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FIRME: Registry-Anchored Memory Graphs for Evolving, Heterogeneous Investor Knowledge· 金融投资者知识的注册记忆图

Financial AI workflows that reuse investor knowledge need persistent memory that integrates observations across sources and periods without losing identity or provenance. In a knowledge graph, recurring observations may use different surface forms, fragmenting relationship histories and preventing evidence from accumulating. We introduce Fusion and Identity Registry for Memory Evolution (FIRME), a registry-anchored memory graph that reconciles incoming observations to persistent canonical relationships and retains their source, time, and context. Within periods, rule-based fusion links investor-call discussions to portfolio cash-flow signals, directly or through a fixed product-topic ontology. Across periods, canonical identities and persistent aliases direct recurring observations to the

领域:cs.AI作者:Yunbai Zhang、Yunyi Gao、Han-Tai Shiao
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