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Author(s): André Cruz
Gil Rocha
Rui Sousa Silva
Henrique Lopes Cardoso
Title: Team Fernando-Pessa at SemEval-2019 Task 4: back to basics in Hyperpartisan News Detection
Issue Date: 2019
Abstract: This paper describes our submission1 to the SemEval 2019 Hyperpartisan News Detection task. Our system aims for a linguistics-based document classification from a minimal set of interpretable features, while maintaining good performance. To this goal, we follow a feature-based approach and perform several experiments with different machine learning classifiers. On the main task, our model achieved an accuracy of 71.7%, which was improved after the task's end to 72.9%. We also participate in the meta-learning sub-task, for classifying documents with the binary classifications of all submitted systems as input, achieving an accuracy of 89.9%.
Subject: Humanidades
Source: Proceedings of the 13th International Workshop on Semantic Evaluation
Document Type: Artigo em Livro de Atas de Conferência Internacional
Rights: openAccess
Appears in Collections:FEUP - Artigo em Livro de Atas de Conferência Internacional
FLUP - Artigo em Livro de Atas de Conferência Internacional

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