ECS AutoTag is changing the way institutions manage their content. For too long, the burden has fallen on end users to manually tag content that is stored in centralised educational platforms such as content and learning management systems.
Utilising Machine Learning, ECS AutoTag automates the process of classifying content, ensuring institutions can maximise their investment in rich, high quality content via increased discoverability.
So how does ECS AutoTag work?
Platform-agnostic, multi-format support
ECS AutoTag has been designed to be interoperable with popular educational platforms, including content management and learning management systems. AutoTag supports the upload of images and other files, such as docs/docx, PDFs, presentations, spreadsheets and packages (QTI, SCORM, Zip).
Leveraging cloud technologies
Uploaded content is analysed by cloud-based, machine learning services (such as Google Vision) and tags are automatically generated. Various services are called to perform the analysis, including label, landmark and web detection, entity analysis and content classification.
Optimising content management
ECS AutoTag returns all values detected and the user is able to manually add additional tags to ensure alignment with existing content management conventions.
Administrators can configure the confidence score to expand or refine returned values.
Enhancing content discoverability
Metadata-rich content can now be more easily discovered by other users, ensuring institutions can maximise their investment in rich, high-quality content, and the burden on busy academics can be reduced.
ECS AutoTag in action