Enhancing deep learning sentiment analysis with ensemble techniques in social applications

Sentiment analysis: Bayesian Ensemble Learning

Applications of Deep Learning to Sentiment Analysis of Movie Reviews

Sentiment analysis is one of the main challenges in natural language processing. Recently, deep learning applications have shown impressive results across different NLP tasks. In this work, I explore performance of different deep learning architectures for semantic analysis of movie reviews, using Stanford Sentiment Treebank as the main dataset. Recurrent, Recursive, and Convolutional neural ne...

Deep Learning for Aspect-Based Sentiment Analysis

Sentiment analysis is an important task in natural language understanding and has a wide range of real-world applications. The typical sentiment analysis focus on predicting the positive or negative polarity of the given sentence(s). This task works in the setting that the given text has only one aspect and polarity. A more general and complicated task would be to predict the aspects mentioned ...

Deep Learning for Sentiment Analysis : A Survey

Deep learning has emerged as a powerful machine learning technique that learns multiple layers of representations or features of the data and produces state-of-the-art prediction results. Along with the success of deep learning in many other application domains, deep learning is also popularly used in sentiment analysis in recent years. This paper first gives an overview of deep learning and th...

A Grouping Hotel Recommender System Based on Deep Learning and Sentiment Analysis

Recommender systems are important tools for users to identify their preferred items and for businesses to improve their products and services. In recent years, the use of online services for selection and reservation of hotels have witnessed a booming growth. Customer’ reviews have replaced the word of mouth marketing, but searching hotels based on user priorities is more time-consuming. This s...