®®®® SIIA Público

Título del libro: Lipn-Iimas At Semeval-2016 Task 1: Random Forest Regression Experiments On Align-And-Differentiate And Word Embeddings Penalizing Strategies

Autores UNAM:
AUREA OROZCO RIVAS;
Autores externos:

Idioma:
Inglés
Año de publicación:
2016
Palabras clave:

Decision trees; Semantics; Embeddings; Learning models; Random forests; Syntactic dependencies; Textual similarities; Wordnet; Search engines


Resumen:

This paper describes the SOPA-N system used by the LIPN-IIMAS team in Semeval 2016 Semantic Textual Similarity (Task 1). We based our work on the SOPA 2015 system. The SOPA-2015 system used 16 similarity features (including Wordnet, Information Retrieval and Syntactic Dependencies) within a Random Forest learning model. We expanded this system with an Align and Differentiate based strategy, word embeddings and penalization, which showed 6.8% of improvement on the development set. However, we found that on the evaluation data for the 2016 STS shared task, the 2015 system outperformed our newer systems. © 2016 Association for Computational Linguistics.


Entidades citadas de la UNAM: