Experimenting with Wikipedia topics for Content
Automatically tagging your content with topics from a known, well described topic base like Wikipedia can have many cool uses. You can organize your content, suggesting keywords and outbound links, not to mention that you can build up interest profiles of your visitors. These interest profiles can the be used to suggest appropriate content and keep your visitors engaged. Inspired by Episerver Content Intelligence and a couple of earlier projects I've done in the past, I decided to perform an experiment to see how far I could get with a DIY approach as opposed to the traditional cloud-based NLP/AI.
Exploring the Episerver Nuget Feed
The best thing about Episerver is the community and all the great contributions coming from it. Many of them make it into packages on the Episerver nuget feed - along side Episervers own packages. I have for a long time worked on building tools to explore and visualize this more - and now I'm finally ready to one-by-one share some of the tools coming out of it.
Publicwww - searching for interesting Episerver CMS use patterns
I recently discovered publicwww.com a cool service that lets you search for any text in the html/css/js of all it's 550 million (2019-05-09) indexed web pages, including the cookies sent out and the http header. In this post I put my Episerver goggles on and had some fun with this data.
Auto Tagging Using Search
You don't always have to go the full AI route to get AI like results. In this blog post I'll describe an approach I've used several times (and for multiple purposes) with pretty decent results. Instead of classification algorithms, deep learning or neural networks I'll just simply query my favorite search engine.