Unverified50% confidenceFactExact time
Neighbor expansion is a strategy in graph retrieval: after initially recalling seed nodes, it traverses one or more hops of neighbors along the graph's edges, bringing associated nodes into context using explicit structural relations rather than semantic similarity.
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50%
Confidence
Long-term
Relevance
11/5/2026
First Seen
Sources
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Related Claims
UnverifiedThe neighborhood heuristic is the key to keeping the HNSW graph navigable; directly connecting the nearest M points causes links to get trapped within clusters in clustered data, and searches get stuck at cluster boundaries.69% similarUnverifiedThe core idea of GraphSAGE is to sample a fixed number of neighbors for the target node and then aggregate neighbor features layer by layer through aggregation functions, enabling inference on unseen nodes.68% similarUnverifiedIn the demo, a call to graph.node.listNeighbors returned 12 neighbor nodes in one go, with each row representing a neighbor and its connecting edge to the committee; among them, the Northwind case itself also has 7 edges.61% similarUnverifiedOpenViking's retrieval logic first locates relevant directories and then drills down layer by layer, returning results while preserving surrounding structural relationships, distinguishing it from vector search which returns isolated fragments.59% similarUnverifiedNeighborhood overlap only concerns whether the nearest-neighbor set of each sample is consistent between the two representations, and is a purely local, nonparametric criterion.57% similar
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