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Enhancing Attention-Based LSTM With Position Context for Aspect-Level Sentiment Classification

Drawing inspirations from the manner of modeling the position context in
information retrieval and question answering, we hypothesize that we should pay much more attention to the
context words neighboring to the aspect than those far away

takes into account the importance of each context word but also incorporates the explicit position information between the aspect and its context words into the aspect-specific attentive representations.