Learning Multi-graph Structure for Temporal Knowledge Graph Reasoning

arXiv:2312.03004v2 Announce Type: replace-cross
Abstract: Temporal Knowledge Graph (TKG) reasoning that forecasts future events based on historical snapshots distributed over timestamps is denoted as extrapolation and has gained significant attention. Owing to its extreme versatility and variation in spatial and temporal correlations, TKG reasoning presents a challenging task, demanding efficient capture of concurrent structures and evolutional interactions among facts. While existing methods have made strides in this direction, they still fall short of harnessing the diverse forms of intrinsic expressive …

abstract arxiv attention correlations cs.ai cs.lg distributed events future graph knowledge knowledge graph reasoning spatial temporal type variation