Pay Attention to Categories: Syntax-Based Sentence Modeling with Metadata Projection Matrix

Won-Ik Cho, Nam Soo Kim
2020 Pacific Asia Conference on Language, Information and Computation  
Sentence modeling is a vital feature engineering for document classification. Various feature extraction and summarization algorithms have been adopted for efficient classification of a sentence, e.g., dense word vectors and neural network classifiers. Recently, the concept of attention for machine translation has been applied to various natural language processing (NLP) tasks and has shown significant performance. In this paper, we take a look at the syntactic categories of the words, to make
more » ... p a metadata projection matrix that assigns strong restrictions on determining the attention weight. Unlike conventional attention models, which are considered as a division of location-based approaches, our model adds a selection layer to highlight categorical metadata that may appear more than once. The proposed algorithm shows improved performance compared to the baselines with the tasks in syntax-semantics, suggesting a possibility of extension to other fields such as symbolic music or bitstream analysis.
dblp:conf/paclic/ChoK20 fatcat:dnqe3vko6zfrbnexo3ucy4czvq