Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Progressive Self-Supervised Attention Learning for Aspect-Level
  Sentiment Analysis   In aspect-level sentiment classification (ASC), it is prevalent to equip
dominant neural models with attention mechanisms, for the sake of acquiring the
importance of each context word on the given aspect. However, such a mechanism
tends to excessively focus on a few frequent words with sentiment polarities,
while ignoring infrequent ones. In this paper, we propose a progressive
self-supervised attention learning approach for neural ASC models, which
automatically mines useful attention supervision information from a training
corpus to refine attention mechanisms. Specifically, we iteratively conduct
sentiment predictions on all training instances. Particularly, at each
iteration, the context word with the maximum attention weight is extracted as
the one with active/misleading influence on the correct/incorrect prediction of
every instance, and then the word itself is masked for subsequent iterations.
Finally, we augment the conventional training objective with a regularization
term, which enables ASC models to continue equally focusing on the extracted
active context words while decreasing weights of those misleading ones.
Experimental results on multiple datasets show that our proposed approach
yields better attention mechanisms, leading to substantial improvements over
the two state-of-the-art neural ASC models. Source code and trained models are
available at https://github.com/DeepLearnXMU/PSSAttention.

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The categories of this paper are: physics
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The categories of this paper are: eess
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The categories of this paper are: solv-int
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The categories of this paper are: nucl-th
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The categories of this paper are: alg-geom
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The categories of this paper are: acc-phys
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The categories of this paper are: math-ph
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The categories of this paper are: gr-qc
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The categories of this paper are: astro-ph
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The categories of this paper are: bayes-an
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The categories of this paper are: quant-ph
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The categories of this paper are: hep-ph
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The categories of this paper are: q-alg
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The categories of this paper are: mtrl-th
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The categories of this paper are: dg-ga
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The categories of this paper are: hep-th