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Parameter-free Sentence Embedding via Orthogonal Basis
[article]
2019
arXiv
pre-print
We propose a simple and robust non-parameterized approach for building sentence representations. Inspired by the Gram-Schmidt Process in geometric theory, we build an orthogonal basis of the subspace spanned by a word and its surrounding context in a sentence. We model the semantic meaning of a word in a sentence based on two aspects. One is its relatedness to the word vector subspace already spanned by its contextual words. The other is the word's novel semantic meaning which shall be
arXiv:1810.00438v2
fatcat:ufed7mjvvvhzvouakbhlxq6czu