activity
20172021
most citedJaTeCS an open-source JAva TExt Categorization System

1 citations · 1 across the 2 of their papers we have counts for

collaborators

6 papers

cs.CL2021

Syllabic Quantity Patterns as Rhythmic Features for Latin Authorship Attribution

Silvia Corbara, Alejandro Moreo, Fabrizio Sebastiani

It is well known that, within the Latin production of written text, peculiar metric schemes were followed not only in poetic compositions, but also in many prose works. Such metric…

cs.LG2021

QuaPy: A Python-Based Framework for Quantification

Alejandro Moreo, Andrea Esuli, Fabrizio Sebastiani

QuaPy is an open-source framework for performing quantification (a.k.a. supervised prevalence estimation), written in Python. Quantification is the task of training quantifiers via…

cs.CL2020

Tweet Sentiment Quantification: An Experimental Re-Evaluation

Alejandro Moreo, Fabrizio Sebastiani

Sentiment quantification is the task of training, by means of supervised learning, estimators of the relative frequency (also called ``prevalence'') of sentiment-related classes (s…

cs.LG2020

Re-Assessing the "Classify and Count" Quantification Method

Alejandro Moreo, Fabrizio Sebastiani

Learning to quantify (a.k.a.\ quantification) is a task concerned with training unbiased estimators of class prevalence via supervised learning. This task originated with the obser…

cs.CL2018

Revisiting Distributional Correspondence Indexing: A Python Reimplementation and New Experiments

Alejandro Moreo, Andrea Esuli, Fabrizio Sebastiani

This paper introduces PyDCI, a new implementation of Distributional Correspondence Indexing (DCI) written in Python. DCI is a transfer learning method for cross-domain and cross-li…

cs.CL20171 cited

JaTeCS an open-source JAva TExt Categorization System

Andrea Esuli, Tiziano Fagni, Alejandro Moreo Fernandez

JaTeCS is an open source Java library that supports research on automatic text categorization and other related problems, such as ordinal regression and quantification, which are o…