Abstract
In this paper, we describe our ensemble-based system designed by guoym Team for the SemEval-2020 Task 8, Memotion Analysis. In our system, we utilize five types of representation of data as input of base classifiers to extract information from different aspects. We train five base classifiers for each type of representation using five-fold cross-validation. Then the outputs of these base classifiers are combined through data-based ensemble method and feature-based ensemble method to make full use of all data and representations from different aspects. Our method achieves the performance within the top 2 ranks in the final leaderboard of Memotion Analysis among 36 Teams.- Anthology ID:
- 2020.semeval-1.148
- Volume:
- Proceedings of the Fourteenth Workshop on Semantic Evaluation
- Month:
- December
- Year:
- 2020
- Address:
- Barcelona (online)
- Venue:
- SemEval
- SIG:
- SIGLEX
- Publisher:
- International Committee for Computational Linguistics
- Note:
- Pages:
- 1120–1125
- Language:
- URL:
- https://aclanthology.org/2020.semeval-1.148
- DOI:
- 10.18653/v1/2020.semeval-1.148
- Cite (ACL):
- Yingmei Guo, Jinfa Huang, Yanlong Dong, and Mingxing Xu. 2020. Guoym at SemEval-2020 Task 8: Ensemble-based Classification of Visuo-Lingual Metaphor in Memes. In Proceedings of the Fourteenth Workshop on Semantic Evaluation, pages 1120–1125, Barcelona (online). International Committee for Computational Linguistics.
- Cite (Informal):
- Guoym at SemEval-2020 Task 8: Ensemble-based Classification of Visuo-Lingual Metaphor in Memes (Guo et al., SemEval 2020)
- PDF:
- https://preview.aclanthology.org/starsem-semeval-split/2020.semeval-1.148.pdf