679 citations · 838 across the 6 of their papers we have counts for
6 papers
A Survey on Aspect-Based Sentiment Classification
Gianni Brauwers, Flavius Frasincar
With the constantly growing number of reviews and other sentiment-bearing texts on the Web, the demand for automatic sentiment analysis algorithms continues to expand. Aspect-based…
A General Survey on Attention Mechanisms in Deep Learning
Gianni Brauwers, Flavius Frasincar
Attention is an important mechanism that can be employed for a variety of deep learning models across many different domains and tasks. This survey provides an overview of the most…
Explaining a Neural Attention Model for Aspect-Based Sentiment Classification Using Diagnostic Classification
Lisa Meijer, Flavius Frasincar, Maria Mihaela Trusca
Many high performance machine learning models for Aspect-Based Sentiment Classification (ABSC) produce black box models, and therefore barely explain how they classify a certain se…
Data Augmentation in a Hybrid Approach for Aspect-Based Sentiment Analysis
Tomas Liesting, Flavius Frasincar, Maria Mihaela Trusca
Data augmentation is a way to increase the diversity of available data by applying constrained transformations on the original data. This strategy has been widely used in image cla…
Pattern Learning for Detecting Defect Reports and Improvement Requests in App Reviews
Gino V. H. Mangnoesing, Maria Mihaela Trusca, Flavius Frasincar
Online reviews are an important source of feedback for understanding customers. In this study, we follow novel approaches that target this absence of actionable insights by classif…
A Hybrid Approach for Aspect-Based Sentiment Analysis Using Deep Contextual Word Embeddings and Hierarchical Attention
Maria Mihaela Trusca, Daan Wassenberg, Flavius Frasincar +1
The Web has become the main platform where people express their opinions about entities of interest and their associated aspects. Aspect-Based Sentiment Analysis (ABSA) aims to aut…