矢量数据库管理系统:基本概念、使用案例和当前挑战

IF 2.1 3区 心理学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Cognitive Systems Research Pub Date : 2024-02-15 DOI:10.1016/j.cogsys.2024.101216
Toni Taipalus
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引用次数: 0

摘要

矢量数据库管理系统已成为现代数据管理的重要组成部分,这是因为在推荐系统、相似性搜索和聊天机器人等不同领域,对文本、图像和视频等丰富数据进行计算描述的需求日益重要。这些数据描述是以数值矢量的形式捕获的,其存储和比较的计算成本很低。然而,矢量化数据的独特特性,包括高维性和稀疏性,要求为高效存储、检索和处理提供专门的解决方案。这篇叙事性文献综述对矢量数据库管理系统的基本概念、使用案例和当前挑战进行了通俗易懂的介绍,为寻求有效矢量数据管理的研究人员和从业人员提供了一个概览。
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Vector database management systems: Fundamental concepts, use-cases, and current challenges

Vector database management systems have emerged as an important component in modern data management, driven by the growing importance for the need to computationally describe rich data such as texts, images and video in various domains such as recommender systems, similarity search, and chatbots. These data descriptions are captured as numerical vectors that are computationally inexpensive to store and compare. However, the unique characteristics of vectorized data, including high dimensionality and sparsity, demand specialized solutions for efficient storage, retrieval, and processing. This narrative literature review provides an accessible introduction to the fundamental concepts, use-cases, and current challenges associated with vector database management systems, offering an overview for researchers and practitioners seeking to facilitate effective vector data management.

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来源期刊
Cognitive Systems Research
Cognitive Systems Research 工程技术-计算机:人工智能
CiteScore
9.40
自引率
5.10%
发文量
40
审稿时长
>12 weeks
期刊介绍: Cognitive Systems Research is dedicated to the study of human-level cognition. As such, it welcomes papers which advance the understanding, design and applications of cognitive and intelligent systems, both natural and artificial. The journal brings together a broad community studying cognition in its many facets in vivo and in silico, across the developmental spectrum, focusing on individual capacities or on entire architectures. It aims to foster debate and integrate ideas, concepts, constructs, theories, models and techniques from across different disciplines and different perspectives on human-level cognition. The scope of interest includes the study of cognitive capacities and architectures - both brain-inspired and non-brain-inspired - and the application of cognitive systems to real-world problems as far as it offers insights relevant for the understanding of cognition. Cognitive Systems Research therefore welcomes mature and cutting-edge research approaching cognition from a systems-oriented perspective, both theoretical and empirically-informed, in the form of original manuscripts, short communications, opinion articles, systematic reviews, and topical survey articles from the fields of Cognitive Science (including Philosophy of Cognitive Science), Artificial Intelligence/Computer Science, Cognitive Robotics, Developmental Science, Psychology, and Neuroscience and Neuromorphic Engineering. Empirical studies will be considered if they are supplemented by theoretical analyses and contributions to theory development and/or computational modelling studies.
期刊最新文献
A mathematical formulation of learner cognition for personalised learning experiences Identification of the emotional component of inner pronunciation: EEG-ERP study Towards emotion-aware intelligent agents by utilizing knowledge graphs of experiences Exploring the impact of virtual reality flight simulations on EEG neural patterns and task performance
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