Home |  English version |  Mappa |  Commenti |  Sondaggio |  Staff |  Contattaci Cerca nel sito  
Istituto di scienza e tecnologie dell'informazione "Alessandro Faedo"

Torna all'elenco Report e working Paper anno 2019

Report e working Paper

Tipo: Rapporto di ricerca (Research report)

Titolo: Cross-Lingual Sentiment Quantification

Anno di pubblicazione: 2019

Formato: Elettronico

Autori: Esuli A.; Moreo Fernandez A. D.; Sebastiani F.

Affiliazioni autori: CNR-ISTI, Pisa, Italy; CNR-ISTI, Pisa, Italy; CNR-ISTI, Pisa, Italy

Autori CNR:

  • ANDREA ESULI
  • ALEJANDRO DAVID MOREO FERNANDEZ
  • FABRIZIO SEBASTIANI

Lingua: inglese

Sintesi: We discuss Cross-Lingual Text Quantification (CLTQ), the task of performing text quantification (i.e., estimating the relative frequency pc(D) of all classes c?C in a set D of unlabelled documents) when training documents are available for a source language S but not for the target language T for which quantification needs to be performed. CLTQ has never been discussed before in the literature; we establish baseline results for the binary case by combining state-of-the-art quantification methods with methods capable of generating cross-lingual vectorial representations of the source and target documents involved. We present experimental results obtained on publicly available datasets for cross-lingual sentiment classification; the results show that the presented methods can perform CLTQ with a surprising level of accuracy.

Lingua sintesi: eng

Pagine totali: 6

Parole chiave:

  • Sentiment Classification
  • Cross-Lingual
  • Quantification
  • Prevalence Estimation

URL: https://arxiv.org/abs/1904.07965

Strutture CNR:

Moduli:

Allegati: Cross-Lingual Sentiment Quantification (application/pdf)
pre-print OA su arxiv

 
Torna indietro Richiedi modifiche Invia per email Stampa
Home Il CNR  |  I servizi News |   Eventi | Istituti |  Focus