1 citations · 2 across the 5 of their papers we have counts for
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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…
Hybrid Tiled Convolutional Neural Networks for Text Sentiment Classification
Maria Mihaela Trusca, Gerasimos Spanakis
The tiled convolutional neural network (tiled CNN) has been applied only to computer vision for learning invariances. We adjust its architecture to NLP to improve the extraction of…