INRIA at SemEval-2019 Task 9: Suggestion Mining Using SVM with Handcrafted Features
| Autor: | Éric Villemonte de la Clergerie, Ilia Markov |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Computer science
business.industry media_common.quotation_subject 02 engineering and technology computer.software_genre SemEval Task (project management) Support vector machine Ranking 020204 information systems 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Artificial intelligence business Function (engineering) computer Natural language processing media_common |
| Zdroj: | SemEval@NAACL-HLT |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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