89 citations · 204 across the 13 of their papers we have counts for
5 papers · 2 filters
Towards a continuous modeling of natural language domains
Sebastian Ruder, Parsa Ghaffari, John G. Breslin
Humans continuously adapt their style and language to a variety of domains. However, a reliable definition of `domain' has eluded researchers thus far. Additionally, the notion of…
INSIGHT-1 at SemEval-2016 Task 5: Deep Learning for Multilingual Aspect-based Sentiment Analysis
Sebastian Ruder, Parsa Ghaffari, John G. Breslin
This paper describes our deep learning-based approach to multilingual aspect-based sentiment analysis as part of SemEval 2016 Task 5. We use a convolutional neural network (CNN) fo…
Character-level and Multi-channel Convolutional Neural Networks for Large-scale Authorship Attribution
Sebastian Ruder, Parsa Ghaffari, John G. Breslin
Convolutional neural networks (CNNs) have demonstrated superior capability for extracting information from raw signals in computer vision. Recently, character-level and multi-chann…
INSIGHT-1 at SemEval-2016 Task 4: Convolutional Neural Networks for Sentiment Classification and Quantification
Sebastian Ruder, Parsa Ghaffari, John G. Breslin
This paper describes our deep learning-based approach to sentiment analysis in Twitter as part of SemEval-2016 Task 4. We use a convolutional neural network to determine sentiment…
A Hierarchical Model of Reviews for Aspect-based Sentiment Analysis
Sebastian Ruder, Parsa Ghaffari, John G. Breslin
Opinion mining from customer reviews has become pervasive in recent years. Sentences in reviews, however, are usually classified independently, even though they form part of a revi…