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    <abstract>We introduce a tree-structured attention neural network for sentences and small phrases and apply it to the problem of sentiment classification. Our model expands the current recursive models by incorporating structural information around a node of a syntactic tree using both bottom-up and top-down information propagation. Also, the model utilizes structural attention to identify the most salient representations during the construction of the syntactic tree.</abstract>
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%0 Conference Proceedings
%T Structural Attention Neural Networks for improved sentiment analysis
%A Kokkinos, Filippos
%A Potamianos, Alexandros
%S Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers
%D 2017
%8 apr
%I Association for Computational Linguistics
%C Valencia, Spain
%F kokkinos-potamianos-2017-structural
%X We introduce a tree-structured attention neural network for sentences and small phrases and apply it to the problem of sentiment classification. Our model expands the current recursive models by incorporating structural information around a node of a syntactic tree using both bottom-up and top-down information propagation. Also, the model utilizes structural attention to identify the most salient representations during the construction of the syntactic tree.
%U https://aclanthology.org/E17-2093
%P 586-591

Markdown (Informal)

[Structural Attention Neural Networks for improved sentiment analysis](https://aclanthology.org/E17-2093) (Kokkinos & Potamianos, EACL 2017)

• Structural Attention Neural Networks for improved sentiment analysis (Kokkinos & Potamianos, EACL 2017)

ACL

• Filippos Kokkinos and Alexandros Potamianos. 2017. Structural Attention Neural Networks for improved sentiment analysis. In Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers, pages 586–591, Valencia, Spain. Association for Computational Linguistics.