HCGR: Hyperbolic Contrastive Graph Representation Learning for Session-based Recommendation

Wed, 01 May 2024 09:00:00 +0000

A user opens a sneaker app, taps “running shoes,” drills into a brand, then a price band, and finally a single SKU. This trajectory forms a tree: each click narrows the candidate set roughly multiplicatively. In Euclidean space, you need many dimensions to keep all the leaves of the tree apart because the volume grows polynomially with radius. In hyperbolic space, volume grows exponentially with radius, so the tree fits naturally — a few dimensions are enough to keep the long tail untangled.

Hyperbolic Geometry on Chen Kai Blog

HCGR: Hyperbolic Contrastive Graph Representation Learning for Session-based Recommendation