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Computer Science

D-Index
33
Citations
12620
World Ranking
12359
National Ranking
431

Overview

Andrea Esuli is affiliated with the Institute of Information Science and Technologies in Italy and has published extensively in the field of Computer Science, with a particular focus on Artificial Intelligence. Their research spans various subfields and topics related to machine learning, information retrieval, and multimodal data analysis.

Esuli's notable research contributions include the following papers:

  • Fine-grained visual textual alignment for cross-modal retrieval using transformer encoders (2021), published in CINECA IRIS Institutial research information system (University of Pisa)
  • MARC: a robust method for multiple-aspect trajectory classification via space, time, and semantic embeddings (2020), published in International Journal of Geographical Information Systems
  • Transformer reasoning network for image-text matching and retrieval (2020), published in Zenodo (CERN European Organization for Nuclear Research)
  • Cross-Lingual Sentiment Quantification (2020), published in IEEE Intelligent Systems
  • Measuring Fairness Under Unawareness of Sensitive Attributes: A Quantification-Based Approach (2023), published in ArTS Archivio della ricerca di Trieste (University of Trieste)

Their main research topics are diverse and include:

  • Text and Document Classification Technologies
  • Topic Modeling
  • Machine Learning and Data Classification
  • Natural Language Processing Techniques
  • Multimodal Machine Learning Applications
  • Advanced Image and Video Retrieval Techniques
  • Imbalanced Data Classification Techniques

Frequent co-authors who have collaborated with Andrea Esuli include:

  • Fabrizio Sebastiani
  • Alejandro Moreo
  • Alessandro Fabris
  • Fabrizio Falchi
  • Nicola Messina

Andrea Esuli's publications are often found in prominent venues such as:

  • Zenodo (CERN European Organization for Nuclear Research)
  • arXiv (Cornell University)
  • ACM Transactions on Information Systems
  • Data Mining and Knowledge Discovery
  • CINECA IRIS Institutial research information system (University of Pisa)

In addition to numerous research papers, they have authored a book titled Learning to Quantify (2023) published in the "Information Retrieval Series."

Best Publications

  • SentiWordNet 3.0: An Enhanced Lexical Resource for Sentiment Analysis and Opinion Mining.

    Stefano Baccianella;Andrea Esuli;Fabrizio Sebastiani

  • SENTIWORDNET: A Publicly Available Lexical Resource for Opinion Mining

    Andrea Esuli;Fabrizio Sebastiani

  • Determining the semantic orientation of terms through gloss classification

    Andrea Esuli;Fabrizio Sebastiani

  • Determining Term Subjectivity and Term Orientation for Opinion Mining

    Andrea Esuli;Fabrizio Sebastiani

  • Evaluation Measures for Ordinal Regression

    Stefano Baccianella;Andrea Esuli;Fabrizio Sebastiani

  • SentiWordNet: A High-Coverage Lexical Resource for Opinion Mining

    Andrea Esuli;Fabrizio Sebastiani

  • PageRanking WordNet Synsets: An Application to Opinion Mining

    Andrea Esuli;Fabrizio Sebastiani

  • Multi-facet Rating of Product Reviews

    Stefano Baccianella;Andrea Esuli;Fabrizio Sebastiani

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

    Paolo Bolettieri;Andrea Esuli;Fabrizio Falchi;Claudio Lucchese

  • Fine-Grained Visual Textual Alignment for Cross-Modal Retrieval Using Transformer Encoders

    Nicola Messina;Giuseppe Amato;Andrea Esuli;Fabrizio Falchi

  • Determining the semantic orientation of terms through gloss analysis

    Andrea Esuli;Fabrizio Sebastiani

  • Boosting multi-label hierarchical text categorization

    Andrea Esuli;Tiziano Fagni;Fabrizio Sebastiani

  • Automatically Determining Attitude Type and Force for Sentiment Analysis

    Shlomo Argamon;Kenneth Bloom;Andrea Esuli;Fabrizio Sebastiani

  • Hierarchical Multi-label Conditional Random Fields for Aspect-Oriented Opinion Mining

    Diego Marcheggiani;Oscar Täckström;Andrea Esuli;Fabrizio Sebastiani

  • Distributional Random Oversampling for Imbalanced Text Classification

    Alejandro Moreo;Andrea Esuli;Fabrizio Sebastiani

  • Optimizing Text Quantifiers for Multivariate Loss Functions.

    Andrea Esuli;Fabrizio Sebastiani

  • Optimizing Text Quantifiers for Multivariate Loss Functions

    Andrea Esuli;Fabrizio Sebastiani

  • An NLP approach for cross-domain ambiguity detection in requirements engineering

    Alessio Ferrari;Andrea Esuli

  • Automatic Generation of Lexical Resources for Opinion Mining: Models, Algorithms and Applications

    Andrea Esuli

  • Active Learning Strategies for Multi-Label Text Classification

    Andrea Esuli;Fabrizio Sebastiani

  • Machines that learn how to code open-ended survey data

    Andrea Esuli;Fabrizio Sebastiani

  • AI and Opinion Mining, Part 2

    Andrea Esuli;Fabrizio Sebastiani;Ahmed Abasi

Frequent Co-Authors

Fabrizio Sebastiani
Fabrizio Sebastiani Institute of Information Science and Technologies
Raffaele Perego
Raffaele Perego Institute of Information Science and Technologies
Claudio Lucchese
Claudio Lucchese Ca Foscari University of Venice
Fabrizio Silvestri
Fabrizio Silvestri Sapienza University of Rome
Stefania Gnesi
Stefania Gnesi Institute of Information Science and Technologies
Dino Pedreschi
Dino Pedreschi University of Pisa
Iadh Ounis
Iadh Ounis University of Glasgow
Craig Macdonald
Craig Macdonald University of Glasgow
Erik Cambria
Erik Cambria Nanyang Technological University

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