JaTeCS an open-source JAva TExt Categorization System
Andrea Esuli, Tiziano Fagni, Alejandro Moreo Fernandez

TL;DR
JaTeCS is an open-source Java library that streamlines research in automatic text categorization by providing comprehensive tools for data handling, processing, machine learning, and experimental setup, facilitating rapid experimentation.
Contribution
It introduces a modular, extensible Java library that covers all steps of text categorization experiments, including data reading, NLP tools, machine learning, and evaluation, with ready-to-use templates.
Findings
Supports multiple text formats and languages
Includes a wide range of machine learning algorithms
Provides ready-to-use experimental templates
Abstract
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 of special interest in opinion mining applications. It covers all the steps of an experimental activity, from reading the corpus to the evaluation of the experimental results. As JaTeCS is focused on text as the main input data, it provides the user with many text-dedicated tools, e.g.: data readers for many formats, including the most commonly used text corpora and lexical resources, natural language processing tools, multi-language support, methods for feature selection and weighting, the implementation of many machine learning algorithms as well as wrappers for well-known external software (e.g., SVM_light) which enable their full control from code. JaTeCS support its expansion by abstracting through…
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Taxonomy
TopicsTopic Modeling · Text and Document Classification Technologies · Machine Learning and Data Classification
