SemEval-2019 Task 9: Suggestion Mining from Online Reviews and Forums

Sapna Negi, Tobias Daudert, Paul Buitelaar


Abstract
We present the pilot SemEval task on Suggestion Mining. The task consists of subtasks A and B, where we created labeled data from feedback forum and hotel reviews respectively. Subtask A provides training and test data from the same domain, while Subtask B evaluates the system on a test dataset from a different domain than the available training data. 33 teams participated in the shared task, with a total of 50 members. We summarize the problem definition, benchmark dataset preparation, and methods used by the participating teams, providing details of the methods used by the top ranked systems. The dataset is made freely available to help advance the research in suggestion mining, and reproduce the systems submitted under this task
Anthology ID:
S19-2151
Volume:
Proceedings of the 13th International Workshop on Semantic Evaluation
Month:
June
Year:
2019
Address:
Minneapolis, Minnesota, USA
Editors:
Jonathan May, Ekaterina Shutova, Aurelie Herbelot, Xiaodan Zhu, Marianna Apidianaki, Saif M. Mohammad
Venue:
SemEval
SIG:
SIGLEX
Publisher:
Association for Computational Linguistics
Note:
Pages:
877–887
Language:
URL:
https://aclanthology.org/S19-2151
DOI:
10.18653/v1/S19-2151
Bibkey:
Cite (ACL):
Sapna Negi, Tobias Daudert, and Paul Buitelaar. 2019. SemEval-2019 Task 9: Suggestion Mining from Online Reviews and Forums. In Proceedings of the 13th International Workshop on Semantic Evaluation, pages 877–887, Minneapolis, Minnesota, USA. Association for Computational Linguistics.
Cite (Informal):
SemEval-2019 Task 9: Suggestion Mining from Online Reviews and Forums (Negi et al., SemEval 2019)
Copy Citation:
PDF:
https://aclanthology.org/S19-2151.pdf