Advanced Machine Learning for Alfresco
Organising documents is vital for finding the right document quickly in large Alfresco repositories with lots of documents. Poorly organised documents is difficult to access and therefore has no real advantage to an organisation.
Alfresco's content model uses categories, aspects and tagging to organise documents. However, this approach requires manual user involvement and in most cases is never completed. Even if the required metadata is completed, it can be inconsistent or erroneous as it relies on the knowledge and experience of each individual user to classify the document. For global organisations with users across different countries and backgrounds speaking different languages, this is of major concern.
Additionally, manually creating and most importantly maintaining an organisational taxonomy to organise documents is time consuming and labor intensive. Once the taxonomy is completed and signed off, it needs to be re-examined as the organisation has evolved and changed.
Join this webinar to learn how to:
- “Automate" content identification, consistent labelling and categorisation for Alfresco document using widely used machine learning techniques such as clustering, classification and topic modelling.
- Enable enhance faceted search available in Alfresco 5 and provide recommendations to end users using conceptually enhanced content.
- Improve Information Governance by automating records classification and leveraging Alfresco’s Records Management capabilities.