SyntNN at SemEval-2018 Task 2: is Syntax Useful for Emoji Prediction? Embedding Syntactic Trees in Multi Layer Perceptrons

Fabio Massimo Zanzotto, Andrea Santilli


Abstract
In this paper, we present SyntNN as a way to include traditional syntactic models in multilayer neural networks used in the task of Semeval Task 2 of emoji prediction. The model builds on the distributed tree embedder also known as distributed tree kernel. Initial results are extremely encouraging but additional analysis is needed to overcome the problem of overfitting.
Anthology ID:
S18-1076
Volume:
Proceedings of The 12th International Workshop on Semantic Evaluation
Month:
June
Year:
2018
Address:
New Orleans, Louisiana
Venue:
*SEMEVAL
SIGs:
SIGLEX | SIGSEM
Publisher:
Association for Computational Linguistics
Note:
Pages:
477–481
Language:
URL:
https://www.aclweb.org/anthology/S18-1076
DOI:
10.18653/v1/S18-1076
Bib Export formats:
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PDF:
http://aclanthology.lst.uni-saarland.de/S18-1076.pdf