Unstructured Data

Unstructured data, encompassing text, images, and other non-tabular formats, presents significant challenges for analysis and knowledge extraction. Current research focuses on leveraging large language models (LLMs) and other deep learning architectures, such as transformers and graph neural networks, to extract meaningful information, perform entity matching, and enable efficient querying and summarization of these diverse data types. This work is crucial for advancing various fields, including healthcare, finance, and scientific research, by unlocking the insights hidden within massive volumes of currently underutilized unstructured data. The development of robust and scalable methods for handling unstructured data is transforming information processing across numerous sectors.