EmotionGIF-IITP-AINLPML: Ensemble-based Automated Deep Neural System for predicting category(ies) of a GIF response
December 23, 2020 ยท Declared Dead ยท ๐ arXiv.org
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Authors
Soumitra Ghosh, Arkaprava Roy, Asif Ekbal, Pushpak Bhattacharyya
arXiv ID
2012.12756
Category
cs.CL: Computation & Language
Cross-listed
cs.AI
Citations
1
Venue
arXiv.org
Last Checked
5 months ago
Abstract
In this paper, we describe the systems submitted by our IITP-AINLPML team in the shared task of SocialNLP 2020, EmotionGIF 2020, on predicting the category(ies) of a GIF response for a given unlabelled tweet. For the round 1 phase of the task, we propose an attention-based Bi-directional GRU network trained on both the tweet (text) and their replies (text wherever available) and the given category(ies) for its GIF response. In the round 2 phase, we build several deep neural-based classifiers for the task and report the final predictions through a majority voting based ensemble technique. Our proposed models attain the best Mean Recall (MR) scores of 52.92% and 53.80% in round 1 and round 2, respectively.
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