Document - Distributional correspondence indexing for cross-lingual and cross-domain sentiment classification

2017

Journal article Open Access

Distributional correspondence indexing for cross-lingual and cross-domain sentiment classification

Moreo Fernandez A, Esuli A, Sebastiani F

Sentiment classification

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.

Source: ERCIM NEWS, vol. 111, p. 48

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BibTeX entry

@article{oai:it.cnr:prodotti:376280,
	title = {Distributional correspondence indexing for cross-lingual and cross-domain sentiment classification},
	author = {Moreo Fernandez A and Esuli A and Sebastiani F},
	year = {2017}
}