Semantics in High-Dimensional Space

FRONTIERS IN ARTIFICIAL INTELLIGENCE(2021)

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摘要
Geometric models are used for modelling meaning in various semantic-space models. They are seductive in their simplicity and their imaginative qualities, and for that reason, their metaphorical power risks leading our intuitions astray: human intuition works well in a three-dimensional world but is overwhelmed by higher dimensionalities. This note is intended to warn about some practical pitfalls of using high-dimensional geometric representation as a knowledge representation and a memory model-challenges that can be met by informed design of the representation and its application.
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关键词
vector-space models, semantic spaces, high-dimensional computing, distributional semantics, word embeddings
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