| Título |
Pinealai at SemEval-2024 Task 1: Exploring Semantic Relatedness Prediction using Syntactic, TF-IDF, and Distance-Based Features |
| Tipo |
Congreso |
| Sub-tipo |
Memoria |
| Descripción |
18th International Workshop on Semantic Evaluation, SemEval 2024, co-located with the 2024 Annual Conference of the North American Chapter of the Association for Computational Linguistics, NAACL 2024 |
| Resumen |
The central aim of this experiment is to establish a system proficient in predicting semantic relatedness between pairs of English texts. Additionally, the study seeks to delve into diverse features capable of enhancing the ability of models to identify semantic relatedness within given sentences. Several strategies have been used that combine TF-IDF, syntactic features, and similarity measures to train machine learning models to predict semantic relatedness between pairs of sentences. The results obtained were above the baseline with an approximate Spearman score of 0.84. © 2024 Association for Computational Linguistics. |
| Observaciones |
|
| Lugar |
Hybrid, Mexico City |
| País |
Mexico |
| No. de páginas |
935-939 |
| Vol. / Cap. |
|
| Inicio |
2024-06-20 |
| Fin |
2024-06-21 |
| ISBN/ISSN |
9798891761070 |
