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
Inglese
Bethard S., Carpuat M., Cer D., Jurgens D., Nakov P., Zesch T.
Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016)
SemEval 2016 - 10th International Workshop on Semantic Evaluation
92
95
978-1-941643-95-2
https://aclanthology.org/S16-1011/
Sì, ma tipo non specificato
16-17 June 2016
San Diego, USA
Text classification
Quantification
Ordinal regression
1
open
Esuli, A
273
info:eu-repo/semantics/conferenceObject
04 Contributo in convegno::04.01 Contributo in Atti di convegno
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/327902
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