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.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.


