Sent2Matrix: Folding Character Sequences in Serpentine Manifolds for Two-Dimensional Sentence

• URL: http://arxiv.org/abs/2103.08387v1
• Date: Mon, 15 Mar 2021 13:52:47 GMT
• Title: Sent2Matrix: Folding Character Sequences in Serpentine Manifolds for Two-Dimensional Sentence
• Authors: Hongyang Gao, Yi Liu, Xuan Zhang, Shuiwang Ji
• Abstract summary: We propose to convert texts into 2-D representations and develop the Sent2Matrix method. Our method allows for the explicit incorporation of both word morphologies and boundaries. Notably, our method is the first attempt to represent texts in 2-D formats.
• Score: 54.6266741821988
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: We study text representation methods using deep models. Current methods, such as word-level embedding and character-level embedding schemes, treat texts as either a sequence of atomic words or a sequence of characters. These methods either ignore word morphologies or word boundaries. To overcome these limitations, we propose to convert texts into 2-D representations and develop the Sent2Matrix method. Our method allows for the explicit incorporation of both word morphologies and boundaries. When coupled with a novel serpentine padding method, our Sent2Matrix method leads to an interesting visualization in which 1-D character sequences are folded into 2-D serpentine manifolds. Notably, our method is the first attempt to represent texts in 2-D formats. Experimental results on text classification tasks shown that our method consistently outperforms prior embedding methods.

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