Similarity Detection

Similarity detection focuses on identifying comparable items across diverse data types, including images, text, and tabular data, aiming to uncover underlying patterns and relationships. Current research explores various approaches, from lightweight neural networks optimized for resource-constrained environments to leveraging the advanced semantic understanding of large language models for summarizing and comparing data points. These advancements are impacting fields ranging from emergency response (e.g., change detection in satellite imagery) to urban planning (e.g., analyzing public transport accessibility) by enabling efficient analysis of complex datasets and facilitating data-driven decision-making.