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QCRI at SemEval-2016 Task 4: Probabilistic methods for binary and ordinal quantification

Contributo in Atti di convegno
Data di Pubblicazione:
2016
Abstract:
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.
Tipologia CRIS:
04.01 Contributo in Atti di convegno
Keywords:
Sentiment classification; ARTIFICIAL INTELLIGENCE. Learning
Elenco autori:
Sebastiani, Fabrizio
Autori di Ateneo:
SEBASTIANI FABRIZIO
Link alla scheda completa:
https://iris.cnr.it/handle/20.500.14243/324340
Link al Full Text:
https://iris.cnr.it//retrieve/handle/20.500.14243/324340/184597/prod_357201-doc_116505.pdf
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URL

https://aclweb.org/anthology/S/S16/S16-1006.pdf
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