This paper details on the participation of ISTI-CNR to task 4 of Semeval 2016. Among the five subtasks, special attention has been paid to the five-point scale quantification subtask. The quantification method we propose is based on the observation that a standard document-by-document regression method usually has a bias towards assigning high prevalence labels. Our method models such bias with a linear model, in order to compensate it and to produce the quantification estimates.

ISTI-CNR at SemEval-2016 Task 4: quantification on an ordinal scale

Esuli A
2016

Abstract

This paper details on the participation of ISTI-CNR to task 4 of Semeval 2016. Among the five subtasks, special attention has been paid to the five-point scale quantification subtask. The quantification method we propose is based on the observation that a standard document-by-document regression method usually has a bias towards assigning high prevalence labels. Our method models such bias with a linear model, in order to compensate it and to produce the quantification estimates.
2016
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" - ISTI
978-1-941643-95-2
Text classification
Quantification
Ordinal regression
File in questo prodotto:
File Dimensione Formato  
prod_368820-doc_122438.pdf

accesso aperto

Descrizione: ISTI-CNR at SemEval-2016 Task 4: Quantification on an ordinal scale
Tipologia: Versione Editoriale (PDF)
Dimensione 186.94 kB
Formato Adobe PDF
186.94 kB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/327902
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 11
  • ???jsp.display-item.citation.isi??? ND
social impact