Andrea Esuli is a tenured Senior Researcher at the Italian National Council of Research. His research interests include learning to quantify, deep learning for text analysis, cross-modal classification, technology-assisted review, and representation learning.Alessandro Fabris is a PhD student at the University of Padova. His research interests include learning to quantify, and the fairness and bias of retrieval and classification systems.Alejandro Moreo is a tenured Researcher at the Italian National Council of Research. His research interests include learning to quantify, deep learning for text analysis, cross-lingual text classification, authorship analysis, and representation learning.Fabrizio Sebastiani is a tenured Director of Research at the Italian National Council of Research. His research interests include learning to quantify, cross-lingual text classification, technology-assisted review, authorship analysis, and representation learning.

• - 1. The Case for Quantification. - 2. Applications of Quantification. - 3. Evaluation of Quantification Algorithms. - 4. Methods for Learning to Quantify. - 5. Advanced Topics. - 6. The Quantification Landscape. - 7. The Road Ahead.

Andrea Esuli is a tenured Senior Researcher at the Italian National Council of Research. His research interests include learning to quantify, deep learning for text analysis, cross-modal classification, technology-assisted review, and representation learning.Alessandro Fabris is a PhD student at the University of Padova. His research interests include learning to quantify, and the fairness and bias of retrieval and classification systems.Alejandro Moreo is a tenured Researcher at the Italian National Council of Research. His research interests include learning to quantify, deep learning for text analysis, cross-lingual text classification, authorship analysis, and representation learning.Fabrizio Sebastiani is a tenured Director of Research at the Italian National Council of Research. His research interests include learning to quantify, cross-lingual text classification, technology-assisted review, authorship analysis, and representation learning.

• - 1. The Case for Quantification. - 2. Applications of Quantification. - 3. Evaluation of Quantification Algorithms. - 4. Methods for Learning to Quantify. - 5. Advanced Topics. - 6. The Quantification Landscape. - 7. The Road Ahead.

Andrea Esuli is a tenured Senior Researcher at the Italian National Council of Research. His research interests include learning to quantify, deep learning for text analysis, cross-modal classification, technology-assisted review, and representation learning.Alessandro Fabris is a PhD student at the University of Padova. His research interests include learning to quantify, and the fairness and bias of retrieval and classification systems.Alejandro Moreo is a tenured Researcher at the Italian National Council of Research. His research interests include learning to quantify, deep learning for text analysis, cross-lingual text classification, authorship analysis, and representation learning.Fabrizio Sebastiani is a tenured Director of Research at the Italian National Council of Research. His research interests include learning to quantify, cross-lingual text classification, technology-assisted review, authorship analysis, and representation learning.

• - 1. The Case for Quantification. - 2. Applications of Quantification. - 3. Evaluation of Quantification Algorithms. - 4. Methods for Learning to Quantify. - 5. Advanced Topics. - 6. The Quantification Landscape. - 7. The Road Ahead.