向量数据库及其应用研究  

Research on Vector Database and Its Application

作　　者：孙雨生 曾俊皓[1] SUN Yusheng;ZENG Junhao(School of Economics and Management,Hubei University of Technology,Wuhan 430068;Hubei Development Research Center of Agricultural Equipment Manufacturing Industry,Hubei University of Technology,Wuhan 430068)

机构地区：[1]湖北工业大学经济与管理学院,武汉430068 [2]湖北工业大学湖北农业装备制造产业发展研究中心,武汉430068

出　　处：《科技情报研究》2024年第4期11-24,共14页Scientific Information Research

基　　金：教育部人文社会科学研究规划基金项目“基于本体的数字图书馆语义用户兴趣模型构建机理及应用模式研究”(编号:17YJA870016);国家社会科学基金一般项目“全文本分析视角下跨学科知识元扩散与知识创新研究”(编号:23BTQ082);湖北农业装备制造产业发展研究中心重点课题“农业装备领域科技创新知识图谱研究”(编号:CAEMI-2024Z1);湖北省图书馆学会重点科研项目“基于微服务架构的智慧图书馆知识服务框架与机制研究”(编号:stxh2023A03)。

摘　　要：[目的/意义]文章通过揭示向量数据库理论、技术、应用等体系,以期推动多模态AI相关理论、技术、应用研究与实践创新。[方法/过程]文章运用文献追溯法、内容分析法阐述了向量数据库演进历程并界定其核心概念,对比分析了其特点、价值,据此梳理了其应用机理、功能及对应的关键技术、应用模式,探讨了向量数据库所面临的挑战及对策,展望了其理论、技术、应用发展趋势。[结果/结论]向量数据库源自向量索引方法体系构建、发展于向量数据检索引擎构建、完善于向量数据库管理系统构建;数据模型、索引机制等方面相比关系数据库、图数据库特点明显;具有用户、数据管理、开发者、研究者等方面的价值;关键技术分为向量数据的嵌入生成、索引、检索3类;应用模式分为数据驱动型、知识驱动型、场景驱动型3类;面临向量数据优质生成、语义描述、存储资源利用、协同共享、伦理安全等方面的挑战;发展态势趋向理论框架体系化、技术方案成熟化、应用服务生态化。[Purpose/significance]The article reveals the theoretical systems,technological systems,and applied systems of vector databases,aiming to promote innovation in the research and practice of multimodal AI related theories,technologies,and applications.[Method/process]This article elaborates on the evolution of vector databases and defines its core concepts through literatures tracing and content analyzing.Subsequently,it compares and analyzes their characteristics and values,and based on this,sorts out their application mechanisms,functions,corresponding key technologies and application modes.Simultaneously,it discusses the challenges and countermeasures faced by vector databases,and looks forward to their development trends from theoretical,technical,and application perspectives.[Result/conclusion]Vector databases originate from the construction of the vector index method system,develop in vector data retrieval engine construction,and mature in vector database management system construction.Compared to relational databases and graph databases,vector databases exhibit obvious characteristics in data models,indexing mechanisms.They hold various value for users,data managers,developers and researchers.The key technologies are divided into three categories:vector data embedding generation,vector data indexing,and vector data retrieval.Application patterns can be divided into three categories:data-driven applications,knowledge-driven applications and scenario driven applications.Challenges exist in various aspects such as high-quality generation,semantic description,storage resource utilization,collaborative sharing,and ethical security of vector data.Trends point towards the systematization of theoretical frameworks,maturation of technical solutions,and ecosystem development of application services.

关 键 词：向量数据库 多模态数据融合 向量数据检索 向量数据索引 AI应用生态 

分 类 号：G202[文化科学—传播学] TP391[自动化与计算机技术—计算机应用技术]