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

Giovanni Martino, Wei Gao, Fabrizio Sebastiani

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

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.

Original languageEnglish
Title of host publicationSemEval 2016 - 10th International Workshop on Semantic Evaluation, Proceedings
PublisherAssociation for Computational Linguistics (ACL)
Pages58-63
Number of pages6
ISBN (Electronic)9781941643952
Publication statusPublished - 1 Jan 2016
Event10th International Workshop on Semantic Evaluation, SemEval 2016 - San Diego, United States
Duration: 16 Jun 201617 Jun 2016

Other

Other10th International Workshop on Semantic Evaluation, SemEval 2016
CountryUnited States
CitySan Diego
Period16/6/1617/6/16

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ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computational Theory and Mathematics
  • Computer Science Applications

Cite this

Martino, G., Gao, W., & Sebastiani, F. (2016). QCRI at SemEval-2016 task 4: Probabilistic methods for binary and ordinal quantification. In SemEval 2016 - 10th International Workshop on Semantic Evaluation, Proceedings (pp. 58-63). Association for Computational Linguistics (ACL).