Injecting Relational Structural Representation in Neural Networks for Question Similarity

meeting of the association for computational linguistics, pp. 285-291, 2018.

Cited by: 4|Bibtex|Views14|DOI:https://doi.org/10.18653/v1/p18-2046
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Other Links: dblp.uni-trier.de|academic.microsoft.com|arxiv.org

Abstract:

Effectively using full syntactic parsing information in Neural Networks (NNs) to solve relational tasks, e.g., question similarity, is still an open problem. In this paper, we propose to inject structural representations in NNs by (i) learning an SVM model using Tree Kernels (TKs) on relatively few pairs of questions (few thousands) as go...More

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