PUMA
Istituto di Scienza e Tecnologie dell'Informazione     
Da San Martino G., Gao W., Sebastiani F. QCRI at SemEval-2016 Task 4: Probabilistic methods for binary and ordinal quantification. In: SemEval 2016 - 10th International Workshop on Semantic Evaluation (San Diego, US, 16-17 June 2016). Proceedings, pp. 58 - 63. Association for Computational Linguistics, 2016.
 
 
Abstract
(English)
We describe the systems we have used for participating in Subtasks D (binary quantification) and E (ordinal quantification) of SemEval-2016 Task 4 "Sentiment Analysis in Twitter". The binary quantification system uses a "Probabilistic Classify and Count" (PCC) approach that leverages the calibrated probabilities obtained from the output of an SVM. The ordinal quantification approach uses an ordinal tree of PCC binary quantifiers, where the tree is generated via a splitting criterion that minimizes the ordinal quantification loss.
URL: http://https://aclweb.org/anthology/S/S16/S16-1006.pdf
Subject Sentiment classification
I.2.6 ARTIFICIAL INTELLIGENCE. Learning


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