Deep learning approaches have achieved great success in the field of Natural Language
Processing (NLP). However, directly training deep neural models often suffer from overfitting …

Aspect-level sentiment classification aims to determine the sentiment polarity of a sentence
towards an aspect. Due to the high cost in annotation, the lack of aspect-level labeled data …

Obstacles hindering the development of capsule networks for challenging NLP applications
include poor scalability to large output spaces and less reliable routing processes. In this …

CNNs, RNNs, GCNs, and CapsNets have shown significant insights in representation
learning and are widely used in various text mining tasks such as large-scale multi-label text …

In regions of visual inference, optimized performance is demonstrated by capsule networks
on structured data. Classification of hierarchical multi-label text is performed with a simple …

User reviews contain rich semantics towards the preference of users to features of items.
Recently, many deep learning based solutions have been proposed by exploiting reviews …

Abstract The World Health Organization (WHO) has highlighted the need to greatly
accelerate the prevention of crime and harassment against women and children, thereby …

Capsule networks have been shown to demonstrate good performance on structured data in
the area of visual inference. In this paper we apply and compare simple shallow capsule …

Context modeling is essential to generate coherent and consistent translation for Document-
level Neural Machine Translations. The widely used method for document-level translation …

Identification of speech acts provides essential cues in understanding the pragmatics of a
user utterance. It typically helps in comprehending the communicative intention of a speaker …