MACHINE LEARNING

Machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience with content, without being explicitly programmed. The primary aim is to allow systems to learn automatically without human intervention or assistance and adjust actions accordingly. Supervised machine-learning algorithms can apply what has been learned in the past to new data.

The unique KnowledgeLake approach to classifying content with this technology was first to create a proprietary neural network, training it on how to identify similar documents. An approach similar to facial recognition, but applied to content classification, reduces the need to manually tag metadata and eliminates traditionally laborious document preparation.

Once a document is identified, extracting relevant information is key. KnowledgeLake’s patent-pending approach enables its platform to convert this unstructured document to structured information without the need for full-page optical character recognition (OCR). The result is a system with significantly faster processing power and more resilience to image quality issues—all with greater accuracy than legacy capture solutions.

Combine all of this with a supervised learning capability and the traditional reliance on IT or developer-level resources to code complicated rule sets is removed. Instead, users are empowered to teach the system about new content types, improving the software through their daily use.