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Learning to Attend via Word-Aspect Associative Fusion for Aspect-based Sentiment Analysis
Yi Tay, Anh Tuan Luu, Siu Cheung Hui
Aspect-based sentiment analysis (ABSA) tries to predict the polarity of a given document with respect to a given aspect entity. While neural network architectures have been success…
Cross Temporal Recurrent Networks for Ranking Question Answer Pairs
Yi Tay, Luu Anh Tuan, Siu Cheung Hui
Temporal gates play a significant role in modern recurrent-based neural encoders, enabling fine-grained control over recursive compositional operations over time. In recurrent mode…
SkipFlow: Incorporating Neural Coherence Features for End-to-End Automatic Text Scoring
Yi Tay, Minh C. Phan, Luu Anh Tuan +1
Deep learning has demonstrated tremendous potential for Automatic Text Scoring (ATS) tasks. In this paper, we describe a new neural architecture that enhances vanilla neural networ…
Learning to Rank Question Answer Pairs with Holographic Dual LSTM Architecture
Yi Tay, Minh C. Phan, Luu Anh Tuan +1
We describe a new deep learning architecture for learning to rank question answer pairs. Our approach extends the long short-term memory (LSTM) network with holographic composition…
Hyperbolic Representation Learning for Fast and Efficient Neural Question Answering
Yi Tay, Luu Anh Tuan, Siu Cheung Hui
The dominant neural architectures in question answer retrieval are based on recurrent or convolutional encoders configured with complex word matching layers. Given that recent arch…
Deep Learning based Recommender System: A Survey and New Perspectives
Shuai Zhang, Lina Yao, Aixin Sun +1
With the ever-growing volume of online information, recommender systems have been an effective strategy to overcome such information overload. The utility of recommender systems ca…