A multi-modal database-oriented adaptive index structure selection method

By performing statistical feature analysis and hidden dimension calculation on multimodal databases, and automatically selecting suitable index structures, the problems of high index configuration costs and unstable query performance in multimodal databases are solved, achieving efficient multimodal similarity retrieval and accurate ranking.

CN121996662BActive Publication Date: 2026-07-10ZHEJIANG UNIV
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
ZHEJIANG UNIV
Filing Date
2026-04-09
Publication Date
2026-07-10

AI Technical Summary

Technical Problem

Existing technologies lack a unified solution for automatically analyzing multimodal data characteristics and selecting appropriate index structures in multimodal databases, resulting in significant fluctuations in query performance and making it difficult to adapt to the index management needs of large-scale, highly variable, and highly real-time scenarios.

Method used

By performing statistical feature analysis on multimodal vector datasets, calculating hidden dimensions, and automatically selecting appropriate index structures based on preset index adaptation rules, the association between local indexes and global routing structures is constructed, enabling efficient routing and execution of multimodal queries.

Benefits of technology

It significantly reduces index configuration costs, improves query efficiency and scalability of multimodal databases, and supports accurate retrieval in large-scale, multi-type data scenarios.

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Abstract

This invention discloses an adaptive index structure selection method for multimodal databases. By analyzing the statistical characteristics of each modality, such as data dimensionality, variance, sparsity, and distance distribution, the hidden dimension of each modality is calculated, and its effective data complexity is characterized. Based on preset index adaptation rules, each modality is automatically mapped to the optimal index type in the candidate index structure set, thereby automatically constructing local indexes and binding them to the global routing structure. Furthermore, multimodal queries can be automatically routed to the corresponding index for retrieval based on the index mapping relationship. This invention achieves an adaptive index structure selection mechanism that requires no manual configuration, significantly reducing the index maintenance cost of multimodal databases and improving query efficiency and scalability in complex retrieval scenarios.
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