Knowledge mining helps uncover latent insights in all types of information
Knowledge mining is an emerging category in artificial intelligence (AI), using a combination of AI services and data mining algorithms to drive content aware understanding over vast amounts of unstructured and structured information. It allows businesses to deeply understand their information, explore it, uncover insights, and find relationships and patterns at scale. While the first wave of AI involved many narrow applications, such as training a single model over one data source of a certain type for a single problem, knowledge mining is part of the next wave of AI, generating a dynamic understanding of relationships and patterns in a corpus of information. It is quickly becoming a key part of enterprise digital transformation initiatives that fundamentally change how organizations make sense of real-world information.
Much of information that’s critical to business exists in unstructured formats like PDFs, images, paper documents, and even handwritten notes. There’s key domain specific information in this content that isn’t readily visible or available to process. Extracting that vital information at scale is a crippling burden for organizations when they try to do it the traditional way, which usually involves someone scanning, interpreting, annotating, cutting, and pasting. Knowledge mining helps uncover latent insights across all types of information, whether structured or unstructured.