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Computer Science

D-Index
39
Citations
6755
World Ranking
9733
National Ranking
285

Overview

Roberto Basili is affiliated with the University of Rome Tor Vergata in Italy. Their research primarily focuses on the field of Computer Science, with a strong emphasis on Artificial Intelligence. Additional subfields include Computer Vision and Pattern Recognition, Molecular Biology, Safety Research, and Information Systems.

The scientist's work covers several main topics, including:

  • Topic Modeling
  • Natural Language Processing Techniques
  • Multimodal Machine Learning Applications
  • Speech and Dialogue Systems
  • Sentiment Analysis and Opinion Mining
  • Hate Speech and Cyberbullying Detection
  • Text Readability and Simplification

Recent papers by Roberto Basili feature diverse applications and methodological advancements, such as:

  • Insideout project: Using big data and machine learning for prevention in psychiatry, 2021, European Psychiatry
  • Integrating Physical and Cognitive Interaction Capabilities in a Robot-Aided Rehabilitation Platform, 2023, IEEE Systems Journal
  • Adversarial training for few-shot text classification, 2021, Intelligenza Artificiale
  • AI-driven transcriptomic encoders: From explainable models to accurate, sample-independent cancer diagnostics, 2024, Expert Systems with Applications
  • U-DepPLLaMA: Universal Dependency Parsing via Auto-regressive Large Language Models, 2024, Italian Journal of Computational Linguistics

Basili collaborates frequently with other researchers, including:

  • Danilo Croce
  • Claudiu Daniel Hromei
  • Lorenzo Cristofori
  • Christian Tamantini
  • Francesco Scotto di Luzio

Much of their research has been published in venues such as the Italian Journal of Computational Linguistics, Intelligenza Artificiale, Zenodo (CERN European Organization for Nuclear Research), European Psychiatry, and IEEE Systems Journal.

Basili has also contributed to academic literature through book publications, including a work published by Springer Science+Business Media titled AIxIA 2023 - Advances in Artificial Intelligence, which appeared in 2023.

Best Publications

  • The Database of Individual Seismogenic Sources (DISS), version 3: Summarizing 20 years of research on Italy's earthquake geology

    Roberto Basili;Gianluca Valensise;Paola Vannoli;Pierfrancesco Burrato

  • Toward a ground-motion logic tree for probabilistic seismic hazard assessment in Europe

    Elise Delavaud;Fabrice Cotton;Fabrice Cotton;Sinan Akkar;Frank Scherbaum

  • Complex Linguistic Features for Text Classification: A Comprehensive Study

    Alessandro Moschitti;Roberto Basili

  • Exploiting Syntactic and Shallow Semantic Kernels for Question Answer Classification

    Alessandro Moschitti;Silvia Quarteroni;Roberto Basili;Suresh Manandhar

  • Tree kernels for semantic role labeling

    Alessandro Moschitti;Alessandro Moschitti;Alessandro Moschitti;Daniele Pighin;Daniele Pighin;Daniele Pighin;Roberto Basili;Roberto Basili;Roberto Basili

  • GAN-BERT: Generative adversarial learning for robust text classification with a bunch of labeled examples

    Danilo Croce;Giuseppe Castellucci;Roberto Basili

  • Earthquake‐generated tsunamis in the Mediterranean Sea: Scenarios of potential threats to Southern Italy

    Stefano Lorito;Mara Monica Tiberti;Roberto Basili;Alessio Piatanesi

  • Building the Italian Syntactic-Semantic Treebank

    Simonetta Montemagni;Francesco Barsotti;Marco Battista;Nicoletta Calzolari

  • The Making of the NEAM Tsunami Hazard Model 2018 (NEAMTHM18)

    Roberto Basili;Beatriz Brizuela;André Herrero;Sarfraz Iqbal

  • Structured Lexical Similarity via Convolution Kernels on Dependency Trees

    Danilo Croce;Alessandro Moschitti;Roberto Basili

  • Probabilistic tsunami hazard and Risk analysis: a review of research gaps

    Jörn Behrens;Finn Løvholt;Fatemeh Jalayer;Stefano Lorito

  • Identification of relevant terms to support the construction of domain ontologies

    Paola Velardi;Michele Missikoff;Roberto Basili

  • Probabilistic hazard for seismically induced tsunamis: accuracy and feasibility of inundation maps

    S. Lorito;J. Selva;R. Basili;F. Romano

  • A global probabilistic tsunami hazard assessment from earthquake sources

    Gareth Davies;Jonathan Griffin;Finn Lovholt;Sylfest Glimsdal

  • Quantification of source uncertainties in Seismic Probabilistic Tsunami Hazard Analysis (SPTHA)

    Jacopo Selva;Roberto Tonini;Irene Molinari;Mara Monica Tiberti

  • Classification of musical genre: a machine learning approach.

    Roberto Basili;Alfredo Serafini;Armando Stellato

  • A context-based model for Sentiment Analysis in Twitter

    Andrea Vanzo;Danilo Croce;Roberto Basili

  • KeLP at SemEval-2016 Task 3: Learning Semantic Relations between Questions and Answers

    Simone Filice;Danilo Croce;Alessandro Moschitti;Roberto Basili

  • Parsing engineering and empirical robustness

    Roberto Basili;Fabio Massimo Zanzotto

  • Probabilistic tsunami forecasting for early warning.

    J Selva;S Lorito;M Volpe;F Romano

  • Semantic Kernels for Text Classification Based on Topological Measures of Feature Similarity

    Stephan Bloehdorn;Roberto Basili;Marco Cammisa;Alessandro Moschitti

Frequent Co-Authors

Alessandro Moschitti
Alessandro Moschitti Amazon (United States)
Daniele Nardi
Daniele Nardi Sapienza University of Rome
Pierfrancesco Burrato
Pierfrancesco Burrato National Institute of Geophysics and Volcanology
Gianluca Valensise
Gianluca Valensise National Institute of Geophysics and Volcanology
Paola Velardi
Paola Velardi Sapienza University of Rome
Jacopo Selva
Jacopo Selva National Institute of Geophysics and Volcanology
Alessio Piatanesi
Alessio Piatanesi National Institute of Geophysics and Volcanology
Alberto Michelini
Alberto Michelini National Institute of Geophysics and Volcanology
Andrey Babeyko
Andrey Babeyko Helmholtz Centre Potsdam - GFZ German Research Centre for Geosciences
Miquel Canals
Miquel Canals University of Barcelona

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