nenordot
Nenordot is a term used in theoretical and exploratory discussions of locality-aware similarity measures in vector spaces. It is described as a generalization of the standard dot product that incorporates neighborhood information from the data, rather than relying on a pointwise comparison alone. In this view, the operation takes two equal-length vectors and a neighborhood relation (often represented by a weighting matrix or kernel) and computes a scalar by weighting combinations of vector components according to their local proximity or relatedness.
Etymology and formal idea. The name combines “neighborhood” and “dot” to reflect its core idea: the similarity
Variants and usage. Reported variants include soft nenordot, which uses continuous weights, and hard nenordot, which
Status and reception. Nenordot remains a specialized concept used in preliminary studies and speculative discussions. It