Multitask Learning with Deep Neural Networks for Community Question Answering
In this paper, we developed a deep neural network (DNN) that learns to solve simultaneously the three tasks of the cQA challenge proposed by the SemEval-2016 Task 3, i.e., question-comment similarity, question-question similarity and new question-comment similarity. The latter is the main task, whic...
Guardado en:
Autores principales: | Daniele Bonadiman, Antonio Uva, Alessandro Moschitti |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
Accademia University Press
2017
|
Materias: | |
Acceso en línea: | https://doaj.org/article/70270dcef614458ea9deeac0dfdebc17 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Recurrent Context Window Networks for Italian Named Entity Recognizer
por: Daniele Bonadiman, et al.
Publicado: (2016) -
Question Dependent Recurrent Entity Network for Question Answering
por: Andrea Madotto, et al.
Publicado: (2017) -
Finding the Neural Net: Deep-learning Idiom Type Identification from Distributional Vectors
por: Yuri Bizzoni, et al.
Publicado: (2018) -
Using Deep Neural Networks for Smoothing Pitch Profiles in Connected Speech
por: Michele Ferro, et al.
Publicado: (2019) -
On the Readability of Kernel-based Deep Learning Models in Semantic Role Labeling Tasks over Multiple Languages
por: Daniele Rossini, et al.
Publicado: (2019)