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Found 3 papers, 1 papers with code
Composition-based Heterogeneous Graph Multi-channel Attention Network for Multi-aspect Multi-sentiment Classification
Aspect-based sentiment analysis (ABSA) has drawn more and more attention because of its extensive applications.
Aspect-Based Sentiment Analysis
Aspect-Based Sentiment Analysis (ABSA)
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Joint Learning of Local and Global Features for Aspect-based Sentiment Classification
Furthermore, we propose a dual-level graph attention network as a global encoder by fully employing dependency tag information to capture long-distance information effectively.
Estimating Treatment Effects from Irregular Time Series Observations with Hidden Confounders
Causal analysis for time series data, in particular estimating individualized treatment effect (ITE), is a key task in many real-world applications, such as finance, retail, healthcare, etc.
