A survey on text classification: Practical perspectives on the Italian language.

ABSTRACT: Text Classification methods have been improving at an unparalleled speed in the last decade thanks to the success brought about by deep learning. Historically, state-of-the-art approaches have been developed for and benchmarked against English datasets, while other languages have had to catch up and deal with inevitable linguistic challenges. This paper offers a survey with practical and linguistic connotations, showcasing the complications and challenges tied to the application of modern Text Classification algorithms to languages other than English. We engage this subject from the perspective of the Italian language, and we discuss in detail issues related to the scarcity of task-specific datasets, as well as the issues posed by the computational expensiveness of modern approaches. We su

SUBMITTER: Gasparetto A 

PROVIDER: S-EPMC9258888 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature