89 citations · 93 across the 4 of their papers we have counts for
4 papers
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…