Equation 17 · Embeddings and the Geometry of Similarity
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A third effect compounds these. Radovanovic, Nanopoulos and Ivanovic showed that as dimensionality increases, the distribution of how often a point occurs among the k nearest neighbours of other points becomes strongly skewed: some points become hubs , appearing in very many neighbour lists, and they characterise this as an inherent property of data distributions in high-dimensional space rather than an artefact of any particular dataset [ 13 ] . In a retrieval system, a hub is a document that surfaces for queries it has nothing to do with, and it will look like a bug in the ingestion pipeline.
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