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Target-Sensitive Memory Networks for Aspect Sentiment Classification
In MNs, attention mechanism plays a crucial role in detecting the sentiment context for the given target.
Disentangling Aspect and Opinion Words in Target-based Sentiment Analysis using Lifelong Learning
Stage one extracts/groups the target-related words (call t-words) for a given target.
Contextual and Position-Aware Factorization Machines for Sentiment Classification
While existing machine learning models have achieved great success for sentiment classification, they typically do not explicitly capture sentiment-oriented word interaction, which can lead to poor results for fine-grained analysis at the snippet level (a phrase or sentence).
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