Publication Date:
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.
Iris type:
04.01 Contributo in Atti di convegno
Keywords:
Text classification; Quantification; Ordinal regression
List of contributors:
Esuli, Andrea
Full Text:
Book title:
Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016)