Semantic Indexing

Semantic indexing aims to represent the meaning of data, such as text or images, in a structured way to facilitate efficient retrieval and analysis. Current research focuses on leveraging large language models and deep learning techniques, including autoencoders and generative models, to create more accurate and nuanced semantic representations, often incorporating hierarchical structures and handling complex relationships between data points. These advancements are improving performance in various applications, such as recommender systems, biomedical literature search, and large-scale image retrieval, by enabling more effective semantic search and knowledge discovery.