INRIA at SemEval-2019 Task 9: Suggestion Mining Using SVM with Handcrafted Features
We present the INRIA approach to the suggestion mining task at SemEval 2019. The task consists of two subtasks: suggestion mining under single-domain (Subtask A) and cross-domain (Subtask B) settings. We used the Support Vector Machines algorithm trained on handcrafted features, function words, sentiment features, digits, and verbs for Subtask A, and handcrafted features for Subtask B. Our best run archived a F1-score of 51.18{\%} on Subtask A, and ranked in the top ten of the submissions for Subtask B with 73.30{\%} F1-score.
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