SeedER: Seed-and-Expand Retrieval from Knowledge Graphs
Researchers have developed SeedER, a new retrieval framework designed to efficiently navigate and extract information from knowledge graphs. SeedER addresses the challenges of rapid ego-graph expansion and the limitations of dense embedding methods for complex queries. The framework uses a two-stage process: initially seeding core nodes with lightweight retrieval, then employing a learned, graph-aware policy trained with reinforcement learning to selectively expand the set of relevant nodes. AI
IMPACT Introduces a novel retrieval method for knowledge graphs, potentially improving efficiency and recall for knowledge-intensive reasoning systems.