人工智能在企业经济数据管理中的应用——基于知识图谱的智能检索模型

Application of Artificial Intelligence in Enterprise Economic Data Management—An Intelligent Retrieval Model Based on Knowledge Graph

摘要: 知识图谱融合人工智能技术，可实现复杂经济数据的语义关联与智能分析，在企业数据管理中具有重要价值。本文分析了企业经济数据管理中多源数据整合难、异构信息清洗效率低、查询精度不足及风险预警滞后的现状，研究了基于知识图谱的智能检索模型构建思路，提出以知识图谱为语义支撑、融合自然语言理解与语义向量匹配的智能检索架构，旨在围绕多源异构经济数据的语义融合方法展开研究，构建统一本体模型与嵌入式表示机制，实现跨系统数据的标准化与智能可检索性。

Abstract: The integration of knowledge graph and artificial intelligence technology can achieve semantic correlation and intelligent analysis of complex economic data, which has important value in enterprise data management. This article analyzes the current situation of difficult integration of multi-source data, low efficiency of heterogeneous information cleaning, insufficient query accuracy, and lagging risk warning in enterprise economic data management. It studies the construction idea of an intelligent retrieval model based on knowledge graph and proposes an intelligent retrieval architecture that integrates natural language understanding and semantic vector matching with knowledge graph as semantic support. The aim is to conduct research on semantic fusion methods for multi-source heterogeneous economic data, construct a unified ontology model and embedded representation mechanism, and achieve standardization and intelligent retrievability of cross system data.