[HTML][HTML] Comparing deep learning architectures for sentiment analysis on drug reviews
Since the turn of the century, as millions of user's opinions are available on the web,
sentiment analysis has become one of the most fruitful research fields in Natural Language …
sentiment analysis has become one of the most fruitful research fields in Natural Language …
Attending to discriminative certainty for domain adaptation
In this paper, we aim to solve for unsupervised domain adaptation of classifiers where we
have access to label information for the source domain while these are not available for a …
have access to label information for the source domain while these are not available for a …
Improving natural language processing tasks with human gaze-guided neural attention
A lack of corpora has so far limited advances in integrating human gaze data as a
supervisory signal in neural attention mechanisms for natural language processing (NLP) …
supervisory signal in neural attention mechanisms for natural language processing (NLP) …
U-cam: Visual explanation using uncertainty based class activation maps
Understanding and explaining deep learning models is an imperative task. Towards this, we
propose a method that obtains gradient-based certainty estimates that also provide visual …
propose a method that obtains gradient-based certainty estimates that also provide visual …
Duplicate questions pair detection using siamese malstm
Quora is a growing platform comprising a user generated collection of questions and
answers. The questions and answers are created, edited, and organized by the users …
answers. The questions and answers are created, edited, and organized by the users …
Recent trends and advances in deep learning-based sentiment analysis
A Ahmet, T Abdullah - Deep learning-based approaches for sentiment …, 2020 - Springer
Sentiment analysis is a fundamental branch of natural language processing. It is an
essential task of identifying and extracting sentiment in opinionated data from sources such …
essential task of identifying and extracting sentiment in opinionated data from sources such …
Looking back at labels: A class based domain adaptation technique
In this paper, we solve the problem of adapting classifiers across domains. We consider the
problem of domain adaptation for multi-class classification where we are provided a labeled …
problem of domain adaptation for multi-class classification where we are provided a labeled …
Incorporating feature representation into BiLSTM for deceptive review detection
Consumers are increasingly influenced by product reviews when purchasing goods or
services. At the same time, deceptive reviews usually mislead users. It is inefficient and …
services. At the same time, deceptive reviews usually mislead users. It is inefficient and …
Fast and robust online handwritten Chinese character recognition with deep spatial and contextual information fusion network
Deep convolutional neuralnetworks have achieved fairly high accuracy for single online
handwritten Chinese character recognition (SOLHCCR). However, in real application …
handwritten Chinese character recognition (SOLHCCR). However, in real application …
Paraphrase diversification using counterfactual debiasing
The problem of generating a set of diverse paraphrase sentences while (1) not
compromising the original meaning of the original sentence, and (2) imposing diversity in …
compromising the original meaning of the original sentence, and (2) imposing diversity in …