Analytical Classification of Multimedia Index Structures by Using a Partitioning Method-Based Framework

TL;DR

This paper proposes a systematic framework based on partitioning methods to classify multimedia index structures, facilitating their comparison and guiding the development of more efficient retrieval methods in multimedia databases.

Contribution

It introduces a novel partitioning method-based framework for classifying multimedia index structures, enabling better comparison and analysis of their efficiency.

Findings

Framework allows systematic classification of index structures

Enables empirical comparison based on functional measures

Supports development of more efficient multimedia retrieval structures

Abstract

Due to the advances in hardware technology and increase in production of multimedia data in many applications, during the last decades, multimedia databases have become increasingly important. Contentbased multimedia retrieval is one of an important research area in the field of multimedia databases. Lots of research on this field has led to proposition of different kinds of index structures to support fast and efficient similarity search to retrieve multimedia data from these databases. Due to variety and plenty of proposed index structures, we suggest a systematic framework based on partitioning method used in these structures to classify multimedia index structures, and then we evaluated these structures based on important functional measures. We hope this proposed framework will lead to empirical and technical comparison of multimedia index structures and development of more efficient structures at future.