrari Dacrema
  • Nicola Ferro
  • Fernando Benjamín Pérez Maurera
  • Gloria Turati
  • Andrea Pasin

The venues where Cremonesi most frequently publishes their work are:

  • arXiv (Cornell University)
  • ACM Computing Surveys
  • 2022 IEEE International Conference on Quantum Computing and Engineering (QCE)
  • Proceedings of the 37th ACM/SIGAPP Symposium on Applied Computing
  • User Modeling and User-Adapted Interaction

Overall, Paolo Cremonesi's research reflects significant involvement in advancing methods and systems at the intersection of artificial intelligence, recommender technologies, and quantum computing.

Best Publications

  • Performance of recommender algorithms on top-n recommendation tasks

    Paolo Cremonesi;Yehuda Koren;Roberto Turrin

  • Personalizing Session-based Recommendations with Hierarchical Recurrent Neural Networks

    Massimo Quadrana;Alexandros Karatzoglou;Balázs Hidasi;Paolo Cremonesi

  • Are we really making much progress? A worrying analysis of recent neural recommendation approaches

    Maurizio Ferrari Dacrema;Paolo Cremonesi;Dietmar Jannach

  • Sequence-Aware Recommender Systems

    Massimo Quadrana;Paolo Cremonesi;Dietmar Jannach

  • A Troubling Analysis of Reproducibility and Progress in Recommender Systems Research

    Maurizio Ferrari Dacrema;Simone Boglio;Paolo Cremonesi;Dietmar Jannach

  • Content-Based Video Recommendation System Based on Stylistic Visual Features

    Yashar Deldjoo;Mehdi Elahi;Paolo Cremonesi;Franca Garzotto

  • Recommender Systems Leveraging Multimedia Content

    Yashar Deldjoo;Markus Schedl;Paolo Cremonesi;Gabriella Pasi

  • Cross-Domain Recommender Systems.

    Iván Cantador;Ignacio Fernández-Tobías;Shlomo Berkovsky;Paolo Cremonesi

  • Cross-Domain Recommender Systems

    Paolo Cremonesi;Antonio Tripodi;Roberto Turrin

  • Investigating the Persuasion Potential of Recommender Systems from a Quality Perspective: An Empirical Study

    Paolo Cremonesi;Franca Garzotto;Roberto Turrin

  • An Evaluation Methodology for Collaborative Recommender Systems

    P. Cremonesi;R. Turrin;E. Lentini;M. Matteucci

  • An Evaluation Methodology for Collaborative Recommender Systems

    P. Cremonesi;R. Turrin;E. Lentini;M. Matteucci

  • Looking for good recommendations: a comparative evaluation of recommender systems

    Paolo Cremonesi;Franca Garzotto;Sara Negro;Alessandro Vittorio Papadopoulos

  • A Recommender System for an IPTV Service Provider: a Real Large-Scale Production Environment

    Riccardo Bambini;Paolo Cremonesi;Roberto Turrin

  • Analysis of cold-start recommendations in IPTV systems

    Paolo Cremonesi;Roberto Turrin

  • Movie genome: alleviating new item cold start in movie recommendation

    Yashar Deldjoo;Maurizio Ferrari Dacrema;Mihai Gabriel Constantin;Hamid Eghbal-zadeh

  • Comparative evaluation of recommender system quality

    Paolo Cremonesi;Franca Garzotto;Sara Negro;Alessandro Papadopoulos

  • Hybrid algorithms for recommending new items

    Paolo Cremonesi;Roberto Turrin;Fabio Airoldi

  • A QoS-based selection approach of autonomic grid services

    Jonatha Anselmi;Danilo Ardagna;Paolo Cremonesi

  • User-Centric vs. System-Centric Evaluation of Recommender Systems

    Paolo Cremonesi;Franca Garzotto;Roberto Turrin

  • Recommender systems evaluation: A 3D benchmark

    Alan Said;Domonkos Tikk;Yue Shi;Martha Larson

  • Sequence-aware Recommender Systems

    Massimo Quadrana;Paolo Cremonesi;Dietmar Jannach

  • Using visual features based on MPEG-7 and deep learning for movie recommendation

    Yashar Deldjoo;Mehdi Elahi;Massimo Quadrana;Paolo Cremonesi

  • CGPTuner: a contextual gaussian process bandit approach for the automatic tuning of IT configurations under varying workload conditions

    Stefano Cereda;Stefano Valladares;Paolo Cremonesi;Stefano Doni

  • Parallel, distributed and network-based processing

    Paolo Cremonesi

Frequent Co-Authors

Franca Garzotto
Franca Garzotto Polytechnic University of Milan
Dietmar Jannach
Dietmar Jannach University of Klagenfurt
Markus Schedl
Markus Schedl Johannes Kepler University of Linz
Martha Larson
Martha Larson Radboud University
Domonkos Tikk
Domonkos Tikk Gravity Research & Development Zrt.
Giuliano Casale
Giuliano Casale Imperial College London
Alexandros Karatzoglou
Alexandros Karatzoglou Google (United States)
Matteo Matteucci
Matteo Matteucci Polytechnic University of Milan
Gabriella Pasi
Gabriella Pasi University of Milano-Bicocca
Iván Cantador
Iván Cantador Autonomous University of Madrid

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