ECM and Machine Learning – What are Box, IBM, OpenText and other Vendors doing?

There are many use cases in Enterprise Content Management (ECM) for which Machine Learning can be deployed. In fact, i’d argue that you can apply machine learning in all the stages of content life cycle. You can apply: Supervised learning e.g, to automatically classify images, archive documents, delete files no longer required (and not likely … Continue reading ECM and Machine Learning – What are Box, IBM, OpenText and other Vendors doing?

Machine Learning for Personalizing Digital Experiences

Personalization has always been a key aspect in almost all kinds of digital experiences. Some examples of commonly found personalisation use cases are: allowing users to customise their dashboards or user interfaces, showing content based on explicit user-defined criteria, showing content based on implicit criteria or even that based on user behaviour. All these required … Continue reading Machine Learning for Personalizing Digital Experiences

Using Factor Analysis to reduce number of attributes

In my last post on using machine learning for everyday use cases, i’d mentioned factor analysis as a way to reduce large number of items (e.g., news articles’ attributes) into smaller set of variables. Some people asked me for examples of this, so this post is an attempt to explain how factor analysis can be used for what … Continue reading Using Factor Analysis to reduce number of attributes

Machine Learning as an alternative to rule based processes

There’s a lot of discussion about machine learning these days and pretty much every one (vendors, users) is talking about it. I remember attending courses on Artificial Intelligence, Machine Learning and even Artificial Neural Networks back in 1998. So what’s new? How have AI and ML evolved? I think a big reason why everyone is … Continue reading Machine Learning as an alternative to rule based processes