{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/nl-fiit-at-semeval-2019-task-9-neural-model","title":"NL-FIIT at SemEval-2019 Task 9: Neural Model Ensemble for Suggestion Mining","arxiv_id":"1904.02981","date":"2019-04-05","proceeding":"SEMEVAL 2019 6","authors":["Samuel Pecar","Marian Simko","Maria Bielikova"],"abstract":"In this paper, we present neural model architecture submitted to the\nSemEval-2019 Task 9 competition: \"Suggestion Mining from Online Reviews and\nForums\". We participated in both subtasks for domain specific and also\ncross-domain suggestion mining. We proposed a recurrent neural network\narchitecture that employs Bi-LSTM layers and also self-attention mechanism. Our\narchitecture tries to encode words via word representations using ELMo and\nensembles multiple models to achieve better results. We performed experiments\nwith different setups of our proposed model involving weighting of prediction\nclasses for loss function. Our best model achieved in official test evaluation\nscore of 0.6816 for subtask A and 0.6850 for subtask B. In official results, we\nachieved 12th and 10th place in subtasks A and B, respectively.","url_abs":"http://arxiv.org/abs/1904.02981v1","url_pdf":"http://arxiv.org/pdf/1904.02981v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"nl-fiit-at-semeval-2019-task-9-neural-model","repo_url":"https://github.com/SamuelPecar/NL-FIIT-SemEval19-Task9","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"suggestion-mining","task_name":"Suggestion mining"}],"methods":[{"method_slug":"bilstm","method_name":"BiLSTM"},{"method_slug":"elmo","method_name":"ELMo"},{"method_slug":"lstm","method_name":"LSTM"},{"method_slug":"sigmoid-activation","method_name":"Sigmoid Activation"},{"method_slug":"softmax","method_name":"Softmax"},{"method_slug":"tanh-activation","method_name":"Tanh Activation"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}