Researchers from ISTI-CNR, Pisa (in a joint effort with the Qatar Computing Research Institute), have developed a transfer learning method that allows cross-domain and cross-lingual sentiment classification to be performed accurately and efficiently. This means sentiment classification efforts can leverage training data originally developed for performing sentiment classification on other domains and/or in other languages.
Distributional correspondence indexing for cross-lingual and cross-domain sentiment classification
Moreo Fernandez A;Esuli A;Sebastiani F
2017
Abstract
Researchers from ISTI-CNR, Pisa (in a joint effort with the Qatar Computing Research Institute), have developed a transfer learning method that allows cross-domain and cross-lingual sentiment classification to be performed accurately and efficiently. This means sentiment classification efforts can leverage training data originally developed for performing sentiment classification on other domains and/or in other languages.File in questo prodotto:
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Descrizione: Distributional correspondence indexing for cross-lingual and cross-domain sentiment classification
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